Articles in PresS. J Neurophysiol (April 19, 2017). doi:10.1152/jn.00055.2017
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Comparison Of Optomotor And Optokinetic Reflexes In Mice
Friedrich Kretschmer1,2, Momina Tariq1, Walid Chatila1,3, Beverly Wu1 and Tudor Constantin Badea1,*
1, Retinal Circuit Development & Genetics Unit, Neurobiology Neurodegeneration & Repair Laboratory, National Eye Institute,
National Institute of Health, Bethesda, MD, U.S.A.
2, current address: Scientific Computing Facility, Max Planck Institute for Brain Research, Frankfurt am Main, Germany
3, current address: Memorial Sloan Kettering Cancer Center, New York, NY, U.S.A
Running title: Comparison of the Optomotor and Optokinetic reflexes in mice
*, Corresponding Author: Tudor C. Badea
Retinal Circuit Development & Genetics Unit,
Neurobiology Neurodegeneration & Repair Laboratory,
National Eye Institute,
National Institute of Health,
Bethesda, Maryland, U.S.A.
[email protected]
Key Words: Optokinetic response; Optomotor Response; Optokinetic Nystagmus; Direction Selective RGCs; Retinal
Ganglion Cells; Mouse genetics; Mouse visual system; Brn3b; Pou4f2
Figures : 8
Supplementary Tables : 1
Supplementary Movies: 4
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Copyright © 2017 by the American Physiological Society.
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Abstract:
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During animal locomotion or position adjustments, the visual system uses image stabilization reflexes to compensate
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for global shifts in the visual scene. These reflexes elicit compensatory head movements (Optomotor response - OMR)
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in unrestrained animals or compensatory eye movements (Optokinetic response - OKR) in head fixed or unrestrained
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animals, exposed to globally rotating striped patterns. In mice, OMR responses are relatively easy to observe and find
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broad use in the rapid evaluation of visual function. OKR determinations are more involved experimentally but yield
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more stereotypical, easily quantifiable results. The relative contributions of head and eye movements to image
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stabilization in mice have not been investigated. We are using newly developed software and apparatus to accurately
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quantitate mouse head movements during OMR, eye movements during OKR, and determine eye movements in freely
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behaving mice. We provide the first direct comparison of OMR and OKR gains (head or eye velocity / stimulus
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velocity), and find that the two reflexes have comparable dependencies on stimulus luminance, contrast, spatial
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frequency and velocity. OMR and OKR are similarly affected in genetically modified mice with defects in Retinal
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Ganglion Cells, as compared to wild types, suggesting they are driven by the same sensory input (RGC type). OKR eye
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movements have much higher gains than the OMR head movements, but neither can fully compensate global visual
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shifts. However combined eye and head movements can be detected in unrestrained mice performing OMR, suggesting
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they can cooperate to achieve image stabilization, as previously described for other species.
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New & Noteworthy
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We provide the first quantitation of head gain during optomotor response in mice and show that optomotor and
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optokinetic responses have similar psychometric curves. Head gains are far smaller than eye gains. Unrestrained mice
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combine head and eye movements to respond to visual stimuli, and both monocular and binocular fields are used during
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optokinetic responses. Mouse OMR and OKR movements are heterogeneous under optimal and suboptimal stimulation,
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and are affected in mice lacking ON-DS RGCs.
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Introduction
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Vertebrates use involuntary compensatory mechanisms for image stabilization during self-motion. The
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vestibulo-ocular reflex (VOR) integrates information from the semicircular canals to evoke eye movements in the
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opposite direction of occurring head movements. Compensatory eye (Optokinetic - OKR) and/or head (Optomotor -
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OMR) reflexes integrate information from the global shift of the visual image over the retina. Stereotypical OKR
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movements (hereafter events) consist of a slow (hereafter called tracking) phase during which the eye moves in
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stimulus direction followed by a fast saccade-like (hereafter reset) phase that occurs in the opposite direction (Collewijn
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1969; Stahl 2004b). Optokinetic events are also known as Optokinetic Nystagmus (Spering and Carrasco 2015; Ter
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Braak 1936). The OKR is well described in species with frontal eyes endowed with a fovea or area centralis (e.g. cats,
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humans, (Dubois and Collewijn 1979; Honrubia et al. 1967)) and afoveated, laterally positioned eyes (e.g. rabbits,
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mice) (Collewijn 1969; Sinex et al. 1979; Stahl et al. 2000). Since OKR is evoked easily and reliably, it can be used to
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measure visual function in human subjects (Fahle et al. 2011; Naber et al. 2011).
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The term "Optomotor response" typically refers to compensatory head and/or body movements in stimulus
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direction, that can be followed by a quick reset phase (Benkner et al. 2013; Gresty 1975; Kopp and Manteuffel 1984).
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The quick reset phase can be observed more commonly in fish (Anstis et al. 1998), salamander (Kopp and Manteuffel
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1984) and frogs (Dieringer et al. 1982), but is also present in mammals (Collewijn 1977; Fuller 1985; 1987; Gresty
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1975). Based on the prominent movement of the neck in rat, rabbit and pigeon compensatory head movements
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are also referred to as the Optocollic reflex (OCR) in these species (Fuller 1985; 1987; Gioanni 1988a; b).
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Given the distinct ecological niches and head mobility relative to neck and body, the contribution of head and
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eye movements to image stabilization can vary significantly between species (Gioanni 1988a; b).
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The OKR and OMR responses are driven by ON-direction selective ganglion cells (ON-DS RGCs) (Oyster et
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al. 1980; Oyster et al. 1972; Yonehara et al. 2009; Yonehara et al. 2008), sending their axons into the Accessory Optic
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System (AOS, (Simpson 1984)). In mammals, axons of ON-DS RGCs follow the main optic tract or the Accessory
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Optic Tract (AOT), and innervate the nucleus of the optic tract (NOT) and the dorsal, lateral and medial terminal nuclei
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(DTN, LTN and MTN), mostly on the contralateral side (Dhande et al. 2013; Distler and Hoffmann 2003; Oyster et al.
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1980; Oyster et al. 1972; Yonehara et al. 2008). Electrophysiological evidence suggests that NOT and DTN are
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predominantly perceiving motion in temporo-nasal direction, while LTN and MTN are preferentially tuned to vertical
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motion components (e.g. (Simpson et al. 1988; Soodak and Simpson 1988). We had previously reported that mice
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missing the transcription factor Brn3b/Pou4f2 (Brn3bKO/KO mice) have specific defects in RGC numbers, with complete
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loss of MTN, DTN and LTN projections, partial loss of RGC projections to the pretectal area (NOT and olivary
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pretectal nucleus - OPN), Lateral Geniculate Nucleus (LGN) and Superior Colliculus (SC), and preserved RGC
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innervation to the suprachiasmatic nucleus (SCN)(Badea et al. 2009). In mice with genetic ablation of MTN and/or
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LTN projecting RGCs (Badea et al. 2009; Sun et al. 2015), there is a complete loss of vertical OKR. Loss or reduction
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of RGC numbers projecting to the pretectal area, including the NOT and the DTN results in partial loss of horizontal
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OKR (Badea et al. 2009; Osterhout et al. 2015). OMR has never been tested in Brn3bKO/KO mice, and it is yet unclear
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how their residual horizontal OKR response compares to the full wild type response.
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The relative contributions of OKR and OMR to image stabilization have not been studied in mice, due to
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technical limitations. Specifically, whereas an extensive body of data is available for mouse OKR, there are few
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quantitative assessments of mouse head movements during OMR (Benkner et al. 2013; Kretschmer et al. 2013). For
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mouse OKR and VOR, eye motion is detected using videographic detection of pupil and corneal reflection in head-
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fixed mice, providing precise information on the number and gain of saccadic eye movements, and the regions of the
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retina involved (Stahl et al. 2000). Previous work has shown that OKR gain decreases with increasing stimulus
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velocities (Collewijn 1969; Stahl et al. 2006; Tabata et al. 2010; van Alphen et al. 2001), consistent with the tuning of
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ON-direction selective ganglion cells to slow speeds (1-2°/s), (Oyster et al. 1972; Sun et al. 2006). OKR spatial acuity
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thresholds range between 0.5 and 0.6 cyc/° (Cahill and Nathans 2008; Sinex et al. 1979; van Alphen et al. 2001; van
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Alphen et al. 2009; van Alphen et al. 2010).
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The most common method for characterizing OMR in mice relies on a trained human observer, which directly
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records number of mouse head movements under different conditions to determine visual thresholds (Prusky et al.
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2004). More recently, a forced choice test involving the human observer has been implemented in order to increase the
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objectivity of the test (Umino et al. 2008). In essence, these approaches rely on counting the number of head tracking
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movements detected by the human observer under various stimulus conditions and reporting an optimal stimulus
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velocity of 12°/s and an absolute visual acuity threshold of 0.39 cyc/° (Prusky et al. 2004; Umino et al. 2012; Umino et
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al. 2008). However, no information on head angular velocity or amplitude and duration of mouse OMR events is
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available.
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Previous studies described combined head and eye movements in unrestrained animals of several species, either
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under free behaving circumstances or upon optokinetic visual stimulation (Collewijn 1977; Fuller 1985; 1987; Gresty
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1975). These studies suggest that the combined gains of the two systems can match stimulus speed only for optokinetic
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stimuli of low velocities. In rats and rabbits, eye movements may be optimized to preserve the binocular visual field of
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the animal during head rotations around the pitch and roll axes (Hughes 1971; Maruta et al. 2001; Wallace et al. 2013).
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Controlled head tilts in head-fixed mice reveal compensatory eye movements (tilt maculo-ocular reflex) that predict a
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vertical eye angle of about 22O during ambulation (Oommen and Stahl 2008). Therefore eye position in the freely
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behaving animal may seek to optimize binocularity. However, there is essentially no information on optokinetic eye
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movements in unrestrained mice and to what extent OKR responses in restrained and unrestrained conditions are
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related.
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We have recently developed apparatus and software allowing for the recording of head movements during
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OMR, eye movements during OKR or combined head and eye movements in unrestrained mice (Kretschmer et al.
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2013; Kretschmer et al. 2015). We introduce a quantitative video-tracking approach to the determination of mouse
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head movements during OMR. We report the properties (angular velocity, duration, angular amplitude) of OMR head
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movements in mice and compare them to eye movements during OKR, under identical stimulation conditions. We then
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show that unrestrained mice, like other species, can respond to moving gratings with concomitant head and eye tracking
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movements. We apply our methodologies to analyze OMR and OKR responses in Brn3bKO/KO mice, which have a
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complete ablation of RGCs projecting into the AOS, while preserving some innervation to the LGN and SC.
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Materials and Methods
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Mice
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Mice were Brn3bKO/KO and Brn3bWT/WT littermate controls, all on a C57Bl6 background. Male and female mice
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two to six months old were used in all experiments. Numbers of tested animals for each experiment are specified in
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figure legends and results. Controls for behaviors in blind mice were derived from 6 months old rd1/rd1 mutants which
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are devoid of rods and cones (Chang et al. 2002). All mouse handling procedures used in this study were approved by
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the National Eye Institute Animal Care and Use Committee (ACUC) under protocol NEI 640. All NIH rodent surgery
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guidelines were followed. For OKR experiments head posts were implanted as previously described (Cahill and
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Nathans 2008; Kretschmer et al. 2015).
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Apparatus and visual stimulus design
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Our custom built setup includes hardware and software for stimulus presentation, calibration procedures, and video
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tracking of head and eye movements, and is described in great detail in (Kretschmer et al. 2015). The software used to
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present the stimuli is available on request from the authors and is provided as free software under GNU GPLv3 license
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(okrarena, http://openetho.com). Visual stimuli are projected on a virtual sphere displayed onto four screens. Patterns
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are mapped onto the inside wall of this sphere and portions of the visual field can be masked. To reduce the light levels
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inside the setup to scotopic conditions, we used neutral density filters. For calibration, we measured the light intensity at
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the center of the platform while presenting a 0.2 cyc/° grating (at maximal contrast, see below) on the four screens. This
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resulted in a combined light intensity of 9 x 1013 photons*s-1*cm-2 (~41 cd/m2) for photopic light conditions or 9 x 1010
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photons*s-1*cm-2 (~0.041 cd/m2) for scotopic light conditions (neutral density filters in front of the screens). The grating
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contrasts are calculated using the Michelson contrast CM = (Lmax-Lmin)/(Lmax+Lmin) formula, where the maximum (Lmax)
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and minimum (Lmin) luminances are set at the extreme values allowed by the hardware (screen lookup table RGB values
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are [255 255 255] and [0 0 0] respectively, corresponding to about a 700 fold range in luminance.). Thus, the maximal
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contrast achievable was 0.997. For simplicity, we refer to this condition as "contrast 1" for the rest of the paper.
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In this study we use rotating sinusoidal gratings to evoke OKR and OMR responses and a set of masks to cover
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the binocular and/or monocular field of the animal. Depending on the experiment, we have varied grating contrast,
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spatial frequency, velocity, direction, and duration of unidirectional rotation epochs. Each combination of conditions
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constituted one trial, and the number of trials per animal and experimental condition are indicated in figure legends. For
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experiments in Figures 2-5, 7A-B and 8, each trial lasted for 1 minute, during which the stimulus rotated at constant
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speed around the animal (12 o/sec), but reversed direction every 5 seconds (for a total of 12 unidirectional stimulation
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epochs / minute), i.e. the stimulus follows a triangular position profile (square wave velocity profile) at a replication
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rate of 0.1 Hz. Stimulus position profiles are represented at the bottom of exemplary head or eye traces (Figures 3 and
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8). For experiments in Figure 2, the light levels (scotopic vs. photopic), contrast level (range = 0.05 to 1) and spatial
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frequency (range = 0.025 to 0.45) of the gratings were changed between trials. Three trials for each combination of
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parameters and animal were collected. For experiments in Figures 3-5, grating velocity (12 o/sec), contrast (1) and
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illumination level (photopic) were kept constant, but spatial frequencies were changed on every trial. Experiments in
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Figure 6 explored OKR/OMR dependency on visual stimulus velocity, so individual trial conditions were slightly
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different: unidirectional stimulus epochs lasted for 30 seconds, under constant illumination level (photopic), contrast (1)
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and spatial frequency (2 cyc/o), but grating velocities varied between 2 and 24 o/sec. For experiments in figure 7 A-B,
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masks were superimposed on the stimuli as described in results and figure legends. For experiments in Figure 7E, the
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unidirectional stimulus epoch duration was set by the angular displacement of the stimulus (between 20o and 120o), and
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illumination (photopic), contrast (1), grating spatial frequency (0.2 cyc/o) and stimulus velocity (12 o/sec) were kept
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constant. Stimuli were generated by the “patternGen” component of our OMR stimulation and recording software suite
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as described (Kretschmer et al. 2015) and protocols were created containing all stimuli for each set of conditions.
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Protocols consisted of presentation of one trial for each condition, in randomized succession, to avoid learning and/or
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adaptation. Individual trials were separated by 30s recovery pauses showing a gray screen.
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Infrared illumination is provided by LED strips fixed to the corners of the setup (Figure 1Aii), and the recording
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camera, placed at the top of the arena is fitted with a high-pass infrared filter, in order to minimize animal coat-color
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and stimulus reflection effects during image processing. The setup can be easily converted between the OKR and OMR
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configurations. In OMR configuration, mirrors are placed on the ceiling and floor of the arena, and the camera is
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looking down at the animal from the center of the ceiling (Figure 1A). In OKR configuration, the animal is held by an
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implanted head mount, and a videocamera is imaging the pupil through a transparent infrared total reflection mirror
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(Figure 1B). In this configuration, top and bottom mirrors are removed. To measure both reflexes simultaneously
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(Figure 1C), the apparatus was configured for OMR, and a second camera was placed on one of the side panels,
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elevated from the platform by 12 cm. Traditionally the gain (eye or head velocity / stimulus velocity) is used as a
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measure to determine the tuning of the visual system to the spatial and temporal aspects of the stimulus. In this study
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we also analyzed the total number, and duration of tracking (slow) phases for each individual trace based on the found
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onsets and offsets of the slow and fast phases. Statistical significance was determined using a two-sample t-test (after
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testing for normal distribution using a Kolmogorov-Smirnov test), or alternatively applying the Kolmogorov-Smirnov
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test for unknown distributions. Optimal curve fits were determined by minimizing the residual mean square error and
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maximizing the correlation (R2) using the Matlab curve fitting toolbox (cftool).
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Measurement of the Optomotor response
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For OMR, the mice were placed on a platform in the center of the setup and virtual sphere (Figure 1A i, ii).
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Experiments were started after a short period of habituation once the animal calmed down. We recorded each animal for
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at most 30 min and interrupted recordings for at least 5 min, allowing us to clean the mirrors and platform. Monitors
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where turned off during this time period to cool down. The same animal was not measured again until it had rested at
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least 2h. Recordings were acquired at 25 frames per second. For recording analysis, a thresholding algorithm was used
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to define the mouse shape, compute the contour and define head angle (Figure 1A ii, Supplementary Movies 1 and 2
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(Kretschmer et al. 2015)). Angular head speed, Vhead, was calculated as the differential between head angle for each pair
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of successive frames. For the automated OMR analysis (Figure 1A iv), the ratio of time the animal moved in the
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correct direction (Tc) and incorrect direction (Ti) is defined as the OMR index: OMRind = Tc / Ti. In this study, we only
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calculated the OMR index for experiments using stimulus speeds of 12o/s. Tc represents the number of frames for
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which the mouse head moved in stimulus direction with speed Vhead ranging from:
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(Vstim – 10) =< Vhead =< (Vstim + 2).
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Vstim is the stimulus angular velocity (Figure 1 A iv, trials falling within the green window). Ti represents the number of
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frames in which the head moved in a direction opposed to the stimulus with speed:
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(Vstim – 10) =< (-Vhead) =< (Vstim + 2).
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Note that for Ti, the head moves with the same absolute speed window as for Tc (Figure 1A iv, trials falling within the
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magenta window). The (Vstim -10 o/sec) to (Vstim +2 o/sec) interval has been previously shown to be optimal for angular
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head movements detection when OMR stimuli are moving at 12 o/sec (Kretschmer, 2015). To calculate spatial
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frequency dependency of OMRind and individual OKR and OMR events parameters, we derived the optimal fits for our
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data (e.g. Figure 2 A-D, Figure 4 A-H) using the cftool function in Matlab. By optimizing the Residual Mean Square
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Error and R2 values, we determined the fourth order polynomial fit (f(x) = a*x4 + b*x3 + c*x2 + d*x + e) as ideal for our
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data. Optimal spatial frequencies and maximal OMRind (maxOMRind) values were derived from the fitted curves, and
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then a threshold criteria was calculated as ((maxOMRind – 1)/4 + 1). Since a complete lack of visual response results
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in an OMRind of 1 (i.e. the animal preforms a similar number of random moves in correct and incorrect direction, Tc/Ti
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= 1), this formula returns the 0.25 of maximal OMRind amplitude. During manual analysis (Figure 1A iii) the video
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file and head tracking locations were loaded into a MATLAB program used to navigate through the video and the
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recorded traces and identify the onsets and offsets of slow (tracking) and fast (reset) phases. To select OMR events the
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user navigated through the video file together with the x and y coordinates of the two markers defining the head angle
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(red dots in Figure 1A ii, examples in Figure 3A) frame by frame. The tracking and reset phases have strong
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translational components along the axes and hence are more easily detectable when the x and y projections are plotted
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separately (see insets in Figure 3A, detailed description in (Kretschmer et al. 2015)). Note that, while the head angle
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tracking and reset phases in Figure 3A have significant angular jitters, the projection along the X axis has a more
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smooth trajectory, which can be easily separated in tracking and reset phase.
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OMR was collected using the following sets of varying conditions: a) variation of the spatial frequency under
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scotopic and photopic light conditions at various contrasts (automated analysis); b) variation of the spatial frequency
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(manual analysis) under photopic light condition c) Variation of stimulus velocity under photopic light conditions.
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Measurement of the Optokinetic reflex
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For a detailed description of all procedures used to record and analyze OKR, see Kretschmer 2015. The mouse
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was restrained in an acrylic holder through an implanted head post. The holder was then positioned in the center of the
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setup and the virtual sphere (Figure 1B ii and iii). The eye was illuminated with an infrared light source and the eye
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image was reflected through an infrared mirror to an ETL-200 videocamera (ISCAN, Burlington, MA, USA) positioned
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at the top of the arena (Figure 1B i-iii). Before recording, each mouse eye was calibrated using a variant of the
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procedure previously described by Stahl et al (Kretschmer et al. 2015; Stahl et al. 2000; Zoccolan et al. 2010). The
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corneal reflection and pupil position were detected via the DQW software (ISCAN), and converted into angular
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coordinates using a Matlab procedure and the acquired calibration data. We recorded each animal for at most 30 min
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and interrupted recordings for at least 5 min, allowing us to clean the mirrors and platform. Monitors where turned off
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during this time period to cool down. The same animal was not measured again until it had rested at least 2 h.
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Recordings were then analyzed semi-automatically. In a first step a MATLAB program was used to detect onsets and
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offsets of tracking (slow) and reset (fast) phases in the recordings. In a second step the onsets and offsets were checked
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manually by the user. Based on the annotated onsets and offsets we then calculated the number of occurring tracking
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phases and their duration, velocity and gain (Figure 1B iv). Eye velocity was approximated by a linear regression over
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each detected time window (Kretschmer 2015). For operational purposes, if the stimulus reversed direction during a
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tracking phase, it was split into two tracking phases at the point of direction reversal (e.g., for each of Figure 3C at 0.05
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cyc/o, six eye tracking phases not followed by reset phases were annotated, one for each unidirectional stimulus epoch).
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The following experiments for OKR measurements were performed under photopic light conditions: a) variation of the
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spatial frequency b) variation of the stimulus velocity c) variation of stimulus amplitude (total angle covered while
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stimulus moves in one direction), d) masking of the visual field subdivisions.
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Simultaneous measurement of Optokinetic and Optomotor responses
Simultaneous eye and head measurements were recorded from unrestrained animals placed on the platform in
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the OMR configuration, with an additional lateral camera (Pro 9000, Logitech, Switzerland) placed on one of the arena
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walls elevated about 12 cm above the mouse platform (Figure 1C i). Recordings from the lateral camera were
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synchronized to the recordings of the camera monitoring the animal from the top. Because the mouse was not restrained
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the eye was not continuously in the focus of the lateral camera. Hence we recorded around 500 trials (1 min each)
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during several sessions out of which only around 100 were used for analysis. The recordings (resolution of 1280 x 720
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px and 25 frames per second) were analyzed semi-automatically using a custom MATLAB program. The pupil position
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of the left and right eye and the two reference locations at the nasal edge of the eyes (Figure 1C ii) were detected using
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a template matching algorithm based on a normalized cross-correlation (Lewis 2007) which was applied to a manually
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defined region of interest. The four templates were manually selected for each recording. The coordinates with the
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highest correlations were then calculated for the pupil positions and reference locations. The reference locations were
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subtracted from the pupil locations. All recordings with the lateral camera were done using sine grating stimuli of 0.2
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cyc/° spatial frequency rotating at 12 °/s and changing its direction every 5s.
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Results
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Automated quantitation of OMR at scotopic and photopic light conditions and various contrasts.
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Mice generate OMR responses only infrequently during any individual recording period, even under optimal
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stimulation conditions. It is perhaps for this reason that previous approaches were focused on counting the number of
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OMR events / unit time. We have recently proposed an unbiased approach in which angular head velocities are
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recorded for all frames of the recording, and then a “overall direction bias” which we call OMR index (OMRind,
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material and methods and Figure 1A iv) is calculated (Kretschmer et al. 2013; Kretschmer et al. 2015).
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Figure 2 shows OMRind dependency on visual stimulus contrast, spatial frequency and scotopic/photopic
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regime. Experiments were performed at a stimulus angular speed of 12°/s (Figure 2 A-D, Supplementary Table 1). Data
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was fitted with a fourth order polynomial function and a criterion for the visual threshold was defined as the spatial
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frequency at which the fit curve of the measured response reaches 0.25 of its maximum (Material and Methods, Figure
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2E-H). Under photopic conditions the OMRind dependency on spatial frequency in Brn3bWT/WT mice is similar with
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previously published observations (Figure 2A, E, I, Supplementary Table 1, (Prusky et al. 2004; Umino et al. 2012;
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Umino et al. 2008)) with maximum OMR at 0.15 – 0.17 cyc/°, decreasing towards both lower and higher spatial
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frequencies, and reaching baseline at 0.4 cyc/°. Both optimal and threshold OMRind amplitudes gradually diminished
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for contrast levels ranging from 1 to 0.05 and OMRind threshold spatial frequencies decreased from 0.39 cyc/° to
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0.3029 (Figure 2E, I Supplementary Table 1). At contrast level 0.05 the maximal OMRind amplitude was still
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marginally higher than the levels of random variation seen in blind animals (Figure 2A, E), but the polynomial fit was
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poor (R2 = 0.1955), and most of the curve fit was essentially aligned to the baseline. Brn3bWT/WT mice exhibited
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qualitatively similar OMRind under scotopic and photopic light conditions (compare Figure 2A, C, E, G). The scotopic
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maximal OMRind amplitudes are somewhat (not statistically significant) lower, than the photopic amplitudes – e.g. at
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spatial frequency = 0.2, p values at contrast levels 1, 0.2, 0.15 and 0.1 are 0.2330, 0.0518, 0.4232 and 0.6208
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respectively. Under scotopic conditions the threshold values range between 0.43 and 0.31 cyc/° for 1 – 0.05 contrast
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levels, (Figure 2G, K, Supplementary Table 1), comparable to those observed under photopic conditions.
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Maximal photopic OMRind amplitudes of Brn3bKO/KO mice were significantly reduced when compared to
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Brn3bWT/WT, at full contrast levels (Figure 2 A, B, E, F; Kolmogorov-Smirnov test, at spatial frequency = 0.2 and
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contrast = 1, p = 0.0204), however the differences at lower contrast levels were not statistically significant (e.g. at
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spatial frequency = 0.2; p for contrast 0.2 = 0.9719 and p for contrast 0.15 = 0.4428), and the optimal and threshold
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spatial frequencies were in similar ranges compared to the Brn3bWT/WT littermates (Figure 2 A, B, E, F, I, J and
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Supplementary Table 1) for all contrast levels. Under scotopic conditions, the maximal amplitude of the OMRind in
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Brn3bKO/KO mice was drastically affected at full contrast (Figure 2 C, D, G, H; Kolmogorov-Smirnov test; at spatial
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frequency = 0.2 and contrast = 1, p = 0.0023). Whereas the maximal amplitudes for all other contrast levels were
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diminished, differences from those observed in Brn3bWT/WT littermates were not significant. Interestingly, just as for
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photopic conditions, the optimal and threshold spatial frequencies were only minimally affected in Brn3bKO/KO
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compared to Brn3bWT/WT littermate controls (Figure 2G, H, K, L). However, it should be noted that most curve fits for
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OMRind in Brn3bKO/KO mice under scotopic conditions were relatively poor (R2 =< 0.2, Supplementary Table 1 and
307
Figure 2H), and OMRind amplitudes comparable to the range of variation in blind mice (Figure 2D, gray area
308
representing the interquartile intervals for OMRind in 6 months old rd1/rd1 rod-less cone-less mice).
309
310
Analysis of individual OMR and OKR events
311
Whereas the OMRind quantitation reveals global biases in head angle movements relative to stimulus direction,
312
this approach cannot directly describe the characteristics of individual OMR events. We therefore manually defined
313
individual Optomotor and Optokinetic responses on the automatically produced traces (Figure 3). We defined
314
individual events tracking (slow) phases and reset (fast) phases that follow/interrupt the slow phase for both OMR and
315
OKR (Figure 3, green and magenta lines respectively). Under optimal OMR stimulus conditions (photopic light levels,
316
contrast = 1, stimulus angular speed 12 o/sec, spatial frequency 0.2 cyc/o), OMR responses in wild type (Brn3bWT/WT)
317
mice can alternate between continuous tracking phases in stimulus direction (Figure 3B), and brief tracking (slow)
318
movements in stimulus direction followed by reset (fast) movements in reverse direction (Figure 3A). These second
319
type of movements were essentially absent from Brn3bKO/KO mice. We note that, in our recordings, head OMR events
320
have strong translational components, and hence are more easily recognized by projections onto the orthogonal axes
321
((Kretschmer et al. 2015) Figure 9 and this work, Figure 3A, top two traces).
322
We also systematically recorded OKR responses at various spatial frequencies under the same stimulus
323
conditions as for OMR in Brn3bWT/WT and Brn3bKO/KO animals. Tracking and reset phases of OKR events were identified
324
automatically (examples in Figure 3C, D, quantitations in Figure 4). In Brn3bWT/WT OKR, slow tracking phases of very
325
low gain (0.1 in median) occured continuously at low spatial frequencies up to 0.05 cyc/° (Figure 3C, top, Figure 4A).
326
These movements lasted for almost the entire 5 seconds of the unidirectional stimulus epoch, uninterrupted by reset
327
phases (Figure 3C top, Figure 4C), similar to the head movement example in Figure 3B. At optimal spatial frequencies
328
(0.2 cyc/°) tracking phases were more numerous, much faster (gain 0.7 in median), shorter (2s) and were typically
329
followed by a fast phase (Figure 3C middle). As spatial frequencies increase beyond the optimum, the slow phase gain
330
decreased resulting in OKR movements similar to those seen at 0.05 cyc/°. Finally, at spatial frequencies above 0.4
331
cyc/° animals completely stopped performing OKR (Figure 3C bottom). During these trials the pupil of the animal
332
rested in the default axis position and only very rarely spontaneous saccade-like eye movements were recorded, more
333
frequently associated with the animal repositioning its body in the holder. To summarize, visual stimuli of optimal
334
spatial frequency (0.2) result in frequent events (25/min in median), with high gain (0.7 in median) and short duration
335
(2s). Outside the optimum, the number of movements declined, they became longer and slower, and were rarely
336
followed by fast phases (Figure 4A-C, magenta traces for Brn3bWT/WT animals). The spatial frequency dependency of
337
OMR events paralleled the results seen for OKR, both in terms of curve shapes and absolute values, with the exception
338
of gain, which was significantly lower (max = 0.3 OMR vs. 0.7 OKR, Figure 3A, B and Figure 4 D-F).
339
340
In Brn3bKO/KO mice, both OKR and OMR responses were dominated by low gain, slow phases tracking the
stimulus continuously, essentially uninterrupted by reset phases. For the OKR, the eye constantly moved in stimulus
10
341
direction (Figure 3D), at very low gain (around 0.1, Figure 4A), with individual tracking phases essentially covering the
342
entire unidirectional stimulus epoch (Figure 3D, Figure 4B, 12 tracking phases/minute hence 1 tracking phase for each
343
of the 12 5s trial segments). Fast reset phases were very rare (Figure 4H), and hence individual tracking phases lasted
344
for the whole 5 seconds of the stimulation epoch (Figure 3D, 4C). For the OMR, head gain was around 0.1 (Figure 4D),
345
and the head tracking movements were less frequent than for OKR (Figure 4E, around 6/minute or only one every other
346
5 s unidirectional stimulus epoch), and lasted only about 4 seconds (Figure 4F).
347
We had previously reported complete loss of vertical OKR in Brn3bKO/KO mice (Badea et al. 2009). We
348
therefore measured vertical eye movements in response to a stimulus presented on a virtual sphere rotated around the
349
roll axis (Figure 4I). For Brn3bWT/WT mice the optimal spatial frequency lied at 0.1-0.15 cyc/° in median, while the
350
threshold was reached at 0.35 cyc/°. As previously reported, Brn3bKO/KO mice did not respond to stimuli rotating around
351
the roll axis, thus the number of tracking phases was consistently zero.
352
The automatically determined OMRind was consistent with the individual OMR movement analysis for both
353
Brn3b
354
0.15 cyc/° to 0.25 cyc/°. The responses decreased both towards higher and lower spatial frequencies and at 0.4 cyc/°
355
both Brn3bWT/WT and Brn3bKO/KO mice moved the same amount of time in the correct and in the incorrect direction
356
(ratio=1).
WT/WT
and Brn3bKO/KO mice in this dataset (Figure 4G). The peak was less well pronounced but in the range of
357
We used fourth order polynomial functions as optimal fits for the Brn3bWT/WT data shown in Figure 4A-H, to
358
directly compare the qualitative trends in the different parameters of the responses. Figure 4J shows the fit curves for
359
OKR gain, number and duration of tracking phases and number of reset phases, corresponding to data in Figure 4A-C
360
and H. All four parameters show similar trends with the threshold spatial frequency lying between 0.33 cyc/° (duration
361
of the tracking phases) and 0.37cyc/° (number of tracking phases). Given the pendular movement of our stimulus,
362
which reverses direction every 5 seconds, the maximum duration of a tracking phase is 5 sec. The plateau of the
363
duration from 0.3 cyc/° to 0.425 cyc/° (Figure 4B) is likely a consequence of this quantification. For OMR, the
364
automated OMRind (Figure 4G), the manually annotated number of tracking phases (Figure 4E) and the duration of
365
these phases (Figure 4F) also show very similar spatial frequency fit curves (Figure 4K). All three parameters show a
366
maximum at 0.2 cyc/°, while the 0.25 quartile threshold ranges from 0.36 to 0.375cyc/°. The only parameter that does
367
not show this trend is the OMR head gain (Figure 2D, K). The head gain remains relatively constant (0.25) in the spatial
368
frequency range of 0.1 to 0.3 cyc/° and only drops to 0.15 at the edges of the spatial frequency range with the goodness
369
of fit being much worse than for the other parameters.
370
Data presented in Figure 3 suggested that both OKR and OMR responses could be heterogeneous in angular
371
velocity and duration. To get a better understanding of the range of their variation, we recorded head and eye
372
movements at the reported optimum for OMR (contrast = 1, spatial frequency = 0.2 cyc/°, stimulus velocity = 12°/s; for
373
OMR: 10 mice measured 10 times for 1 min; for OKR 7 mice measured 3 times for 1 min). After manually annotating
374
the traces, we calculated the duration and velocity of all occurring tracking phases. We distinguished two types of OMR
375
and OKR episodes, based on the presence or absence of the fast reset phase in stimulus-opposed direction following a
376
slow movement phase in stimulus direction (Figure 5). Overall OMR response duration shows a much higher degree of
11
377
variation compared to eye movements (compare Figure 5A, B to D, E). Most OMR responses have durations of around
378
1s and a velocity of 2°/s and only about half are followed by a reset movement (Figure 5A, B). Slow and long
379
movements (>4s) are never followed by such a retraction. In contrast, OKR velocity is only slightly below stimulus
380
velocity. Most OKR movements are performed at 10°/s, last 800 ms (median) and are followed by a fast reset
381
movement (Figure 5D, E). To relate the head/eye excursions of the animal to the maximal unidirectional stimulus
382
excursion (60°), we calculated the angle the head and eye cover during an individual tracking phase. Most eye and head
383
tracking phases cover 1° to 10° angular amplitude (Figure 5C, F). The loglogistic fit suggests a very similar maximum
384
of 3° for both OMR and OKR, and very few events extend to 30°, thus far from the maximum unidirectional stimulus
385
angular amplitude of 60°. In conclusion, OMR head movements are more heterogeneous, much slower and less likely
386
to be followed by fast reset phases than OKR eye movements, however typically cover similar angular amplitudes.
387
388
389
Optomotor and Optokinetic responses at various stimulus velocities
Our experiments, performed at a stimulus speed of 12 o/sec, reported to be optimal for OMR (Prusky et al.
390
2004; Umino et al. 2008), revealed much smaller gains for OMR in comparison to OKR. We therefore re-evaluated the
391
stimulus speed dependency of OMR and OKR gain, under maximal contrast and optimal spatial frequency (0.2 cyc/°)
392
conditions. The stimulus rotated around the animal in either clockwise or counter clockwise direction for 30 seconds at
393
a time (unidirectional stimulation epoch = 30 seconds). Epochs of different directions and speeds were presented in
394
random order to prevent adaptation, and results for the two directions were pooled. Figures 6A and 6B are exemplary
395
traces showing dissimilar number/durations of the slow phases at different stimulus velocities (2 and 12 o/sec, top two
396
panels) but also within the same stimulus velocity (22 o/sec, two example traces, bottom panels). The stimulus velocity
397
dependency curves for number and duration of tracking phases for both OKR and OMR had a bell shape, with the
398
maximum number of movements being evoked at around 10-15°/s (Figure 6 C, D, F, G). However, the gain for both
399
OMR and OKR decreased with increasing stimulus velocity, with maximal gains of 0.7-0.8 for OKR (Figure 6E) and
400
0.3 for OMR (Figure 6H). Therefore eye and head velocities (gain x stimulus velocity) were highest in the interval 10 -
401
15°/s stimulus velocity, and thus the number of OKR or OMR movements / unit time was highest and their duration
402
shortest (1-2 s) within this interval. At high stimulus velocities the spread of response duration increased (Figure 6D, G
403
at velocities >=15°/s), as result of a mixture of frequent, low velocity eye or head drifts (Figure 6A, B, third panels,
404
example 1) and less common trials during which eye or head were able to better keep up with stimulus velocity (Figure
405
6A, B, bottom panels, example 2).
406
407
408
Relative contribution of visual field to OMR and OKR.
409
We find that OMR and OKR responses have equivalent sensitivity curves with respect to spatial frequency and
410
speed of moving stimuli, but strongly differ in gain. If both reflexes are driven by the same detectors, what could be the
411
conditions that result in the gain difference? An obvious difference between OMR and OKR recording is the head
12
412
fixation, that results in differential input from the vestibular and proprioceptive systems, and different effector muscle
413
groups involved, but also in constraints on the areas of the field of view of the animal that are stimulated (e.g.
414
monocular versus binocular, eye excursions within the orbit versus head and body excursions). During OMR the mouse
415
might observe the visual stimulus under a variety of angles, and with distinct relative contributions of the monocular
416
and binocular fields of view, depending on the head angle under the Yaw, Pitch and Roll axes. To determine whether
417
different retinal regions have distinct efficiency in eliciting OKR, we designed virtual masks to cover the left (ipsi,
418
measured) or right (contra) binocular or monocular hemifields, either individually or in combination (Figure 7A, B).
419
Figure 7A depicts the unfolded virtual sphere as projected onto our four screens in the recording setup, and highlights
420
the boundaries between presumed monocular and binocular fields of view (Bleckert et al. 2014; Dräger 1978; Sterratt et
421
al. 2013). The ipsilateral and contralateral fields are labeled relative to the recorded (left) eye. The set of masks (1-9)
422
are represented as symbols at the bottom of figure 7B, with black areas signifying the subdivisions of the visual field
423
that were occluded. This set of masks were overlayed on top of the sinusoidal vertical gratings moving under optimal
424
stimulation conditions (0.2 cyc/°, 12 °/s, contrast = 1) in either nasal-to-temporal (N-T) or temporal-to-nasal (T-N)
425
direction relative to the recorded (left) eye. In the subsequent description the T-N and N-T directions, as well as the ipsi
426
– contra distinctions will always refer to the recorded (left) eye. Although the OKR is conjugate, it has previously been
427
reported that monocular stimulation in temporal nasal (T-N) direction relative to the stimulated eye is more effective
428
(Cahill and Nathans 2008; Stahl et al. 2006). Under full field stimulation (mask 1) 36 tracking phases / minute (median)
429
are detected for either stimulus direction. We indeed find that the effects of masking either the monocular or binocular
430
hemifields are highly dependent on the direction of the stimulus relative to the stimulated eye. For statistical
431
comparisons, see Supplementary Table 1. Thus, right (contra) binocular hemifield occlusion impaired OKR only during
432
N-T stimulation (median = 29 phases, mask 2, green, p = 0.0183 vs. mask 1), while left (ipsi) binocular hemifield
433
occlusion affected OKR under N-T (median = 25 phases, mask 3, green, p = 0.0023 vs. mask 1) and not significantly
434
for T-N (median = 32 phases, mask 3, magenta, p = 0.367) conditions. Occlusion of the entire binocular field resulted
435
in an even stronger reduction in OKR responses regardless of stimulus direction (median = 20, mask 4, p = 0.0023 for
436
either T-N or N-T vs. mask 1). The effects of the left or right monocular hemifield occlusions were even more
437
pronounced, reducing the number of OKR phases to almost half when compared to the unmasked condition, under
438
either T-N or N-T stimulation. Occlusion of the left (ipsi) eye reduced OKR response in both directions of stimulation
439
(median = 17 phases, mask 6, p = 0.0023 for either T-N or N-T vs. mask 1). However, occlusion of the contra eye was
440
more deleterious to the OKR response during stimulus presentation in the N-T direction (mask 5, N-T, green, median =
441
10 vs. T-N, magenta, median = 26, p = 0.0013). Finally, occlusions of the complete left or right hemifields impaired
442
OKR more than just occluding the monocular hemifields (masks 7 and 8), and the least potent OKR stimulation was
443
elicited by stimulating the full binocular field alone (mask 9, N-T = 4, T-N = 8 in median, p = 0.0023 for either T-N or
444
N-T vs. mask 1). Covering the entire right (contra) field had dramatically different consequences depending on
445
stimulus direction (mask 7). Stimulation of the ipsi eye in its preferred direction (mask 7, T-N, magenta) resulted in
446
around 22 OKR events (median), while N-T stimulation (mask 7, green) yields only 2 (median) (p = 0.0013). The effect
447
is reversed when the left (ipsi) field of view is covered, only stimulating the right eye (mask 8, N-T, green, median =
13
448
449
13, vs T-N, magenta, median = 2, p = 0.0122).
In our hands, stimulating the recorded eye results in a moderate but consistent increase in OKR tracking when
450
compared to stimulating the contralateral eye, even when the stimulus direction is optimal for the respective stimulated
451
eye (e.g. masks 5 and 7 in T-N, versus masks 6 and 8 in N-T, p = 0.0013).
452
Thus, both binocular and monocular fields can elicit OKR. In our experiments, the binocular field (see Figure
453
7A), represented by the area centered around vertical meridian 0, and delimited by the horizontal meridian at 30o and
454
the two gray monocular regions, is relatively small. However, it has an unexpectedly large contribution to the OKR,
455
compared to its size relative to the monocular fields. Thus, for mask 4, almost half of OKR movements are gone when
456
the full binocular region is covered.
457
Significantly, during OKR recordings the mouse head is positioned in the setup on a horizontal axis. In
458
unrestrained mice, distinct areas of the visual field can actively be directed towards stimuli by adjusting the body
459
posture, most importantly head inclination. We therefore determined the inclination of the head during 100 OMR
460
recordings (10 mice, 10 trials each), with the mouse freely moving on the platform (Figure 7C, D). All animals incline
461
their head by 40° to 60° in median during OMR experiments, most likely resulting in a larger portion of the binocular
462
field of view facing the stimulus.
463
464
465
Influence of visual stimulus angular amplitude
As described in Figure 5, the slow phases of head and especially eye movements cluster around an angular
466
amplitude of about 3.5o, but reached as much as 30o. During those experiments the visual stimulus moved at 12 o/sec,
467
changing direction every five seconds and therefore covering an angular amplitude of 60o. At suboptimal spatial
468
frequency conditions, or in Brn3bKO/KO mice, head or eye movements exhibit mostly a low gain and can continuously
469
follow the stimulus over multiple unidirectional stimulation epochs of five seconds, without being interrupted by fast
470
reset movements, and reversing direction together with the stimulus; however such events can also be observed in
471
Brn3bWT/WT mice under optimal stimulation conditions (Figure 3B, and C - D - top traces). We therefore wanted to
472
explore the influence of stimulus angular amplitude on the length of slow phases of eye movements. We designed a set
473
of stimuli that change direction after a defined angular amplitude. We varied the amplitude from 20° to 120° in steps of
474
10°, while stimulating under optimal conditions, (stimulus velocity of 12°/s, spatial frequency 0.2cyc/°, contrast 1). We
475
then analyzed the effect the amplitude has on the length of the slow phase of OKR movements (Figure 7E). At an
476
amplitude of 20° the animal manages to follow the stimulus for the entire duration of one epoch (20° / 12°/s = 1666ms)
477
most of the time. At higher amplitudes the animal is still able to track for the entire stimulus amplitude up to 60° but
478
mostly performs movements that last up to 1s. Thus mice can perform OKR movements of up to 5.5 s (~ 55o amplitude,
479
considering a gain of 0.8 and stimulus velocity of 12°/s), however the most stereotypical OKR eye movements last for
480
0.5 seconds (~ 5° representing the customary range) or less, regardless of unidirectional stimulation epoch amplitude.
481
482
483
Simultaneous recordings of head and eye movements in response to moving gratings.
We find in this study that mouse head gains during OMR are significantly lower than eye gains during OKR.
14
484
One potential explanation is that image stabilization is achieved through combined head and eye movements in freely
485
behaving mice, as has been seen in other species (Collewijn 1977; Fuller 1987; Gresty 1975). We therefore recorded
486
eye and head movements simultaneously under OMR stimulation and recording conditions (Figure 1C, Figure 8,
487
supplementary movies 3 and 4). Supplementary movies 3 and 4 show examples of the lateral camera recording of a
488
mouse performing head and eye tracking simultaneously. Note that, whereas eyes are almost continuously engaged in
489
OKR events, clear head OMR episodes are noticeable between seconds 2-5 and 11-13 of the movie. Figures 8A, B
490
show exemplary traces of head and eye movements recorded simultaneously under optimal stimulation conditions.
491
Figure 8A illustrates eye movements that look similar with those observed during head restrained OKR experiments.
492
The two eyes perform synchronized tracking phases, followed by fast reset phases, while the head moves in stimulus
493
direction at a very low gain. No head retractions/resets could be observed. However, in the Figure 8B recording, head
494
movements had larger gain, shorter tracking phases at constant velocity in stimulus direction followed by fast reset
495
phases. Due to the expansive head movements only the right eye was in focus during the recording, and fewer saccadic
496
movements are observed. Figure 8C shows the distribution of eye and head velocities during head-eye coincident
497
tracking movements. Since no calibration for the spherical eye shape is possible under head free conditions, we used a
498
theoretical spherical model of the eye to transform pixel distances in the image plane into eye angular coordinates.
499
Relative velocities should hence be seen as estimates. The eye velocity histogram has a maximum in the 8-10 °/s
500
interval, slightly lower than the value derived for eye velocities in the head restrained animal (Figure 5D, E), while the
501
head velocity histogram exhibits the same distribution as in previous experiments (Figure 5A, B). There seems to be no
502
strong correlation between eye and head velocity (Figure 8C), while the correlation between angles covered by the two
503
eyes during coincident OKR movements is reasonably high (Figure 8E, R2 for the linear regression line = 0.76).
504
Interestingly, the distribution of summated head + eye velocities, peaks between 12 and 16 o/s, slightly higher than the
505
stimulus speed (12 o/s). Given the various measurement constraints, this falls very close to unitary gain.
506
507
Discussion
508
We use our automated head tracking algorithm to report the first determinations of head angular velocities
509
during mouse OMR and perform a direct, quantitative comparison between OMR and OKR responses. We find that
510
mouse OMR and OKR tuning for stimulus speed and spatial frequency are in good agreement for most parameters
511
investigated, but that OMR gain is significantly lower than OKR gain under all stimulation conditions. We also provide
512
the first evidence that mice, like other mammalian species, perform combined head and eye movements during
513
unrestrained horizontal optokinetic response. We then show that Brn3bKO/KO mice, previously known to be devoid of
514
ON-DS RGCs, the input neurons to the Accesory Optic System, have profound defects in both OMR and OKR.
515
Previous work had reported that optimal stimulus conditions for eliciting mouse OMR range around velocities
o
516
of 12 /sec, and spatial frequencies of 0.15 – 0.2 cyc/o, and found that the OMR spatial visual acuity threshold is around
517
0.4 cyc/o (Prusky et al. 2004; Umino et al. 2008). In these experiments, an observer is asked to identify mouse head
518
movements in stimulus direction, a decision which might be related to the number, amplitude and speed of the
519
movements made by the tested animals and the subjective perception of the observer. Our own quantitations, based on
15
520
an automatic overall directional bias index of the head movement (OMRind) or the direct computation of gain, number
521
and duration of individual OMR slow (tracking) phases come up with similar ranges for spatial frequency optimum
522
(0.15 – 0.2 cyc/o) and visual acuity threshold (0.375- 0.4 cyc/o) (Figures 2 and 4). These values are also in good
523
agreement with OKR tuning for spatial frequency, when parameters such as the gain, numbers and duration of slow
524
(tracking) and fast (reset) phases are computed (Figure 4 and (Sinex et al. 1979; Tabata et al. 2010; van Alphen et al.
525
2009)). The absolute value of head or eye velocity, as well as the customary ranges for head and eye excursions during
526
OMR and OKR are probably more related to the kinematic properties of the systems subserving them (head and neck
527
muscles, oculomotor muscles, interactions with vestibular and proprioceptive systems, etc.). However, the similar
528
tuning of OKR and OMR parameters to spatial frequency suggests that they derive their input from similarly tuned
529
visual inputs (possibly ON-DS RGCs). This notion is further supported by the fact that both OKR and OMR gain are
530
maximal at low stimulus velocities (less than 5 o/sec, Figure 6 and (Stahl 2004a; Stahl et al. 2006; Tabata et al. 2010;
531
van Alphen et al. 2009)), consistent with reported optima for the ON-DS RGCs in rabbits and mice (Collewijn 1969;
532
Oyster et al. 1972; Sun et al. 2006; Yonehara et al. 2009). At higher stimulus velocities (beyond 16°/s) the variability of
533
both OMR and OKR responses, increases and mice seem to alternate between high and low gain tracking, in both head
534
and eye movements (see examples 1 and 2 in Figure 6A, and 6B). It is possible that these stimulus speeds occasionally
535
engage alternative visual mechanisms driven by other detectors, for instance ON-OFF-DS RGCs, which respond
536
optimally to stimulus speeds of 25°/s in rabbits and mice, (Collewijn 1969; Elstrott et al. 2008; Oyster et al. 1972;
537
Weng et al. 2005).
538
In our experiments, the eye continuously participates in OKR events during (optimal) stimulus presentation
539
under head fixed conditions, with most slow (tracking) phases exhibiting rather stereotypical velocities, durations and
540
eye angle excursions, followed by fast (reset) phases (Figure 5, see also (Cahill and Nathans 2008)). Hence the duration,
541
number and velocity of slow tracking (eye) phases are linked; e.g. a higher velocity results in a quicker reach of
542
preferred angular excursion of the eye (customary range), hence shorter movements, more consistently followed by fast
543
(reset) phases and overall more OKR events / unit time. In contrast, participation during OMR (under the same stimulus
544
conditions) is far less consistent, i.e. the amount of time the mouse spends engaging in OMR events is reduced and
545
highly variable (see Figures 3 - 5). As a result, mouse OMR quantitations are more dependent on the number of events
546
/unit time, and their duration, to relay a sense of how salient the stimulus is. We now show that mouse head gain
547
decreases with increasing stimulus velocity, and the maximal velocities for both eye and head are reached at a stimulus
548
speed of about 12 o/sec (see also (Stahl 2004a; Stahl et al. 2006; Tabata et al. 2010; van Alphen et al. 2009) for OKR
549
stimulus speed dependency). Hence mice perform most head/eye tracking phases at velocities of 10-14°/s, and
550
determining the number of individual tracking phases results in a bell shaped curve around this “optimum”. Similar
551
gain dependencies on stimulus velocities for head and eye movements have been previously reported for rabbits, guinea
552
pigs and rats (Collewijn 1977; 1969; Fuller 1985; 1987; Gresty 1975).
553
An interesting observation to us is that slow (tracking) phases for head movements during OMR and to a lesser
554
degree for eye movements during head – fixed OKR can exhibit heterogeneity with regard to velocity, duration and
555
presence or absence of the reset (fast) phase (Examples in Figure 3, quantitated in Figure 5). Mice seem able to switch
16
556
between (i) periods of low gain, continuous head tracking (slow) phases in stimulus direction, amounting to small
557
angular excursions and uninterrupted by fast reset phases, and (ii) shorter, faster head tracking (slow) phases, that are
558
followed by reset (fast) phases essentially resembling classic OKR eye movements (equivalent to a head nystagmus).
559
Type (i) head OMR events can be seen quite often even under optimal conditions for stimulus spatial frequency and
560
velocity, but are predominant at suboptimal stimulus spatial frequencies or speeds. This phenomenon was previously
561
described for tracking (slow) phases in the cited mouse OKR literature, as well as head and eye movements in the rat,
562
gerbil and rabbit (e.g. Collewijn, Fuller). Given the presence of OKR eye movements in unrestrained mice, one trivial
563
explanation could be that the mouse alternates between movement of eyes, head, or a summation of both to achieve
564
image stabilization (e.g. Collewijn, Fuller, Gioanni). We note that type (i) tracking (slow) phases can also be seen for
565
head fixed OKR, predominantly under suboptimal stimulus conditions. Heterogeneity in excursion angular amplitude of
566
eye slow (tracking) phases during OKR can also be influenced by the angular amplitude of the unidirectional
567
stimulation epoch (Figure 7E). It appears that for small stimulus angular amplitudes (20o), mice prefer to follow the
568
stimulus with uninterrupted slow (tracking) phases, akin to our type (i) movements. Tracking movements covering the
569
entire unidirectional stimulation epoch become less and less frequent as the stimulus angular amplitude increases from
570
20 to 120o, and gradually get replaced by the more stereotypical short tracking phases covering the “customary range”
571
of 3.5-5o.
572
Head and eye velocity ranges we recorded in unrestrained mice are consistent with the isolated head OMR and
573
head-restrained eye OKR recordings, (compare Figure 8C to Figure 5), despite the discussed limitations to angular eye
574
velocity calibration. A somewhat unexpected finding to us is that pairs of head and eye velocities under unrestrained
575
conditions do not show a strong anti-correlation, as would be expected if the head and eye velocities would add up to
576
result in a constant gaze velocity, close to or matching the stimulus speed (Figure 8C). However our estimate suggests
577
that head and eye gain could almost fully compensate for stimulus motion (histogram peak head 4°/s + histogram peak
578
eye 8°/s = 12°/s = stimulus velocity), and the histogram of combined (head + eye) velocities has a peak between 12-16
579
o
580
full image stabilization as a result of combined head and eye movements is not consistently achieved unless stimulus
581
speeds are in the range of a few o/sec. Interspersed periods of stabilization have been observed (Fuller 1985; 1987;
582
Gresty 1975) resulting in minimized retinal slippage through combined eye and head motion. It should be noted that, as
583
described above, slow and fast phases of horizontal head OMR are not necessarily taking the trajectory of rotations
584
around the yaw axis, but in many cases have strong translational components (see detailed examples in (Kretschmer et
585
al. 2015). For illustration, in Supplementary Movie 4 between 5 and 11 seconds there are several iterations of head
586
tracking movements with strong rotational components, while between 22-25 seconds the head slow (tracking) phase
587
exhibits a strong downwards trajectory, with the snout nearly reaching the lower edge of the image. Be it as it may, the
588
angular excursions for the two eyes relative to the head are comparatively well synchronized (Figure 8D). The
589
variation of head and eye movement participation and gain could be explained by alternation between different viewing
590
modes (Dawkins 2002) and could be affected by the level of attention and the behavioral context (see (Maurice and
591
Gioanni 2004) for examples in pigeons). Similarly, in fish, OKR is mainly driven by rotational motion, whereas OMR
/s, resulting in a combined gain of 1 – 1.33. Studies in other afoveated species come to similar conclusions, i.e. that
17
592
is mainly driven by translational movement and rapid head displacements might occur during voluntary search (Kubo et
593
al. 2014).
594
The correct estimation of combined head + eye gaze orientation and hence the relative contributions of head
595
and eye angular velocities to image stabilization during optokinetic stimulation depends on the angle of the head around
596
the pitch axis and the axes of the eyes relative to the head. In our head-fixed OKR recordings aimed at determining the
597
contribution of monocular and binocular fields to OKR, the head was fixed in the OKR apparatus such that the snout
598
would point at the 0 meridian, with an inclination of the snout-orbit axis of about 15-20o forward around the pitch axis.
599
In contrast the head inclination during OMR recordings, as defined by a line connecting the snout to the center of the
600
orbit is about 55o forward around the pitch axis, which seems consistent with the ambulatory position described in
601
(Oommen and Stahl 2008) and hence placing the eye inclination at about 22o on the vertical axis. This difference in
602
head inclination around the pitch axis could result in an enlarged binocular field of view contribution to the OMR
603
compared to the OKR, and reorientation of the eyes relative to the head as a result of the maculo – ocular tilt reflex
604
(Maruta et al. 2001; Oommen and Stahl 2008; Wallace et al. 2013). Our head-fixed OKR data seem to suggest a
605
significant participation of the binocular field of view to OKR, so given the differences in head pitch, it is entirely
606
possible that its contribution is much higher during OMR. Monocular and binocular subdivisions of the retina could
607
provide distinct contributions to OKR/OMR by exhibiting relative differences in either cell type density/distribution,
608
and/or receptive field sizes. In humans, peripheral and central velocity detectors might operate in different velocity
609
ranges and OKR stimuli can elicit different gains when presented at different retinal eccentricities (Dubois and
610
Collewijn 1979; Van Die and Collewijn 1986). In mice, RGC types do exhibit topographic differences in dendritic
611
arbor (and receptive field) size across the retina ((Badea and Nathans 2011; Bleckert et al. 2014). However, we are
612
unaware of such topographic distinctions for ON and ON-OFF DS RGCs, the likely substrates of OKR/OMR.
613
Mice lacking the Brn3b transcription factor (Brn3bKO/KO) have significant losses in multiple RGC cell types, and
614
exhibit major defects in pupil constriction and OKR responses, accompanied by inconsistent defects in circadian
615
photoentrainment (Badea et al. 2009). We now report a more complete picture of the OKR deficit, and in addition
616
identify OMR defects. The overall directional index OMRind, as well OMR slow (tracking) phase gain, duration and
617
number is reduced in Brn3bKO/KO mice when compared to Brn3bWT/WT controls, but the tuning to spatial frequency is not
618
significantly affected, with both optimal and threshold spatial frequencies in ranges similar to the control animals. The
619
gain of horizontal OKR tracking (slow) phases is dramatically affected, and Brn3bKO/KO OKR events consist of
620
essentially continuous, low gain tracking uninterrupted by reset (fast) phases (as seen in examples in Figure 3 and
621
quantitated in Figure 4), while the vertical OKR is completely abolished. Both OMR and horizontal OKR events are
622
highly reminiscent of Brn3bWT/WT type (i) OKR and OMR events (low gain, continuous tracking phases in stimulus
623
direction, uninterrupted by fast reset phases). One could interpret the residual optokinetic behavior in Brn3bKO/KO mice
624
in several ways: a) a few remaining ON-DS RGCs projecting into the NOT/DTN provide a low level of visual input
625
that converts into low gain tracking phases that do not reach the effector customary range; b) other types of RGCs,
626
which project to the SC and LGN engage an alternative circuit, which is characterized by the type (i) movements; c) the
627
RGCs surviving in the Brn3bKO/KO mice, regardless of the targeted nucleus, have altered stimulus input functions and
18
628
hence drive the low gain. An argument for alternative RGCs being involved is that the type (i) movements are also
629
present in WT mice, at suboptimal but also optimal stimulation conditions. However, our mutants preserve spatial
630
frequency tuning for both OKR and OMR. This fact is more consistent with the loss of detectors that can signal motion
631
individually (ON-DS RGCs) than with the loss of single units out of a mosaic which conveys motion information in a
632
cooperative fashion (e. g. alpha or parasol RGCs). Intuitively, losing individual ON-DS RGCs will result in reduced
633
response strength (number of movements, and gain) but should only affect spatial frequency tuning after extensive RGC
634
loss, as each individual ON-DS cell can detect the movement, and the whole retina would have to lose a large number
635
of ON-DS RGCs before the edges of the pattern would fall on tissue devoid of detectors. However, motion detection
636
dependency on stimulus spatial frequency would be much more rapidly affected by the fallout of RGCs from the
637
parasol/alpha system, as it depends on the pattern moving across neighboring RGC receptive fields. In addition, if
638
RGCs projecting to LGN or SC could drive a hypothetical alternative circuit they should be able to do so for the vertical
639
OKR component, which is not what we observed (Figure 4I).
640
641
In conclusion, we show that OMR and OKR are similarly tuned for stimulus speed and spatial frequency, and
642
are similarly affected by loss of AOS projecting RGCs, arguing for common visual afferent inputs. The previously
643
reported differences in spatio-temporal tuning for OMR and OKR are a function of the applied metrics (human observer
644
detecting mouse motion for OMR vs. gain for OKR). Our “overall directional bias” OMR index offers an objective
645
assessment of OMR dependency on stimulus properties, but will not provide more in depth information regarding gain
646
and other individual head OMR event properties. While OKR signal to noise ratios are much better, we show that OMR
647
can yield similar results without the need for invasive procedure, fixation of the animal, or calibration procedures.
648
However, unrestrained mice perform OKR type eye movements, and head gains are very small compared to eye gains,
649
therefore OMR experiments may miss subtle differences under suboptimal conditions (see Brn3bWT/WT vs. Brn3bKO/KO
650
OMRind comparison at lower contrast values). We would therefore advocate for a graded approach where automated
651
OMRind determinations can be used to screen for effects of manipulations suspected to affect optokinetic responses,
652
followed by in depth investigations of the OMR head traces, and eventually OKR responses if needed. OMR gain
653
dependency on stimulus parameters is probably the most appropriate measure as is customary for OKR in mice (Stahl
654
2004a; Stahl et al. 2006) or other species. Ideally, combined head and eye recordings are necessary and to a certain
655
degree feasible by expansions of the approach we employed.
656
657
658
659
660
Figure Legends
661
662
663
Figure 1 Recording configurations for OMR and OKR measurements.
Three different apparatus configurations were used to evaluate OMR (A), OKR (B), and eye movements in
19
664
freely behaving animals (C). Experiments in A and B were carried out using the same conditions as presented in
665
Kretschmer et al 2015. A, Measurement of head movements (OMR). i, Schematic of recording configuration. The
666
animal moves unrestrained on a platform and is monitored from above with a camera fitted with an Infrared (IR) high-
667
pass filter. ii, Example of a frame recorded by the top camera, with annotations of the automated online tracking
668
algorithm. Four screens are presenting a stimulus consisting of vertical sinusoidal bars, and the arena is illuminated with
669
IR LED strips placed at the corners between the screens. The green dot represents the center of mass for the
670
automatically detected mouse contour (green outline), while the two red dots define the head orientation of the animal
671
(for examples see supplementary movies 1 and 2). iii, Example and naming convention for the manual trace annotation.
672
Tracking movements were identified from the automatically derived head tracking trace. x axis is time, y axis is head
673
angle. The onset and offset of the slow (“tracking”, green) and fast (“reset”, magenta) phases were derived, and then the
674
duration (gray dashed line) and the velocity (blue dashed line) of the slow phase computed. iv, Calculation of the OMR
675
index. For the automated analysis of head movements, the pairwise head angle differentials between all successive
676
frames of the recording were determined (histogram, normalized to total number of observations). We then defined
677
windows of (+2 o/sec to -10 o/sec) around the stimulus speed (+/- 12 o/sec black vertical lines), for the correct (green)
678
and incorrect (magenta) directions and counted the total correct (Tc) and incorrect (Ti) movements contained within the
679
two windows. The OMR index was computed as Tc/Ti. B, Measurements of eye movements (OKR). i, example of
680
pupil tracking using the Iscan videocamera. Pupil position is calculated relative to an IR corneal reflection landmark,
681
and the pixel displacement converted to angular coordinates using the calibration technique adapted from Stahl et al
682
2000. ii, iii, Schematics of the recording setup, showing side view (ii), and frontal view (iii) of the mouse in the holder.
683
The animal is restrained using an implanted head mount and the eye image projected to the camera through a 45O IR
684
reflective mirror (placed in a plane parallel to the axis of the mouse). iv, Eye movements were analyzed semi-
685
automatically. Several parameters were derived from the Iscan recorded traces: the onset and offset of the slow
686
(tracking) phase (green), the duration (gray dashed line), the velocity (blue dashed line) and the onset of the fast (reset)
687
phase (magenta). The automatically detected phases were checked manually in a second step. C, For simultaneous head
688
and eye detection, we recorded the head movements of the unrestrained mouse as in A, while imaging the eyes with an
689
additional camera fixed onto the arena wall, at 12 cm elevation above the mouse platform (i). ii, Pupil locations (green
690
circles) and the nasal edges of the eyes (magenta cross) are determined by a pattern matching algorithm, while head
691
position was collected using the same protocol as in A.
692
693
Figure 2: OMR dependency on visual stimulus contrast, spatial frequency and photopic/scotopic conditions in
694
Brn3bKO/KO and Brn3bWT/WT mice
695
A-D, OMR index (see Figure 1A iv) collected from Brn3bWT/WT (A, C, n = 7) and Brn3bKO/KO (B, D, n=5) mice under
696
photopic (A, B) and scotopic (C, D) conditions, at 5 contrast levels (top to bottom, contrasts = 1, 0.2, 0.15, 0.1 and 0.05)
697
and 9 spatial frequencies (0.025, 0.05, 0.1, 0.2, 0.3, 0.35, 0.375, 0.4, 0.45). Black solid lines represent medians for all
698
mice of the same genotype, and data points (circles) represent medians for individual animals. Each animal was
699
measured three times at each condition. Note that some poor recordings were discarded from the analysis (e.g. mouse
20
700
jumping off the platform), resulting in lower numbers of observations at some combinations of spatial frequency and
701
contrast. Three outlier observations are represented as blue crosses, placed at the spatial frequencies they occurred. The
702
OMRind values for the outliers were: B, second plot = 3.53; D second plot = 2.72, and fourth plot = 3.16). E-H, Fourth
703
order polynomial fits (f(x) = a*x4+ b*x3+ c*x2+ d*x + e) for data in A-D. Coefficients a-e, R2 values, maximal OMRind,
704
optimal spatial frequencies are provided in supplementary table 1. Curve fits for contrasts = 1 (blue), 0.2 (black), 0.15
705
(green), 0.1 (magenta) and 0.05 (red), for each genotype and light conditions have been superimposed. Throughout, the
706
stippled horizontal line and gray area represent the median and upper and lower quartiles of the OMR index previously
707
collected in the same setup from a set of three control blind animals (retinal degeneration rd1, 6 months old). We
708
include it to illustrate the degree of variation of the OMR index resulting from random movements in a blind mouse
709
(i.e. independent of vision). Arrows point at the spatial frequency at which the fit has reached the 25% threshold. I-L,
710
Contrast dependency of optimal and threshold (criterion) spatial frequencies for Brn3bWT/WT (I, K) and Brn3bKO/KO (J, L)
711
mice under photopic (I, J) and scotopic (K, L) conditions, as computed from the fits in Figures E-H. See also
712
Supplementary table 1.
713
714
Figure 3 Exemplary annotated Head and Eye movements.
715
A, B, Examples of head movement traces collected with the top camera (Figure 1A), from a Brn3bWT/WT mouse exposed
716
to moving vertical sine gratings (contrast = 1, spatial frequency = 0.2 cyc/O, stimulus velocity = 12 o/sec, changing
717
direction every five seconds bottom of figure C and D). The coordinates along the orthogonal directions (x-top, y-
718
middle) and head angle (bottom) are presented. Green: tracking phases, Magenta: reset phases. In A, tracking phases
719
(green) are followed by reset phases of opposing direction (magenta), and the animal follows only infrequently (most of
720
the trace is black). The boxed regions along the trace have been magnified along the y axis and are shown in the insets.
721
In B, the mouse followed continuously and only once repositioned its body/head (black trace at ~3s). C, D, Example
722
traces of recorded eye movements (OKR, Figure 1B) from Brn3bWT/WT (C) and Brn3bKO/KO (D) mice at three different
723
spatial frequencies (0.05 cyc/°, 0.2 cyc/°, 0.45 cyc/°). The Brn3bWT/WT mouse (C) exhibits high-gain tracking phases
724
frequently followed by reset phases at optimal spatial frequency (0.2 cyc/°), and low-gain tracking phases not followed
725
by reset phases at suboptimal spatial frequency (0.05 cyc/°). The Brn3bKO/KO mouse (D) tracks with low-gain slow
726
phases not followed by fast phases at both 0.05 cyc/° and 0.2 cyc/°. Neither genotype exhibits observable eye
727
movements at high spatial frequency (0.45 cyc/°).
728
729
730
Figure 4 Comparison of OKR and OMR dependency on spatial frequency in Brn3bKO/KO and Brn3bWT/WT mice.
A-F, Spatial frequency dependency of gain (A, D), number (B, E) and duration (C, F) of tracking phases for
731
OKR (A-C) and OMR (D-F) recordings of Brn3bKO/KO (green, n = 3) and Brn3bWT/WT (magenta, n= 3) mice. Data are
732
presented as median (black lines) and observation ranges (shaded areas, observations represent medians of individual
733
mice). For recording conditions and example traces see Figure 3. Note that the y scale for C, F is inverted. G,
734
Automated OMR Index for the same experiments as D-F. Horizontal stippled line at 1 and shaded gray area (0.8 – 1.2)
735
represent OMR Index median and interquartile interval for a blind mouse. H, Number of reset phases for OKR
21
736
experiments in A-C. I, Vertical OKR recordings for Brn3bKO/KO (green, n = 2) and Brn3bWT/WT (magenta, n= 3) mice. J,
737
K, Data for Brn3bWT/WT mice shown in A-H was fitted following the fourth order polynomial function (using the
738
MATLAB curve fitting toolbox and the nonlinear least absolute residual method: f(x) = a*x4+ b*x3+ c*x2+ d*x + e. We
739
used degrees of freedom adjusted R-Square to determine the goodness of fit. For OKR measurements: number of slow
740
OKR phases (black, data from B), R2 = 0.84; number of reset phases (blue, data from H), R2 = 0.68; gain (purple, data
741
from A), R2 = 0.80; duration of tracking phases (red, data from C), R2 = 0.50. For OMR curves: number of tracking
742
phases (black, data from E), R2 = 0.80; OMRind (blue, data from G), R2 = 0.72; gain of OMR response (purple, data
743
from G), R2 = 0.46; duration of OMR phases (red, data from F), R2 = 0.79. The curves were scaled for better
744
comparison of the qualitative trends, and color coded together with their respective axes.
745
746
Figure 5 Velocity, duration and amplitude of OMR and OKR slow phases.
747
OMR (A-C) and OKR (D-F) were recorded from 3 Brn3bWT/WT mice at the reported optimum for OMR
748
(contrast = 1, spatial frequency 0.2 cyc/◦, velocity of 12 ◦/s). A, D, Scatter plots and histograms for tracking phases that
749
were not followed by reset phases. B, E, Scatter plots and histograms for tracking phases that were succeeded by reset
750
phases. Horizontal black line indicates stimulus velocity (12 ◦/s). C, F, Histograms for head (C) and eye (F) slow phase
751
amplitudes overlayed with the loglogistic fit (red). For C and F, slow phases were pooled regardless of the presence or
752
absence of a fast phase.
753
754
755
Figure 6 Comparison of OKR and OMR dependency on stimulus velocity.
OMR and OKR were recorded from 5 animals, (measured 3 times each) at contrast 1 and spatial frequency of
756
0.2 cyc/°. Individual unidirectional stimulus epochs lasted for 30s. A, Exemplary traces of eye movements at three
757
different stimulus velocities (2, 12 and 22°/s). At 22°/s the animals were not able to keep up with stimulus velocity most
758
of the time (example 1) and performed fewer tracking phases. In rare occasions eye velocity was significantly higher
759
and more tracking phases were performed (example 2). B, Exemplary traces of head movements at three different
760
stimulus velocities (2,12 and 22°/s – two examples). Green traces represent slow movements in stimulus direction
761
while magenta traces represent fast reset movements. C-H, Number (C, F), Duration (D, G), and gain (E, H) of OKR
762
(C-E) and OMR (F-H) tracking phases exhibit distinct dependencies on stimulus velocity. Note that y axis (duration)
763
for D and G are inverted. Data are presented as medians across all animals (median of medians, black line) and range of
764
medians for each animal (magenta areas).
765
766
767
Figure 7 OKR dependency on visual field topography and stimulus direction and duration.
For all experiments, stimulation was done at contrast = 1, spatial frequency = 0.2 cyc/o and speed = 12 o/sec. A,
768
B, OKR Masking experiments. A, Planar projection of the virtual sphere displayed in our apparatus, showing the
769
subdivisions of the mouse visual field (based on Dräger, 1978). Binocular and monocular regions and angular
770
eccentricities in horizontal and vertical plane are indicated, for a mouse facing the schematic and pointing its snout at
771
the intersection of zero horizontal and vertical axes. The red lines at +/- 30 degrees indicate the limits of the virtual
22
772
sphere as visible on the four screens. Ipsilateral and contralateral fields are identified relative to the recorded (left) eye.
773
B, Number of slow tracking phases during presentation of sinusoidal vertical grating stimuli moving in either temporo-
774
nasal (magenta) or naso-temporal (green) direction relative to the recorded (left) eye. Nine different masks were
775
applied to the visual field, indicated at the bottom of B, ordered from left to right as follows: 1 – full field visible; 2 –
776
contralateral binocular field occluded; 3 – ipsilateral binocular field occluded; 4 – bilateral binocular field occluded; 5 –
777
contralateral monocular field occluded; 6 – ipsilateral monocular field occluded; 7 – full contralateral field occluded; 8
778
– full ipsilateral field occluded; 9 – bilateral monocular fields occluded. White areas in the diagrams are visible, black
779
areas occluded. Bottom left, schematic of the mouse head seen from the top with camera imaging left eye, and
780
convention for stimulus directions relative to the imaged eye. Note that the magenta stimulus direction is temporo-nasal
781
(T-N) for the imaged left eye, but naso-temporal for the right eye. Recordings are from 2 animals, 3 trials for each
782
condition. Results are presented as medians (black line) and observation ranges of all measurements (magenta and
783
green areas). C, D, Inclination of the head during OMR experiments. C, Head inclination is defined as the angle
784
between a horizontal axis through the mouse trunk, and a head axis through the snout tip and orbit. D, Angles were
785
computed for 10 trials for each of 10 animals, and are presented as box-whisker plots. Red lines are medians, boxes
786
define the interquartile intervals, and whiskers the range of observations. The median inclination over all animals is
787
54.5 o. E, Dependency of OKR tracking phase duration (y axis) on the angular amplitude of the unidirectional
788
stimulation epoch (angle after which the stimulus changes direction, x axis). Angular amplitudes were varied between
789
20o and 120o in increments of 10o. Number of slow movements are presented normalized to the maximal value within
790
each angular amplitude (scale ranging from 0 to 1, heat map to the right). The maximum length of a tracking phase
791
cannot be longer than the duration of one unidirectional stimulus epoch (e.g. 2.5 sec at amplitude = 30o; 5 sec at
792
amplitude = 60o). Results were derived from 4 animals, 3 trials each.
793
794
795
Figure 8 Simultaneous recording of head and eye movements.
Recording conditions were described in Figure 1C. Visual stimuli are sinusoidal vertical bars of contrast = 1,
796
spatial frequency = 0.2 cyc/o moving at speed = 12 o/sec, reversing direction every 5 s (panels at the bottom of A and
797
B). Two C57Bl6 Brn3bWT/WT mice were used for these recordings. Eye angles were calculated from the images acquired
798
by the side camera, using a conversion based on a spherical eye model, and ignoring perspective distortion. Head angles
799
were calculated as for all previous OMR experiments, using the data provided by the top camera. A, Simultaneous
800
recording of both eyes and head. Panels represent from top to bottom: angular velocities for left eye, right eye and
801
head. Tracking phases (green) and reset phases (magenta) were semi-automatically annotated. Eye velocities for the two
802
marked tracking phases (magenta +, *) are indicated in the scattergram in panel E. B, Example of recording in which
803
large head movements (second panel) prevented collection of meaningful images for the left eye, and only intermittent
804
focused eye images for the right eye (first panel). Periods during which the right eye was out of focus are marked as
805
dotted gray lines. Note different y scales for the different plots. Bottom panels for A and B show stimulus positions
806
plots. C, Velocity of head and eye movements (tracking phases where collected from 7 recordings, 1 min each). The
807
histograms depict the distribution of head and eye velocities. All recordings where at least one eye was in focus were
23
808
analyzed. D, Histogram of combined (head + eye) velocities, for the observations shown in D. E, The relative angle
809
covered during individual tracking phases by left (y axis) and right (x axis) eyes, expressed as percentage of head
810
movement. Tracking phases were collected from 5 recordings, 1 min each, in cases where both eyes and the head was in
811
focus. Linear regression line is shown (green, R2 = 0.76).
812
813
814
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26
A
B
C
i
ii
i
iii
iii
ii
iv
iv
i
ii
photopic
Brn3b
Brn3b
Brn3b
WT/WT
Brn3bKO/KO
A
B
C
D
E
F
G
H
contrast = 0.2
contrast = 0.15
contrast = 0.1
Optomotor Index (Tcorrect/Tincorrect)
scotopic
KO/KO
contrast = 1
2. 4
2
1. 6
1. 2
0. 8
0. 4
2. 4
2
1. 6
1. 2
0. 8
0. 4
2. 4
2
1. 6
1. 2
0. 8
0. 4
2. 4
2
1. 6
1. 2
0. 8
0. 4
2. 4
2
1. 6
1. 2
0. 8
0. 4
WT/WT
contrast = 0.05
2.2
1.8
ct 1
ct 0.2
ct 0.15
ct 0.10
ct 0.05
1.4
1
0.6
Spatial frequency (cyc/o)
0
0.1 0.2 0.3 0.4
0
0.1 0.2 0.3 0.4
0
0.1 0.2 0.3 0.4
0
0.1 0.2 0.3 0.4
Spatial frequency (cyc/o)
0.5
0.4
I
J
K
L
0.3
0.2
Optimal
Criterion
0.1
0
0 0.2 0.4 0.6 0.8
1 0 0.2 0.4 0.6 0.8
1 0
0.2 0.4 0.6 0.8
Contrast
1 0 0.2 0.4 0.6 0.8
1
A
Brn3bWT/WT
0.2 cyc/o
B Brn3bWT/WT
0.2 cyc/o
0.05 cyc/o
D Brn3bKO/KO
0.05 cyc/o
220
200
188
174
66
52
C Brn3bWT/WT
0
5
10
15
Time [s]
20
0.2 cyc/o
0.2 cyc/o
0.45 cyc/o
0.45 cyc/o
25
30
0
5
10
15
Time [s]
20
25
30
J
Number tracking phases (B)
Azim. eye gain (A)
OKR
2.5
3
4
3.5
4.5
K
OMR
Number tracking phases (E)
OMR
G
OMRind
E
OMR
H
OKR
F
OMR
Reset phases /minute (n)
D
2
2.5
3
3.5
4
4.5
Duration tracking phases (F)
OKR
OMRind (G)
C
Head gain (D)
OKR
Duration tracking phases (C)
B
Tracking phases /minute (n)
OKR
Number reset phases (H)
Tracking phases /minute (n)
A
I Vertical OKR
Brn3bKO/KO
Brn3bWT/WT
OMR
50
40
30
20
10
0
15
10
5
0
50
40
30
20
10
0
0
Eye velocity [o/s]
15
10
5
1
2
3
4
5
Duration of tracking phase [s]
5
50
10 30 50
count
E 5040
with reset
0
10
100
20
0
15
count
count
Head velocity [o/s]
50
count
without reset
30
20
10
0
20
Eye velocity [o/s]
Head velocity [o/s]
20
B
OKR
D 5040
without reset
count
count
A
30
20
10
0
20
15
10
5
0
100
with reset
0
1
2
3
4
5 10 30 50
Duration of tracking phase [s]
count
C 100
F
120
count
200
count
150
80
60
100
40
50
20
0
0
5
10
15
20
25
30
Head angle excursion during tracking phase [o]
0
0
5
10
15
20
25
30
Eye angle excursion during tracking phase [o]
10
0
-10
10
0
-10
10
0
-10
10
0
-10
B
50
head angle [o]
azim. eye [o]
A
50
o
2 /s
0
o
12 /s
22o/s (example 1)
0
22o/s (example 2)
10
D
25
20
15
10
5
5
10
15
20
30
25
G
Duration [s]
Duration [s]
2
3
22o/s (example 2)
20
30
OMR
20
15
10
5
0
0
5
10
15
20
25
0
5
10
15
20
25
0
5
10
15
20
Stimulus velocity [O/s]
25
0
2
3
4
4
5
0
5
10
15
20
25
1
0.8
0.6
0.4
0.2
0
5
10
15
20
Stimulus velocity [O/s]
25
H
1
Gain [Vhead/Vstim]
Azim. eye gain [Veye/Vstim]
10
1
1
E
0
F
25
0
5
22o/s (example 1)
0
50
time [s]
OKR
0
0
Tracking phases/min (n)
Tracking phases/min (n)
C 30
12o/s
50
0
30
20
time [s]
0
2o/s
0.8
0.6
0.4
0.2
0
C
E
n
Angle covered by left eye
(% of angle covered by head)
50
Head velocity [o/s]
0
24
20
16
12
8
4
0
0
D
4 8 12 16 20
Eye velocity [o/s]
0
25
20
15
n
B
Stim[o] Head[o] Right eye[o] Stim[o] Head[o] Right eye[o] Left eye [o]
A
10
5
0
0
4
8 12 16 20 24 28 32 36
head + eye velocity (o/s)
50
n
104
103
102
101
100 0
10
101
102
103
Angle covered by right eye
(% of angle covered by head)
104