Isolation of ipRGC Contribution to the Human Pupillary Light Response
Thesis
Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in
the Graduate School of The Ohio State University
By
Phillip Thomas Yuhas, B.A.
Graduate Program in Vision Science
The Ohio State University
2014
Thesis Committee:
Andrew Hartwick, O.D., Ph.D., Advisor
Angela Brown, Ph.D.
Nicklaus Fogt, O.D., Ph.D.
Copyright by
Phillip Thomas Yuhas
2014
1
Abstract
Intrinsically photosensitive retinal ganglion cells (ipRGCs) contain melanopsin, a
recently discovered photopigment. A major role of these photoreceptors is to send
information regarding ambient light levels (irradiance) to the brain centers that regulate
circadian rhythms and the size of the pupil of the eye. They are most sensitive to short
wavelength light, with peak sensitivity to approximately 480 nm light. The known
sluggishness of ipRGC light responses causes these photoreceptors to have a diminished
ability to distinguish flickering light from steady light stimuli (i.e. poor temporal
resolution).
Rods, cones, and ipRGCs all play a role in driving the human pupillary light
reflex (PLR). Specifically, ipRGCs are thought to mediate the maximum pupillary
constriction during a pulse of short wavelength light and the sustained pupillary
constriction that persists after light offset. Up to this point, most tests that seek to isolate
the ipRGC-mediated portion of the human PLR have compared a single pulse of long
wavelength light to a single pulse of short wavelength light.
My goals are to isolate and characterize the ipRGC-generated aspect of the human
PLR using flashing light stimuli, and to assess the flicker sensitivity of the human PLR. I
hypothesize that the human PLR to flickering, bright blue stimuli will show reduced
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amplitudes between constriction and redilation due to the increased ipRGC contribution
to such stimuli.
Three stimulus variables were modulated to optimize the ipRGC contribution to
the PLR: stimulus intensity, stimulus frequency, and alternation of short and long
wavelength stimuli. We found the difference in pupil fluctuation between the long and
short wavelength flickering stimuli to reach significance at an intensity of 1014
photons/cm2/s. A frequency of 0.1 Hz produced a significant difference in the pupil
fluctuation evoked by the two colored stimuli and was well-tolerated by the test subjects.
The third experiment revealed that a stimulus alternating between long and short
wavelength light induces greater pupillary constriction during the stimulus and sustained
constriction after each light flash, as compared to short or long wavelength stimuli
applied alone.
In summary, the temporal dynamics of the PLR to flickering red and blue light
stimuli exhibit characteristics consistent with the involvement of ipRGCs, and the
contribution of these ganglion cell photoreceptors can be best isolated using bright (1014
photons/cm2/s), slowly flickering stimuli (less than or equal to 0.20 Hz). Prior exposure
to blue light alters pupil responses to red light, and vice versa. As a result, alternating red
and blue flashing stimuli cause enhanced pupil constriction with slower re-dilation, as
compared to monochromic stimuli.
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Dedication
To my parents and my fiancée
iv
Acknowledgments
A special thanks needs to be expressed to my advisor, Andrew Hartwick. Without his
guidance and vision, this project would have never been completed. Others who have
been helpful in the completion of this work include Thomas Raasch, Gregory Good,
Holly Moose, Puneet Sodhi, Patrick Shorter, Shane Mulvihill, and Nicholas Perichak.
v
Vita
June 2006…………………………………………………..Saint Ignatius High School
May 2010…………………………………………...……...B.A. University of Notre
Dame
May 2014…………………………………………………..O.D./M.S (Expected) The
Ohio State University
Fields of Study
Major Field: Vision Science
Professional Field: Optometry
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Table of Contents
Abstract .........................................................................................................ii
Dedication .....................................................................................................iv
Acknowledgments ........................................................................................v
Vita ................................................................................................................vi
List of Figures ...............................................................................................viii
List of Tables ................................................................................................x
Chapter 1: Clinical Pupil Testing .................................................................1
Chapter 2: Melanopsin-Containing
Retinal Ganglion Cells ...................................................................................12
Chapter 3: Ganglion Cell Photoreceptors and
the Pupillary Light Response .........................................................................33
Chapter 4: Methods ......................................................................................52
Chapter 5: Results ........................................................................................61
Chapter 6: Discussion ..................................................................................78
References .....................................................................................................97
Appendix: Inter-subject Differences in ipRGC
Contribution to PLR .......................................................................................115
vii
List of Figures
Figure 1. Insensitivity of intrinsically photosensitive retinal
ganglion cells to flickering light ....................................................................22
Figure 2. Schematic of the open-loop extended-Maxwellian
view system utilized in this study ..................................................................54
Figure 3. Quantification of pupil size fluctuation evoked
by flickering light stimuli...............................................................................60
Figure 4. Effect of light irradiance on pupil responses
to 0.1 Hz flickering red or blue light..............................................................64
Figure 5. Inter-session repeatability of pupil responses
to 0.1 Hz flickering light ................................................................................66
Figure 6. Effect of flicker frequency on pupil responses
to flashing red or blue light ............................................................................68
Figure 7. Recovery rate of pupil re-dilation after stimulation
with different flicker frequencies of red or blue light ....................................70
Figure 8. Effect of alternating the red and blue light
stimuli on pupil responses ..............................................................................73
Figure 9. Effect of increasing duration of darkness
between alternating pulses of long and short wavelength light .....................76
viii
Figure 10. Inter-subject variability of ipRGC influence
over the pupillary light response ....................................................................116
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List of Tables
Table 1. Light levels of the blue stimulus utilized in this study ....................56
Table 2. Light levels of the red stimulus utilized in this study ......................56
x
Chapter 1: Clinical Pupil Testing
Clinical examination of the human pupils and their response to light offers a
concise and noninvasive approach for assessing ocular and neurological health. Changes
in the size, shape, and light responsiveness of the pupil can often be the first, only, or
most sensitive indicator of pathology located in the eye, in the brain, or along the neural
circuits that connect these two central nervous system structures. Physicians have
understood the value of careful assessment of the pupillary light response since the
Roman Empire, and recent advancements have improved the clinician’s ability to detect
subtle changes in this physiological process. This segment will examine the
developments in pupillary testing that occurred over the last two millennia and will
highlight their clinical impact.
Pupil assessments began as a crude marker of ocular health. A second century
Roman physician and philosopher living in modern western Turkey, Aelius Galenus, is
credited with being the first clinician to examine a patient’s pupillary light reflex as an
appraisal of crystalline lens clarity (Potter & Mattingly, 1999; Thompson & Corbett,
1991). He cultivated a system for determining the density of cataracts by covering one
eye and assessing the natural dilation of the fellow eye (Thompson & Corbett, 1991). If
the dilation was attenuated or lethargic, he judged that the cataract necessitated removal
using a surgical procedure that he had developed (Thompson & Corbett, 1991). A more
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formal understanding of the impetus for the pupillary light reflex would not be recorded
until near the end of the first millennium, when Arab physician-philosophers determined
that light falling on the back wall of the eye was the catalyst for pupillary contracture
(Thompson & Corbett, 1991). These discoverers were also the first to observe and record
that the pupils constricted “in consensus,” even if light were presented to only one of the
eyes (Thompson & Corbett, 1991). Unfortunately, the advances of these inquisitive
Romans and Arabs were not immediately expanded, and investigations into the
diagnostic power of pupillary assessment ceased for one thousand years.
Interest in the pupillary light reflex was rekindled in Europe in the late 19th
century when a woman claiming vision loss, but who was thought to be malingering on
the account of unremarkable ophthalmoscopy findings, was sent to German physicianscientist Julius Hirschberg. He noted that the patient’s pupil did not constrict in response
to light, but rather dilated, and consequently diagnosed retrobulbar optic neuritis as the
etiology of the woman’s vision loss (Anonymous, 1923). This was the first recorded
description of an afferent pupillary defect. A few years later Scottish physician-scientist
Marcus Gunn described how he had developed a methodology for differentiating
malingering from ocular disease by gauging pupillary escape after extended monocular
bright light exposure (Thompson & Corbett, 1991). Gunn’s work was formalized by
Alfred Kestenbaum nearly fifty years later when he assigned the name “Marcus Gunn
pupil” to afferent pupillary defects and developed a quantitative system for measuring the
severity of the defect (Kestenbaum, 1961). In fewer than fifty years, the use of pupillary
light reflex abnormalities to detect pathology had gone from a forgotten peculiarity to a
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valuable clinical tool. In addition, clinicians could now use afferent pupillary defects and
other pupillary light reflex abnormalities to appraise not only ocular health but
neurological health as well, an important advancement in the age before advanced
neurological imaging.
As the assessment of the pupillary light reflex became a useful and standard test
employed in clinical practice, there was a need for better understanding of its underlying
physiological mechanisms. During the first half of the twentieth century, fundamental
research on the pupil and its response dynamics was limited by the fact that observation
of the pupils’ behavior under dark conditions was impossible. That impediment was
removed, however, with the introduction of infrared video pupillography in 1958 by Otto
Lowenstein and Irene Loewenfeld (Lowenstein & Loewenfeld, 1958). Matthew Alpern
embraced this technological breakthrough and with it conducted groundbreaking basic
research on pupil physiology and biomechanics. He was the first researcher to establish
that the photoreceptors driving the pupillary light reflex had similar directional sensitivity
(Alpern & Benson, 1953), dark adaptation characteristics (Alpern, Kitai, & Isaacson,
1959), and spectral sensitivity (Alpern & Campbell, 1962) as image-producing
photoreceptors. However, later investigations by Alpern and his laboratory established
that the time period during which complete temporal summation occurs, often referred to
as the critical duration, was 0.5-0.6 seconds for the pupillary light reflex (Alpern,
McCready, & Barr, 1963). This is significantly longer than that of rods (0.1 seconds) or
cones [0.015 s; (Biersdorf, 1955)], which suggested that some properties of pupil
responses may not be identical to those associated with the visual system. While Alpern
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was making substantial research progress on pupil dynamics in his laboratory, Paul
Levatin was having a similar impact on the renaissance of clinical pupillary tests. In 1959
he introduced a clinical procedure that would become ubiquitous as a technique to assess
ocular and neurological health, the swinging flashlight test (Levatin, 1959). An afferent
pupillary defect occurs when the conduction of electrophysiological signals from the
retina to the brainstem is attenuated unilaterally or asymmetrically (Bremner, 2004). As a
result, a collimated light stimulus will elicit bilateral miosis when introduced to the
healthier of the two eyes, but subsequent exposure of the eye with the conduction deficit
to the same light source will cause bilateral mydriasis (Bremner, 2004). Over the course
of the next decade, Levatin refined his technique (Levatin, Prasloski, & Collen, 1973)
and applied it to diseases of the visual system, including optic nerve compression
(Levatin, 1961), unilateral papilledema (Levatin, 1969), and neurosyphilis (Levatin &
Ogilvie, 1964). H. Stanley Thompson refined Levatin’s findings (Thompson, 1966),
introducing in 1976 a more formalized rendition of the test that is still currently used in
practice (Thompson, 1976). The swinging flashlight test is now the most common
pupillary clinical test (Bremner, 2004), and research in multiple decades has confirmed
its excellent accuracy at detecting afferent pupillary defects (Ichhpujani et al., 2011; N.
R. Miller, Walsh, & Hoyt, 2005; Stanley & Baise, 1968).
The swinging flashlight test is a valuable clinical tool because it has the power to
detect several significant ocular and neurological diseases. Although the correlation
between an afferent pupillary defect and visual acuity is poor (Bremner, 2004), several
groups have demonstrated a significant correlation between asymmetric visual field loss
4
and severity of the afferent pupillary defect (R. H. Brown, Zilis, Lynch, & Sanborn,
1987; Johnson, Hill, & Bartholomew, 1988; Lagreze & Kardon, 1998). The swinging
flashlight test can detect an ipsilateral afferent pupillary defect in most unilateral or
asymmetric retinal or optic nerve diseases, including retinal detachment (Thompson &
Corbett, 1991), central retinal vein occlusion (Servais, Thompson, & Hayreh, 1986),
central retinal artery occlusion (Nowak, Amin, Robeson, & Schindler, 2012), unilateral
cone dystrophy (Mochizuki et al., 2012), ocular ischemic syndrome (Obuchowska &
Mariak, 2006; Roberts & Sears, 1992), optic nerve head drusen (Bohlman, 2000; Vicary
& Swann, 1991), retrobulbar optic neuritis (Stanley & Baise, 1968), and ischemic optic
neuropathies (Alexander, 1994; Kerr, Chew, & Danesh-Meyer, 2009). Lesions located
behind the optic chiasm produce more complicated afferent pupillary defects. Optic tract
lesions can produce contralateral afferent pupillary defects (R. A. Bell & Thompson,
1978). Additionally, contralateral afferent pupillary defects without a visual field defect
can be caused by unilateral ischemia or space occupying lesions in the pretectal nucleus
or in the brachium of the superior colliculus (Forman, Behrens, Odel, Spector, & Hilal,
1990).
Although the swinging flashlight test has significant clinical utility, it is not a
flawless procedure. It can be influenced by the skill of the clinician, depends on
asymmetric pathology, and can produce false positive results. Bilateral retinal or optic
pathway disorders may not produce a detectable afferent pupillary defect unless the
pathology is sufficiently asymmetric (Bremner, 2004). Clinicians can induce an artificial
relative afferent pupillary defect during the course of the swinging flashlight test by
5
exposing one eye to more light than the other, causing unequal retinal bleaching
(Thompson & Jiang, 1987). Normal subjects can demonstrate afferent pupillary defects
of up to three decibels resulting from naturally occurring imbalances in the connections
between the optic tracts and the olivary pretectal nuclei in the midbrain (H. Wilhelm,
Peters, Ludtke, & Wilhelm, 2007). Benign anisocoria causes a relative afferent pupillary
defect of approximately one decibel for every one millimeter but is not indicative of a
visual defect (Lam & Thompson, 1999).
Several prominent diseases of the eye and visual pathway do not produce an
afferent pupillary defect and cannot be detected with the swinging flashlight test.
Amblyopia typically does not present with an afferent pupillary defect (Firth, 1990). If it
does occur, the density of the afferent pupillary defect does not correlate with the density
of the amblyopia (Firth, 1990; Miki, Iijima, Takagi, Yaoeda, et al., 2008) and is instead
associated with concurrent myelinated nerve fibers (Merritt, 1977; Miki, Iijima, Takagi,
Tanimoto, et al., 2008). Functional vision loss does not produce an afferent pupillary
defect (Thompson & Corbett, 1991). Macular diseases, most notably macular
degeneration, are not usually associated with afferent pupillary defects, especially if
visual acuity remains better than 20/200 (Alexander, 1994; Thompson & Corbett, 1991);
although a recent study has described an increased likelihood of pupil abnormalities in
the presence of macular degeneration with subsequent neovascularization (Brozou et al.,
2009). Unilateral opacities of the cornea or lens will not cause afferent pupillary defects
(Bremner, 2004), but dense cataracts can cause mild afferent defects to occur in the
6
contralateral eye due to Ulbrichts’s bowl effect, where the cataract scatters light more
evenly across the retina (Lam & Thompson, 1990; H. Wilhelm, 1998).
The utility of the swinging flashlight test as a screening test for glaucoma is still
widely debated. An afferent pupillary defect can be detected in one-third of glaucoma
patients, typically those with advanced and asymmetric visual field loss (Skorkovska,
Wilhelm, Ludtke, & Wilhelm, 2011). Recent studies have shown significant correlation
between the magnitude of the relative afferent pupillary defect and inter-ocular
differences in either retinal ganglion cell counts or mean deviation values on visual field
tests (Skorkovska et al., 2011; Tatham et al., 2014). Several large clinical studies have
shown that the swinging flashlight test exhibits moderate-to-strong sensitivity and
specificity for detection of glaucomatous optic neuropathy, and subsequently endorse this
test as a screening tool for the disease (Charalel, Lin, & Singh, 2013; Kalaboukhova,
Fridhammar, & Lindblom, 2007; Skorkovska et al., 2011).
However, limitations do exist for using this pupil test to accurately detect
glaucoma. First, employing a test designed to detect unilateral disease (Bremner, 2004)
for a typically bilateral disease like glaucoma (Perasalo & Raitta, 1992; Sangawe, 1986)
is problematic if the optic nerve damage in a given patient is roughly symmetrical.
Second, animal studies indicate that the test may be less effective for detection of mild
glaucomatous damage, as a threshold 0.6 log unit afferent pupillary defect was reached in
monkeys only after 25% to 50% of the retinal nerve fiber layer was destroyed unilaterally
by laser ablation (Kerrison et al., 2001). Similar results have been observed in human
studies, as between a 25% and 83% difference in retinal nerve fiber layer thickness
7
between the eyes is needed for a relative afferent pupillary defect to be evident (Chew,
Cunnningham, Gamble, & Danesh-Meyer, 2010; Nakanishi, Nakamura, Tatsumi, NagaiKusuhara, & Negi, 2006). Furthermore, one large prospective study in India found that
pupil testing was impractical and inaccurate for glaucoma screening when employed
outside of a hospital setting (Hennessy et al., 2011). Thus, further validation of the
swinging flashlight test’s usefulness as a glaucoma screening tool is needed.
Recent advances in automated pupillometry have enhanced the capability of
clinical pupillary tests to detect ocular and neurological diseases. Automated swinging
flashlight tests are less prone to subjective clinical interpretation (B. Wilhelm et al., 2001)
and are more sensitive to mild afferent pupillary defects (Lankaranian, Altangerel,
Spaeth, Leavitt, & Steinmann, 2005; Meeker et al., 2005), which in glaucoma may
precede neuroretinal rim and visual field defects (Lankaranian et al., 2005).
Investigations into fatigue assessment have demonstrated that online, real-time
pupillometry can accurately appraise an individual’s state of alertness (Morad, Lemberg,
Yofe, & Dagan, 2000; B. Wilhelm, Wilhelm, Ludtke, Streicher, & Adler, 1998). Several
authors are researching multifocal pupillographic perimetry as an objective correlate for
visual field determination. This technique involves measuring the magnitude of pupillary
constriction after the presentation of a light stimulus to multiple points on the peripheral
retina (S. Hong, Narkiewicz, & Kardon, 2001; R. H. Kardon, Kirkali, & Thompson,
1991). Patients with ocular disease who had previously shown visual field defects using
standard perimetry also demonstrated pupillary response defects in the same regions as
their scotomas (R. H. Kardon et al., 1991). Several small studies have shown that early
8
detection of ocular diseases such as age-related macular degeneration (Sabeti, James,
Essex, & Maddess, 2013), diabetic retinopathy (A. Bell, James, Kolic, Essex, &
Maddess, 2010), and glaucoma (Carle, James, Kolic, Loh, & Maddess, 2011; Maddess,
Essex, Kolic, Carle, & James, 2013) can be facilitated by multifocal pupillographic
objective perimetry. Although subjects with ocular disease demonstrate good correlation
between the results from standard automated perimetry and multifocal pupillographic
objective perimetry, this relationship was not found in healthy subjects (S. Hong et al.,
2001), raising concerns about multifocal pupillographic objective perimetry’s capacity as
a diagnostic tool. Finally, recent investigations into early detection of complex
neurological diseases, including Alzheimer’s disease and Parkinson’s disease (Frost et
al., 2013; Giza et al., 2012), by probing for subtle pupillary abnormalities have shown
intriguing potential.
Measurement of pupil cycle time is an alternative method of determining
neuroretinal health. Whereas the swinging flashlight test uses pupillary redilation during
exposure to a bright stimulus to detect an afferent pupillary defect, pupil cycle time
quantifies visible pupillary oscillations produced by a thin slit lamp beam aimed at the
pupillary margin (S. D. Miller & Thompson, 1978a; Stern, 1944). The amount of time
needed to detect thirty oscillations is defined as pupil cycle time (Stern, 1944); a normal
value for a healthy subject is under 954 milliseconds (S. D. Miller & Thompson, 1978a).
This method of detecting afferent conduction abnormalities has been shown to be
sensitive in cases of optic neuritis (S. D. Miller & Thompson, 1978b), central retinal vein
occlusion (Menon, Nachiketa, & Kumar, 1995), Behçet's disease (Bayramlar, Hepsen,
9
Uguralp, Boluk, & Ozcan, 1998), and longstanding diabetic retinopathy (Lee, Kim, &
Park, 2011). However, as a diagnostic tool, pupil cycle time is not as sensitive as the
swinging flashlight to detecting unilateral neuroretinal anomalies (Cox, Thompson,
Hayreh, & Snyder, 1982). Biases along the entirety of the circuit that mediates the
pupillary reflex, such as fluctuations in iris sphincter neuro-effector junction signal
transmission, iris abnormalities, autonomic dysfunction, and even baseline pupil size can
have significant influence over the quantity of oscillations detected (Bremner, 2004;
Howarth, Heron, & Whittaker, 2000; Smith, Masek, Ichinose, Watanabe, & Stark, 1970;
Terdiman, Smith, & Stark, 1969). Furthermore, no standardization of background
lighting, stimulus intensity or stimulus size has been established, which contributes to the
poor inter-tester reliability for this test (Bremner, 2004). As a result, pupil cycle time is
not routinely measured in clinical practice.
Over the past two millennia, much progress has been made in our understanding
of the pupil and its response to light. As a result, ocular disease detection has become
more accurate and immediate, and patient care has improved. Despite the impressive
advancements in pupillary testing, problems with modern techniques remain. Most
modern pupil tests depend on the presence of an afferent pupillary defect to be effective,
but many ocular and neurological diseases do not produce this aberration. Automated
pupillometry has removed some the subjectivity of the old swinging flashlight test but
still depends on extensive, unilateral neuroretinal damage. Needed is a diagnostic
pupillary test that is objective, can detect bilateral disease, and does not necessitate
extensive preexisting pathology. This thesis will attempt to design a pupil test that
10
isolates a component of the human pupillary light reflex mediated by the recently
discovered photoreceptors of the inner retina, intrinsically photosensitive retinal ganglion
cells (described in the next section). A pupil test that compares the function of an inner
retinal photoreceptor to that of outer retinal photoreceptors (rods and cones) could be
advantageous in that a comparison between the two eyes may not be necessary. A pupil
test employing this approach may therefore especially have merit for the detection of
bilateral ocular diseases that differentially affect the inner versus outer retina (e.g.
retinitis pigmentosa and glaucoma, respectively), as compared to the standard swinging
flashlight test.
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Chapter 2: Melanopsin-Containing Retinal Ganglion Cells
Rods and cones are well established as the primary visual photoreceptors,
translating electromagnetic radiation into electrophysiological signals that are the basis
for image formation. These photoreceptors were long postulated to be the sole encoders
of environmental irradiance levels, mediating both vision and nonvisual functions, such
as photoentrainment of circadian rhythms and baseline pupil size. Researchers began
suspecting a third photoreceptor when rodents with degenerative outer retinae were
shown to maintain sleep-wake cycles (Foster et al., 1991; Provencio, Wong, Lederman,
Argamaso, & Foster, 1994), albeit with an altered spectral sensitivity from wild-type
animals (Yoshimura & Ebihara, 1996). The existence of a third photoreceptor could not
be proved from these investigations, however, as the prospect of small populations of
remaining cones capable of driving photoentrainment could not be ruled out (Do & Yau,
2010). Other investigations fueled interest in a novel photopigment by demonstrating that
human subjects lacking conscious visual perception from outer retinal disease still
showed circadian rhythms that were in sync with external day-night cycles (Czeisler et
al., 1995; Zaidi et al., 2007). Although these studies did not provide conclusive evidence
of the existence of a third photoreceptor, the traditional “two photoreceptor paradigm”
was beginning to be thought of as inaccurate. The subsequent discovery of a novel
photopigment called melanopsin in the melanphores, brain, and eye of Xenopus laevis
12
was the initial explicit evidence for the existence of a third photoreceptor (Provencio,
Jiang, De Grip, Hayes, & Rollag, 1998). Soon after, melanopsin was identified in a
subgroup of mammalian retinal ganglion cells that were shown to be intrinsically
photosensitive [termed ‘ipRGCs’; (Berson, Dunn, & Takao, 2002; Qiu et al., 2005)]. This
discovery has had ramifications for both researchers and clinicians.
In rodents, melanopsin has been detected in 1-2.5% of retinal ganglion cells
(Berson et al., 2002) and in the iris (Xue et al., 2011). Primate melanopsin-containing
ganglion cells are located primarily in the retinal ganglion cell layer, with a few cells
populating the inner nuclear layer (Hattar, Liao, Takao, Berson, & Yau, 2002; Provencio
et al., 2000; Sekaran, Foster, Lucas, & Hankins, 2003). Compared to rodents, there is a
proportionally lower number of melanopsin-containing ipRGCs, as only 0.2% of primate
retinal ganglion cells are these photoreceptive neurons (Dacey et al., 2005). In both
rodents and primates, ipRGCs express melanopsin along the plasma membrane of their
somata, dendrites, and axons until the optic disc (Hattar et al., 2002). The effective
density of melanopsin on ipRGCs is approximately 240 molecules per square micron,
which is 105 times lower than the effective density of photopigment found in rods and
cones, approximately 25,000 molecules per square micron (Do et al., 2009). Melanopsin
does not play a role in plasma membrane stability, as experiments on melanopsin
knockout rodents have demonstrated that the morphology of ipRGCs lacking melanopsin
is not altered (Lucas et al., 2003).
ipRGC dendrites have several unique characteristics. Their dendritic fields are
large with extensive overlap, creating a “photoreceptive net” over the extramacular retina
13
(Hattar et al., 2002). It has been shown that different classes of ipRGCs send highly
arborized dendrites into either the ON and OFF sublamina of the inner plexiform layer
(IPL) where they receive bipolar and amacrine input (Belenky, Smeraski, Provencio,
Sollars, & Pickard, 2003; Sakamoto, Liu, & Tosini, 2004). Regardless of the location of
the dendrites in the IPL, all ipRGCs receive rod- and cone-driven signals through ON
bipolar cells (Grunert, Jusuf, Lee, & Nguyen, 2011; Jusuf, Lee, Hannibal, & Grunert,
2007; Ostergaard, Hannibal, & Fahrenkrug, 2007). Typically, ON bipolar cells synapse
with retinal ganglion cells and amacrine cells only in the inner sublamina of the IPL.
Certain classes of ipRGCs (classification discussed in detail later) breach this axiom by
making synapses with ON bipolar cells in the outer OFF sublamina of the IPL
(Dumitrescu, Pucci, Wong, & Berson, 2009). There is evidence that ipRGCs also
communicate with amacrine cells (Belenky et al., 2003; Sakamoto et al., 2004), including
the dopaminergic amacrine cells (Hattar et al., 2002; Jusuf et al., 2007; Ostergaard et al.,
2007), in this OFF sublamina of the IPL through both axodendritic and axosomatic
contacts.
ipRGC axons project to several important non-visual brain centers. ipRGCs travel
in the caudal portion of the optic tract (Morin, Blanchard, & Provencio, 2003) and
innervate target brain centers without making intermediate synapses (Noseda, Constandil,
Bourgeais, Chalus, & Villanueva, 2010). The suprachiasmatic nucleus of hypothalamus
(Gooley, Lu, Chou, Scammell, & Saper, 2001; Hannibal, Hindersson, Knudsen, Georg, &
Fahrenkrug, 2002; Hattar et al., 2006; Hattar et al., 2002; Morin et al., 2003; Provencio et
al., 2000) and the intergeniculate leaflet of the lateral geniculate complex (Hattar et al.,
14
2006; Hattar et al., 2002; Morin et al., 2003) are essential for regulation of circadian
rhythms and receive information about environmental irradiance levels primarily from
ipRGC axons. ipRGCs provide much of the axonal innervation to the outer shell and core
of olivary pretectal nucleus (Berson et al., 2002; Hattar et al., 2006; Lucas, Douglas, &
Foster, 2001; Morin et al., 2003) which mediate the pupillary light response. Recent
works have demonstrated ipRGC innervation of the somatosensation and pain centers in
the posterior thalamus, implicating these cells in playing a role in the photophobia
experienced by patients with traumatic brain injury or migraine (Noseda et al., 2010;
Okamoto, Thompson, Tashiro, Chang, & Bereiter, 2009). A provocative new
investigation has demonstrated that ipRGCs also project to the dorsal aspect of the lateral
geniculate nucleus (T. M. Brown et al., 2010), the primary thalamic target for the visual
pathway, which challenges the widely-held notion that ipRGCs are not involved in image
formation (Hattar et al., 2002; Provencio et al., 2000; Schmucker, Seeliger, Humphries,
Biel, & Schaeffel, 2005). ipRGC axons have been shown to cross extensively at the optic
chiasm, save for projections to the bilaterally symmetric suprachiasmatic nucleus (Hattar
et al., 2006). Glutamate and pituitary adenylate cyclase-activating polypeptide (PACAP)
have been identified as the primary neurotransmitters utilized by ipRGCs to communicate
with their brain targets in rodents (Bergstrom, Hannibal, Hindersson, & Fahrenkrug,
2003; Engelund, Fahrenkrug, Harrison, Luuk, & Hannibal, 2012; Hannibal, 2002;
Hannibal & Fahrenkrug, 2004b) and primates (Hannibal et al., 2004). Of particular
importance to the transmission of irradiance information to non-visual brain centers is the
PACAP receptor PAC1R. Knockout mice lacking this receptor demonstrated a severely
15
diminished pupillary light reflex compared to wild type controls (Engelund et al., 2012).
Due to their low conduction velocity, ipRGC axons are thought to be unmyelinated in
rodents (Hattar et al., 2006; Kim & Dudek, 1991). Whether ipRGCs are myelinated in
primates remains under investigation (Do & Yau, 2010).
Increasing evidence supports the premise that ipRGCs are not a homogenous cell
type, and ipRGC classification schemes have emerged among investigators. Just as each
class of bipolar, amacrine, horizontal, or traditional retinal ganglion cells has unique
anatomical and functional properties, so too do the five classes of ipRGCs (Pires et al.,
2009; Zhao, Stafford, Godin, King, & Wong, 2014). Differentiation of the ipRGC
population into distinct classes occurs early in development, as a recent investigation
conducted on rodents has shown that three ipRGC classes can be identified based on
physiological responses to light by the eighth postnatal day: slow onset but fast offset,
slow onset and offset, and fast onset but slow offset (Tu et al., 2005). Although the
evolutionary benefit of having multiple ipRGC classes remains unclear, two theories have
emerged in an attempt to explain how differences between the five ipRGC classes may
originate. The first assigns the diversity expressed in the classes to the substantial genetic
variety observed within OPN4, the gene that encodes melanopsin, resulting in different
isoforms of melanopsin protein being produced (Pires et al., 2009). The second accredits
the differences seen between classes to an uneven expression of transcription factor
Brn3b in the ipRGC population as a whole (Chen, Badea, & Hattar, 2011).
Currently, ipRGCs are generally divided into five classes, termed M1 through
M5. Several characteristics are shared by all or many of the five ipRGC classes. Zhou
16
and colleagues have found that phototransduction kinetics and waveforms, as well as the
presence of rod input are ubiquitous among all ipRGCs (Zhao et al., 2014). All five
classes receive inhibitory input from amacrine cells and excitatory input from ON bipolar
cells (Belenky et al., 2003; Sakamoto et al., 2004; Van Hook, Wong, & Berson, 2012;
Wong, Dunn, Graham, & Berson, 2007). In addition to other brain targets, classes M1
through M4 respond selectively to the speed of a moving stimulus and project to the
superior colliculus, which is a sensory-motor center in the midbrain. Like many nonphotosensitive RGCs, M2 through M5 demonstrate center-surround receptive fields,
while M1 cells do not (Hu, Hill, & Wong, 2013; Zhao et al., 2014). The sensitivity of
ipRGCs to motion and stimulus patterns implicates a potential role for ipRGCs in
primitive image formation, which will be discussed in a later section.
M1 ipRGCs are the best studied of all the ipRGC classes and have several unique
anatomical and phototransductive features. M1 somata are found primarily in the retinal
ganglion cell layer, but small populations have been described in the inner nuclear layer
(Schmidt & Kofuji, 2011). Their dendrites have large diameters but are not extensively
branched (Schmidt & Kofuji, 2011). ON bipolar cells deliver excitatory input to M1
dendrites in a unique manner. As previously mentioned, ON bipolar cells typically
synapse with retinal ganglion cells in the inner sublamina of the inner plexiform layer,
and OFF bipolar cells synapse with retinal ganglion cells in the outer sublamina of the
inner plexiform layer. M1 cells do not follow this model, as their dendrites receive ON
bipolar synapses in the outer sublamina of the inner plexiform layer (Grunert et al., 2011;
Schmidt & Kofuji, 2011). Inhibitory input is mediated through glycine and GABA
17
receptors on M1 dendrites (Neumann, Haverkamp, & Auferkorte, 2011; Perez-Leon,
Warren, Allen, Robinson, & Brown, 2006) in the outer sublamina of the inner plexiform
layer (Zhao et al., 2014). M1 ipRGCs do not play a role in vision formation, and thus
send axons exclusively to non-vision brain centers (Hu et al., 2013). A retrograde tracer
injection study has shown that M1 axons comprise 80% of ipRGC innervation to the
suprachiasmatic nucleus and 45% of ipRGC innervation to the outer shell of the olivary
pretectal nucleus (Baver, Pickard, Sollars, & Pickard, 2008). Two subclasses of M1
ipRGCs have been identified based on the expression of the transcription factor Brn3b.
Brn3b-negative M1 ipRGCs innervate the suprachiasmatic nucleus, and Brn3b-positive
M1 ipRGCs innervate the olivary pretectal nucleus (Chen et al., 2011). The functional
implications of the existence of two M1 subclasses remain under investigation. Much like
its anatomy, M1 phototransduction is specialized for non-visual irradiance detection.
Surround antagonism has not been detected in the receptive fields of M1 cells (Zhao et
al., 2014), making these cells unsuitable for vision formation but useful for gauging gross
light levels. Of all ipRGC subclasses, M1 cells are the most sensitive to light in that they
have the lowest threshold and express most robust light response (Xue et al., 2011; Zhao
et al., 2014). This heightened sensitivity to light is thought the be the consequence of the
depolarized membrane potentials, which are due to altered voltage-gated K(+) currents,
and slow repolarizing mechanisms of the M1 class (Hu et al., 2013).
M2 ipRGCs are distinct from M1 cells in form and function. Slightly fewer M2
cells can be found in the mammalian retina, for example 800 M2 cells versus 900 M1
cells in mice (Ecker et al., 2010). M2 somata are larger than those of M1 cells but are
18
found in the same retinal layers (Berson, Castrucci, & Provencio, 2010; Ecker et al.,
2010). The average width of the dendritic tree from M2 cells is smaller than that for M1
cells, but it is still larger than those of traditional retinal ganglion cells (Berson et al.,
2010; Ecker et al., 2010). These dendrites are highly arborized (Schmidt & Kofuji, 2009)
in the inner ON sublamina of the inner plexiform layer (Berson et al., 2010; Ecker et al.,
2010; Schmidt & Kofuji, 2011) where they receive excitatory input (Schmidt & Kofuji,
2010). Approximately 20% of ipRGC innervation to the suprachiasmatic nucleus is
supplied by M2 ipRGCs, and the shell of the olivary pretectal nucleus receives
approximately 55% of its ipRGC input from M2 axons (Baver et al., 2008). M2 cells are
less sensitive to light and demonstrate decreased maximal responses to light than M1
cells, despite having the ability to fire action potentials at a higher frequency than M1
cells (Schmidt & Kofuji, 2009). In contrast, M2 ipRGCs have a heightened sensitivity to
cone-mediated signals (Schmidt & Kofuji, 2010). Excitatory input from ON bipolar cells
has the ability to have a more significant role in modulating the M2 intrinsic light
response and resting membrane potentials (Schmidt & Kofuji, 2010). M2 cells are also
less influenced by inhibitory input from amacrine sources (Neumann et al., 2011).
Less is known about classes M3 through M5. M3 cells are the only class of
ipRGCs that are known to be bistratified, sending dendrites to both the ON and OFF
sublamina of the inner plexiform layer (Schmidt & Kofuji, 2011). In this fashion, M3
cells receive both ON and OFF bipolar input (Zhao et al., 2014). M4 dendrites extend
into the ON sublamina of the inner plexiform layer (Schmidt & Kofuji, 2011) where they
are capable of receiving sustained ON bipolar input (Estevez et al., 2012). Additionally,
19
M4 cells have been shown to have ON center with OFF surround receptive fields and to
project to the dorsal lateral geniculate nucleus, implicating a possible role in vision
formation (Estevez et al., 2012). M5 ipRGC have been shown to have dendrite
arborization in the ON sublamina of the inner plexiform layer, but little is known about
their structure or function (Schmidt & Kofuji, 2011).
ipRGCs act as traditional retinal ganglion cells in serving as output neurons for
the retina, in addition to being capable of independent phototransduction. As outlined
above, ipRGCs synapse with both bipolar cells and amacrine cells and can be conduits
for light-evoked signals that are initially driven by both rods and cones (Zhao et al.,
2014). Their intrinsic phototransduction mechanisms have garnered significant
investigative attention. As previously noted, the maintenance of circadian rhythm
photoentrainment and a pupillary light response in rodents with rod and cone
degeneration indicated that a third photoreceptor existed in the eye (Do et al., 2009;
Hattar et al., 2002; Hattar et al., 2003; Semo et al., 2003; Van Gelder, 2001). An
alternative class of photoreceptive molecules constituting of flavin and floate, called
cyptochromes, were hypothesized to mediate these functions in rod/cone knockout mice
(Kavakli & Sancar, 2002). However, cyptochromes have since been shown to contribute
to the amplitude of inner retinal phototransduction but are not required for it to occur
(Hattar et al., 2003; Van Gelder, 2005). Instead, the effects of light on circadian behavior
and pupil constriction in rodless/coneless rodents were eliminated when melanopsin was
knocked out, indicating that this protein was the photopigment for the third photoreceptor
(Panda et al., 2003). In vitro, melanopsin-containing ipRGCs have been shown to fire
20
action potentials upon light exposure, even when they are synapatically separated from
bipolar and amacrine cells (Berson et al., 2002; Qiu et al., 2005). These studies leave
little doubt as to the capacity of ipRGCs to produce a light response autonomously.
Melanopsin-based phototransduction differs from the phototransduction cascade
that has been characterized for traditional rod and cone photoreceptors. Firstly, whereas
rods and cones hyperpolarize in respond to light, ipRGCs depolarize (Berson et al., 2002;
Hartwick et al., 2007). Secondly, ipRGCs contain much less photopigment than rods or
cones. The plasma membrane effective density of melanopsin on ipRGCs is
approximately 105 times lower than density of photopigment found in the outer segments
of rods and cones, resulting in a low photon capture rate and the necessity of a bright
stimulus for activation (Do et al., 2009). In vivo, 1011-12 photons/cm2/s is necessary for
melanopsin activation (Dacey et al., 2005). This value for retinal activation corresponds
to a corneal irradiance of approximately 2 × 1013 photons/cm2/s (Berson et al., 2002;
Lucas et al., 2003). Although melanopsin is a rare molecule in the plasma membrane of
ipRGCs, which necessitates a large amount of photons to be delivered to the corneal
surface for activation, ipRGCs are capable of signaling single photon capture, similar to
rods and cones (Berson et al., 2002; Do et al., 2009). Furthermore, threshold for
activation of the melanopsin-based pupillary light reflex has been shown to be only a few
hundred isomerized melanopsin molecules (Berson et al., 2002; Do et al., 2009). Thirdly,
when activated by light, ipRGCs exhibit a transient peak in action potential firing with
stimulus onset that decreases to a stable rate of firing with continuation of the stimulus
(Berson et al., 2002). A feline in vivo model has shown a linear relationship between light
21
intensity and action potential frequency in a rare group of ganglion cells that are now
thought to have been ipRGCs (Barlow & Levick, 1969). ipRGCs are not able to faithfully
encode abrupt changes in stimulus intensity, as their response kinetics have been shown
to be lethargic (Berson et al., 2002; Do et al., 2009). After light offset, ipRGCs continue
to fire action potentials, lethargically encoding the termination of the stimulus (Berson et
al., 2002). Furthermore, recordings from isolated ipRGCs demonstrate that these cells
cannot accurately encode a slowly flickering stimulus [(Moose, Sodhi, & Hartwick,
2011); Fig. 1]. Instead, they fire action potentials continuously, as if the stimulus were
continuous and not flickering. ipRGCs are better equipped for long periods of temporal
light summation and sustained firing over the course of hours (Do et al., 2009; Wong,
2012). These characteristics suggest that ipRGCs are best suited for tracking gradual
changes in irradiance throughout the course of the day to regulate circadian rhythms and
to control baseline pupil size.
Figure 1. Insensitivity of intrinsically photosensitive retinal ganglion cells to flickering
(Continued)
22
(Figure 1: Continued)
light. Recording taken from rat retinas mounted on multielectrode arrays. The stimulus
consisted of a bright (1.1 x 1015 photons/cm2/s), blue (470 nm) light flickered at either
0.10 Hz or 0.50 Hz. A) Non-photosensitive retinal ganglion cells driven by rods and
cones are able to faithfully encode flickering stimuli at 0.10 Hz and 0.50 Hz. They fire
actions potentials when the stimulus is emitting light but cease firing upon stimulus
offset. B) ipRGCs fire action potentials continuously during the entire duration of 0.10
Hz or 0.50 Hz flickering stimulus, with spiking occurring at a similar rate whether the
stimulus is on or off.
ipRGCs are most sensitive to short wavelength light. Several studies have shown
that the maximum sensitivity of melanopsin is approximately 480 nm in both rodents and
primates (Bailes & Lucas, 2013; Dacey et al., 2005; Newman, Walker, Brown, Cronin, &
Robinson, 2003). This value places ipRGCs between the spectral peaks of short
wavelength cones (420 nm) and rods [498 nm; (Bowmaker & Dartnall, 1980)]. Long
wavelength light has been demonstrated to be ineffective in producing a functional
response in ipRGCs, especially in the photoentrainment of circadian rhythms
(Papamichael, Skene, & Revell, 2012).
The melanopsin photocascade remains under investigation, and some aspects of
ipRGC photoresponses are better understood than others. It is clear that the melanopsindependent ipRGC photocycle is independent of the visual retinoid cycle (Tu et al., 2006),
23
but similarities exist between the two. The chromophore for melanopsin is 11-cis
retinaldehyde, which is isomerized to all-trans retinaldehyde after light stimulation
(Rollag, 2008). The now-activated photopigment in turn activates the G-proteins Gt or Gq
(Newman et al., 2003), which in turn activate phospholipase C beta 4 (Graham et al.,
2008). Activated phosopholipase C beta 4 hydrolyzes phosphatidylinositol (4, 5)bisphosphate into secondary messenger inositol 1,4,5-trisphosphate (Do et al., 2009;
Graham et al., 2008), which is released into the cytosol (Graham et al., 2008). Through
an unknown pathway, canonical transient receptor potential (TRPC) channels are opened
which depolarizes the cell and triggers action potential firing (Hartwick et al., 2007; Xue
et al., 2011). The large depolarization associated with spiking causes voltage-gated
calcium channels to open, leading to a rise in intracellular calcium levels (Hartwick et al.,
2007). The amount of intracellular Ca2+ has been linked to irradiance levels, suggesting
that a brighter environment provokes a stronger ipRGC calcium response (Hartwick et
al., 2007; Kumbalasiri, Rollag, Isoldi, Castrucci, & Provencio, 2007). Continued Ca2+
influx after action potential firing is thought to be a substantial source of Weber-Fechner
light adaptation to a continuous light source (Do & Yau, 2013; Wong, Dunn, & Berson,
2005).
The mechanism of regeneration of 11-cis retinaldehyde in ipRGCs has been a
subject of much debate. It is unlikely that the ipRGCs share a chromophore regeneration
pathway with traditional photoreceptors, given their distance from the retinal pigment
epithelium (Panda et al., 2005). One alternative theory is that melanopsin is a bistable
molecule; that is short wavelength light drives phototransduction by isomerizing a
24
photopigment into an intermediate form, but long wavelength light has the ability to
regenerate the chromophore in photobleached opsin without an independent isomerase
intermediate (Rollag, 2008). Bistability is frequently seen in invertebrate rhabdomeric
opsins, to which melanopsin is related (T. Sexton, Buhr, & Van Gelder, 2012). If
melanopsin is bistable, short wavelength light drives phototransduction and creates alltrans retinaldehyde. Long wavelength light drives it back to 11-cis retinaldehyde.
Melanopsin’s strong resistance to bleaching has been hypothesized to be a product of the
capability of photon absorption in multiple isomeric states, which is characteristic of a
bistable molecule (T. J. Sexton, Golczak, Palczewski, & Van Gelder, 2012; Zhu et al.,
2007). Prior exposure to long wavelength light has been shown to enhance pupillary
constriction to short wavelength light and short wavelength induced photoentrainment of
free running cycles in rodents (Mawad & Van Gelder, 2008; Mure et al., 2009; Mure,
Rieux, Hattar, & Cooper, 2007). Other investigations have cast doubt on the potential
bistability of melanopsin. ipRGC-controlled melatonin suppression was shown to receive
no additional benefit from simultaneous long and short wavelength light administration
(Papamichael et al., 2012). Another study demonstrated that prior long wavelength light
did enhance the pupillary response to short wavelength light, but this response could not
be replicated in vitro on a multielectrode array (Mawad & Van Gelder, 2008). Other
electrophysiological experiments have found that prior long wavelength exposure
provides no enhancement of melanopsin’s response (Enezi et al., 2011), or that an
enhancement is only detected with modulated expression of arrestin molecules not found
in wild-type animals (Panda et al., 2005). In summary, prior long wavelength exposure
25
seems to enhance the functionality of physiological process modulated by ipRGCs, but in
vitro experiments have failed to verify bistability as the mechanism of this phenomenon.
The mechanisms underlying 11-cis retinaldehyde regeneration remain unknown.
Although it remains unclear whether intrinsic bistability affects ipRGC
sensitivity, several extrinsic factors have been demonstrated to have an effect.
Melanopsin expression is subject to diurnal variation. A shift of circadian spectral
sensitivity toward lower wavelengths has been demonstrated to increase ipRGC influence
over serum melatonin levels in pre-dawn hours (Figueiro, Bullough, Parsons, & Rea,
2005). Additionally, melanopsin expression in ipRGCs is increased in conditions of
constant darkness, making photocapture more likely during the night (Hannibal, 2006).
Previous light exposure alters the sensitivity of ipRGCs. This light exposure can have
long term effects on sensitivity, as constant light exposure during the first week of life
increases the number of identifiable ipRGCs in rodents (J. Hong et al., 2013).
Additionally, alteration of ipRGC function can be more immediate, as long wavelength
exposure directly before the presentation of a short wavelength stimulus seems to
enhance the response of ipRGCs. As discussed above, bistability might be an intrinsic
source of this immediate effect, but two extrinsic factors are receiving attention, as well.
The first extrinsic factor that could lead to the modification of ipRGC response properties
is the direct connection between ON bipolar cells and ipRGCs (Belenky et al., 2003;
Sakamoto et al., 2004). Another study found that when mediating extrinsic
photoresponses that are rod- and cone-driven, ipRGCs are five times more sensitive to
light and extend their temporal bandpass to higher frequencies (Wong et al., 2007). The
26
second extrinsic factor is dopaminergic neuromodulation of ipRGCs through their
synaptic connections with dopamine-containing amacrine cells. The influence of
dopamine on ipRGC function remains under investigation. One study suggests that
dopamine interaction with ipRGC D2 receptors increases melanopsin production, possibly
enhancing their intrinsic light response (Sakamoto et al., 2005). Another study has
demonstrated that dopamine diminished melanopsin-based photocurrent by acting on D1
receptors (Van Hook et al., 2012). Interestingly, this same study also determined that
dopamine also caused to the normal resting potential of ipRGCs to become more
depolarized, suggesting that dopamine might actually lower their intrinsic photoresponse
threshold. Clearly, dopamine has an effect on ipRGC function, but the nature of this
effect is still unknown.
Not only can ipRGC function be modulated through post-synaptic connections
with dopaminergic amacrine cells, but there is also evidence that ipRGCs can alter retinal
dopamine levels by releasing glutamate onto α-amino-3-hydroxy-5-methyl-4isoxazolepropionic acid (AMPA)-type glutamate receptors located on the dopaminecontaining amacrines (Zhang, Belenky, Sollars, Pickard, & McMahon, 2012). In turn,
dopamine influences periodical gene expression in rods and cones, indicating a
contributory role for ipRGCs in regulating the circadian rhythms of overall retinal
sensitivity (Dkhissi-Benyahya et al., 2013). Not all agree that ipRGCs have a retrograde
effect on dopamine amacrine cells, however, and more research is needed to better
understand the synaptic relationship between these cells (Cameron et al., 2009). It is not
clear whether the release of glutamate within the retina by ipRGCs is dendritic (which is
27
rare in the CNS) or axonal, but in support of the latter, it has recently been discovered
that some ipRGCs express collateral axons that travel and terminate in the IPL instead of
leaving the eye through the lamina cribosa of the optic nerve head (Joo, Peterson, Dacey,
Hattar, & Chen, 2013).
The discovery of melanopsin-containing ipRGCs in the mammalian retina has
spurred extensive investigation into the functional roles of this third photoreceptor. Three
areas of particular interest are their contributions to: 1) photoentrainment of circadian
rhythms; 2) vision formation; and 3) the pupillary light reflex. Researchers have only just
begun to comprehend the influence ipRGCs have over visual and non-visual brain
functions, and much work is yet to be done. As these cells become better understood, the
clinical implications become more evident.
Melanopsin has been demonstrated to play a large role in the photoentrainment of
circadian rhythms. This claim has been supported through multiple anatomical and
physiological findings. ipRGCs send many axons to the suprachiasmatic nucleus, the
brain center that controls circadian rhythms (Gooley et al., 2001; Hannibal et al., 2002;
Hattar et al., 2002; Morin et al., 2003; Provencio et al., 2000). Functional evidence of
melanopsin’s role in circadian rhythm photoentrainment can be found in rodent models
and is suggested in humans. Animals with outer retinal degeneration have repeatedly
demonstrated that the synchronization of internal circadian rhythm to external day/night
cycles can be maintained despite loss of traditional photoreceptors (Freedman et al.,
1999; Hannibal et al., 2002; Hattar et al., 2002; Panda et al., 2002; Provencio et al., 2000;
Ruby et al., 2002). Furthermore, postnatal mice lacking mature rods and cones produce
28
detectable retinal light responses and are able regulate their biological clocks from birth
(Hannibal & Fahrenkrug, 2004a).
ipRGCs also influence melatonin synthesis and release from the pineal gland.
Neuronal connections between the suprachiasmatic nucleus (which receives extensive
ipRGC synaptic input) and the pineal gland regulate the synthesis and release of this
hormone. Short wavelength light exposure is especially potent for decreasing melatonin
synthesis in both vertebrates and invertebrates (Bruce & Minis, 1969; Cahill, Parsons, &
Besharse, 1998; Frank & Zimmerman, 1969). Specifically, a 479 nm wavelength
stimulus has been shown to be optimal in melatonin suppression and subsequent
photoentrainment of circadian rhythms (Papamichael et al., 2012) which closely matches
the 480 nm peak of the melanopsin action spectrum (Bailes & Lucas, 2013; Dacey et al.,
2005; Newman et al., 2003). Human subjects with severe outer retinal disease also have
been shown to exhibit light-evoked alterations in serum melatonin levels (Munch, Leon,
Crippa, & Kawasaki, 2012).
Rods, cones, and ipRGCs all contribute to photoentrainment of circadian rhythms;
the contribution of each is still under investigation. Do and Yau claim that ipRGCs drive
approximately half of biological clock regulations (Do & Yau, 2010), with the other half
coming from a combination of rods and cones (van Diepen, Ramkisoensing, Peirson,
Foster, & Meijer, 2013). Input provided by ipRGCs is a mix between their intrinsic
response to light and mediation of extrinsic irradiance data from rods and cones (PerezLeon et al., 2006). Whether ipRGCs or traditional photoreceptors are the primary
mediator of irradiance levels to the suprachiasmatic nucleus is largely dependent on the
29
nature of the light stimulus. Following what is known about their phototransduction
properties, it comes as no surprise that ipRGCs play a large role in the control of
biological rhythms when the light stimulus is bright and sustained (Lucas, Lall, Allen, &
Brown, 2012; Mure et al., 2007). In conditions too dim to stimulate melanopsin, such as
twilight, rods become the primary regulators (Lucas et al., 2012; Morin & Studholme,
2011). Cones alone are undependable regulators under stable bright or dim conditions
(Lall et al., 2010; Lucas et al., 2012; Mrosovsky & Hattar, 2005), but are the primary
mediators of relatively rapid changes in environmental irradiance (Drouyer, Rieux, Hut,
& Cooper, 2007; Lucas et al., 2012).
New evidence has emerged that ipRGCs do contribute to some aspects of vision
formation. Some believe that the role of melanopsin is mere modulation and optimization
of rod-cone input into the visual centers of the brain (Barnard, Hattar, Hankins, & Lucas,
2006), but others conclude that the intrinsic response of ipRGCs plays a direct role in
vision formation (T. M. Brown et al., 2010; Dacey et al., 2005). Since melanopsin’s
discovery until recently, it was largely thought that ipRGCs had no role in image
formation for several reasons, from their inability to encode high spatial and temporal
frequencies to their proven role in nonvisual functions such as circadian rhythm
photoentrainment (Hattar et al., 2002; Provencio et al., 2000; Schmucker et al., 2005).
This hypothesis was first challenged by studies utilizing tracer injection that clearly
demonstrate that ipRGCs provide synaptic input into the dorsal aspect of the lateral
geniculate nucleus (T. M. Brown et al., 2010; Dacey et al., 2005), a key brain center for
image formation. An investigation with a rod-cone knockout rodent model has
30
demonstrated that animals lacking traditional photoreceptors maintain physiological light
response on the dorsal aspect of the lateral geniculate nucleus (T. M. Brown et al., 2010).
A “blindsight” in blind or near-blind human patients has been long described (Sanders,
Warrington, Marshall, & Wieskrantz, 1974), and some have suggested that this
phenomenon is based on primitive visual input delivered by ipRGCs (T. M. Brown et al.,
2010). In particular it is thought that melanopsin contributes up to 40% of the input for
sustained vision formation over a long time period (T. M. Brown et al., 2010), although it
has been shown that ipRGCs respond selectively to the velocity of stimuli within
receptive fields (Zhao et al., 2014). ipRGC-mediated input into the dorsal aspect of the
lateral geniculate nucleus has a unique S-Off, (L + M)-ON type of color-opponent system
(Dacey et al., 2005). The specific class of ipRGC speculated to influence vision
formation is the M4 class. These cells have large, ON center with antagonistic OFF
surround receptive fields (Estevez et al., 2012). Additionally, their axons were the ipRGC
axon labeled in the dorsal aspect of the lateral geniculate nucleus (T. M. Brown et al.,
2010; Dacey et al., 2005; Estevez et al., 2012).
Of most interest to this work in this thesis is the influence of ipRGCs on the
pupillary light response. Rods, cones, and ipRGCs all provide the photic information that
regulates the pupillary light response (Lucas et al., 2003), with traditional photoreceptors
mediating approximately 80% of the response (Do & Yau, 2010). Rods and cones are the
primary brokers at low light levels (Lall et al., 2010), but ipRGCs generate the pupillary
light reflex at corneal irradiances above 1011.5 photons/cm2/s (Lall et al., 2010; Lucas et
al., 2003). In addition to needing a bright stimulus, the ipRGC-mediated pupillary
31
response is best elicited when the stimulus has a wavelength of 480 nm, matching
melanopsin’s spectral sensitivity (Gamlin et al., 2007; R. Kardon et al., 2009). Like
ipRGC phototransduction, the ipRGC-mediated pupillary light reflex reacts lethargically
to light onset and offset. When stimulated with a melanopsin-specific stimulus – bright,
short wavelength light – the pupil exhibits a longer latency in its light reflex than when
the stimulus is better suited for rod or cone stimulation (Tsujimura & Tokuda, 2011).
When presented as a square-wave stimulus, light was not able to induce a square-wave
pupillary light reflex, but a sinusoidal stimulus prompted a sinusoidal pupillary light
reflex (Tsujimura & Tokuda, 2011). These data suggest that ipRGCs can be selectively
activated with a bright, short wavelength, and slowly flickering or continuous stimulus.
Furthermore, the function of ipRGCs can be measured by analyzing the pupillary light
reflex under conditions known to stimulate ipRGCs. Only the basic attributes of the
ipRGC-driven pupillary light reflex have been presented here; this topic will be
investigated in depth in the next chapter.
32
Chapter 3: Ganglion Cell Photoreceptors and the Pupillary Light Response
The goal of this study is to characterize the temporal dynamics of the human
pupillary light response (PLR) to flickering long and short wavelength light in order to
establish the PLR as a biomarker for the assessment of ipRGC function in vivo. To this
end it will investigate the changes in pupil size that occur in response to long or short
wavelength flickering light of different intensities and flicker frequencies. Also to be
determined is the effect of prior long wavelength light exposure on the pupil responses to
short wavelength light, and vice versa, through the use of alternating short and long
wavelength light stimuli.
In the previous chapter a novel photopigment called melanopsin was introduced,
and a class of melanopsin-containing retinal ganglion cells was described. These
intrinsically photosensitive retinal ganglion cells (ipRGCs) have been shown to have
unique phototransduction, temporal, and functional properties, as compared to rods and
cones. In the ocular research community, there is a growing interest in utilizing these
cells as a biomarker for retinal and neurological health, due to their relative scarcity in the
mammalian retina and unique functional capabilities (Dacey et al., 2005; Hattar et al.,
2002). It is hypothesized that their functional capacity can be best assessed by examining
features of the pupillary light reflex that are thought to be ipRGC-driven. This chapter
33
will provide a detailed understanding of why and how ipRGCs impact the pupillary light
reflex and of what investigation has already been conducted on this topic.
Several investigations have sought to examine the contribution of ipRGCs to the
pupillary light reflex. As discussed in the last chapter, anatomical evidence supports a
role for ipRGC influencing the pupillary light reflex. ipRGC axons, particularly the M2
class of ipRGCs (Baver et al., 2008), provide significant innervation to the midbrain’s
olivary pretectal nucleus, which mediates the pupillary light reflex (Berson et al., 2002;
Lucas et al., 2001; Morin et al., 2003). Functional studies provide perhaps the strongest
evidence for ipRGC modulation of the pupillary light reflex, as rodents (Semo et al.,
2003; Van Gelder, 2001) and canines (Grozdanic, Matic, Sakaguchi, & Kardon, 2007)
blind from outer retinal disease maintain a pupillary light reflex despite the loss of rods
and cones. Rodents bred without melanopsin show normal pupillary responses to dim
stimuli thanks to intact rods and cones, but demonstrate diminished pupillary responses to
bright stimuli (Lucas et al., 2003; Panda et al., 2003).
Data supporting an ipRGC contribution to the primate and human pupillary light
reflex exists, with strong evidence being reported by Gamlin and colleagues (Gamlin et
al., 2007). This group was first to identify the ipRGC signature in the primate pupillary
light reflex. In humans and macaques they observed that the pupil constricted to the onset
of both bright long and short wavelength stimuli. After the bright short wavelength light
was turned off, the pupil remained constricted for several seconds; whereas redilation
after bright long wavelength light was more immediate. The difference in this postillumination pupillary constriction is thought to be ipRGC-driven, as it matches the
34
known properties of melanopsin phototransduction, namely that it lethargically encodes
light onset and offset (Berson et al., 2002), it is more sensitive to short wavelength light
(Bailes & Lucas, 2013; Dacey et al., 2005; Newman et al., 2003), and it activates only in
response to a bright stimulus (Berson et al., 2002; Dacey et al., 2005; Do et al., 2009). To
confirm that ipRGCs, and not S-cones, were driving this response to bright, short
wavelength light in vivo, Gamlin’s group made intravitreal injections of l-2-amino-4phosphobutyrate (l-AP4) and 6-cyano-7-nitroquinoxaline-2,3-dione into macaques to
inhibit ON and OFF retinal channels. Even after the blockade of rod- and cone-driven
retinal circuits, the primates demonstrated a pupillary light reflex to a bright, short
wavelength stimulus that persisted after stimulus offset. An intact macaque retina with
the synaptic blockers present responded almost identically in vitro by selectively firing in
a lethargic manner to a bright, short wavelength stimulus. This work is the current
definitive work showing the role of ipRGCs in mediating a specific aspect of the primate
pupillary light response.
Two other studies give circumstantial evidence for the ipRGC influence over the
pupillary light reflex. In the first, human subjects wearing 470 nm-blocking filters
showed a decreased sustained pupillary response and a more rapid redilation when
exposed to an extended white light stimulus, as compared to the same stimulus
administered without the 470-nm filters; visual acuity, color vision, and contrast
sensitivity were unaffected (Ishikawa, Onodera, Asakawa, Nakadomari, & Shimizu,
2012). The authors of this study hypothesized that a lack of ipRGC stimulation was
responsible for the abnormal pupil behavior with the blue filters in place. The second
35
study investigated the ipRGC-pupillary light reflex relationship by utilizing serum
melatonin levels in human beings as an objective marker of ipRGC function (Munch et
al., 2012). Previous works have suggested ipRGC modulation over serum melatonin
levels (Bruce & Minis, 1969; Cahill et al., 1998; Figueiro et al., 2005; Frank &
Zimmerman, 1969; Papamichael et al., 2012). This study built on those works to establish
the amount of sustained pupillary constriction present at six seconds after short
wavelength stimulus offset was positively correlated with serum melatonin levels.
Although ipRGCs effects on melatonin and the pupillary light reflex had been previously
shown, this study is important because it demonstrates that the pupillary light reflex can
be used as a biomarker for otherwise clandestine physiological processes.
The studies described above make strong arguments that ipRGCs have an
influence over the pupillary light reflex. The second step in the development of a
pupillary test to assess ipRGC function is the determination of what specific aspects of
the pupillary light reflex they modulate. In vitro, ipRGCs have been shown to be able to
integrate photic data (Do et al., 2009) and fire action potentials for longer periods of time
(Wong, 2012), especially in response to short wavelength stimuli (Bailes & Lucas, 2013;
Dacey et al., 2005; Newman et al., 2003). These characteristics have led many
researchers to believe that the best place to quantify ipRGC impact on the pupillary light
reflex is after the offset of a bright stimulus. For example, Gamlin (Gamlin et al., 2007)
and Kankipati (Kankipati, Girkin, & Gamlin, 2010) have found that at a ten second
exposure of a 1012 photons/cm2/s, short wavelength stimulus elicits a stronger sustained
pupillary response at both five and thirty seconds after stimulus offset than a similarly
36
long and bright long wavelength stimulus. These groups ascribe this difference in
redilation to sustained ipRGC firing after stimulus offset. This response has been shown
to have good intra-subject repeatability (Herbst, Sander, Milea, Lund-Andersen, &
Kawasaki, 2011), and has been replicated by several other investigators (Herbst et al.,
2011; R. Kardon et al., 2009; Mure et al., 2009; Park et al., 2011; Young & Kimura,
2008). Stimuli that are one second in duration and have an intensity of at least 12 log
photons/cm2/s produce the largest difference in sustained constriction between long and
short wavelength conditions at six seconds after stimulus offset (Park et al., 2011). These
stimulus settings have not been widely adapted, and many investigations use a longer and
brighter stimulus to better match the relatively insensitive, lethargic light responses of
ipRGCs (Herbst et al., 2011; Ishikawa et al., 2012; Kankipati et al., 2010; Mure et al.,
2009).
Sustained pupillary constriction after light offset is not the only potential indicator
of ipRGC influence over the pupillary light reflex. An alternative assessment could be
made by measurement of the peak amplitude of pupillary constriction in response to
stimulus onset or a change in stimulus intensity. For example, one investigation
demonstrated that increasing the intensity of a short wavelength stimulus in a steppedmanner every six seconds caused greater transient pupillary constriction than similar
increases to a long wavelength stimulus (Young & Kimura, 2008). This test design is
well suited for ipRGC detection because it gauges pupillary constriction over a longer
time period, matching ipRGC’s lethargic light response. Other studies have utilized
single, brief pulses of long or short wavelength light to assess ipRGC’s contributions to
37
maximum pupillary constriction. One employed photopically matched short and long
wavelength pulses and found greater pupillary constriction in response to the short
wavelength stimulus (Herbst et al., 2011). A second study found that the intensity of the
long and short wavelength stimuli appears to affect the difference in maximum
constriction between the two colored stimuli. When the photopically matched long and
short wavelength stimuli have intensities under 1012 photons/cm2/s, maximum pupillary
constriction was provoked by the short wavelength stimulus; but at intensities over 1012
photos/cm2/s, the difference in pupillary constriction between long and short wavelength
stimuli dissipated (R. Kardon et al., 2009). At this intensity of long wavelength light,
either cone contribution to the magnitude of pupillary constriction may match that of
ipRGCs, or ipRGCs are being insufficiently stimulated. Assessment of ipRGC function
by comparison of maximum pupillary constriction to solely a long or short wavelength
pulse of light appears to be less predictable and repeatable than the assessment of the
post-illumination response.
The third step in the development of a pupillary test to assess ipRGC function is
to determine whether the differences in the pupillary light reflex in response to long or
short wavelength can be enhanced by prior light exposure or modulation of the temporal
properties of the stimulus. Prior light exposure does change the ipRGC response
characteristics of the pupillary light response. Mure and colleagues (Mure et al., 2009)
have demonstrated that a long wavelength (>515 nm) adapting light presented before a
short wavelength stimulus will cause an approximately 28% increase in sustained
pupillary constriction in human subjects. A short wavelength (<515 nm) adapting light
38
preceding a short wavelength stimulus had the opposite effect, decreasing sustained
constriction by approximately 21%. Zhu and colleagues (Zhu et al., 2007) have shown a
50% enhancement in pupillary constriction when a white adapting light was presented
immediately prior to a bright short wavelength stimulus in wild type mice and knockout
mice lacking rods and cones. They named this enhancement photopotentiation. In the
same study they demonstrated that only an adapting light presented to the ipsilateral eye
as the stimulus can cause photopotentiation; the effect is lost when the adapting light is
presented to the contralateral eye as the stimulus. This result suggests that
photopotentiation occurs before the optic chiasm, and the fact that rod-cone knockout
mice are able to photopotentiate suggests a bistable mechanism. As mentioned in the
previous chapter, in vitro studies have not been able to prove that melanopsin is a bistable
molecule (Enezi et al., 2011; Mawad & Van Gelder, 2008), and Zhu and colleagues (Zhu
et al., 2007) were not able to replicate in vitro the photopotentiation of the pupillary light
response or demonstrate bistability of isolated ipRGCs. Although the mechanism is still
undetermined, exposure to a bright, long wavelength “priming” stimulus before the
presentation of a short wavelength stimulus may enhance the pupillary response.
Use of a flickering stimulus is another approach to isolating ipRGC-mediated
aspects of the pupillary light response. Two studies have investigated this topic. In the
first, a human subject blind from outer retinal disease not only maintains a pupillary
response that follows a slowly flickering stimulus, but the pupillary response was greater
for the second pulse of light, as compared to the first pulse (Gooley et al., 2012). Normal
subjects showed a similarly enhanced response to the second pulse. The fact that this
39
enhancement was present for both a subject with outer retinal degeneration and normal
subjects suggests that it might be ipRGC-mediated. Additionally, this study demonstrated
that over the course of a thirty minute continuous green stimulus the pupil will initially
constrict and then will slowly redilate during the remainder of the stimulus. If the light
source flickers at any one of a wide range of frequencies (0.1-4.0 Hz), however, the pupil
will initially constrict and then remain constricted throughout the thirty minute stimulus
duration. This result does not prove that ipRGCs are responsible for the enhanced effect
of the flickering stimulus, but does suggest that a flickering stimulus is able to enhance
the pupillary light response. Furthermore, a second study on normal human subjects has
demonstrated that the amplitude of the pupillary light reflex peaks when a sinusoidal
stimulus with a frequency of 1.0 Hz is utilized (Barrionuevo et al., 2014). Frequencies
above 1.0 Hz elicited less pupillary constriction. Enhancement of the pupillary light
reflex by a flickering stimulus is a novel topic, and much work remains to better
understand the full effect of this stimulus modality.
Finally, it is important to note that pharmacological dilation of the eye receiving
the stimulus has an effect on ipRGC influence on the pupillary light response. A short
wavelength stimulus delivered to the retinal of an eye with a dilated pupil will cause a
greater consensual pupillary response in the contralateral eye, as compared to an
undilated pupil; however, pupillary dilation had no effect on the efficacy of long
wavelength stimuli (Nissen, Sander, & Lund-Andersen, 2011). Considering the fact that
ipRGC density is greatest in the extramacular retina (Hattar et al., 2002), it stands to
reason that dilation allows for more ipRGC exposure to a stimulus. Compounding the
40
dilation effect is the fact that ipRGCs are relatively insensitive to light and need large
quantities of light for activation. A dilated pupil will allow more light to reach the
extrafoveal retina, allowing for a greater ipRGC influence on the pupillary light response.
Interest is growing in the utilization of ipRGC-based pupil tests for detection of
retinal disease. ipRGCs are intriguing biomarkers for pathology due to their scarcity,
inner retinal location, and large dendridic spread. This section will outline what studies
have already been conducted to investigate pathological alterations in the pupillary light
reflex.
In healthy patients, certain demographic features have no influence over ipRGC
input into the pupillary light reflex. Race (Kankipati et al., 2010) and sex (Fan et al.,
2009; Kankipati et al., 2010) do not alter the magnitude of sustained pupillary
constriction after stimulus offset. ipRGC density in the peripheral retina has been shown
to decrease with age (La Morgia et al., 2011). The pupillary effects of normal aging are
still debated. Baseline pupil size (Daneault et al., 2012; Fotiou et al., 2007; Kankipati et
al., 2010) and certain kinetic aspects (Fotiou et al., 2007) of the pupillary response have
been shown to decrease with age. These changes do not necessarily translate into
significant changes in the human pupillary response, as several groups (Daneault et al.,
2012; Kankipati et al., 2010; R. Kardon et al., 2009) have shown that age has a negligible
effect on ipRGC-modulated characteristics of the pupillary light response, such as
sustained pupillary constriction after light offset. Other groups, however, have found that
age contributes to changes in the ipRGC-mediated aspects of the pupillary light response.
For example, one group (Herbst et al., 2012) has found that older patients exhibit an
41
enhanced pupillary reaction to bright short wavelength light, which they attributed to
increased light scatter created by lenticular cataracts. Another group has found that
cataracts inhibit the normal function of ipRGCs. Older patients with blue-filtering
cataracts display disrupted circadian rhythms and a decrease in ipRGC-mediated
melatonin suppression, as compared to age-matched controls who had undergone cataract
extraction (Brondsted, Lundeman, & Kessel, 2013). Many patients with retinal or
neurological disease have concurrent senile cataracts; therefore, characterization of the
effect that cataracts have on the ability of ipRGCs to modulate circadian rhythms and the
pupillary light reflex is essential for the development of a pupillary test dependent on
measuring the differences in the pupillary light responses to short and long wavelength
stimuli.
Outer retinal diseases preferentially destroy rods, cones, and/or the retinal
pigment epithelium. It might seem that these diseases are largely unfit for a diagnostic
test based on a photoreceptor that resides in the inner retina, but this assumption is not
necessarily true. Diseases such as retinitis pigmentosa offer a unique insight into ipRGC
influence over the pupillary light reflex. Rod and cone damage causes retinitis
pigmentosa patients to display severely attenuated transient pupillary light responses to
dim long and short wavelength stimuli (R. Kardon et al., 2009, 2011). Spared is the
sustained pupillary constriction present after the offset of a bright short wavelength
stimulus (R. Kardon et al., 2009, 2011; Park et al., 2011). These tests are the human
equivalent to experiments conducted on knockout rodents lacking rods and cones; for
they provide substantial evidence that a bright, short wavelength stimulus can activate
42
ipRGCs and affect the pupillary light reflex. Furthermore, a rodent model has
demonstrated that in late outer retinal disease ipRGC density declines by 67% (Esquiva,
Lax, & Cuenca, 2013). This finding has been shown to be of significance in human
subjects with an advanced form of retinitis pigmentosa. In the rare yet severe NR2E3
iteration of retinitis pigmentosa, ipRGC degeneration occurs quickly after rod and cone
death, causing attenuation of the post-illumination pupil response to a short wavelength
stimulus (Kawasaki, Crippa, Kardon, Leon, & Hamel, 2012). A diagnostic test for most
outer retinal diseases would be different from many of the others discussed in this
chapter, as abnormal rod-cone-driven pupillary constriction would be compared to the
ipRGC-driven component. Instead of a comparison between the pupillary light response
to bright long and short wavelength stimuli, the comparison would be between a bright
and dim stimulus of the same wavelength. Some advanced outer retinal diseases with
ipRGC destruction may be monitored using a comparison of the sustained response
elicited by long and short wavelength stimuli.
New research on the effects of diabetes mellitus on the ipRGC-mediated pupillary
response have offered mixed results. Small capillaries found extensively in the retina’s
nerve fiber layer and ganglion cell layer are the first structures damaged by elevated
blood sugar levels (Alexander, 1994). Damage to the vessels supplying ipRGCs likely
causes an alteration in their function. Surprisingly, a rodent model has demonstrated that
the pupillary light reflex to short wavelength light is enhanced in diabetic mice, as
compared to controls (Kumar & Zhuo, 2011). Human studies have yielded varying
results. In the absence of severe unilateral retinopathy, traditional white-light pupil tests –
43
such as the swinging flashlight test – are unable to detect diabetic retinopathy
(Zangemeister, Gronow, & Grzyska, 2009). Feigl and colleagues (Feigl et al., 2012) show
that diabetic patients with or without retinopathy demonstrate a reduced sustained
pupillary response after the offset of a bright short wavelength stimulus, as compared to
controls. They also establish a negative correlation between diabetes duration and
severity and the attenuation of the post-illumination sustained response. Contrarily,
Kardon and colleagues (R. Kardon et al., 2009) found no such reduction in the ipRGC
pupillary response in diabetic patients, unless the disease was unilateral. Despite these
inconclusive results, investigations into the development of a pupil-based screening test
will continue in an attempt to efficiently detect retinopathy in a diabetic population that is
growing worldwide (Cowie et al., 2006).
Retinal ganglion cell axons are damaged in optic nerve pathology. ipRGCs project
axons to their targets throughout the thalamus and midbrain via the optic nerve (Hattar et
al., 2002) and are subsequently susceptible to ischemic, compressive, and chemical insult.
For this reason, a pupillary test to detect ipRGC dysfunction could be a sensitive
screening tool for optic neuropathies. Several investigations into this topic have already
occurred and are discussed below.
Hereditary neuropathies such as dominant optic atrophy and Leber’s hereditary
optic neuropathy have been shown to have a minimal effect on the ipRGC-mediated
aspects of the mammalian pupillary light reflex. A rodent model for dominant optic
atrophy suggests that ipRGC quantity, morphology, and genotype are unaffected by this
disease (Perganta et al., 2013). Furthermore, this study demonstrated that rodents bred
44
with dominant optic atrophy have similar circadian rhythms and pupillary responses, as
compared to controls. Two small human studies have found similar results. Patients with
dominant optic atrophy (Kawasaki, Collomb, Leon, & Munch, 2014) and Leber’s
hereditary optic neuropathy (La Morgia et al., 2010) do not show abnormalities in the
ipRGC-mediated pupillary response until end-stage disease. Other evidence suggests that
hereditary optic neuropathies mildly affect ipRGCs. A study on Leber’s hereditary optic
neuropathy patients found reduced maximum pupillary constriction and post-illumination
constriction, both of which are thought to be markers of ipRGC function (Moura et al.,
2013). The effect found in this study was small, however, and it is unclear to what extent
ipRGCs are damaged in these diseases. In hereditary optic neuropathies, ipRGCs seem to
be relatively spared. Investigations into the mechanisms of protection utilized by these
cells could be beneficial in the development of synthetic defense mechanisms for
traditional retinal ganglion cells.
Ischemic optic neuropathies also have a limited effect on ipRGC pupillary
influence. Studies on unilateral non-arteritic anterior ischemic optic neuropathy patients
have shown that the pupillary response to both long and short wavelength stimuli is
reduced in the affected eye, as compared to the fellow eye (Herbst et al., 2013; R. Kardon
et al., 2009). Reduction of the pupillary light response to long and short wavelength
stimuli does not specifically imply selective damage to ipRGCs. Furthermore, sustained
pupillary constriction after the offset of a short wavelength stimulus is not affected in
non-arteritic anterior ischemic optic neuropathy, as compared to controls (Herbst et al.,
45
2013). Although this result suggests that ipRGCs may be selectively spared, more
investigation is needed to substantiate this hypothesis.
ipRGC function as a biomarker for glaucomatous retinal ganglion cell death has
received the most attention of all retinal and neurological conditions. Glaucoma deserves
this devotion because it is a difficult disease to diagnose in its early stages and early
detection and treatment are essential for a good visual outcome (Leske et al., 2003).
Current glaucoma screening tests are either subjective, such as automated visual field
screening tests, or demand certain levels of clinical skill, such as intraocular pressure
measurement. An objective, easily administered screening test would be of great clinical
value to the early glaucoma recognition and intervention. Several investigations have
studied the merit of using the pupillary light response to detect glaucomatous damage
with the long-term goal of developing and effective diagnostic tool. The results of these
investigations are discussed below.
Similar to hereditary optic neuropathies, some evidence suggests that ipRGCs are
protected from glaucomatous damage. Two investigations utilizing
immunohistochemistry have shown that ipRGCs are selectively spared from damage
secondary to induced ocular hypertension (La Morgia et al., 2010; Li et al., 2006).
Another rodent study has demonstrated that ipRGC cellular density is resistant to
intravitreal injections of an apoptotic mediator, NMDA (a glutamate receptor agonist),
that causes a reduction in overall RGC densities (DeParis, Caprara, & Grimm, 2012).
These findings have been replicated in a small human clinical study. No difference in
sustained pupillary constriction after the offset of a short wavelength stimulus was found
46
between controls and early or moderate stage glaucoma patients (Feigl, Mattes, Thomas,
& Zele, 2011). The only difference found was between controls and advanced glaucoma
patients. Although the results of these specific tests suggest that ipRGCs are an
ineffective biomarker for glaucomatous damage to retinal ganglion cells, other studies on
the topic have come to different conclusions.
Evidence exists suggesting that glaucomatous damage does affect ipRGCs in a
detectable manner. A rodent ocular hypertension model has demonstrated that short
wavelength light exposure alters the expression of certain ipRGC proteins that are
essential to intrinsic phototransduction and cell survival (Osborne, Li, Ji, Mortiboys, &
Jackson, 2008). This group hypothesizes that a loss of melanopsin expression in ipRGCs
might be detectable with a pupil test. Additional rodent models have shown that chronic
ocular hypertension damages ipRGCs and traditional retinal ganglion cells projecting to
the superior colliculus (de Zavalia et al., 2011; Wang et al., 2008). Other studies have
shown a difference between glaucoma patients and controls in the human pupillary
response to short and long wavelength light. Kankipati and colleagues (Kankipati, Girkin,
& Gamlin, 2011) have demonstrated that the sustained pupillary response after short
wavelength stimuli offset is similar to that seen after long wavelength stimuli offset in
glaucoma patients, suggesting detectable damage to ipRGCs. In control patients, the
sustained constriction after short wavelength stimulus offset is much greater than after
long wavelength offset (Kankipati et al., 2010, 2011). Another human investigation found
that no difference in sustained post-illumination pupillary constriction between long and
short wavelength stimuli was found in eyes with ocular hypertension (R. Kardon et al.,
47
2009). A difference was found, however, in the sustained and transient pupillary response
to both long and short wavelength light when hypertensive eyes were compared to
control eyes, suggesting damage to both traditional and intrinsically photosensitive retinal
ganglion cells. Finally, a third human study has found that glaucoma patients with central
field loss have an attenuated sustained pupillary response after short wavelength stimulus
offset, as compared to patients with more peripheral field loss (Bergamin & Kardon,
2002). This result is surprising considering that ipRGCs reside mostly in the extrafoveal
retina (Hattar et al., 2002), but still demonstrates that aspects of the human pupillary
response thought to be controlled by ipRGCs are affected by glaucoma.
Non-pupillary evidence suggests that ipRGCs are damaged in glaucoma. Such
evidence is provided by studies investigating circadian rhythm disruption in glaucoma
patients. Two large studies (Drouyer et al., 2008; Lanzani et al., 2012) have shown that
many aspects related to circadian cycles, especially sleep quality, are altered by
glaucoma. Since ipRGCs project prominently to the suprachiasmatic nucleus,
glaucomatous insult to them is hypothesized as the source of circadian abnormalities in
glaucoma patients (Lanzani et al., 2012). Although clinical quantification of circadian
irregularities is cumbersome and unfit as a screening tool, it does provide additional
evidence that ipRGCs are damaged in a detectable manner from glaucoma.
Finally, some neurological disorders might be detectable by quantifying the
ipRGC pupillary response. Studies into detecting neurological disease by assessment of
ipRGC function have been mixed. A rodent model has demonstrated retinal ganglion cell
loss in the months following a blast injury, but no pupillary abnormalities in response to
48
either a long or short wavelength stimulus were observed (Mohan, Kecova, HernandezMerino, Kardon, & Harper, 2013). Contrarily, a recent study has identified trigeminal
nerve activity in response to short wavelength light, raising suspicion that ipRGCs
mediate the photophobia frequently associated with post-concussion syndrome
(Okamoto, Tashiro, Chang, & Bereiter, 2010). In seasonal effective disorder, diminished
retinal sensitivity has been shown to be measureable by quantifying loss in the ipRGCmediated aspects of the pupillary light reflex (Roecklein et al., 2013). More evidence is
needed to determine whether ipRGCs can be used to detect neurological disease.
This introduction has provided an overview of many topics pertaining to the
pupillary light reflex. First, the history of diagnostic pupillary testing was described along
with its current clinical applications. Then the photopigment melanopsin was introduced
and the unique characteristics and functions of melanopsin-containing intrinsically
photosensitive retinal ganglion cells were outlined. Finally, the most recent ipRGC-based
pupil tests were described in detail and their applications in ocular pathology were
reviewed.
Previous studies on both animal models and human subjects have provided some
important characteristics of the ipRGC-modulated pupillary response. A short wavelength
stimulus will elicit stronger sustained pupillary responses than a long wavelength
stimulus of similar brightness and duration. Exposure to a long wavelength adapting light
will enhance the subsequent transient and sustained pupillary response to a short
wavelength stimulus. Most investigations of the ipRGC-modulated pupillary response
utilized a stimulus consisting of a single pulse of light, varying in duration. If an adapting
49
stimulus was used, it was typically long in duration. The poor temporal resolution of
ipRGCs might respond best to a flickering stimulus. Tests utilizing a flickering stimulus
are rare and only present one wavelength of light when used. Overall, data characterizing
the pupillary response to a slowly flickering light is scarce. No study has yet investigated
what affect a slowly flickering stimulus alternating between long and short wavelength
light has on the human pupillary light response.
Furthermore, detection of retinal and neurological disease by searching for an
alteration in the ipRGC-modulated pupillary response has enjoyed only moderate
success. All investigations into the pathological alterations of ipRGCs and the resulting
changes in the pupillary light reflex employ methods dependent on finding a difference in
the pupil’s response to long and short wavelength stimuli. The results have been mixed,
as some papers have reported differences while others have not. Alternative methods of
quantifying ipRGC input into the pupillary light reflex that improve the accuracy of
detection are warranted.
The goal of the work presented here is to characterize the flicker sensitivity of the
human pupillary light reflex and isolate the ipRGC-driven component of the pupil
response based on the unique temporal properties of these photoreceptors. Specifically,
this work investigates the changes in pupil size that occur in response to long or short
wavelength flickering light of different intensities and flicker frequencies. It also
determines the effect of prior long wavelength light exposure on the pupil responses to
short wavelength light, and vice versa, through the use of alternating long and short
wavelength stimuli. By optimizing the parameters that cause the greatest differences in
50
the pupil responses to the long versus short wavelength light stimuli, my aim is to
develop a flicker-based testing protocol that can be used to assess the ipRGC-driven
component of the pupillary light response in human patients.
51
Chapter 4: Methods
This research was approved by the Institutional Review Board (IRB) in
Biomedical Sciences at The Ohio State University and the tenants of the Declaration of
Helsinki were followed. A group of healthy university students (N = 20; age range: 23 to
27) was recruited for this study and informed consent was obtained from all participants.
One subject exhibited excessive blinking during the light exposures and withdrew from
the study during the first visit, and an equipment malfunction rendered a portion of the
data for another subject unusable. In all, 18 subjects completed the study (10 males, 8
females). Each of these subjects had had a comprehensive eye examination within the
previous 18 months and reported no significant ocular or neurological disease. The
spherical equivalent refractive error of the 18 subjects ranged from -7.00 D to +1.25 D
(mean = -2.33 DS OD and -2.49 DS OS) and corrected visual acuity (measured at each
visit) was at least 20/25 in each eye.
The light stimuli were generated using a custom-made optical system that was
based on an apparatus utilized by Kankipati and colleagues (Kankipati et al., 2010),
which employed an extended Maxwellian-view system. In a traditional Maxwellian-view
system, a single convex lens places an image of a light source at the pupillary plane of an
observer (Westheimer, 1966). None of the light reaching the pupil is obstructed by the
iris, allowing for a complete, intense image of the light source. Traditional Maxwellian52
view systems depend on exact placement of the pupil and the secondary focal point of the
lens and a monocular viewing system to deliver. Extended Maxwellian-view systems
employ two convex lenses of equal power, separated by a distance of double their focus
lengths (Beer, MacLeod, & Miller, 2005). A diffuser is placed after the second light
source. Instead of a single image placed at the pupil, an extended image is placed in the
region around the pupil. This system sacrifices some of the intensity and saturation of
traditional Maxwellian-view system but allows for more flexibility in pupil location.
For the system employed in this study, blue light (peak λ= 465 nm, dominant λ =
470 nm, full width at half maximum = 22 nm) and red light (peak λ= 635 nm, dominant λ
= 625 nm, full width at half maximum = 17 nm) were generated using a light-emitting
diode (LED) illumination system (DiCon LED, Richmond CA). Two 3” x 3” Fresnel
lenses (Edmund Optics, Barrington NJ) with 3” focal lengths were placed in succession
on an optical bench, separated by a distance of 6”. The LED-generated light was
transmitted through a fiber optic light guide (Edmund Optics), with the end of the guide
(3/8” diameter) placed at the focal point (3” away) of the first Fresnel lens. A 5°
holographic diffuser (Edmund Optics) was placed against the second Fresnel and
produced a uniform stimulus with a visual angle of approximately 53 degrees. Using a
chin and forehead rest, the subject was placed in the apparatus so that their left cornea
was set at the focal point (3”) of the second Fresnel lens with the diffuser. A schematic
representation of the stimulation and recording apparatus can be found in Figure 2.
53
Figure 2. Schematic of the extended-Maxwellian view system utilized in this
study. The Fresnel lenses and LED source were contained within an opaque
housing unit (not depicted) in order to minimize the right eye’s light exposure. A
barrier extending from the edge of this housing to the subject’s nose provided
additional light shielding.
In all experiments, the pupil of the left eye was dilated with 0.5% tropicamide.
Monocular dilation was performed to minimize changes in retinal illumination during the
light pulses (open-loop paradigm). The subjects were placed in the apparatus for the first
trial 30 minutes after instillation of the drop, with the lights off for the last 20 minutes to
ensure dark adaptation of both rods and cones (Rushton, 1963) and ipRGCs (Wong et al.,
2005). The apparatus was located in a dark window-less room and was separated from
54
the computer controlling the LED system by a black curtain. The flickering, LEDgenerated stimulus was presented to the dilated left eye. Light irradiance at the corneal
plane was determined using an optical power meter (Newport, Irvine CA) the irradiance
was adjusted through both computer control (LightControl software, DiCon LED) and the
addition of neutral density filters in front of the fiber optic light guide. Under infrared
illumination, a Sony HDR-XR500V high-definition digital video camera (Tokyo, Japan)
was focused on the pupil of the right eye and used to record the consensual pupil
response. The camera recorded at a rate of 60 frames per second.
Three sets of experiments were conducted, each involving two experimental
sessions that were separated by at least 24 hours. Testing was conducted from the hours
of 12:00 PM to 4:00 PM to limit any effect of circadian shifts in ipRGC sensitivity
(Figueiro et al., 2005). In the first experiment, a group of subjects (n= 6) sat for two
separate sessions investigating the effect of stimulus irradiance (range: 1x1012 to 7x1015
photons per centimeters squared per second; see Tables 1 and 2) on the pupillary light
response to slowly flickering (constant rate of 0.1 Hz) red or blue light presented for 1
minute in duration. Each session consisted of five trials separated by 10 minute dark
adaptation periods. Half the subjects (n = 3) were tested with four irradiances of blue
light in the first session and four irradiances of red light in the second session, while the
other half (n = 3) were tested in the opposite order (red before blue). The light stimuli
were always presented in order of increasing illumination. The fifth trial used a 0.1 Hz
flickering light (~1015 photons/cm2/s) that was a different color (red or blue) than the
light used in the preceding four trials.
55
Photons/cm2/s
1 x 1012
Scoptoic
Trolands
1.88 × 109
Photopic
Trolands
1.01 × 109
1 x 1013
1.88 × 1010
1.01 × 1010
1 x 1014
1.88 × 1011
1.01 × 1011
1 x 1015
1.88 × 1012
1.01 × 1012
Table 1. Light levels of the blue stimulus utilized in this study. Photons/cm2/s measured
at the corneal surface. (Spillmann & Werner, 1990)
Photons/cm2/s
7 x 1012
Scoptoic
Trolands
7.30 × 107
Photopic
Trolands
3.58 × 109
7 x 1013
7.30 × 108
3.58 × 1010
7 x 1014
7.30 × 109
3.58 × 1011
7 x 1015
7.30 × 1010
3.58 × 1012
Table 2. Light levels of the red stimulus utilized in this study. Photons/cm2/s measured at
the corneal surface. (Spillmann & Werner, 1990)
In the second experiment, a different group of subjects (n = 6) sat for two separate
sessions investigating the effect of flicker frequency (range: 0.05 to 1.0 Hz) on the
56
pupillary light response to the red and blue light (irradiance of ~1014 photons/cm2/s for
each frequency tested) stimuli presented for 1 minute in duration. Each session consisted
of five trials separated by 10 minute dark adaptation periods. Half the subjects (n = 3)
were tested with the five different flicker frequencies of the blue light in the first session
and then the five flicker frequencies of red light in the second session, while the other
half were tested in the opposite order (red before blue). The order of presentation for the
different frequencies was randomized in each session.
In the third experiment, a different group of subjects (n = 6) sat for two separate
sessions investigating the effect of prior light exposure on the pupillary light response to
flickering red and blue light. Each session consisted of five trials separated by 10 minute
dark adaptation periods. For the first session, the subjects were stimulated with a slowly
flickering (0.1 Hz, 2 minute duration) light that alternated back and forth between the red
and blue light stimuli. For the first 3 trials, the irradiance of the lights increased by one
log unit (~1012, ~1013, ~1014 photons/cm2/s) with each successive trial. In the last two
trials, the subject was stimulated with the red light alone (7x1014 photons/cm2/s) and the
blue light alone (1x1014 photons/cm2/s), presented at the 0.1 Hz flickering rate for 1
minute. For the latter two trials, the ‘red light only’ stimulus was presented before the
‘blue light only’ stimulus in 3 of the subjects, while the opposite order was used for the
other 3 subjects. For the second session, six alternating pulses (5 s in duration) of the red
and blue light (~1014 photons/cm2/s) were presented to each subject. The gap of darkness
that separated the light pulses was varied in each trial (2.5 s, 5 s, 25 s, 50 s, 100 s) in
57
order to assess the persistence of the effect of prior light exposure. The order of the five
trials used in this second session was randomized.
The digital recordings of all trials were analyzed offline. The videos were
converted to uncompressed .avi files and opened using ImageJ (National Institutes of
Health, Bethesda MD) image processing software (Schneider, Rasband, & Eliceiri,
2012). In ImageJ, the circle tool was used to manually place a circle around the perimeter
of the pupil in the image and to calculate the area in pixels. Using the video recordings,
pupil area measurements were made twice (every 30th frame) or four times (every 15th
frame) per second.
The pupil measurements (in pixel area) prior to the light exposures were averaged
to determine the ‘baseline pupil size.’ The smallest pupil area measurement for a given
subject during a single session was identified and used as the ‘minimum pupil size.’ All
other pupil measurements were then normalized using the following equation:
𝑁𝑜𝑟𝑚𝑎𝑙𝑖𝑧𝑒𝑑 𝑃𝑢𝑝𝑖𝑙 𝐶𝑜𝑛𝑠𝑡𝑟𝑖𝑐𝑡𝑖𝑜𝑛
=
𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑃𝑢𝑝𝑖𝑙 𝑆𝑖𝑧𝑒 − 𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑑 𝑃𝑢𝑝𝑖𝑙 𝑆𝑖𝑧𝑒
𝑥 100
𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑃𝑢𝑝𝑖𝑙 𝑆𝑖𝑧𝑒 − 𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝑃𝑢𝑝𝑖𝑙 𝑆𝑖𝑧𝑒
Thus, 0% represented the average baseline pupil size and 100% represented the
maximum pupil constriction achieved for a subject within each experimental session. For
each experiment, normalized pupil measurements from all six subjects were averaged at
each time point collected. These averaged normalized pupil responses were then plotted
58
with standard error of the mean error bars on a Cartesian coordinate system (x-axis: time
from light onset [s]; y-axis: normalized pupil constriction [%]; see Fig. 3).
To analyze the amplitude of the pupillary response to the flickering red and blue
light, the normalized pupil constriction data was translated from the time domain to the
frequency domain by performing a fast Fourier transform (FFT) of the data in Microsoft
Excel. A total of either 128 or 256 data points was used for each transform, depending on
the duration of the stimulus (1 to 2 minute) and sampling frequency of the pupil
measurements (2 to 4 per second). For each trial, the FFT amplitude was determined at
the frequency of the flickering light stimulus used in that trial (i.e. at the fundamental
frequency). This method enabled the average amplitude of the pupil flicker during the 1
to 2 minute trials to be calculated objectively. Similar to the amplitude of a sine wave, the
FFT amplitude provides an estimate of half the difference between the average maximum
values minus the average minimum values for a given waveform. The normalization of
the data and determination of the FFT amplitude is illustrated in Figure 3. Decay
functions were utilized to analyzed redilation characteristics in experiments two and three
(see results).
All data is expressed as the mean ± standard error of the mean (SEM). Statistical
comparisons of the mean FFT amplitudes and the change in the pupil constriction and redilation during the flickering stimuli using paired two-tailed T-tests and repeated-measure
ANOVA tests were done in SigmaPlot 12 (Systat Software, San Jose CA).
59
A
B
1
C
2
D
Figure 3. Quantification of pupil size fluctuation evoked by flickering light stimuli. A)
Example trace of change in pupil area (in pixels) for a subject stimulated with 1x1014
blue light flickering at 0.1 Hz (5 s on and 5 s off) for 1 min. Inset: Images illustrate pupil
size in this subject before (1) light exposure and at maximum constriction (2). B) The
data was normalized, with the average baseline pupil size set at 0% and the maximum
constriction (smallest pupil size) set at 100%. C) After a fast Fourier transform (FFT) of
the data was performed, the peak amplitude occurs at the frequency (0.1 Hz) of the
flickering light stimulus. D) Magnified view of the same trace in B), with the solid gray
line indicating the average pupil size during the time period shown. The addition and
subtraction of the peak FFT amplitude (11.1%) from the average pupil size is shown by
the dotted gray lines. Twice the FFT amplitude provides an estimate of the average
difference between the peaks and troughs in pupil size during the 1 min light stimulus.
60
Chapter 5: Results
In the first experiment, 6 subjects participated in two experimental sessions in
which the pupil responses to 0.1 Hz (5 s on; 5 s off) flickering red and blue light of
different irradiances were recorded (testing strategy in Figure 4A). Although the software
(DiCon LightControl) used to control the LED light source was set at 0.1 Hz, subsequent
measurement of the timing of the light pulses using frame-by-frame video analysis
indicated that the light actually flickered on and off at a slower frequency of 0.095 Hz.
For convenience, this setting is referred to as 0.1 Hz throughout this work.
At an irradiance denoted as ‘12 log units’, the blue stimulus was measured as
1x1012 photons/cm2/s at 470 nm while the red stimulus was measured as 7x1012
photons/cm2/s at 625 nm. The difference in irradiance between the red and blue lights
was chosen based on pilot studies that sought to equalize the initial pupil constriction
induced by the two stimuli. The near-complete overlap of the red and blue traces of pupil
size (Figure 4B) shows that the pupil constriction and re-dilation induced by the two
stimuli were almost identical at these irradiances. Quantitatively, there was no significant
difference (P = 0.150, paired T-test) in the amplitude of the pupil fluctuation (after
performing FFT of data; see Figure 3) induced by the red versus blue flashing light
stimuli at the ‘12 log unit’ irradiances (Figure 4F). After increasing the irradiance of both
the blue (1x1013 photons/cm2/s) and red (7x1013 photons/cm2/s) light stimuli by one log
61
unit, the mean amplitude of the pupil flicker induced by the blue stimulus was less than
that for the red stimulus (Figure 4C, F), but the difference did not quite achieve statistical
significance (P = 0.078). However, with an additional increase in irradiance of 1 log unit
(blue: 1x1014 photons/cm2/s; red: 7x1014 photons/cm2/s), there was a striking difference
in the re-dilation that occurred during the 5 s ‘light off’ periods for the two stimuli
(Figure 4D). At these ‘14 log unit’ irradiances, the amplitude of the pupil flicker evoked
by the blue flashing light was substantially (P = 0.003) lower than that for the flashing
red light (Figure 4F). A significant (P = 0.014) difference in the pupil fluctuation induced
by the blue versus red light stimuli persisted when the irradiance increased (blue: 1x1015
photons/cm2/s; red: 7x1015 photons/cm2/s) one more log unit (Figure 4E, F).
Comparing the amplitude of pupil fluctuation (Figure 4F) evoked by the four
irradiances of blue light, there was a significant change (P < 0.001, one-way repeated
measures ANOVA) in the amplitude as irradiance increased. Posthoc all-pairwise
comparisons revealed that the amplitudes for each of the four blue irradiances were
significantly (P < 0.05, Holm-Sidak) different from each other except for the two
dimmest stimuli (1x1012 versus 1x1013 photons/cm2/s; P = 0.075). For the red stimuli, the
amplitudes of the pupil fluctuation evoked by the three dimmest irradiances were not
significantly (P > 0.05) different from each other, but they were all significantly (P <
0.01) larger than the amplitude associated with the brightest (7x1015 photons/cm2/s) red
light stimuli. With a larger contribution of ipRGCs to the PLR, the pupil fluctuation
elicited by the flickering stimuli would be expected to decrease (see Discussion). Thus,
the greater decrease in FFT-derived amplitudes that occurred as the irradiance of the blue
62
light increased, relative to that for the red light, is consistent with the greater involvement
of blue light-sensitive ipRGCs.
To determine whether pupil constriction and re-dilation were changing over time
in a given trial, we compared the maximum constriction caused by the first pulse to that
caused by the last (6th) pulse in each trial (Figure 4G). There was no significant (P > 0.05,
paired T-tests) change in constriction occurring over time in any of the trials, with the
exception of the brightest (1x1015 photons/cm2/s) blue light stimulus. At this irradiance of
blue light, the pupil constriction was more pronounced (P = 0.006) at the end of the trial
compared to the start (Figure 46E, G). There was a trend for the pupil constriction due to
the brightest (7x1015 photons/cm2/s) red light to also increase by the last pulse, as
compared to the first pulse, but this change did not reach statistical significance (P =
0.060). A similar analysis was performed on the re-dilation that occurred between the 1st
and 2nd light pulse versus that which occurred between the 5th and 6th light pulses (Figure
4H). There was a statistically significant (P = 0.018, 0.010, and 0.020, respectively)
change in the re-dilation over time for the red light stimuli at the 12, 13 and 14 log unit
irradiances. At these lower red light irradiances, the re-dilation that occurred after each
light pulse tended to become less by the end of the 1 minute-long flickering light
stimulus. Although there was a similar trend for the 12 and 13 log unit irradiances of the
blue light, there was more variability in the data and the change in re-dilation was not
significant (P > 0.05) for any of the blue light stimuli.
63
A
B
C
12 log units
D
13 log units
E
14 log units
F
G
15 log units
H
Figure 4. Effect of light irradiance on pupil responses to 0.1 Hz flickering red or blue
light. A) Outline of testing protocol used for the subjects (n = 6) participating in these
two experimental sessions. B-E) Traces of mean (± SEM) pupil size (normalized; 100%
= smallest measured pupil area in experimental session, and 0% = baseline pupil area)
elicited by 0.1 Hz flickering blue or red light (bars at top indicate light was on) of four
different irradiances. The blue light stimuli had irradiances of 1x10y photons/cm2/s and
the red light stimuli had irradiances of 7x10y photons/cm2/s, where y equaled B) 12, C)
13, D) 14 or E) 15. F) Mean (± SEM) amplitude of the fluctuation in the pupil responses
(Continued)
64
(Figure 4: Continued)
to the flickering lights, as determined by fast Fourier transforms (FFT) of the data. * P <
0.05, ** P < 0.01, Paired T-test. G) Plot of difference (± SEM) in maximum pupil
constriction elicited by the 6th versus 1st light pulses (see inset; 1st ‘peak’ subtracted from
6th ‘peak’). H) Plot of difference (± SEM) in pupil re-dilation occurring after the 1st
versus 5th light pulses (see inset; 1st ‘valley’ subtracted from 5th ‘valley’). * P < 0.05, ** P
< 0.01, Paired T-test. A significant value indicated that the pupil constriction (‘peaks’) or
recovery (‘valleys’) changed.
The data used in Figure 4 for the brightest (‘15 log units’) blue and red light
stimulation trials were obtained in the fourth trial of the two experimental sessions. As
shown in Figure 4A, the fifth trial in each session consisted of the brightest light stimulus
that was opposite in color to the light that was used in the preceding four trials of the
session. The overall FFT amplitude evoked by the 1x1015 photons/cm2/s blue light was
9.7% ± 1.4 when it was presented during the fourth trial of the ‘Blue Session’, and it was
8.1% ± 1.8 when it was presented as the fifth trial of the ‘Red Session’. While the
difference in the amplitude of the pupil fluctuation between the two trials was most
pronounced after the first light pulse (Figure 5A), the FFT-derived amplitudes were not
significantly (P = 0.295, paired T-test) different from each other (Figure 5C). This
indicated that the overall amplitude of pupil fluctuation evoked by this flickering blue
light stimulus was repeatable across the two experimental sessions (Figure 5C).
65
Similarly, there was no difference (P = 0.113) in the pupil flicker amplitude for the
7x1015 photons/cm2/s red light stimulus, as it was 15.5% ± 2.6 when measured in the
‘Red Session’ and it was 17.9 ± 1.7 when measured in the ‘Blue Session’ (Figure 5B, C).
In either experimental session, the FFT-derived amplitude for the blue light was
significantly (P < 0.01) reduced compared to that for the red light stimuli. These results
indicate that prior exposure to light of the opposite color did not significantly affect the
pupil responses to the brightest blue and red light stimuli when separated by 10 min of
dark adaptation.
A
B
C
15 log units
15 log units
Figure 5. Inter-session repeatability of pupil responses to 0.1 Hz flickering light. A)
Traces of normalized mean pupil size to 1x1015 photons/cm2/s blue light and B) 7x1015
photons/cm2/s red light, with the two trials conducted at the two experimental sessions
(see Figure 2A). C) FFT-derived mean amplitudes of the pupil fluctuation evoked by the
flickering light. ** P < 0.01, NS = not significant, Paired T-test.
66
For the second experiment, 6 different subjects participated in two experimental
sessions in which the pupil response was recorded after stimulation with red and blue
light that flickered at different frequencies (outline of testing strategy shown in Figure
6A). The flicker frequencies of the light stimuli ranged from 0.05 Hz (10 s on; 10 s off) to
1.0 Hz (0.5 s on; 0.5 s off), and the order of the stimuli within either session was
randomized. Regardless of frequency, the stimuli were 1 min in duration for every trial
and were presented at an irradiance of 1x1014 photons/cm2/s for the blue light and 7x1014
photons/cm2/s for the red light. These irradiances (‘14 log units’) were chosen based on
the data from the first experiment, which showed a significant difference in the flicker
amplitude evoked by the red versus blue light when used at this irradiance and flashed at
0.1 Hz (Figure 4F).
In response to the light presented at the three slowest flicker frequencies (0.05,
0.1 and 0.2 Hz), the amplitude of the pupil fluctuation evoked by the flashing blue light
was significantly (P = 0.009, 0.008, 0.045, respectively; paired T-tests) less than that
evoked by the flashing red light (Figure 6B-D, G). The significant difference between the
0.1 Hz flickering red and blue light stimuli is consistent with that observed with the 6
different subjects tested in the first experiment (Figure 4D, F). As the flicker rate of the
light stimuli increased to 0.5 Hz, the difference in the mean amplitude of pupil fluctuation
for red versus blue light was no longer statistically (P = 0.174) significant (Figure 5 E,
G). Similarly, there was no difference (P = 0.315) in the pupil fluctuation that occurred in
response to the blue versus red light stimuli that were presented at a flicker rate of 1.0 Hz
(Figure 6F, G).
67
A
B
C
0.05 Hz
0.1 Hz
D
E
0.2 Hz
0.5 Hz
F
G
1.0 Hz
Figure 6. Effect of flicker frequency on pupil responses to flashing red or blue light. A)
Outline of testing protocol used for the subjects (n = 6) participating in these two
experimental sessions. B-F) Traces of mean normalized pupil size elicited by 1x1014
photons/cm2/s blue light or 7x1014 photons/cm2/s red light, presented at flicker
frequencies of B) 0.05, C) 0.1, D) 0.2, E) 0.5 or F) 1.0 Hz. Error bars omitted from the
1.0 Hz data to facilitate visibility of the smaller fluctuations in pupil size. G) Mean FFTderived amplitudes of pupil fluctuation evoked by the flickering lights. * P < 0.05, ** P <
0.01, Paired T-test.
68
While the overall pupil fluctuation was not different between the red and blue
light stimuli when presented at flicker frequencies faster than 0.5 Hz, examination of the
traces (Figure 6E, F) reveal differences in re-dilation that occurred at the end of the trials.
To assess whether flicker frequency affected the pupil recovery at the end of the trials,
the pupil size during the 10 seconds after the blue light turned off in the 5 trials (blue
traces in Figure 6B-F) were re-plotted together (Figure 7A). A similar re-plotting of the
re-dilation that occurred at the end of the 5 red light trials (red traces in Figure 6B-F)
demonstrated how similar the rates of pupil size recovery were, irrespective of flicker
frequency (Figure 7B). The recovery in pupil size during the 10 seconds following each
trial were then averaged together and fit with a simple exponential decay equation (y = e –
bx
) to determine if the re-dilation occurred at a proportional rate over this period. For the
blue light stimuli, there was an excellent fit (R2 = 0.97) when b = 0.068, while the red
light stimuli was best fit (R2 = 0.99) using a faster decay constant of b = 0.125. Therefore,
these data indicate that the similarity in FFT-derived amplitudes for the red versus blue
stimuli that flickered at 0.5 and 1.0 Hz was not due to an alteration in the re-dilation
dynamics of the pupil response at these faster frequencies. Rather, there was simply not
enough time during the brief ‘lights off’ periods during these trials for pupil fluctuation
(to red versus blue stimuli) to separate significantly from each another, at least with this
sample size.
69
A
B
C
Blue light
Red light
Figure 7. Recovery rate of pupil re-dilation after stimulation with different flicker
frequencies of red or blue light. A-B) Normalized pupil size in the 10 s of darkness
following stimulation with different frequencies of A) blue or B) red light. The data
represents the tail of the blue and red traces, respectively, shown in Figure 5B-F, starting
after last light pulse turned off. C) The data in A) and B) were averaged together (solid
lines) and re-normalized so that at x = 0, y = 1. Dotted lines represent regression curves
using equation y = e –bx, where b = 0.068 (blue) and 0.125 (red).
In the third experiment, 6 additional subjects were recruited to participate in two
experimental sessions. In the first session, the first three trials utilized an alternating red
and blue light stimulus that was presented for 2 min at three irradiance levels, matching
the 12, 13 and 14 log unit irradiance levels used in the first experiment, all with a flicker
frequency of 0.1 Hz. The fourth and fifth trials consisted of a 1 min light stimulus that
flickered at 0.1 Hz and consisted of either the blue light (1x1014 photons/ cm2/s or red
light (7x1014 photons/cm2/s) alone (outline of testing strategy shown in Figure 8A). As in
the previous experiments, the pupil flicker evoked by this ‘blue light only’ stimulus was
70
significantly less than that evoked by the ‘red light only’ stimulus (non-hatched blue and
red bars, Figure 8G).
The mean pupil response to the alternating red/blue stimulus, when presented at
an irradiance of ‘12 log units’ (blue: 1x1012 photons/cm2/s; red: 7x1012 photons/cm2/s), is
shown in Figure 8B. To analyze the amplitude of the pupil fluctuation elicited by the blue
versus red light, the data obtained during the six blue light stimulations (blue portions of
trace) were separated from the data obtained during the six red light stimulations (red
portions of trace). Using the separated data, there was no difference (P = 0.314) in the
mean pupil flicker amplitude (calculated using FFTs) evoked by the six pulses of blue
light, relative to the six pulses of red light. (Figure 8G). The equality of the pupil
response to the red and blue light at this irradiance is similar to that observed in the first
experiment (Figure 4B, F). After increasing the irradiance of both the red and blue light
by one log unit (Figure 8C), there was significantly (P = 0.017) less pupil flicker during
the blue light stimulations as compared to the red light stimulations (Figure 8G), when
presented in this alternating fashion.
The amplitude of the pupil flicker during the blue light stimulations remained
significantly (P = 0.009) less than that during the red light stimulations when the
irradiance (blue: 1x1014 photons/cm2/s; red: 7x1014 photons/cm2/s) was increased by
another log unit (Figure 8G). However, examination of the mean data trace for this
alternating red/blue stimulus (Figure 8D) suggests that the amplitude of the pupil flicker
becomes smaller towards the end of the 2-min trial. This effect becomes more apparent
when the blue and red portions of the trace are separated out (blue portions of trace in
71
Figure 8D are connected together as blue trace in Figure 8E; red portions of trace in
Figure 8D are connected together as red trace in Figure 8F), and compared to the pupil
response data from the fourth and fifth trials in this experimental session involving either
blue light only (black trace in Figure 8E) or red light only (black trace in Figure 8F). At
these irradiances, the amplitude of the pupil fluctuation evoked during the flickering light
stimulation was significantly smaller when red or blue light were presented in alternating
fashion, as opposed to when presented alone (Figure 8G).
72
A
B
C
13 log units
12 log units
D
E
14 log units
F
14 log units
G
14 log units
Figure 8. Effect of alternating the red and blue light stimuli on pupil responses. A)
Outline of testing protocol used for the subjects (n = 6) participating in the first
(Continued)
73
(Figure 8: Continued)
experimental session. B-D) Traces of mean normalized pupil size elicited by alternating
red and blue light stimuli, presented at 0.1 Hz. The 6 pulses of blue light had irradiances
of 1x10y photons/cm2/s and the 6 pulses of red light stimuli had irradiances of 7x10y
photons/cm2/s, where y equaled B) 12, C) 13 or D) 14. E) Blue components of trace in D)
were extracted and joined together (blue trace) and compared to trial involving 6 pulses
of blue light (1x1014 photons/cm2/s) only (black trace). F) Red components of trace in D)
were extracted and joined together (red trace) and compared to trial involving 6 pulses of
red light (7x1014 photons/cm2/s) only (black trace). G) Mean FFT-derived amplitudes of
pupil fluctuation evoked by the flickering lights. * P < 0.05, ** P < 0.01, Paired T-test.
In the second session of the third experiment, the five trials utilized an alternating
red and blue light stimulus that was presented at the 14 log unit irradiance level used in
the first experiment. Rather than varying intensity or frequency, three alternating cycles
of 5s red and 5s blue light were presented with inter-pulse gaps of either 2.5s, 5s, 25s,
50s, or 100s (outline of testing strategy shown in Figure 9A). The post-illumination pupil
response was analyzed by assigning decay functions to pupil redilation after the offset of
a light pulse (see Fig.7).
When the darkness gap between pulses is relatively brief, pupil redilation is after
the offset of the third pulse of red light is less than the redilation measured after the first
red pulse. Decay constants for the third red pulse were significantly (P < 0.01, Paired T74
test) smaller than that of the first red pulse when the inter-stimulus darkness gap was 25s
and less (Fig. 9E). This result suggests that the pupil remains more constricted after the
offset of the third pulse, as compared to after the first pulse. The effect is lost when the
inter-pulse darkness extends 50s and longer. This effect is illustrated in Fig. 9B. Note that
the pupil size redilates more quickly after initial pulse of red light as compared to the first
pulse of blue light (consistent with Fig 7C). However, after the third red pulse in these
alternating stimuli, the redilation is slower and is similar to the sustained constriction
observed after the offset of all of the blue light pulses. When the inter-pulse darkness gap
is extended to 100s (Fig. 9C), this effect is lost, and the redilation after the offset of the
third red pulse is more similar to that of the redilation of the first pulse, with both red
light-driven pupil responses exhibiting quicker redilation as compared to the blue lightdriven responses. Thus the photopotentiation effect of the alternating stimuli diminishes
as the duration of the darkness between consecutive light pulses increases.
No enhancement of post-illumination sustained pupillary constriction elicited by
the blue light pulses was detected for any inter-stimulus darkness gap. For all five interstimulus darkness gaps, the decay constant for pupil redilation in response to the third
blue pulse was not significantly different from the decay constant in response to the first
pulse (Fig. 9D). For both the 5s and 100s inter-pulse darkness gaps, the sustained
pupillary constriction after the offset of the first and third blue pulses is identical (Fig.
9B-C).
75
Figure 9. Effect of increasing duration of darkness between alternating pulses of long
and short wavelength light. A) Outline of testing protocol used for the subjects (n = 6)
participating in the second experimental session. B-C) Comparison of the relative
redilation measured after the initial red pulse, the initial blue pulse, the final red pulse,
and final blue pulse with a B) 5 second gap between alternating light pulses and a C) 100
second gap between alternating light pulses. The arrows denote the traces of pupil
redilation (normalized and shown on right side) that were fit with an exponential decay
equation (red versus blue denote color of stimuli; light versus dark denote first versus last
pulse, respectively). D-E) Comparison of decay constants for the pupillary redilation
occurring after the first and final pulse of each colored light, with varying durations of
inter-pulse darkness. Responses to D) blue and E) red portions of the alternating stimulus
outlined in A) have been separated. ** P < 0.01, Paired T-test.
76
A
B
5 seconds darkness between light pulses
C
100 seconds darkness between light pulses
D
E
77
Chapter 6: Discussion
Rods, cones, and intrinsically photosensitive retinal ganglion cells (ipRGCs) all
contribute to the human pupillary light reflex (Do & Yau, 2010; Gamlin et al., 2007;
Gooley et al., 2012; Guler et al., 2008; Hattar et al., 2003; Lucas et al., 2001). Elements
of each can be readily seen in the light-evoked pupil responses elicited by the stimuli
employed in this study, including an isolated ipRGC component. This discussion chapter
will focus on three topics: 1) rod-cone-driven aspects of pupil constriction; 2) the effect
of stimulus wavelength, intensity, frequency on the influence of ipRGCs on the pupillary
light reflex; and 3) potentiation of the ipRGC contribution to the light-evoked pupillary
responses when stimuli consisting of alternating long- and short-wavelength light are
utilized. The work presented here confirms the results of previous investigations into the
intensity of stimulus needed to elicit a detectable ipRGC influence over pupillary
constriction. For flickering stimuli, it suggests a range of desirable frequencies for the
detection and measurement of ipRGC influence over pupillary constriction. Finally, it
presents a novel flickering stimulus that enhances the influence of ipRGCs on pupillary
constriction.
The relative contribution of outer retinal photoreceptors to the pupillary light
response is affected by both the intensity and wavelength of the light stimuli. At 470 nm,
the blue stimulus is near the peak spectral sensitivity of ipRGCs (480 nm). The red
78
stimulus (625 nm) was chosen to primarily stimulate cones. ipRGCs have been shown to
contribute minimally to the human pupillary light response at intensities below 1013
photons/cm2/s at the cornea (Barrionuevo et al., 2014). Rods dominate the continuous
pupillary light response at intensities below ipRGC threshold (Barrionuevo et al., 2014;
McDougal & Gamlin, 2010; Park et al., 2011), with a small contribution from cones
(Park et al., 2011). This paradigm holds true for a continuous low-intensity stimulus
(Gooley et al., 2012) and for a stimulus that increases intensity slowly over an extended
exposure but remains below ipRGC threshold (McDougal & Gamlin, 2010).
Additionally, a recent study (Allen, Brown, & Lucas, 2011) has proposed S-cones make a
small but detectable contribution to the pupillary light response under these conditions.
With respect to the spectral nature of light stimuli, ipRGCs are relatively insensitive to
long wavelength light (Bailes & Lucas, 2013; Dacey et al., 2005). Cones have a large role
in mediating pupil constriction driven by higher intensity, long wavelength stimuli
(Barrionuevo et al., 2014; Gooley et al., 2012), with a small contribution from rods
(Barrionuevo et al., 2014). In this study, the pupillary light responses elicited by the 1012
photons/cm2/s long and short wavelength stimuli are likely predominantly driven by rods
and cones, respectively. At this intensity, there was no difference in the pupil fluctuation
evoked by the long versus short wavelength light, indicating that it was below ipRGC
threshold. An additional 0.845 log photons/cm2/s added to the short wavelength stimuli
was required to equilibrate initial pupil constriction driven by the long wavelength light
to that driven by the short-wavelength light. This relatively dim short wavelength
stimulus likely stimulates rod contribution to the pupillary light response in addition to
79
the cone contribution present in response to both long and short wavelength stimuli. The
additional rod input in response to the short wavelength stimulus necessitates that this
stimulus be slightly dimmer than the short-wavelength stimulus to equilibrate the pupil
constriction.
Rods and cones are also likely responsible for the initial phasic pupillary response
seen shortly after stimulus onset at all intensities and frequencies studied here. ipRGC’s
lethargic response to light (Berson et al., 2002; Do et al., 2009) make them an unlikely
source of the rapid pupillary constriction seen with stimulus onset (Gooley et al., 2012).
Instead, rods and cones could solely influence the early phases of the pupillary light
response and mask the sluggishness of the ipRGC contribution (Gooley et al., 2012).
Furthermore, cones are able to encode rapidly oscillating stimuli (Hecht & Shlaer, 1936;
Lowenstein & Loewenfeld, 1958), and have subsequently been identified as the primary
mediators of the very initial changes in pupillary constriction following stimulus onset
(Allen et al., 2011). Iris dilatory muscle kinetics and not delays in outer photoreceptor
signaling are the cause of the pupillary light response latency of approximately 220 ms
(Ellis, 1981; Lowenstein & Loewenfeld, 1958).
Although the initial phases of the pupillary light response are rod- or cone-driven,
new evidence has emerged suggesting ipRGC influence over the pupillary light response
closer to stimulus onset than previously thought. McDougal and Gamlin (McDougal &
Gamlin, 2010) and Barrionuevo and colleagues (Barrionuevo et al., 2014) have utilized
intraocular pharmacological blockages and silent substitution methods, respectively, to
observe ipRGC influence in the phasic pupillary response to light pulses with durations
80
as short as 1.78 seconds. An electroretinography-based investigation has recently
demonstrated peaks in the ipRGC response to a pulsed stimulus at 80 ms after stimulus
onset and 30 ms after stimulus offset (Fukuda, Higuchi, Yasukouchi, & Morita, 2012).
ipRGC’s implicit time to first peak is longer that the latency of the cone-driven B-wave,
but a bright, short wavelength stimulus evokes a stronger ipRGC response than cone
response at 80 ms. Early ipRGC influence is made manifest in the pupillary light
response as an increased magnitude of maximum pupillary constriction that is achieved
shortly after stimulus onset. Herbst and colleagues (Herbst et al., 2011) have
demonstrated that maximum pupillary constriction typically occurs within five seconds
after stimulus onset and that maximum constriction is greater in response to a short
wavelength stimulus than to a long wavelength stimulus of equal intensity. This
difference in maximum constriction was attributed to the influence of ipRGCs. The effect
is not inconsequential, as Tsujimura and colleagues (Tsujimura, Ukai, Ohama, Nuruki, &
Yunokuchi, 2010) have shown with silent substitution techniques that pupil constriction
in response to an ipRGC-activating stimulus was three times larger than that of an M- and
L-cone-activating stimulus.
In order to achieve equal maximum pupillary constriction in the responses to the
first pulse of the long versus short wavelength stimuli, the long wavelength stimulus
needed to be 0.845 log units brighter than the short wavelength stimulus. The lowest
intensity tested (1012 photos/cm2/s) is likely below ipRGC threshold, so the difference is
likely due to additional rod contribution to the pupillary light response to short
wavelength stimuli at lower intensities. As all stimuli become brighter, ipRGCs likely
81
replace cones as the primary photoreceptor used for maintaining pupil constriction to
short wavelength light, but the 0.845 log unit difference in photon flux continued to keep
the initial peak constriction evoked by the first pulse of a flickering stimulus equal for the
two colored lights at all irradiances tested. The pupil constriction evoked by the blue light
increased over time, relative to the red light stimuli, as subsequent pulses of bright (above
ipRGC threshold, 1014 and 1015 photons/cm2/s) and low-frequency (0.05 Hz, 0.10 Hz, and
0.20 Hz) flickering stimuli were employed. Multiple pulses of short wavelength light
separated by equal periods of darkness allow for more ipRGC summation of light and
subsequent increased contribution to the pupillary light response, as detected by an
increase in maximum pupillary constriction in later pulses. By equalizing the amplitude
of peak constriction in response first pulse of red and blue light, rod and cone influence
over the amplitude of constriction was balanced. Any change to the amount of peak
constriction to subsequent pulses is therefore likely ipRGC driven. This finding agrees
with the work of Gooley and colleagues (Gooley et al., 2012) that found ipRGC-driven
pupillary constriction in response to intermediate-wavelength stimuli were greater than
those to continuous stimuli. In the work presented here, long wavelength light did not
have a similar effect on maximum pupillary constriction. The modest increase in
maximum pupillary constriction seen in the second half of the 1015 photons/cm2/s
presentation of long wavelength light is likely not cone-mediated, but likely due to
ipRGC stimulation by long wavelength light at the highest intensity tested.
Photoreceptor adaptation and bleaching play a prominent role in the pupillary
light response. McDougal and Gamlin (McDougal & Gamlin, 2010) have determined that
82
cones are susceptible to greater adaptation than rods or ipRGCs and that their dominance
of the pupillary light response is only transient and is inversely proportional to stimulus
duration. Specifically, M- and L-cones were shown to lose approximately three log units
of sensitivity within the first 100 seconds of continuous stimulus. Rods and ipRGCs
adapted at equivalent rates, but rods were susceptible to greater magnitudes of bleaching.
Not surprisingly, rod and cone adaptation increases as stimulus intensity increases. In
particular, the rod input becomes insignificant when stimuli exceed 1013 photons/cm2/s
(Barrionuevo et al., 2014). ipRGCs, however, are more resistant to bleaching (Zhu et al.,
2007) and compensate for the adaptation of rods and cones (McDougal & Gamlin, 2010).
The effects of adaptation are apparent in this study. At the lowest stimulus
intensity (1012 photons/cm2/s) the maximum pupillary contraction slightly decreases with
each subsequent pulse of both the long- and short-wavelength light. This intensity is
below ipRGC threshold but is bright enough to stimulate rod saturation and cone
adaptation. The result is reduction in maximum pupillary constriction to the later light
flashes in the minute-long stimuli. As the blue light intensity increases to 1014
photons/cm2/s, there is instead a gradual increase in the pupil constriction elicited at the
end of the minute-long stimuli. Resistance to bleaching and lethargic temporal dynamics
allow ipRGCs to counteract the loss of the rod and cone contribution to the PLR later in
the duration of a flickering stimulus. Post-illumination sustained constriction does not
seem susceptible to the same adaptation mechanisms as maximum pupillary constriction.
At all stimulus intensities and frequencies, post-illumination constriction increased with
each subsequent pulse of both long and short wavelength light. This aspect of the
83
pupillary light response is likely heavily influenced by ipRGCs with likely little direct
rod or cone influence (discussed below), sparing it from sensitivity loss from adaptation
or bleaching.
When activated, ipRGCs enhance pupil constriction, but measurement of this
effect is not currently the prevalent method of ipRGC assessment in vivo. Sustained
pupillary constriction after stimulus offset is mediated by ipRGCs (Gamlin et al., 2007).
Studies involving healthy human subjects have demonstrated that the amount of postillumination sustained constriction is greater after a bright, short wavelength stimulus
than after a short wavelength stimulus of similar intensity (Kankipati et al., 2010; Park et
al., 2011; Young & Kimura, 2008). In populations with inner retinal disease, this
difference is not detected, leading to the provocative conclusion that ipRGCs impairment
can be detected with a pupil test (Feigl et al., 2011; Feigl et al., 2012; Kankipati et al.,
2011). Pulse durations of one second at an intensity of greater than 1012 photons/cm2/s
have been hypothesized as the optimal stimulus duration and intensity to elicit a
difference between long and short wavelength light in sustained post-illumination
pupillary constriction (Park et al., 2011). Others believe that pulse durations of short
duration, regardless of intensity and wavelength, are under outer photoreceptor control
(McDougal & Gamlin, 2010). The optimal pulse duration and the threshold intensity for
pupil test that seeks to isolate the ipRGC contribution have not been established, and
much variety exists in stimuli parameters (Feigl et al., 2011; Feigl et al., 2012; Kankipati
et al., 2010, 2011; Young & Kimura, 2008).
84
Experiment 1 in the work presented here sought to determine the minimum
intensity to elicit a difference in the post-illumination pupillary response to short and long
wavelength light. Beginning at 1013 photons/cm2/s a small separation between the traces
of the pupillary light response elicited by flickering red versus blue light stimuli was
detected. The Fourier-derived measurement of pupillary flicker was not statistically
significant at this brightness, however. This difference in Fourier-driven pupillary flicker
became statistically significant at 1014 photons/cm2/s. Although the red versus blue
comparison was not statistically significant at 1013 photons/cm2/s, there was a significant
difference in the pupil fluctuation measured for each of the four tested blue light
intensities. In comparing the pupil fluctuation for the four red light intensities, only the
brightest (1015 photons/cm2/s) was statistically different from the other three. Taken
together, these findings agree well with previous investigations that suggest a retinal
illuminance of 1011-1012 photons/cm2/s is the threshold for melanopsin activation (Dacey
et al., 2005), which translates to approximately 1012-1013 photons/cm2/s at the corneal
surface (Berson et al., 2002; Tsujimura et al., 2010). The sustained pupillary response
after light offset offers a more isolated measurement of ipRGC function than the
maximum pupil constriction. Rods, cones, and ipRGCs all contribute to the pupillary
light response to a bright, relatively sustained stimulus. After light offset, however, rods
and cones cease firing, but lethargic ipRGC continue to fire. In this phase of the pupillary
light reflex, ipRGCs are the primary photoreceptors driving constriction, providing a
better assessment of their function.
85
Due to ipRGC’s relative light insensitivity, lethargy, and resistance to bleaching,
isolation of their influence over the pupillary light response is better achieved with a long
duration stimulus, as compared to a stimulus consisting of a single, brief light pulse.
Continuous stimuli can be used to assess ipRGC function through measurements of
maximum pupillary constriction and the amount of pupil-redilation that occurs both
during and after the light exposure. These pupil responses are thought to be ipRGCdriven and are robustly elicited in response to a short wavelength, bright stimulus
(Gooley et al., 2012; McDougal & Gamlin, 2010; Tsujimura et al., 2010; Young &
Kimura, 2008). Long wavelength or dim continuous light stimuli do not generate
comparable peak or sustained pupillary constriction. The spectral sensitivity of the
pupillary response shifts toward shorter wavelengths over the course of a long (at least
17.8 seconds) continuous, and bright light stimuli, suggesting cone adaptation and ipRGC
conscription (Gooley et al., 2012; McDougal & Gamlin, 2010). Although maintained
constriction during the course of a long, continuous stimulus is likely ipRGC-mediated, it
is more difficult to quantify and is less suited for a clinical application.
Long duration, flickering stimuli are gaining more attention as investigators of
ipRGC function. Green, flickering (0.1-4 Hz) stimuli produce a twofold increase in
sustained pupillary response than a continuous stimulus of identical wavelength and
duration (Gooley et al., 2012). This effect is discussed in more detail below. In the same
study, the pupillary light responses of normal human subjects were able to accurately
encode all frequencies of a flickering stimulus, but a human subject blind from outer
retinal degeneration was only able to accurately encode a slowly flickering stimulus (5s
86
on, 15s off). At the highest frequency (4 Hz), the pupillary response was similar to one
elicited by a continuous stimulus. This was thought to be due to only ipRGCs being
present in the patient’s retina, as lethargic ipRGCs cannot distinguish between continuous
light and light flickering at high frequencies. Interestingly, the pupil constriction to the
slowly flickering stimulus increased after the first pulse, as it was in subjects lacking
ocular disease. These findings suggest that outer photoreceptors likely mediate the
immediate pupillary response to flickering stimuli (Barrionuevo et al., 2014; Gooley et
al., 2012) and that their degeneration causes lethargic pupillary light responses to
flickering stimuli (Gooley et al., 2012). In addition, the results indicated that ipRGC
responses become more robust over time during flickering light exposure, as compared to
continuous light. The cause of this effect is still unknown, but the topic is visited later in
this discussion. As seen with continuous stimuli, the long duration of these tests allows
for decreased outer photoreceptor influence and increased ipRGC contribution over the
course of the presentation. A flickering stimulus of appropriate frequency is a better
indicator of ipRGC function, however, as it allows for enhancement of the ipRGC
contribution to the pupillary light response and for multiple measurements of maximum
pupillary constriction and sustained post-illumination constriction with each presentation.
The results presented here affirm the value of a flickering stimulus. A gradual
increase in peak pupil constriction occurred during the course of all short wavelength
flickering (0.05-1.0 Hz at 1014 photons/cm2/s) stimuli, in agreement with the results of
Gooley and colleagues (Gooley et al., 2012). The enhancement of pupil constriction was
not evident when long wavelength stimuli of identical duration and frequency were
87
utilized. A frequency of 1 Hz has been suggested as the optimal frequency to yield
maximum ipRGC-mediated response amplitude (Barrionuevo et al., 2014). Although the
work presented here did find an increase in maximum constriction amplitude at this
frequency, it cannot reach the same conclusion. At this frequency, ipRGCs respond as if
the stimulus were a continuous light source (Gooley et al., 2012; McDougal & Gamlin,
2010). A small increase in peak pupillary constriction is seen with each pulse of short
wavelength light, which is evidence of ipRGC contribution to the pupillary light response
at high frequencies. No difference in the sustained post-illumination pupillary response (a
better marker of ipRGC function than peak pupil constriction) was observed, as the time
between pulses was not long enough to allow detection of a difference in the amount of
pupillary redilation after stimulus offset. However, a difference in sustained constriction
was detected only in the 10 seconds after the final pulse of the 0.5 and 1.0 Hz trials. This
difference is further evidence that ipRGCs are active at these frequencies, but their
influence is relatively undetected due to iris motor kinetics. Lower frequencies of short
wavelength (0.05-0.20 Hz) allow for easier assessment of ipRGC function. Enhancement
of maximum pupillary constriction and overall pupil fluctuation are good markers of
ipRGC function and are more easily quantified with slowly flickering stimuli. In this
study, frequencies less than or equal to 0.20 Hz (at 1014 photons/cm2/s) demonstrated a
significant difference in the amplitude of pupillary fluctuation between long and short
wavelength stimuli. A frequency of 0.10 Hz was chosen for experiment 3 of this study
because it showed an increase in maximum pupillary constriction over the duration of the
88
response to short wavelength light, there was less pupil fluctuation (due to sustained pupil
constriction after light offset), and it was well tolerated by subjects.
Flickering alone provides some enhancement of the pupillary light response. As
introduced above, Gooley and colleagues (Gooley et al., 2012) demonstrated that a
flickering green stimulus elicits a greater pupillary light response than a continuous
stimulus of identical duration, intensity, and wavelength. They concluded that flickering
alone is enough to enhance the pupillary light response. The study presented here did not
utilize a continuous stimulus, so the difference between flickering and continuous light
was not analyzed directly. One finding from our results supports this prior conclusion,
however. At the lowest intensity (1012 photons/cm2/s) tested, pupil constriction slightly
decreased with each pulse, likely from rod saturation and cone adaptation. Contrarily, the
post-illumination sustained constriction slightly increased with each pulse. This intensity
of each single flash is below ipRGC-threshold, but these results suggest that the
contribution of ipRGCs increases over the duration of the stimulus. This effect was seen
in response to both short and long wavelength light, dissimilar to Gooley’s report of the
effect only in response to short wavelength stimuli. That study looked at total pupillary
constriction, which is influenced by rods, cones, and ipRGCs. The work presented here
places significant emphasis on post-illumination constriction, which is likely ipRGCdominated. As argued below, I postulate that the flickering presentation of the light
flashes is enhancing the ipRGC light sensitivity. ipRGC influence over the pupillary light
response better detected in the sustained post-illumination response, as compared to total
89
pupil constriction, and is the reason for the difference in conclusions between the two
studies.
In this study, a novel flickering stimulus that alternates between long and short
wavelengths provided greater enhancement of the response than a monochromic
flickering stimulus of identical frequency and intensity. Several previous studies have
demonstrated that exposure to a priming short wavelength stimulus enhances
physiological processes – such as circadian rhythms photoentrainment (Mure et al., 2007)
and the pupillary light responses (Mure et al., 2009; Zhu et al., 2007) – that are thought to
be under ipRGC control. The exact mechanism of this potentiation is still debated (see
Chapters 2 & 3). Photopotentiation was reproduced here using a stimulus that alternated
between long and short wavelength light. Whereas the studies referenced above utilize
lengthy blocks of long wavelength priming light, this study repeatedly alternates between
short pulses of long and short wavelength light. I hypothesize that ipRGCs, either directly
or indirectly, mediate this photopotentiation effect. Therefore, the measurement of this
effect may serve as a sensitive method for assessing ipRGC function.
In this study, photopotentiation refers to the decrease in pupil fluctuation in
response to a slow flickering stimulus employed alternating long- and short-wavelength
light flashes. As discussed above, the two aspects of pupillary light reflex under ipRGC
influence are maximum constriction and sustained post-illumination constriction. Both of
these responses are enhanced through the use of the alternating stimuli, as compared to
monochromic stimuli of equivalent intensity and frequency (Fig. 8 E-F). The Fourierderived pupil fluctuation is reduced because post-illumination constriction is enhanced
90
more than the maximum constriction. The sustained response likely shows a larger effect
as compared to maximum constriction because it is not limited by a ceiling effect created
by the physical limitations of the iris sphincter’s ability to constrict past a certain point.
Photopotentiation is most prominent in response to stimuli above ipRGC
threshold. The post-illumination sustained pupillary response is modestly enhanced with
each subsequent alternating pulse with the lowest intensity stimulus (1012 photons/cm2/s,
below ipRGC threshold), but this effect was seen during the monochromic experiments
and could be a function of flicker alone and not wavelength alteration (see above). When
the intensity of the alternating stimuli exceeds ipRGC threshold (1014 photon/cm2/s
stimulus), pupil constriction becomes more pronounced, and the post-illumination
sustained pupillary constriction is enhanced (i.e. slower pupil redilation). Due to this
effect, the pupillary light response to long and short wavelength light become equivalent
in terms of maximum constriction during light exposure and the post-illumination
redilation dynamics. The most dramatic effect is seen in the pupillary light response to
the long wavelength pulses, but the pupillary light response to short wavelengths is
photopotentiated, as well. Previous studies into the enhancement of ipRGCs with a
priming stimulus investigated the effect of prior long wavelength exposure to the ipRGC
light response to a short wavelength stimulus (Enezi et al., 2011; Mawad & Van Gelder,
2008; Mure et al., 2009; Mure et al., 2007; T. J. Sexton et al., 2012; Zhu et al., 2007). The
effect of a priming short wavelength light on long wavelength stimulus has not garnered
much investigation. In the study presented here, both long and short wavelength light
responses are photopotentiated, although the effect is more obvious for long wavelength
91
responses. The physiological basis for this effect cannot be deduced from this study and
warrants further in vitro investigation. The result presented here that full
photopotentiation is only seen at stimuli intensities above ipRGC threshold is strong
evidence that the effect is ipRGC-mediated.
Photopotentiation is potentially driven by one of several physiological processes.
Melanopsin may be a bistable photopigment. In traditional bistability, short wavelength
light drives phototransduction by converting the active form of a photopigment into an
inactive intermediate. Short wavelength light then converts the intermediate back into an
active photopigment without the need of an enzymatic process. The alternating stimulus
employed in this study would theoretically be very effective at stimulating a bistable
pigment. Suggestive of a bistable photopigment, long wavelength light did potentiate the
pupil response to lo short wavelength light in this study. The fact that this study also
demonstrated that short wavelength light potentiated the pupil response to long
wavelength light is not consistent with melanopsin’s potential bistability, however. If the
difference in spectral sensitivity between active melanopsin and its intermediate were
small enough for both to be driven by short wavelength light, then photopotentiation
would likely be detected with a blue-only stimulus. Such photopotentiation was not
observed in this study. Overall, this results presented here do not provide strong evidence
for melanopsin bistability.
Even if melanopsin is not bistable, photopotentiation might still be an intrinsic
phenomenon mediated by enzymes within ipRGCs. Light-sensitive melanopsin has been
detected in ipRGCs after exposure to a single long-duration, high intensity stimulus
92
(Walker, Brown, Cronin, & Robinson, 2008). Regeneration of light-sensitive melanopsin
occurred without a long wavelength stimulus presented after the initial short wavelength
stimulus. This finding suggests that light-sensitive melanopsin can be regenerated
without being exported to the retinal pigment epithelium (like rod and cone
photopigments) or without a regenerative long wavelength light exposure (characteristic
of a bistable photopigment). A light-independent enzymatic pathway for the regeneration
of active melanopsin has not yet been identified, so exact mechanism of active
melanopsin regeneration remains speculative in nature.
Extrinsic factors might be the physiological origin of photopotentiation. ON
bipolar cells drive the majority of ipRGC’s extrinsic photoresponse (Wong et al., 2007).
It is possible that this excitatory synaptic input drives up certain secondary messengers
(such as cAMP) within ipRGCs. cAMP can stimulate cAMP-dependent protein kinase A
enzymes (Cass et al., 1999), and the subsequent phosphorylation of certain ion channels
could mediate a potentiation of the intrinsic photoresponse of ipRGCs. Intracellular
levels of cAMP could also be increased following exposure to dopamine. Light exposure
drives dopamine release from amacrine cells. As discussed above, dopamine has several
effects on ipRGCs. Increases in melanopsin production after exposure to dopamine was
shown to take at least four hours (Sakamoto et al., 2005), making such an increase an
unlikely source of the photopotentiation detected with our alternating stimulus. It has
been demonstrated that dopamine also causes the resting potential of ipRGC to become
relatively more depolarized (Van Hook et al., 2012). Since ipRGCs depolarize in
response to light, ipRGCs that have been exposed to dopamine are closer to threshold
93
than cells that have not been exposed to dopamine. This effect would potentiate a cell’s
response to both long and short wavelength light. Dopamine release in the retina occurs
over the course of seconds, meaning that its effect would be somewhat delayed (Kramer,
1971). The pupillary light response to an alternating stimulus in this study is
photopotentiated in response to both long and short wavelength light, and the effect is
first seen a few seconds after the initial light pulse. These characteristics are consistent
with a dopamine-related photopotentiation pathway, but this hypothesis has yet to be
proven in vitro.
The evidence provided here that ipRGC mediate photopotentiation remains
strictly circumstantial. Photopotentiation has yet to be replicated in vitro. Although Zhu
and colleagues provide evidence that photopotentiation occurs within the retina (Zhu et
al., 2007), questions remain whether the effect is conferred by melanopsin bistability,
changes in ipRGC phototransduction mediated by ipRGC-rod/cone or ipRGC-amacrine
interaction, or another mechanism. These questions cannot be sufficiently addressed until
the effect is duplicated in vitro.
Photopotentiation can be a powerful tool to isolate the ipRGC influence over the
human pupillary light response in order to assess the function and health of these unique
cells. A clinical test utilizing the stimuli described in this study may be an effective tool
in detecting retinal and neurological disease. Recent investigations into ipRGC function
in disease rely on the comparison of the pupillary light response to short and long
wavelength light. Photopotentiation assessment may prove to be a more powerful tool in
94
disease detection because it provides a more direct measurement of ipRGC function
independent of outer photoreceptor influence.
An ipRGC-based pupil test has several advantages over the traditional swinging
flashlight test in detecting neurological and retinal disease. A major drawback of the
swinging flashlight test is that it only has the power to detect unilateral or significantly
asymmetric pathology. Some diseases, such as traumatic brain injury and seasonal
affective disorder, are not typically detectable with the swinging flashlight test.
Comparison between the eyes is not necessary for an ipRGC-based test. Instead the test
compares between the inner and outer photoreceptors in one eye at a time, allowing for
better detection of bilateral, symmetric disease. Neurological diseases not typically
associated with the visual pathway may be detectable using an ipRGC-based pupillary
test, as these cells project to brain centers not typically associated with vision, such as the
thalamic pain nuclei. Execution and interpretation of the swinging flashlight test demand
a certain level of clinical skill and experience. Automated swinging flashlight tests exist,
but they depend on unilateral or asymmetric disease. An ipRGC-based pupil test would
be strictly objective. No response would be needed from the patient, and the test would
demand minimal clinical skill and interpretation. An ipRGC pupil test can be conducted
quickly, and a mobile testing apparatus is not difficult to imagine. These characteristics
suggest that an ipRGC-based pupil test may one day be a better screening test for ocular
and neurological disease than the swinging flashlight test. More research is necessary to
characterize ipRGC influence over the pupillary light response in normal and diseased
patients before such a screening test can be clinically useful.
95
In summary, the temporal dynamics of the PLR to flickering red and blue light
stimuli exhibit characteristics consistent with the involvement of ipRGCs, and the
contribution of these ganglion cell photoreceptors can be best isolated using bright (1014
photons/cm2/s), slowly flickering stimuli (less than 0.20 Hz). Prior exposure to blue light
alters pupil responses to red light, and vice versa. As a result, alternating red and blue
flashing stimuli cause enhanced pupil constriction with slower re-dilation, as compared to
monochromic stimuli. This is the first study to show this photopotentiation of the
pupillary light reflex in response to a flickering stimulus that alternates between red and
blue light. The potential clinical applications of a pupil test able to isolate the ipRGC
input into the human pupillary light response are expansive but demand further
investigation.
96
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Appendix: Inter-subject Differences in ipRGC Contribution to PLR
Figure 5 demonstrated good inter-session repeatability of pupil responses to 0.1
Hz flickering light, indicating that intra-subject variability of ipRGC influence over the
pupillary light response is low. Inter-subject variability was not directly measured in this
study. ipRGC contribution to the pupillary light response does not appear to be
homogenous, however. Several subjects show an exaggerated ipRGC response (Fig.
10A), while others show nearly no ipRGC response to the same stimulus (Fig. 10B). The
largest amount of variability in ipRGC contribution was observed in the amount of pupil
redilation after blue stimulus offset. When the stimulus is turned off, only ipRGC are
driving pupillary constriction. Differences in the amount of sustained pupillary
constriction after blue stimulus offset are likely due to variability in ipRGC influence
over the pupillary light response. A subject with strong ipRGC influence over the
pupillary light reflex (Fig. 10A) will show little pupil redilation after stimulus offset,
whereas a subject with little ipRGC influence (Fig. 10B) will redilate quickly after
stimulus offset. Inter-subject variability is also detected in the magnitude of peak pupil
constriction in response to a blue stimulus. Peak pupil constriction in response to the first
pulse of a blue stimulus was equal between all subjects, regardless of ipRGC robustness.
Rods and cones likely drive this initial constriction, and no difference is seen between
subjects. With each subsequent blue pulse, however, ipRGC contribute more to peak
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pupillary constriction. By the last three pulses, a large difference in peak constriction is
seen between a subject with a strong ipRGC response (Fig.10A) and a subject with a
weak ipRGC response (Fig. 10B). Whether these differences are due to unequal
populations of ipRGCs, unequal melanopsin expression in ipRGCs, or difference in
ipRGC axonal projections remains unclear.
Figure 10. Inter-subject variability of ipRGC influence over the pupillary light response.
Stimulus: 7 x 1014 photons/cm2s (red) or 1 x 1014 photons/cm2/s (blue) at 0.1 Hz for 1
minute. A) Example of a subject with robust ipRGC influence over the pupillary light
reflex. Post-illumination sustained constriction and peak constriction to later pulses show
strong signs of ipRGC influence in response to the blue stimulus. B) Example of a subject
with minimal ipRGC influence over any aspect of the pupillary light reflex. The pupillary
response to the red and blue stimuli is almost identical, and little post-illumination
sustained constriction and increase in peak constriction is seen.
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