Sleep and auditory input
J. Sleep Res. (2010) 19, 585–590
doi: 10.1111/j.1365-2869.2010.00829.x
Auditory input modulates sleep: an intra-cochlear-implanted
human model
R I C A R D O A . V E L L U T I 1 , M A R I S A P E D E M O N T E 2 , H Á M L E T S U Á R E Z 3 ,
C L A U D I A B E N T A N C O R 2 and Z U L M A R O D R Í G U E Z - S E R V E T T I 4
1
Neuro-Otologı́a Experimental, ORL, Hospital de Clı́nicas, Programa de Desarrollo de Ciencias Básicas (PEDECIBA), Universidad de la
República, 2Centro de Medicina del Sueño, Facultad de Medicina, CLAEH, Punta del Este, 3Laboratorio de Otoneurologı́a, British Hospital and
4
Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
Accepted in revised form 11 December 2009; received 20 July 2009
SUMMARY
To properly demonstrate the effect of auditory input on sleep of intra-cochlearimplanted patients, the following approach was developed. Four implanted deaf
patients were recorded during four nights: two nights with the implant OFF, with no
auditory input, and two nights with the implant ON, that is, with normal auditory
input, being only the common night sounds present, without any additional auditory
stimuli delivered. The sleep patterns of another five deaf people were used as controls,
exhibiting normal sleep organization. Moreover, the four experimental patients with
intra-cochlear devices and the implant OFF also showed normal sleep patterns. On
comparison of the night recordings with the implant ON and OFF, a new sleep
organization was observed for the recordings with the implant ON, suggesting that
brain plasticity may produce changes in the sleep stage percentages while maintaining
the ultradian rhythm. During sleep with the implant ON, the analysis of the
electroencephalographic delta, theta and alpha bands in the frequency domain, using
the Fast Fourier Transform, revealed a diversity of changes in the power originated in
the contralateral cortical temporal region. Different power shifts were observed,
perhaps related to the exact position of the implant inside the cochlea and the scalp
electrode location. In conclusion, this pilot study shows that the auditory input in
humans can introduce changes in central nervous system activity leading to shifts in
sleep characteristics, as previously demonstrated in guinea pigs. We are postulating that
an intra-cochlear-implanted deaf patient may have a better recovery if the implant is
maintained ON during the night, that is, during sleep.
keywords
interactions
auditory processing, cochlear implants, deafness, sleep, sleep–sensory
INTRODUCTION
The principal function of the central nervous system (CNS) is
information ⁄ signals processing, which it does continuously
during the circadian cycle, that is, including sleep periods. The
capacity to process auditory information during sleep is a fact
demonstrated by several experimental approaches, including a
Correspondence: Ricardo A. Velluti, Libertad 2647 ⁄ 801, 11300
Montevideo, Uruguay. Tel.: +598-99-210-425, fax: +5982-585-8629;
e-mail: [email protected]
2010 European Sleep Research Society
variety of different techniques such as evoked potentials, eventrelated potentials, magnetoencephalography-evoked activity
and functional magnetic resonance imaging (fMRI) in
humans, and auditory neuronal firing in guinea pigs, cats,
and primates (Bastuji and Garcı́a-Larrea, 2005; Bastuji et al.,
2002; Campbell and Bartoli, 1986; Edeline et al., 2001; Issa
and Wang, 2008; Kakigi et al., 2003; Pedemonte and Velluti,
2005; Portas, 2005; Portas et al., 2000; Vanzulli et al., 1961;
Velluti, 2005; Velluti and Pedemonte, 2002).
Sleep, in turn, is a special physiological state postulated to
be influenced by the sensory incoming data from the body
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(inner world) and from the environment (Velluti, 1997, 2008).
Because the sensory incoming data are continuously reaching
the CNS – including the usual night noises without any specific
sound stimulation – its processing will depend on the current
physiological state of the brain, that is, quiet wakefulness,
sleep stages I, II, slow-wave sleep (SWS; III, IV) and
paradoxical sleep (PS; Velluti, 1997, 2008; Velluti and Pedemonte, 2002).
Cochlear implants can improve physiological communication ability in the most severely deaf patients, leading to social
and psychological benefits, even considering the abnormal
and, in many ways, poor input provided by these devices.
Brain activity analysis with modern imaging techniques in
humans has provided evidence for plasticity of the central
auditory pathway following profound hearing loss (Fallon
et al., 2008; Giraud et al., 2001; Hari et al., 1988; Seghier
et al., 2005). Plasticity means dynamic shifts in preexisting
connections across neuronal networks taking place in response
to changes in afferent input (Pascual-Leone et al., 2005), the
latter being the auditory activity in our experimental approach.
Human imaging techniques reported low levels of auditory
cortical activity among deaf subjects: the longer the duration
of deafness, the lower the level of activity recorded. Moreover,
the metabolic activity in the primary auditory cortex was
observed to increase bilaterally to nearly normal levels after a
successful cochlear implantation, although the greatest activity
was obtained using fMRI on the side contralateral to the
implant (Lazeyras et al., 2002).
The sleep analysis of profound postlingual deaf human
patients successfully implanted with intra-cochlear devices was
our target to further support the hypothesis that auditory
input does have effects on sleep organization. This hypothesis
finds additional support from animal experimental data
(Pedemonte and Velluti, 2005; Velluti, 2005; Velluti and
Pedemonte, 2002), where auditory unit firing exhibited discharge shifts and different temporal patterns in sleep. Moreover, no auditory unit has ever been found that stops firing
when passing into a sleep phase. Thus, auditory input arriving
at the guinea pig, cat and monkey cortex (Edeline et al., 2001;
Issa and Wang, 2008; Peña et al., 1999) and pathway nuclei
(Velluti, 2008; Velluti and Pedemonte, 2002) produces functional changes in sleep patterns. Moreover, Amici et al. (2000)
reported the increase of PS after auditory stimulation during
SWS in rats. In humans, the income of new auditory
information during both sleep phases modifies the general
sleep organization.
MATERIALS AND METHODS
Nine postlingual profound deaf patients (age range 19–
65 years) were included in this study. Four of them (age range
55–65 years) had been previously implanted (by H. Suárez)
with multichannel cochlear implant devices (2 years before
this study), with successful hearing results (Table 1). Sleep
cycle characteristics were studied in all deaf patients, whereas
four of them were analyzed with the intra-cochlear implant
Table 1 Auditory characteristics of four intra-cochlear-implanted
patients
1. TGC: Vowel recognition, 78–88%; Consonant recognition,
48–55%; Speech tracking, 47–70 per min.
2. AMP: Vowel recognition, 78%; Consonant recognition,
48%; Speech tracking, 50 per min.
3. CMZ: Vowel recognition, 69%; Consonant recognition,
46%; Speech tracking, 45 per min.
4. RS: Vowel recognition, 73%; Consonant recognition,
50%; Speech tracking, 48–55 per min.
ON or OFF without any sound stimulation other than usual
night noise (50–55 dB in our sleep laboratory). Each implanted
patient was recorded as their own control (implant OFF), thus
allowing assessment of the experimental condition (implant
ON) and its control in the same patient.
All subjects were invited to sleep overnight in the Sleep
Laboratory, five of them for sleep recording as deaf persons,
whereas the group of four previously implanted patients
completed four nights of recording (one night per week) each.
They completed two control nights with the cochlear implant
OFF, that is, simulating the input experienced by a deaf
person, and two experimental nights with the implant ON, that
is, receiving the input experienced by a hearing person. None
of the patients had a history of neurological, psychiatric, or
sleep disorders and were not taking any medication.
The polysomnographic (PSG) study was carried out as a
regular PSG clinical test. A computerized Polysomnograph
(ATI Delphos) was used to record electroencephalographic
(EEG), electrocardiogram, electromyogram, eye movement,
oxygen saturation, and respiratory movements. In addition to
the EEG electrodes, two temporal leads (left T3 and right T4)
were placed on the scalp over the temporal lobe, according to
the 10–20 electrode positioning method.
Data processing
Because the sleep stage percentages for most of our patientsÕ
ages are known to be uneven, each patient was analyzed as
their own control. Sleep stage percentages of five deaf persons
and four implanted patients were studied. The sleep examination considered all the current stages: I, II, III, IV, and PS,
according to the atlas of Rechtschaffen and Kales (1968).
The T3–T4 EEG recording was analyzed in the frequency
domain using the Fast Fourier Transform (FFT) during the
different sleep stages, and comparing the EEG frequency power
distributions with the implant ON and OFF. Twenty EEG
windows of 20 s each in sleep stages II, III, IV, and PS were
selected for the FFT analysis during steady state recordings
with the implant ON and OFF. The delta (d, 0.5–2.5 c s)1),
theta (h, 3–7 c s)1), and alpha (a, 8–12 c s)1) brain rhythms
were assessed with FFT power analysis in each sleep stage.
Off-line sleep scrutiny – to establish the corresponding sleep
state percentages – was performed by two different trained
judges.
2010 European Sleep Research Society, J. Sleep Res., 19, 585–590
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Auditory input modulates sleep
50
Statistical analysis
RESULTS
The four intra-cochlear-implanted patientsÕ hearing conditions
are shown in Table 1. The sleep architecture analysis (hypnogram), that is, the relative sleep stages percentage, did not
show significant differences between deaf and normal persons,
while all patients were in bed for 7–8 h.
Figure 1 displays the sleep stage percentages of five deaf
patients, which closely resemble the percentages of a normal
hearing subject, taking into account the well-known variability.
When comparing PSG records of the four deaf intracochlear-implanted patients from two nights, recorded with
the implant OFF and with the implant ON, shifts in the sleep
percentages emerged. On the contrary, no significant sleep
efficiency changes, between 0.87 and 0.94, were observed
between nights with the implant ON or OFF. First, the four
patients analyzed with the implant OFF showed sleep patterns
similar to the deaf control patients. Secondly, when recorded
during sleep with the implant ON – allowing habitual night
noise hearing – different sleep percentages were observed.
Figure 2 exhibits these percentages; with the implant ON
(white bars) subjects exhibited a significant decrease in stage II,
an increase in stages III and IV, and also a significant
percentage decrease during PS.
F.S., 19 years old
A.B., 33 years old
60
A.M.B., 41 years old
T.G.C., 65 years old
%
A.P.R., 60 years old
30
0
I
II
III
IV
Sleep stages
PS
Figure 1. The sleep stage percentages of five deaf persons were equal
to a normal person considering the variability exhibited for the
different ages. Sleep stages are I, II, III, IV (equivalent to SWS or
non-REM sleep), and paradoxical sleep (PS; equivalent to REM sleep).
2010 European Sleep Research Society, J. Sleep Res., 19, 585–590
Intra-Cochlear Implant
40
OFF
ON
*
30
%
The StudentÕs t-test was used for the resulting sleep stages
percentages comparison and to establish the validity of the
different frequency power bands observed with the implant
ON and OFF.
Switching on the intra-cochlear device power, with the
sound off, allowed us to control the reported effects of
magnetic fields on subjectsÕ EEG or sleep.
Full written consent to a non-invasive procedure was given
by all subjects. These non-invasive experiments were carried
out according to the local regulations of the Medical School
Committee for Animal and Human Research (Montevideo)
and the patientÕs signed consent.
*
*
20
*
10
ON
0
I
ON
II
ON
III
ON
IV
ON
PS
Figure 2. Four deaf implanted patients showing the sleep stage percentages (standard deviation and statistical significance, P < 0.05)
with the intra-cochlear implant OFF (gray bars) and ON (white bars).
A significant percentage decrease was evident for stage II and paradoxical sleep (PS; P < 0.05), while an increase in stages III and IV
appeared (P < 0.05). Sleep stages are I, II, III, IV (equivalent to SWS
or non-REM sleep), and PS (equivalent to REM sleep).
An example of sleep stage percentage distributions during
two nights of control (implant OFF) and two nights with the
implant ON (Fig. 3a) exhibits a decrease in stage II percentage,
an increase in stage IV and a decrease during PS. Fig. 3b
shows that the sleep ultradian cycles exhibit a normal
distribution of stages during the night with implant either
OFF or ON.
Figure 4 shows the results of the FFT analysis of T3 and T4
EEG leads exhibiting differences when recording with the
implant ON or OFF. The FFT analysis was performed on
signals from the temporal cortical EEG contralateral to the
implanted cochlea. The FFT power spectra of the delta (d, 0.5–
3 c s)1), theta (h, 4–7 c s)1) and alpha (a, 8–12 c s)1) bands
during the different sleep stages with the implant OFF and ON
from the four implanted patients are presented. The FFT
showed power shifts in all patients. However, the changes
obtained exhibited differences among them.
Patient 1 exhibited a significant decrement in d, h, and a
band power during sleep stage II, and a power decrease in the h
and a bands during stages III, IV, and PS during the ON
condition.
Patient 2 showed a similar FFT power decrease in stage II, d
and h frequency bands in the ON condition, whereas stages III
and IV exhibited no significant power shifts. Besides, the PS
presented a significant power increase in h and a bands.
Patient 3 showed significant power increases in the d, h, and
a bands.
Patient 4 exhibited power increments in the h and a
frequency bands, both in sleep stage II in the ON condition.
During stages III and IV these patients exhibited opposite
patterns, patient 3 significantly decreasing power in the h
and a bands, whereas patient 4 showed an increase in the
power of the h and a frequency bands. During PS, patient 3
showed a significant increase in a band power, whereas
patient 4 exhibited no power shifts on passing to the ON
condition.
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R. A. Velluti et al.
(a) 60
T.G.C.
T.G.C 65 y.o.
Implant
OFF
Implant OFF
Implant ON
ON
1
*
%
*
30
δ
θ
*
*
*
*
α
δ
θ
*
*
α
*
*
*
δ
θ
α
A.M.P.
OFF
ON
0
*
*
2
I
II
III
IV
PS
*
(b) Hypnograms
*
*
Cochlear Implant “OFF”
W
PS
I
II
III
IV
δ
θ
α
δ
α
θ
δ
θ
α
R.S.
OFF
*
ON
3
*
*
Cochlear Implant “ON”
δ
θ
*
α
*
δ
θ
*
α
*
*
δ
θ
α
50
%
C.M.Z.
OFF
ON
0
7.5 h
Figure 3. Example of sleep stages organization in a deaf implanted
patient. (a) The filled circles show control recording nights with the
implant OFF, that is, recorded as a deaf patient, and the open circles,
implant ON, that is, as a hearing patient. The decrease of stage II and
paradoxical sleep (PS), together with the stage IV percentage increase,
are seen once more. (b) The hypnograms display the whole nightÕs
sleep ultradian cycle recordings (7.5 h), two nights with the implant
OFF and two nights with the implant ON. No shifts in the sleep
ultradian cycles were observed. Sleep stages are I, II, III, IV (equivalent to SWS or non-REM sleep), and PS (equivalent to REM sleep).
The reported effects of the magnetic field generated by a
hearing aid or a cell phone that may have an influence on
subjectsÕ EEG or sleep (Huber et al., 2002) were discarded
using an intra-cochlear device ON with the sound off. No
magnetic field effects were observed in the EEG or sleep
organization of the recorded patients.
DISCUSSION
Sleep analysis, carried out with the intra-cochlear implant
OFF or ON, that is, when ÔnewÕ auditory information ⁄ signal
arrives at the CNS, demonstrated shifts in sleep organization,
changing sleep stage percentages as well as the contralateral
cortical (temporal region) EEG frequency bandsÕ power
spectra distribution.
4
*
*
0
δ
θ
II
*
*
α
*
δ
*
α
θ
III-IV
Sleep stages
δ
θ
PS
α
Figure 4. Power spectra (FFT) analysis of the EEG delta (d), theta (h),
and alpha (a) frequency bands recorded with contralateral scalp temporal leads. The variability of the results was the main change introduced by the implant ON. Patient 1 with the implant ON exhibited a
power decrease in stage II in the d, h, and a bands, whereas a power
decrement was observed in bands h and a in sleep stages III, IV, and
paradoxical sleep (PS). In patient 2, the implant ON resulted in a power
decrease in the d and h frequency bands during sleep stage II, and an
increase in the h and a bands during PS. In patient 3, the implant ON
produced a significant power increase in bands d, h, and a during sleep
stage II, associated with a power decrease in the h and a bands in stages
III and IV, while an increase in a band power was observed during PS.
Patient 4 showed a power increase in the h and a frequency bands
during sleep stages II–IV with the implant ON. Power shifts were always present, that is, during the sleep recordings in the contralateral
temporal cortex during different sleep stages when the implant was ON,
over four nights. Sleep stages are I, II, III, IV (equivalent to SWS or
non-REM sleep), and PS (equivalent to REM sleep).
In this pilot study, all the patients subjectively reported that
the night with implant ON was more restorative, perhaps
related to the significant increase in stage IV sleep (Fig. 2).
2010 European Sleep Research Society, J. Sleep Res., 19, 585–590
Auditory input modulates sleep
On the contrary, no significant changes in the ultradian cycle
were depicted, that is, the succession of sleep stages throughout
the night appeared normal (Fig. 3, hypnograms).
When studying the cortical temporal power spectra (analyzed contralateral to the cochlear implant), the only
consistent was that all patients showed shifts during the
different sleep stages, some frequency bands decreasing while
others increasing the power in the different sleep stages
(Fig. 4). A possible explanation for the power band diverse
behavior may be technical, that is, the stimulating point at
the cochlear level is not always the same because of the intracochlear surgical electrodes positioning. Moreover, a scalp
electrode to record the temporal EEG may record power
differences even due to minimum position shifts. Furthermore, Lazeyras et al. (2002) reported that after a successful
implant the metabolic cortical activity increases in contralateral auditory regions.
The herein reported results and control experiments suggest
the hypothesis that profound postlingual deaf persons suffer,
at the onset of deafness, changes in their central auditory
neuronal firings and network reorganization – cortical plasticity – that finally approach a close to normal sleep patterns,
as shown in Fig. 1. On the contrary, when the deaf implanted
patient ÔrecoversÕ his ⁄ her hearing ability with an intra-cochlear
implant, the opposite occurs. New neuronal networks and cell
assembly reorganization appeared altering shifts in sleep stage
percentages when deaf patients were studied with the implant
ON (Figs 2 and 3).
Several lines of evidence support the notion that the
auditory activity encompasses a special relationship with sleep.
Incoming auditory signals may introduce changes in sleep
characteristics and, in turn, sleep may introduce changes in
every auditory nucleus via the auditory efferent system, or at a
cortical level. For instance, the auditory is a tele-receptor
system continuously active that informs the CNS about the
environment during wakefulness and sleep. The blood flow in
the auditory brainstem nuclei and the auditory cortex increases
on falling asleep. In particular, the cochlear nucleus exhibits a
170% increase in blood flow during PS in comparison with a
waking state (Reivich et al., 1968). Human oneiric activity
shows auditory ÔimagesÕ in 65% of the dream contents
(McCarley and Hoffman, 1981). A noisy night may reduce
total sleep time and produce several awakenings in humans
(Pearson et al., 1995; Terzano et al., 1990; Vallet, 1982) as well
as in rodents (Bouyer et al., 2004). Experimental guinea pig
deafening increases sleep time, particularly PS, whereas
wakefulness is reduced (Cutrera et al., 2000; Pedemonte et al.,
1996). Shifts in auditory-evoked potential amplitudes and
waveforms, event-related potentials and evoked magnetoencephalography activity have been reported in both humans
and animal experimental models (Bastuji and Garcı́a-Larrea,
1999, 2005; Campbell and Bartoli, 1986; Kakigi et al., 2003;
Vanzulli et al., 1961).
Analyzing the single auditory neuronal activity during sleep
in the guinea pig, the evoked auditory unit firing recorded at
every nucleus including the primary cortex increases, decreases
2010 European Sleep Research Society, J. Sleep Res., 19, 585–590
589
or remains similar to that observed during quiet wakefulness.
Approximately half of the cortical (A1) neurons studied did
not change firing rate when passing into sleep, whereas others
increased or decreased their activity, that is, the CNS was
continuously aware of the environment (Pedemonte and
Velluti, 2005; Peña et al., 1999; Velluti, 2005, 2008; Velluti
and Pedemonte, 2002; Velluti et al., 2000). Primate cortical
unit responses in sleep (Issa and Wang, 2008) confirm the
previous work by Peña et al. (1999), showing original data on
the guinea pig cortical (A1) auditory unit firing in sleep.
Functional magnetic resonance approaches also contribute
to the concept that auditory cortical activity is maintained
during sleep, for example, showing differences between significant and non-significant sound stimuli (Maquet et al., 2005;
Portas, 2005; Portas et al., 2000). A single photon emission
tomography (SPECT) study was carried out during waking,
after cochlear implantation, showing great activity in bilateral
temporal regions as well as in frontal lobes, with clicks and
Spanish word stimulation (Suárez et al., 1999).
With the help of a successful intra-cochlear implant, hearing
recovery could produce network reorganization that would
consequently alter sleep patterns. Furthermore, we postulate
that the continuous use – including during sleep – of an intracochlear-implanted hearing device will produce a more rapid
recovery of the auditory function with less training time
because auditory processing continues and can be finished ⁄
completed during sleep (Velluti, 2008). This is particularly
important in prelingual deaf infants whose hearing recovery requires a lengthy training period. It is our assumption
that this recovery period can be greatly shortened if the
implant is maintained ON both during awake and sleep
periods.
ACKNOWLEDGEMENT
We are grateful to the Basic Science Development Program
(PEDECIBA, Uruguay) for partial support.
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2010 European Sleep Research Society, J. Sleep Res., 19, 585–590