Download Long-term, passive exposure to non-traumatic acoustic noise

NeuroImage 107 (2015) 1–9
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NeuroImage
journal homepage: www.elsevier.com/locate/ynimg
Long-term, passive exposure to non-traumatic acoustic noise induces
neural adaptation in the adult rat medial geniculate body and
auditory cortex
Condon Lau a,b,⁎, Jevin W. Zhang c,d, Bradley McPherson e, Martin Pienkowski f, Ed X. Wu c,d,g,h
a
Department of Physics and Materials Science, The City University of Hong Kong, Hong Kong, China
Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
c
Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong, China
d
Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China
e
Division of Speech and Hearing Sciences, The University of Hong Kong, Hong Kong, China
f
Osborne College of Audiology, Salus University, Elkins Park, PA, USA
g
Department of Anatomy, The University of Hong Kong, Hong Kong, China
h
Department of Medicine, The University of Hong Kong, Hong Kong, China
b
a r t i c l e
i n f o
Article history:
Accepted 22 November 2014
Available online 3 December 2014
Keywords:
Functional magnetic resonance imaging
Auditory system
Acoustic exposure
Rat
a b s t r a c t
Exposure to loud sounds can lead to permanent hearing loss, i.e., the elevation of hearing thresholds. Exposure at
more moderate sound pressure levels (SPLs) (non-traumatic and within occupational limits) may not elevate
thresholds, but could in the long-term be detrimental to speech intelligibility by altering its spectrotemporal
representation in the central auditory system. In support of this, electrophysiological and behavioral changes
following long-term, passive (no conditioned learning) exposure at moderate SPLs have recently been observed
in adult animals. To assess the potential effects of moderately loud noise on the entire auditory brain, we
employed functional magnetic resonance imaging (fMRI) to study noise-exposed adult rats. We find that passive,
pulsed broadband noise exposure for two months at 65 dB SPL leads to a decrease of the sound-evoked blood oxygenation level-dependent fMRI signal in the thalamic medial geniculate body (MGB) and in the auditory cortex
(AC). This points to the thalamo-cortex as the site of the neural adaptation to the moderately noisy environment.
The signal reduction is statistically significant during 10 Hz pulsed acoustic stimulation (MGB: p b 0.05, AC:
p b 10−4), but not during 5 Hz stimulation. This indicates that noise exposure has a greater effect on the processing of higher pulse rate sounds. This study has enhanced our understanding of functional changes following
exposure by mapping changes across the entire auditory brain. These findings have important implications for
speech processing, which depends on accurate processing of sounds with a wide spectrum of pulse rates.
© 2014 Elsevier Inc. All rights reserved.
Introduction
Exposure to high sound pressure levels (SPLs) can permanently
damage the sensory apparatus of the inner ear (Liberman and Kiang,
1978). The resulting hearing loss (i.e., increase of the minimum detectible SPL, or hearing threshold) can produce extensive reorganization of
the central auditory system (Gold and Bajo, 2014). For example, following a high-frequency hearing loss, neurons in the auditory cortex (AC)
that were formerly sensitive to high frequencies become sensitive to
neighboring mid-frequencies (Rajan et al., 1993; Robertson and Irvine,
1989), i.e., the mid-frequencies become “over-represented” as a consequence of the high-frequency hearing loss. Some of these central effects
⁎ Corresponding author at: Department of Physics and Materials Science, The City
University of Hong Kong, Hong Kong, China.
E-mail address: [email protected] (C. Lau).
http://dx.doi.org/10.1016/j.neuroimage.2014.11.048
1053-8119/© 2014 Elsevier Inc. All rights reserved.
of deafness can be reversed following the restoration of hearing, as in
cochlear implantation (Pantev et al., 2006; Seghier et al., 2005). Exposure to somewhat lower SPLs may lead to only temporary elevations
of hearing thresholds, followed by recovery. Such exposures are presently permitted by occupational noise standards (NIOSH, 1998; OSHA,
2002). However, recent studies found that such exposures can result
in a permanent loss of inner hair cell synaptic terminals and degeneration of auditory nerve fibers, even if hearing thresholds are (initially)
only temporarily affected (Kujawa and Liberman, 2009; Wang and
Ren, 2012). In light of these findings, there is a serious need to further
assess the potential impact of acoustic exposures that do not permanently elevate hearing thresholds.
Traditionally, research on more moderate acoustic exposures (well
within present occupational limits) has focused on the more plastic
developing brain (Hensch, 2004). In mature subjects, after “critical” or
“sensitive” developmental periods have closed, conventional wisdom
held that moderate-level acoustic exposure could not, under passive
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C. Lau et al. / NeuroImage 107 (2015) 1–9
conditions (not paired with conditioned learning or stimulated
neuromodulator release from the forebrain), have any long-term impact on the auditory brain (Pienkowski and Eggermont, 2011). However, the impact of long-term, passive exposure at moderate SPL in
adulthood has recently gained renewed attention (Brattico et al.,
2005; Gourévitch et al., 2014; Kujala et al., 2004; Noreña et al., 2006;
Pienkowski and Eggermont, 2009, 2010a, 2010b; Pienkowski et al.,
2011, 2013; Zhou and Merzenich, 2012; Zhou et al., 2011). Eggermont
et al. exposed adult cats for several weeks to months to various types
of noise at levels of 68–80 dB SPL (Noreña et al., 2006; Pienkowski
and Eggermont, 2009, 2010a, 2010b; Pienkowski et al., 2011, 2013).
The general finding was that the auditory cortical representation of
sound frequencies within the noise band was profoundly suppressed,
and the representation of frequencies outside of the noise band was
enhanced. This is reminiscent of the effects of restricted hearing
loss (Rajan et al., 1993; Robertson and Irvine, 1989), although the
moderate-level exposures produced no observable signs of cochlear
damage. Zhou and Merzenich extended this work to show that moderate exposure of adult rats led to behavioral deficits on an auditory temporal discrimination task (Zhou and Merzenich, 2012). Prior to this
animal work, Kujala et al. had observed impaired syllable discrimination (as assessed electrophysiologically, using the mismatch negativity
response) in eight shipyard workers and two preschool teachers
(23– 36 years old), with an average six years of moderate occupational
noise exposure but no elevation of hearing threshold (Kujala et al.,
2004). Brattico et al. extended this work by comparing the effects of
moderate occupational exposure on the cortical representation of
speech and non-speech sounds (Brattico et al., 2005).
Previous studies on the effects on the mature auditory brain of
persistent exposure to moderate-level noise have employed primarily
electrophysiological testing. However, electrophysiology does not
allow easy study of functional changes across the entire central auditory
system, and is limited to poorly localized far-field recordings in human
subjects. To advance this direction of research, including opening avenues for future measurements in humans, we here employ functional
magnetic resonance imaging (fMRI) to simultaneously examine the
entire central auditory system of moderate noise-exposed rats.
Blood oxygenation level dependent (BOLD) fMRI is a noninvasive
neuroimaging technique (Ogawa et al., 1990) that offers a whole brain
field of view with relatively high spatial resolution. fMRI has been applied extensively to study the auditory system (Binder et al., 1996; De
Martino et al., 2013; Saenz and Langers, 2014), helping to show that
music and language training alter response patterns in the hippocampus, AC, and other cortical and subcortical regions (Angulo-Perkins
et al., 2014; Callan et al., 2003; Herdener et al., 2010; Rauschecker
et al., 2008; Wang et al., 2003). fMRI has also been used to confirm
that the AC of cochlear implant users is activated by electrical stimulation (Seghier et al., 2005), and that hearing loss and tinnitus alter
auditory system responses (Adjamian et al., 2009; Bilecen et al.,
2000; Langguth et al., 2012; Melcher et al., 2000; Middleton and
Tzounopoulos, 2012). fMRI has been applied in animal models
(Bach et al., 2013; Baumann et al., 2011; Brown et al., 2014; Jin and
Kim, 2008; Van Ruijssevelt et al., 2013), including rats (Pawela
et al., 2008; Sicard et al., 2003; Smith et al., 2002; Van Camp et al.,
2006). We and others have recently developed rat auditory fMRI capabilities (Cheung et al., 2012a,2012b; Gao et al., 2014; Lau et al.,
2013; Yu et al., 2009; Zhang et al., 2013).
In this study, adult rats were passively exposed for two months to
pulsed noise at 65 dB SPL. Following the cessation of exposure, control
(unexposed) and exposed subjects underwent fMRI with acoustic stimulation pulsed at two different rates. Region of interest analysis was performed on fMRI signals measured from the contralateral superior
olivary complex, lateral lemniscus, inferior colliculus, medial geniculate
body, and auditory cortex of the central auditory system. The amplitudes of fMRI signals from the different brain structures, subject groups,
and stimulation rates were compared.
Methods
Animals and housing
All aspects of this study were approved by the Committee on Research Practices of the Hong Kong University of Science and Technology
and the Committee on the Use of Live Animals in Teaching and Research
of the University of Hong Kong. Normal female Sprague–Dawley rats
(three months of age, N = 24) were used in this study. Twelve were
randomly assigned to receive continuous acoustic exposure while the
remaining 12 were assigned to standard housing. Exposed and control
subjects were housed in separate rooms. Background noise in the
rooms was less than 40 dB total sound pressure level (SPL). All subjects
were housed in pairs, exposed to 12 hour light/dark cycles, and received
standard food and water ad libitum. Acoustic exposure began when
subjects were three months old. During this time, control subjects
continued to be housed in standard acoustic conditions.
Acoustic exposure
The acoustic exposure consisted of 50 ms pulses of broadband noise,
low-pass filtered at 30 kHz, and presented at 65 dB total SPL. Total
n
SPL = 10 log ∑10SPLðkÞ=10 , where SPL(k) was the SPL at each frequenk¼1
cy. Five pulses were presented per second and repeated 24 hours/day
for two months. Pulses were generated using wide bandwidth speakers
(MF1, Tucker-Davis Technologies, USA) and played to the subjects
inside their cages. The power spectrum of the acoustic exposure was
recorded inside a cage with a calibrated reference microphone (M50,
Earthworks, USA) to verify output (Fig. 1). The microphone had flat
and known response properties up to 50 kHz. This rat acoustic exposure
model was chosen because it had been used in comparable behavioral
and electrophysiological studies and demonstrated not to elevate
auditory brainstem response thresholds (Zhou and Merzenich, 2012).
Magnetic resonance imaging
Functional magnetic resonance imaging (fMRI) was performed at
five months of age. Each subject was anesthetized with 3 % isoflurane
(mixed with room air) and anesthesia was maintained with 1 %
isoflurane throughout the course of setup and scanning. The subject
was placed in the prone position on a body holder with a head motion
restricting nose cone and tooth bar. A surface coil was placed over
the head. A custom-made sound transmission tube was inserted into
Fig. 1. Power spectra of the acoustic exposure (blue) and stimulus (red) recorded with a
reference microphone (M50, Earthworks, USA). The exposure spectrum was recorded inside the cage and the stimulus spectrum was recorded at the tip of the sound transmission
tube that entered the ear. The acoustic exposure was low pass filtered at 30 kHz and the
acoustic stimulus was low pass filtered at 25 kHz. The total sound pressure level (SPL)
of the exposure was 65 dB and the total SPL of the stimulus was 85 dB. A broadband stimulus was employed to excite more neurons in the central auditory system, which leads to
higher functional magnetic resonance imaging (fMRI) signals compared with tone stimuli.
Note that 0 dB SPL is a standard reference point set to the threshold of human hearing at
1 kHz and a negative SPL does not mean the sound has less than zero energy.
C. Lau et al. / NeuroImage 107 (2015) 1–9
the right ear and the left ear was occluded with an ear plug. This configuration reduced the scanner acoustic noise reaching the ears. Warm
water was circulated beneath the animal. Respiration rate, heart rate,
saturation of peripheral oxygen, and rectal temperature were continuously monitored (SA Instruments, USA).
The rats were scanned using a 7 T magnetic resonance imaging (MRI)
scanner with a maximum gradient of 360 mT/m (PharmaScan, Bruker
BioSpin, Germany). A birdcage transmit-only coil with 72 mm inner diameter was used in combination with an actively decoupled receiveonly quadrature surface coil. Once the animal was properly anesthetized
and positioned in the scanner, scout images were acquired to determine
the coronal and sagittal planes of the brain. Eleven 0.63 mm thick slices,
spaced 0.13 mm apart, were positioned by referencing the rat brain
atlas (Paxinos and Watson, 2006) such that the fourth slice was centered
on the inferior colliculus (IC) (Fig. 2). Slices were oriented along the coronal plane of the brain. Anatomical images were acquired with rapid acquisition with refocusing echoes (RARE) along the above slices. The
imaging parameters were RARE factor = 8, repetition time/echo
time = 4200/32 ms, field of view = 4.03 ×4.03 cm2, and data matrix =
256 × 256. Functional images were acquired with gradient echo echo planar imaging (GE-EPI) along the same slices. The imaging parameters
were flip angle = 56 °, repetition time/echo time = 1000/18 ms, field
of view = 4.03 × 4.03 cm2, data matrix = 64 × 64, and 280 repetitions.
Acoustic stimulation
During the acquisition of functional images, acoustic stimulation
was presented to the subject. The stimulation setup was similar to
that employed in our earlier studies (Cheung et al., 2012a, 2012b; Gao
et al., 2014; Lau et al., 2013; Zhang et al., 2013). Sound was transmitted
from the high frequency speaker (MF1, Tucker-Davis Technologies,
USA) to the subject's right ear. Transmission occurred through a custom
rigid tube that placed the speaker outside of the high magnetic field
area. The stimulus sound was pulsed at either 5 or 10 Hz with 25 %
duty cycle (pulse durations were 50 ms for 5 Hz and 25 ms for 10 Hz).
Each pulse was 85 dB total SPL and had a frequency spectrum that fell
off above 25 kHz (Fig. 1). This broadband stimulus was chosen to stimulate more neurons and increase the fMRI signal. The stimulus SPL was
below the threshold for causing hearing loss (Sullivan and Conolly,
1988). All acoustic measurements to verify speaker output were made
at the tip of the tube that entered the ear using the reference microphone (M50, Earthworks, USA).
The stimulation paradigm consisted of 40 s stimulus off (no sound)
followed by four repetitions of 20 s stimulus on (pulsed sound) and
40 s stimulus off. This 40 s off/20 s on paradigm has been used in
many rat fMRI studies (Chan et al., 2010; Cheung et al., 2012a; Gao
et al., 2014; Lau et al., 2011a, 2013; Pawela et al., 2008; Zhou et al.,
2012). During a 20 s on period, the pulse rate was pseudorandomly
set to 5 or 10 Hz with the condition that each rate was presented an
Fig. 2. Anatomical image of the rat brain at midline showing the magnetic resonance imaging (MRI) slice positioning. Eleven 0.63 mm thick slices (indicated by pink boxes),
spaced 0.13 mm apart, were positioned by referencing the rat brain atlas (Paxinos and
Watson, 2006) such that the fourth from posterior slice was centered on the inferior
colliculus (IC). The location of the IC at midline is labeled along with the anterior, posterior,
dorsal, and ventral sides of the brain.
3
equal number of times to each subject. One fMRI scan, consisting of
GE-EPI and acoustic stimulation following the above paradigm, lasted
for 280 s. The scan was repeated 10 times per subject to improve
signal-to-noise ratio. There were 5 min between scans. Each subject
spent approximately 2.5 hours in the scanner. This included the time
for setup and acquiring anatomical images.
Data analysis
The data analysis procedures were adapted from those of recent rat
fMRI studies (Cheung et al., 2012a; Lau et al., 2011a, 2011b, 2013;
Pawela et al., 2008; Zhang et al., 2013). The GE-EPI images from all ten
fMRI scans were realigned (SPM8, Wellcome Trust Centre, UK). Images
from different animals were registered to a template image acquired
from a separate five months old subject. The template was acquired
with the same GE-EPI settings. Registration was performed using affine
transformation with Gaussian smoothing (full width at half maximum
of one voxel) and non-brain structures masked out (Lau et al., 2011b).
The first and last slices from each image were discarded to avoid truncation artifacts from realignment and registration. Images from each fMRI
scan were split into four 60 s blocks (one for each on period), each
starting 10 s before the onset of stimulation and ending 30 s after the
cessation of stimulation. Blocks corresponding to the same stimulation
rate (5 or 10 Hz) were averaged. This resulted in a 60 images long
block for each subject and stimulation rate. A general linear model
(GLM) was applied to the 60 s time course of each voxel of a block to calculate the response estimate coefficient (beta-value) maps and t-value
maps (SPM8, Wellcome Trust Centre, UK). Activated voxels were
identified using the threshold t N 1.67 (equivalent to p b 0.05) and
cluster size ≥ 3. The activation (t-value) maps in Figs. 3 and 4 were
plotted by averaging all blocks from a group (control or exposure) and
stimulation rate (5 or 10 Hz) and applying the GLM.
Functionally defined regions of interest (ROIs) were used to quantify
the amplitude of fMRI signals from structures in the central auditory
system. This is important because the rat brain is considerably smaller
than the human brain, making anatomical ROI definition more challenging. ROIs were defined by selecting voxels in each structure activated
across all subjects and both rates. This involved averaging the image
blocks from all subjects and rates and applying the GLM (Fig. 5). Voxels
that passed the activation threshold and were within one voxel width of
an auditory structure, as defined by the rat brain atlas (Paxinos and
Watson, 2006), were included in that structure's ROI. A one voxel margin was included to account for smoothing during image registration.
Also, voxels spanning more than one structure or with less than half
their length along the through-plane direction within a structure were
excluded to reduce partial volume effects. This ROI definition ensured
that ROIs spanned the same voxels in both groups (control vs. exposure)
and pulse rates (5 vs 10 Hz) being compared to avoid comparing signals
from different brain regions. ROIs were defined for the superior olivary
complex, lateral lemniscus, inferior colliculus, medial geniculate body,
and auditory cortex. The 60 s long fMRI signals from each structure
were obtained by averaging the time series from all voxels in the ROI.
The corresponding fMRI signal amplitude was defined as ((the average
value of the signal during the 20 s when the stimulus was on) / (the average value of the signal during the first 10 s of the block) − 1) × 100%.
This puts the signal amplitudes in units of % baseline MRI signal. fMRI
signal ratios were defined as ((amplitude of structure 1) / 100% + 1) /
((amplitude of structure 2) / 100% + 1) for comparing the signal amplitudes of two structures. This ratio analysis was adapted from related
fMRI studies (Yu et al., 2012). One was added to the signal amplitude
to avoid division by numbers close to zero.
Results
Fig. 3 shows the fMRI activation map of control and exposed subjects
receiving 5 Hz acoustic stimulation, overlaid on an anatomical image.
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C. Lau et al. / NeuroImage 107 (2015) 1–9
Fig. 3. Activation (t-value) maps of control (A) and exposed (B) subjects receiving 5 Hz acoustic stimulation, overlaid on an anatomical image. The primary structures in the central auditory system are active and labeled, including the contralateral (left) superior olivary complex (SOC), lateral lemniscus (LL), IC, medial geniculate body (MGB), and auditory cortex (AC).
The ipsilateral (right) cochlear nucleus (CN), SOC, and AC are also active. The response in the AC of exposed subjects is reduced in both brain hemispheres compared to that of control
subjects. Also, activation of the CN is only observed in exposed subjects. The anterior, posterior, dorsal, ventral, left, and right sides of the brain are labeled. The t-value at each voxel is
color coded.
The primary structures in the central auditory system are active, including the contralateral (left) superior olivary complex (SOC), lateral lemniscus (LL), inferior colliculus (IC), medial geniculate body (MGB), and
auditory cortex (AC). The ipsilateral (right) cochlear nucleus (CN),
SOC, and AC are also active. The highest t-values are observed in the
LL and IC. This is in good agreement with earlier fMRI studies of the
rat auditory system (Cheung et al., 2012a; Lau et al., 2013; Zhang
et al., 2013). The response in the AC of exposed subjects is reduced in
both brain hemispheres compared to that of control subjects. Also,
activation of the CN is only observed in exposed subjects.
C. Lau et al. / NeuroImage 107 (2015) 1–9
5
Fig. 4. Activation maps of control (A) and exposed (B) subjects receiving 10 Hz acoustic stimulation, overlaid on an anatomical image. Refer to Fig. 3 for the labeling of sides of the brain.
Compared to 5 Hz stimulation (Fig. 3), the t-values are higher in all structures and hemispheres and more voxels cross the activation threshold. Further, the ipsilateral CN is active at 10 Hz
in both control and exposed subjects. The responses in the contralateral MGB and both AC hemispheres of exposed subjects are significantly reduced compared to those in control subjects.
Fig. 4 shows the activation map of control and exposed subjects receiving 10 Hz acoustic stimulation. The primary structures in the auditory system are active. The highest t-values are observed in the SOC, LL
and IC. Compared to 5 Hz stimulation (Fig. 3), the t-values are higher
in all structures and hemispheres and more voxels cross the activation
threshold. Further, the ipsilateral CN is active at 10 Hz in both control
and exposed subjects. The responses in the contralateral MGB and
both AC hemispheres of exposed subjects are significantly reduced
compared to those in control subjects. Overall, switching from 5 to
10 Hz acoustic stimulation increases responses across the auditory
system. More importantly, acoustic exposure reduces responses in the
MGB and AC, particularly at 10 Hz stimulation.
Fig. 5 shows the activation map plotted by averaging the image
blocks from all subjects and both pulse rates, and was used for ROI
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C. Lau et al. / NeuroImage 107 (2015) 1–9
Fig. 5. Activation map obtained by averaging the image blocks from control and exposed subjects, and 5 and 10 Hz stimulation. Refer to Fig. 3 for the labeling of sides of the brain and the
color coding of t-value. Voxels in the SOC, LL, IC, MGB, and AC that passed the activation threshold were included in the regions of interest (ROIs). ROI analysis was only performed on
auditory system structures in the contralateral hemisphere as the fMRI signals there are considerably higher than those in the ipsilateral hemisphere. More details on ROI definition
are available in the Methods section.
definition purposes. ROIs were defined based on the voxels that crossed
the activation threshold (refer to Methods for more details). Note that tvalues in the AC are lower in this figure than in Fig. 4 (control, 10 Hz)
because data from exposed subjects and 5 Hz stimulation were included
in the General Linear Model. Active structures in the ipsilateral hemisphere, such as the CN, SOC, and AC, were not included in the ROI
analysis because they had small fMRI signals compared with the contralateral structures.
Tables 1 and 2 show the means and standard deviations of fMRI signal amplitudes from control and exposed subjects stimulated at 5 and
10 Hz, respectively. For both subject groups and stimulation rates, the
highest amplitudes are observed in the SOC, LL, and IC. This is consistent
with previous rat auditory fMRI studies (Cheung et al., 2012a; Lau et al.,
2013; Zhang et al., 2013). Signal amplitudes in general are higher during
10 Hz stimulation than during 5 Hz (except the AC of exposed subjects).
In control subjects, the 10 Hz amplitude is significantly greater than the
5 Hz amplitude in the SOC (p b 0.01), LL (p b 0.001), and IC (p b 10−6). In
exposed subjects, the 10 Hz amplitude is also significantly greater than
the 5 Hz amplitude in the SOC (p b 0.05), LL (p b 0.01), and IC (p b 10−4).
In contrast, when comparing control and exposed subjects at either
Table 1
Functional magnetic resonance imaging (fMRI) signal amplitudes obtained from the ROIs
in Fig. 5 during 5 Hz acoustic stimulation and expressed in units of % baseline MRI signal.
Signal amplitudes are presented as mean ± standard deviation across the subjects in each
group (control and exposed). p-values were obtained by performing the t-test between
groups. NS indicates p N 0.05. Note that this p-value is not the same as that used to define
the fMRI activation threshold (refer to Methods). There are no statistically significant differences between signal amplitudes measured from the two groups in any auditory
structure.
stimulation rate, no statistically significant differences are observed between the amplitudes from the SOC, LL, and IC. In the MGB, the signal
amplitude from exposed subjects is significantly lower than that from
controls during 10 Hz acoustic stimulation. During 5 Hz stimulation,
no statistically significant differences are observed. In the AC, the signal
amplitude from exposed subjects is also significantly lower than that
from controls during 10 Hz stimulation. During 5 Hz stimulation, no
statistically significant differences are observed. In summary, acoustic
exposure reduces fMRI signal amplitudes in the MGB and AC. The reduction is greater during 10 Hz acoustic stimulation than during 5 Hz
stimulation.
Table 3 shows the means and standard deviations of fMRI signal ratios from control and exposed subjects stimulated at 5 and 10 Hz. Ratios
were computed for the MGB/IC and AC/MGB pairs to test if the thalamocortex was the site of neural adapation to the acoustic exposure. The
MGB/IC ratio at 10 Hz is significantly lower in exposed subjects than
in control subjects.
Fig. 6 shows the fMRI signals from the central auditory structures of
control and exposed subjects receiving 5 Hz (top row) and 10 Hz
(bottom row) acoustic stimulation. All signals rise several seconds
after the onset of stimulation and return to baseline approximately
10 s after the cessation of stimulation. The signal amplitudes during
10 Hz stimulation are higher than those during 5 Hz stimulation. In
the SOC and LL, fMRI signals increase throughout the 20 s period of
Table 2
fMRI signal amplitudes obtained from the ROIs in Fig. 5 during 10 Hz acoustic stimulation.
The amplitudes are significantly lower in the contralateral MGB and AC of exposed
compared to control subjects.
5 Hz
SOC
LL
IC
MGB
AC
10 Hz
SOC
LL
IC
MGB
AC
Controls
Exposed
p
0.24 ± 0.16
0.26 ± 0.14
NS
0.23 ± 0.16
0.15 ± 0.09
NS
0.30 ± 0.11
0.37 ± 0.15
NS
0.09 ± 0.10
0.05 ± 0.08
NS
0.07 ± 0.11
0.05 ± 0.07
NS
Controls
Exposed
p
0.49 ± 0.13
0.42 ± 0.17
NS
0.45 ± 0.14
0.37 ± 0.13
NS
0.53 ± 0.17
0.63 ± 0.18
NS
0.14 ± 0.10
0.06 ± 0.07
b0.05
0.14 ± 0.06
−0.02 ± 0.09
b10−4
C. Lau et al. / NeuroImage 107 (2015) 1–9
Table 3
fMRI signal ratios obtained from the ROIs in Fig. 5 during 5 and 10 Hz acoustic stimulation.
The MGB/IC ratio during 10 Hz stimulation is significantly lower in exposed compared to
control subjects.
MGB/IC (5Hz)
MGB/IC (10Hz)
AC/MGB (5Hz)
AC/MGB (10Hz)
Controls 0.9979 ± 0.0017 0.9961 ± 0.0018 0.9998 ± 0.0014 1.0000 ± 0.0010
Exposed 0.9968 ± 0.0017 0.9944 ± 0.0021 1.0000 ± 0.0007 0.9992 ± 0.0012
p
NS
b0.05
NS
NS
acoustic stimulation. In the IC, signals reach a first peak approximately
4 s after the onset of stimulation before decreasing for approximately
5 s and rising to a second peak near the cessation of stimulation. In
the MGB, signals reach a peak approximately 3 s after onset of stimulation and gradually return to baseline. In the AC, signals reach their
maximum approximately 4 s after the onset of stimulation and maintain
the amplitude until the cessation of stimulation. Again, the fMRI signal
amplitude is considerably lower in the MGB and AC of exposed subjects
than in controls during 10 Hz acoustic stimulation.
Discussion
Functional magnetic resonance imaging (fMRI) with pulsed acoustic
stimulation was performed on adult rats which were passively exposed
for two months to broadband noise at 65 dB total sound pressure level
(SPL). Higher fMRI signal amplitudes were recorded during 10 Hz compared to 5 Hz pulsed acoustic stimulation. During 10 Hz (but not 5 Hz)
stimulation, the contralateral medial geniculate body (MGB) and auditory cortex (AC) of exposed subjects showed significantly lower signal
amplitudes compared to controls. No significant differences were seen
in the superior olivary complex (SOC), lateral lemniscus (LL), or inferior
colliculus (IC). Also, the MGB/IC fMRI signal ratio during 10 Hz stimulation was significantly lower in exposed compared to control subjects.
This data points to the thalamo-cortex as the site of the neural adaptation to the moderately noisy environment. The results also indicate
that noise exposure has a greater effect on the processing of higher
pulse rate sounds.
Related electrophysiological studies
Recent electrophysiological studies have demonstrated that the
adult AC undergoes reorganization following long-term, passive exposure to moderate-level noise. Generally, sound frequencies contained
within the bandwidth of the acoustic exposure were profoundly suppressed after exposure, whereas frequencies outside of the bandwidth
were enhanced (Noreña et al., 2006; Pienkowski and Eggermont,
2009, 2010a, 2010b; Pienkowski et al., 2011, 2013). Further, high
pulse rate sounds were suppressed more than low pulse rate sounds
7
(Zhou and Merzenich, 2012). The electrophysiological studies have
also observed decreased cortical local field potentials (LFPs) (Noreña
et al., 2006; Pienkowski and Eggermont, 2009, 2010a, 2010b;
Pienkowski et al., 2011, 2013). These suggest reorganization in the
MGB following exposure because short-latency LFPs reflect synchronous post-synaptic potentials from thalamocortical inputs (Mitzdorf,
1985). At present, the effects of moderate-level exposure on subcortical
auditory nuclei in adult subjects have not been investigated electrophysiologically. However, electrophysiological studies of central auditory plasticity following traumatic noise exposure show little evidence of
the kind of reorganization observed in the thalamus (Kamke et al.,
2003) and cortex (Rajan et al., 1993; Robertson and Irvine, 1989) at
the levels of the cochlear nucleus (Rajan and Irvine, 1998) and inferior
colliculus (Irvine et al., 2003).
Related fMRI studies
fMRI has been employed to study functional changes following
various forms of long-term, but not passive, acoustic exposure. For example, musical training, which involves long-term exposure to sound,
has been shown to alter subsequent responses to acoustic stimuli.
Herdener et al. observed enhanced hippocampal responses to temporal
novelty in acoustic stimuli in adult musicians compared with nonmusicians (Herdener et al., 2010). Angulo-Perkins et al. observed
response differences in the temporal lobes of musicians and nonmusicians during music listening (Angulo-Perkins et al., 2014). Specifically, bilateral responses were more prevalent in the planum polare
of musicians than non-musicians. Also, the right posterior planum
temporale of musicians had stronger responses. As with musical training, learning a new language involves long-term acoustic exposure
and alters responses to acoustic stimuli. Callan et al. trained nonEnglish speakers for one month to distinguish/r/sounds from/l/sounds
(Callan et al., 2003). Subsequent fMRI with/r/and/l/sounds showed a
significant enhancement of responses in temporal regions typically associated with auditory processing, along with enhancement in other
brain regions associated with auditory-articulatory mapping. Wang
et al. performed fMRI on subjects learning Mandarin Chinese as a second
language (Wang et al., 2003). They observed increased activation in the
left superior temporal gyrus, Brodmann's area 42, and right inferior
frontal gyrus during a task to identify Mandarin words.
Underlying mechanisms
The results of our study likely reflect homeostatic plasticity during
long-term acoustic exposure (Gourévitch et al., 2014). In homeostatic
plasticity, the brain attempts to stabilize neural firing rates within a prescribed long-term range (when averaged over hours or days), by
adjusting the intrinsic excitability of neurons (Desai et al., 1999), and/
Fig. 6. fMRI signals from the ROIs in Fig. 5. Solid lines denote control subjects and dashed lines exposed subjects. The top row of signals (panel A) was acquired during 5 Hz stimulation
while the bottom row of signals (panel B) was acquired during 10 Hz stimulation. The pink rectangles indicate the 20 s period of acoustic stimulation. The fMRI signal amplitude is
expressed in units of % baseline MRI signal. In the MGB and AC during 10 Hz stimulation, the signal in exposed subjects is significantly lower than that in controls.
8
C. Lau et al. / NeuroImage 107 (2015) 1–9
or the number and strength of their excitatory (Turrigiano et al., 1998)
and inhibitory (Kilman et al., 2002) synaptic inputs (Burrone and
Murthy, 2003; Maffei and Fontanini, 2009; Turrigiano, 1999, 2008;
Turrigiano and Nelson, 2004). Long-term acoustic exposure at moderate
(non-traumatic) SPLs leads to a prolonged increase of auditory nerve
and central auditory system activity. Over time, frequently active MGB
and AC neurons may compensate by reducing their synaptic gains.
This would result in reduced fMRI signals during post-exposure acoustic
stimulation, as seen in Figs. 4 and 6 and Table 2. Reduced gains in
the MGB and AC, but not the IC, would also lead to the lower postexposure MGB/IC fMRI signal ratio seen in Table 3.
of controls. The MGB/inferior colliculus signal ratio was also significantly lower in exposed subjects. These findings point to the thalamo-cortex
as the site of the neural adaptation to the moderately noisy environment and have important implications for speech processing.
Acknowledgments
This research was supported by the Hong Kong General Research
Fund (#661313), the Hong Kong Health and Medical Research Fund
(#11122581), and start-up funding from the City University of Hong
Kong and the Hong Kong University of Science and Technology.
Clinical implications
References
Long-term, passive exposure to moderate-level noise adversely affects auditory temporal rate discrimination and pitch discrimination
abilities. This could lead to difficulties processing the complex temporal
patterns present in speech. Zhou and Merzenich employed an acoustic
exposure similar to that in our study (Zhou and Merzenich, 2012).
They found that exposed rats had more difficulty distinguishing
between different click repetition rates. Zheng et al. also exposed rats
to similar acoustic conditions and observed that exposure impaired
fine pitch discrimination (Zheng, 2012). The fMRI results of our study
support increasing concerns about such potential negative impacts of
long-term exposure to moderate-level noise (Gourévitch et al., 2014;
Pienkowski and Eggermont, 2012).
Technical considerations
The moderate noise exposure employed in our study does not
elevate hearing thresholds, as measured by the auditory brainstem
response (ABR) (Zhou and Merzenich, 2012). The fMRI data in Figs. 3,
4, and 6 and Tables 1 and 2 further confirm the previous ABR measurements, as fMRI signals measured from the superior olivary complex
(SOC), lateral lemniscus (LL), and inferior colliculus (IC) of control and
exposed subjects do not vary significantly between groups. In fact, signals from the IC are higher in exposed animals (but not significantly so).
fMRI signals are larger in response to the 10 Hz compared to 5 Hz
acoustic stimulation in both exposed and control rats (Fig. 3, 4, and 6
and Tables 1 and 2). In the MGB and AC, where the signals are smallest,
the lower signal-to-noise ratios at 5 Hz may have contributed to the insignificant (p N 0.05) differences between the control and exposed
groups. However, it may also be that moderate noise exposure has a
greater effect on the processing of faster compared to slower temporal
modulations in sounds.
We do not employ sparse temporal sampling image acquisition
(Talavage and Hall, 2012) as our recent work demonstrated that this
may not be a prerequisite for auditory fMRI studies (Cheung et al.,
2012a, 2012b; Gao et al., 2014; Lau et al., 2013), and continuous imaging
produces more time points for analysis.
The AC responses observed in Figs. 3 – 5 may involve contributions
from the neighboring temporal association cortex (TeA). This likely
reflects previously observed projections from the MGB to the TeA
(Linke and Schwegler, 2000). Our study may be observing responses
in the TeA because of the relatively large number of subjects and fMRI
scans employed.
Conclusion
Functional magnetic resonance imaging (fMRI) was performed on
rats after long-term, passive acoustic exposure at moderate sound pressure levels. Higher fMRI signal amplitudes were recorded from subjects
receiving high pulse rate acoustic stimulation than from subjects receiving low pulse rate stimulation. During high pulse rate stimulation, the
contralateral medial geniculate body (MGB) and auditory cortex of
exposed subjects had significantly lower signal amplitudes than those
Adjamian, P., Sereda, M., Hall, D.A., 2009. The mechanisms of tinnitus: perspectives from
human functional neuroimaging. Hear. Res. 253, 15–31.
Angulo-Perkins, A., Aubé, W., Peretz, I., Barrios, F.A., Armony, J.L., Concha, L., 2014. Music
listening engages specific cortical regions within the temporal lobes: differences
between musicians and non-musicians. Cortex 59C, 126–137.
Bach, J.P., Lüpke, M., Dziallas, P., Wefstaedt, P., Uppenkamp, S., Seifert, H., Nolte, I., 2013.
Functional magnetic resonance imaging of the ascending stages of the auditory
system in dogs. BMC Vet. Res. 9, 210.
Baumann, S., Griffiths, T.D., Sun, L., Petkov, C.I., Thiele, A., Rees, A., 2011. Orthogonal
representation of sound dimensions in the primate midbrain. Nat. Neurosci. 14,
423–425.
Bilecen, D., Seifritz, E., Radü, E.W., Schmid, N., Wetzel, S., Probst, R., Scheffler, K., 2000.
Cortical reorganization after acute unilateral hearing loss traced by fMRI. Neurology
54, 765–767.
Binder, J.R., Frost, J.A., Hammeke, T.A., Rao, S.M., Cox, R.W., 1996. Function of the left
planum temporale in auditory and linguistic processing. Brain 119 (Pt 4), 1239–1247.
Brattico, E., Kujala, T., Tervaniemi, M., Alku, P., Ambrosi, L., Monitillo, V., 2005. Long-term
exposure to occupational noise alters the cortical organization of sound processing.
Clin. Neurophysiol. 116, 190–203.
Brown, T.A., Gati, J.S., Hughes, S.M., Nixon, P.L., Menon, R.S., Lomber, S.G., 2014. Functional
imaging of auditory cortex in adult cats using high-field fMRI. J Vis Exp. e50872.
Burrone, J., Murthy, V.N., 2003. Synaptic gain control and homeostasis. Curr. Opin.
Neurobiol. 13, 560–567.
Callan, D.E., Tajima, K., Callan, A.M., Kubo, R., Masaki, S., Akahane-Yamada, R., 2003.
Learning-induced neural plasticity associated with improved identification performance after training of a difficult second-language phonetic contrast. NeuroImage
19, 113–124.
Chan, K.C., Xing, K.K., Cheung, M.M., Zhou, I.Y., Wu, E.X., 2010. Functional MRI of postnatal
visual development in normal and hypoxic–ischemic-injured superior colliculi.
NeuroImage 49, 2013–2020.
Cheung, M.M., Lau, C., Zhou, I.Y., Chan, K.C., Cheng, J.S., Zhang, J.W., Ho, L.C., Wu, E.X.,
2012a. BOLD fMRI investigation of the rat auditory pathway and tonotopic organization. NeuroImage 60, 1205–1211.
Cheung, M.M., Lau, C., Zhou, I.Y., Chan, K.C., Zhang, J.W., Fan, S.J., Wu, E.X., 2012b. High
fidelity tonotopic mapping using swept source functional magnetic resonance
imaging. NeuroImage 61, 978–986.
De Martino, F., Moerel, M., van de Moortele, P.F., Ugurbil, K., Goebel, R., Yacoub, E.,
Formisano, E., 2013. Spatial organization of frequency preference and selectivity in
the human inferior colliculus. Nat. Commun. 4, 1386.
Desai, N.S., Rutherford, L.C., Turrigiano, G.G., 1999. Plasticity in the intrinsic excitability of
cortical pyramidal neurons. Nat. Neurosci. 2, 515–520.
Gao, P.P., Zhang, J.W., Cheng, J.S., Zhou, I.Y., Wu, E.X., 2014. The inferior colliculus is
involved in deviant sound detection as revealed by BOLD fMRI. NeuroImage 91,
220–227.
Gold, J.R., Bajo, V.M., 2014. Insult-induced adaptive plasticity of the auditory system.
Front. Neurosci. 8, 110.
Gourévitch, B., Edeline, J.M., Occelli, F., Eggermont, J.J., 2014. Is the din really harmless?
Long-term effects of non-traumatic noise on the adult auditory system. Nat. Rev.
Neurosci. 15, 483–491.
Hensch, T.K., 2004. Critical period regulation. Annu. Rev. Neurosci. 27, 549–579.
Herdener, M., Esposito, F., di Salle, F., Boller, C., Hilti, C.C., Habermeyer, B., Scheffler, K.,
Wetzel, S., Seifritz, E., Cattapan-Ludewig, K., 2010. Musical training induces functional
plasticity in human hippocampus. J. Neurosci. 30, 1377–1384.
Irvine, D.R., Rajan, R., Smith, S., 2003. Effects of restricted cochlear lesions in adult cats on
the frequency organization of the inferior colliculus. J. Comp. Neurol. 467, 354–374.
Jin, T., Kim, S.G., 2008. Cortical layer-dependent dynamic blood oxygenation, cerebral
blood flow and cerebral blood volume responses during visual stimulation.
NeuroImage 43, 1–9.
Kamke, M.R., Brown, M., Irvine, D.R., 2003. Plasticity in the tonotopic organization of the
medial geniculate body in adult cats following restricted unilateral cochlear lesions. J.
Comp. Neurol. 459, 355–367.
Kilman, V., van Rossum, M.C., Turrigiano, G.G., 2002. Activity deprivation reduces miniature IPSC amplitude by decreasing the number of postsynaptic GABA(A) receptors
clustered at neocortical synapses. J. Neurosci. 22, 1328–1337.
Kujala, T., Shtyrov, Y., Winkler, I., Saher, M., Tervaniemi, M., Sallinen, M., Teder-Sälejärvi,
W., Alho, K., Reinikainen, K., Näätänen, R., 2004. Long-term exposure to noise impairs
cortical sound processing and attention control. Psychophysiology 41, 875–881.
C. Lau et al. / NeuroImage 107 (2015) 1–9
Kujawa, S.G., Liberman, M.C., 2009. Adding insult to injury: cochlear nerve degeneration
after “temporary” noise-induced hearing loss. J. Neurosci. 29, 14077–14085.
Langguth, B., Schecklmann, M., Lehner, A., Landgrebe, M., Poeppl, T.B., Kreuzer, P.M.,
Schlee, W., Weisz, N., Vanneste, S., De Ridder, D., 2012. Neuroimaging and
neuromodulation: complementary approaches for identifying the neuronal correlates
of tinnitus. Front. Syst. Neurosci. 6, 15.
Lau, C., Zhang, J.W., Xing, K.K., Zhou, I.Y., Cheung, M.M., Chan, K.C., Wu, E.X., 2011a. BOLD
responses in the superior colliculus and lateral geniculate nucleus of the rat viewing
an apparent motion stimulus. NeuroImage 58, 878–884.
Lau, C., Zhou, I.Y., Cheung, M.M., Chan, K.C., Wu, E.X., 2011b. BOLD temporal dynamics of
rat superior colliculus and lateral geniculate nucleus following short duration visual
stimulation. PLoS ONE 6, e18914.
Lau, C., Zhang, J.W., Cheng, J.S., Zhou, I.Y., Cheung, M.M., Wu, E.X., 2013. Noninvasive fMRI
investigation of interaural level difference processing in the rat auditory subcortex.
PLoS ONE 8, e70706.
Liberman, M.C., Kiang, N.Y., 1978. Acoustic trauma in cats. Cochlear pathology and
auditory-nerve activity. Acta Otolaryngol. Suppl. 358, 1–63.
Linke, R., Schwegler, H., 2000. Convergent and complementary projections of the caudal
paralaminar thalamic nuclei to rat temporal and insular cortex. Cereb. Cortex 10,
753–771.
Maffei, A., Fontanini, A., 2009. Network homeostasis: a matter of coordination. Curr. Opin.
Neurobiol. 19, 168–173.
Melcher, J.R., Sigalovsky, I.S., Guinan, J.J., Levine, R.A., 2000. Lateralized tinnitus studied
with functional magnetic resonance imaging: abnormal inferior colliculus activation.
J. Neurophysiol. 83, 1058–1072.
Middleton, J.W., Tzounopoulos, T., 2012. Imaging the neural correlates of tinnitus: a comparison between animal models and human studies. Front. Syst. Neurosci. 6, 35.
Mitzdorf, U., 1985. Current source-density method and application in cat cerebral cortex:
investigation of evoked potentials and EEG phenomena. Physiol. Rev. 65, 37–100.
NIOSH, 1998. Criteria for a Recommended Standard.
Noreña, A.J., Gourévitch, B., Gourevich, B., Aizawa, N., Eggermont, J.J., 2006. Spectrally
enhanced acoustic environment disrupts frequency representation in cat auditory
cortex. Nat. Neurosci. 9, 932–939.
Ogawa, S., Lee, T.M., Kay, A.R., Tank, D.W., 1990. Brain magnetic resonance imaging with
contrast dependent on blood oxygenation. Proc. Natl. Acad. Sci. U. S. A. 87, 9868–9872.
OSHA, 2002. Job Hazard Analysis.
Pantev, C., Dinnesen, A., Ross, B., Wollbrink, A., Knief, A., 2006. Dynamics of auditory plasticity after cochlear implantation: a longitudinal study. Cereb. Cortex 16, 31–36.
Pawela, C.P., Hudetz, A.G., Ward, B.D., Schulte, M.L., Li, R., Kao, D.S., Mauck, M.C., Cho, Y.R.,
Neitz, J., Hyde, J.S., 2008. Modeling of region-specific fMRI BOLD neurovascular
response functions in rat brain reveals residual differences that correlate with the
differences in regional evoked potentials. NeuroImage 41, 525–534.
Paxinos, G., Watson, C., 2006. The Rat Brain in Stereotaxic Coordinates, Hard Cover ed.
Academic Press.
Pienkowski, M., Eggermont, J.J., 2009. Long-term, partially-reversible reorganization of
frequency tuning in mature cat primary auditory cortex can be induced by passive
exposure to moderate-level sounds. Hear. Res. 257, 24–40.
Pienkowski, M., Eggermont, J.J., 2010a. Intermittent exposure with moderate-level sound
impairs central auditory function of mature animals without concomitant hearing
loss. Hear. Res. 261, 30–35.
Pienkowski, M., Eggermont, J.J., 2010b. Passive exposure of adult cats to moderate-level
tone pip ensembles differentially decreases AI and AII responsiveness in the exposure
frequency range. Hear. Res. 268, 151–162.
Pienkowski, M., Eggermont, J.J., 2011. Cortical tonotopic map plasticity and behavior.
Neurosci. Biobehav. Rev. 35, 2117–2128.
Pienkowski, M., Eggermont, J.J., 2012. Reversible long-term changes in auditory processing in mature auditory cortex in the absence of hearing loss induced by passive,
moderate-level sound exposure. Ear Hear. 33, 305–314.
Pienkowski, M., Munguia, R., Eggermont, J.J., 2011. Passive exposure of adult cats to
bandlimited tone pip ensembles or noise leads to long-term response suppression
in auditory cortex. Hear. Res. 277, 117–126.
Pienkowski, M., Munguia, R., Eggermont, J.J., 2013. Effects of passive, moderate-level
sound exposure on the mature auditory cortex: spectral edges, spectrotemporal
density, and real-world noise. Hear. Res. 296, 121–130.
9
Rajan, R., Irvine, D.R., 1998. Absence of plasticity of the frequency map in dorsal cochlear
nucleus of adult cats after unilateral partial cochlear lesions. J. Comp. Neurol. 399,
35–46.
Rajan, R., Irvine, D.R., Wise, L.Z., Heil, P., 1993. Effect of unilateral partial cochlear lesions in
adult cats on the representation of lesioned and unlesioned cochleas in primary auditory cortex. J. Comp. Neurol. 338, 17–49.
Rauschecker, A.M., Pringle, A., Watkins, K.E., 2008. Changes in neural activity associated
with learning to articulate novel auditory pseudowords by covert repetition. Hum.
Brain Mapp. 29, 1231–1242.
Robertson, D., Irvine, D.R., 1989. Plasticity of frequency organization in auditory cortex of
guinea pigs with partial unilateral deafness. J. Comp. Neurol. 282, 456–471.
Saenz, M., Langers, D.R., 2014. Tonotopic mapping of human auditory cortex. Hear. Res.
307, 42–52.
Seghier, M.L., Boëx, C., Lazeyras, F., Sigrist, A., Pelizzone, M., 2005. FMRI evidence for activation of multiple cortical regions in the primary auditory cortex of deaf subjects
users of multichannel cochlear implants. Cereb. Cortex 15, 40–48.
Sicard, K., Shen, Q., Brevard, M.E., Sullivan, R., Ferris, C.F., King, J.A., Duong, T.Q., 2003.
Regional cerebral blood flow and BOLD responses in conscious and anesthetized
rats under basal and hypercapnic conditions: implications for functional MRI studies.
J. Cereb. Blood Flow Metab. 23, 472–481.
Smith, A.J., Blumenfeld, H., Behar, K.L., Rothman, D.L., Shulman, R.G., Hyder, F., 2002.
Cerebral energetics and spiking frequency: the neurophysiological basis of fMRI.
Proc. Natl. Acad. Sci. U. S. A. 99, 10765–10770.
Sullivan, M.J., Conolly, R.B., 1988. Dose–response hearing loss for white noise in the
Sprague–Dawley rat. Fundam. Appl. Toxicol. 10, 109–113.
Talavage, T.M., Hall, D.A., 2012. How challenges in auditory fMRI led to general advancements for the field. NeuroImage 62, 641–647.
Turrigiano, G.G., 1999. Homeostatic plasticity in neuronal networks: the more things
change, the more they stay the same. Trends Neurosci. 22, 221–227.
Turrigiano, G.G., 2008. The self-tuning neuron: synaptic scaling of excitatory synapses.
Cell 135, 422–435.
Turrigiano, G.G., Nelson, S.B., 2004. Homeostatic plasticity in the developing nervous
system. Nat. Rev. Neurosci. 5, 97–107.
Turrigiano, G.G., Leslie, K.R., Desai, N.S., Rutherford, L.C., Nelson, S.B., 1998. Activitydependent scaling of quantal amplitude in neocortical neurons. Nature 391,
892–896.
Van Camp, N., Verhoye, M., De Zeeuw, C.I., Van der Linden, A., 2006. Light stimulus
frequency dependence of activity in the rat visual system as studied with highresolution BOLD fMRI. J. Neurophysiol. 95, 3164–3170.
Van Ruijssevelt, L., De Groof, G., Van der Kant, A., Poirier, C., Van Audekerke, J., Verhoye,
M., Van der Linden, A., 2013. Functional magnetic resonance imaging (FMRI) with
auditory stimulation in songbirds. J Vis Exp. 76, e4369.
Wang, Y., Ren, C., 2012. Effects of repeated “benign” noise exposures in young CBA mice:
shedding light on age-related hearing loss. J. Assoc. Res. Otolaryngol. 13, 505–515.
Wang, Y., Sereno, J.A., Jongman, A., Hirsch, J., 2003. fMRI evidence for cortical modification
during learning of Mandarin lexical tone. J. Cogn. Neurosci. 15, 1019–1027.
Yu, X., Goloshevsky, A., Dodd, S., Silva, A., Koretsky, A., 2009. High Resolution BOLD-fMRI
of the Auditory System in Rats. Annual Meeting of the ISMRM, Hawaii, USA.
Yu, X., Chung, S., Chen, D.Y., Wang, S.M., Dodd, S.J., Walters, J.R., Isaac, J.T.R., Koretsky, A.P.,
2012. Thalamocortical inputs show post-critical-period plasticity. Neuron 74,
731–742.
Zhang, J.W., Lau, C., Cheng, J.S., Xing, K.K., Zhou, I.Y., Cheung, M.M., Wu, E.X., 2013. Functional magnetic resonance imaging of sound pressure level encoding in the rat central
auditory system. NeuroImage 65, 119–126.
Zheng, W., 2012. Auditory map reorganization and pitch discrimination in adult rats
chronically exposed to low-level ambient noise. Front. Syst. Neurosci. 6, 65.
Zhou, X., Merzenich, M.M., 2012. Environmental noise exposure degrades normal listening processes. Nat. Commun. 3, 843.
Zhou, X., Panizzutti, R., de Villers-Sidani, E., Madeira, C., Merzenich, M.M., 2011. Natural
restoration of critical period plasticity in the juvenile and adult primary auditory
cortex. J. Neurosci. 31, 5625–5634.
Zhou, I.Y., Cheung, M.M., Lau, C., Chan, K.C., Wu, E.X., 2012. Balanced steady-state free
precession fMRI with intravascular susceptibility contrast agent. Magn. Reson. Med.
68, 65–73.