Functional Preference for Object Sounds and - Specialized Research AI at MIT

Functional Preference for Object Sounds and
Voices in the Brain of Early Blind
and Sighted Individuals

Giulia Dormal1,2, Maxime Pelland1, Mohamed Rezk2, Esther Yakobov4,
Franco Lepore1, and Olivier Collignon1,2,3

Abstract

■ Sounds activate occipital regions in early blind individuals.
However, how different sound categories map onto specific re-
gions of the occipital cortex remains a matter of debate. We
used fMRI to characterize brain responses of early blind and
sighted individuals to familiar object sounds, human voices, and
their respective low-level control sounds. In addition, sighted
participants were tested while viewing pictures of faces, objects,
and phase-scrambled control pictures. In both early blind and
sighted, a double dissociation was evidenced in bilateral auditory
cortices between responses to voices and object sounds: Voices
elicited categorical responses in bilateral superior temporal sulci,
whereas object sounds elicited categorical responses along the
lateral fissure bilaterally, including the primary auditory cortex
and planum temporale. Outside the auditory regions, object
sounds also elicited categorical responses in the left lateral and
in the ventral occipitotemporal regions in both groups. These
regions also showed response preference for images of objects

in the sighted group, thus suggesting a functional specialization
that is independent of sensory input and visual experience.
Between-group comparisons revealed that, only in the blind
group, categorical responses to object sounds extended more
posteriorly into the occipital cortex. Functional connectivity anal-
yses evidenced a selective increase in the functional coupling
between these reorganized regions and regions of the ventral
occipitotemporal cortex in the blind group. In contrast, vocal
sounds did not elicit preferential responses in the occipital cortex
in either group. Nevertheless, enhanced voice-selective con-
nectivity between the left temporal voice area and the right fusi-
form gyrus were found in the blind group. Altogether, these
findings suggest that, in the absence of developmental vision,
separate auditory categories are not equipotent in driving se-
lective auditory recruitment of occipitotemporal regions and
highlight the presence of domain-selective constraints on the
expression of cross-modal plasticity. ■

INTRODUCTION

In the visual and auditory areas of the human brain, sepa-
rate brain clusters show category preferences. For in-
stance, regions in the lateral part of the fusiform gyrus
(fusiform face area [FFA]) respond more to faces than to
nonface objects (Rossion, Hanseeuw, & Dricot, 2012;
Kanwisher, McDermott, & Chun, 1997), whereas nonface
objects elicit larger responses in parahippocampal gyri
and in the lateroventral aspect of the occipitotemporal
cortex (Andrews & Schluppeck, 2004). Although less
frequently investigated than in vision, similar categorical
preferences have been evidenced for sound processing
in temporal cortex in the auditory cortices. It was found
that listening to different categories of sounds such as
humans voices (von Kriegstein, Kleinschmidt, Sterzer, &
Giraud, 2005; Belin, Zatorre, & Ahad, 2002; Belin, Zatorre,
Lafaille, Ahad, & Pike, 2000) and artifacts (Lewis,
Talkington, Tallaksen, & Frum, 2012; Lewis, Talkington,

1University of Montreal, 2University of Louvain, 3University of
Trento, 4McGill University, Montreal, Canada

Puce, Engel, & Frum, 2011; Lewis, Brefczynski, Phinney,
Janik, & DeYoe, 2005) activates distinct regions of the
auditory temporal cortices (for a review, see Brefczynski-
Lewis & Lewis, in press). Importantly, a few studies that
have directly compared brain responses elicited by these
sound categories while also taking into account their low-
level characteristics suggest that categorical responses in
temporal cortex partially abstract away from differences
in basic sensory properties (Giordano, McAdams, Zatorre,
Kriegeskorte, & Belin, 2013; Leaver & Rauschecker, 2010).
Research on how sensory experience shapes these cat-
egorical preferences has recently received considerable
attention. In people who lack visual experience because
of early blindness, auditory and tactile stimulations mas-
sively activate the occipital cortex (e.g., Weeks et al.,
2000; Sadato et al., 1996). Importantly, this reorganized
occipital cortex is thought to follow a division of compu-
tational labor that is similar to the one observed in the
sighted group (for reviews, see Reich, Maidenbaum, &
Amedi, 2012; Voss & Zatorre, 2012; Dormal & Collignon,
2011; Ricciardi & Pietrini, 2011; Collignon, Voss, Lassonde,
& Lepore, 2009). For instance, dorsal occipitoparietal

Journal of Cognitive Neuroscience 30:1, pp. 86–106
doi:10.1162/jocn_a_01186

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regions support spatial localization and motion process-
ing in early blind participants (Dormal, Rezk, Yakobov,
Lepore, & Collignon, 2016; Collignon et al., 2011; Ricciardi
et al., 2007; for reviews, see Dormal, Lepore, & Collignon,
2012; Collignon et al., 2009), whereas occipitotemporal
regions respond during tasks that require identification
of a nonvisual input such as speech comprehension and
semantic processing (Bedny, Pascual-Leone, Dodell-Feder,
Fedorenko, & Saxe, 2011; Noppeney, Friston, & Price,
2003; Röder, Stock, Bien, Neville, & Rösler, 2002), Braille
reading (Reich, Szwed, Cohen, & Amedi, 2011; Büchel,
Price, & Friston, 1998), or the discrimination of shape
attributes of objects based on tactile (Amedi, Raz, Azulay,
& Malach, 2010; Amedi et al., 2007; Pietrini et al., 2004),
auditory (Amedi et al., 2007), or verbal material (He
et al., 2013; Peelen et al., 2013). Results from these studies
suggest that categorical organization of the ventral occipito-
temporal cortex ( VOTC) may develop independently
of visual experience. Importantly, some authors have also
observed similar domain preference in the VOTC of
sighted individuals during tasks that require processing
of nonvisual material, therefore suggesting that those
regions may at least partially abstract from vision (Bi, Wang,
& Caramazza, 2016; Heimler, Striem-Amit, & Amedi, 2015;
Wang et al., 2015; Ricciardi, Handjaras, & Pietrini, 2014;
Reich et al., 2012). In contrast, other studies have failed to
show preferential responses to specific auditory catego-
ries in the VOTC of either blind (He et al., 2013; Mahon,
Anzellotti, Schwarzbach, Zampini, & Caramazza, 2009) or
sighted participants (Adam & Noppeney, 2010; Engel,
Frum, Puce, Walker, & Lewis, 2009; Doehrmann, Naumer,
Volz, Kaiser, & Altmann, 2008; Lewis et al., 2005; Tranel,
Grabowski, Lyon, & Damasio, 2005).

To date, categorical responses to sounds of objects
per se (i.e., with nonverbal material and contrasting
sounds of objects to another sound category) have only
been investigated in sighted participants. These few stud-
ies failed to identify a clear categorical selectivity in the
VOTC (Adam & Noppeney, 2010; Engel et al., 2009;
Doehrmann et al., 2008; Lewis et al., 2005; Tranel et al.,
2005). Numerous studies demonstrated that nonvisual
information elicits radically distinct patterns of responses
in the occipital cortex of individuals without visual ex-
perience (Collignon et al., 2013; Laurienti et al., 2002;
Sadato, Okada, Honda, & Yonekura, 2002) and that
unique patterns of functional specialization (Dormal
et al., 2016; Collignon et al., 2011; Bedny, Konkle, Pelphrey,
Saxe, & Pascual-Leone, 2010; Weeks et al., 2000) and con-
nectivity (Dormal et al., 2016) exist in early blind people.
In light of these findings, specific categorical responses
to sounds of objects per se could be expected in early blind
individuals as a result of cross-modal plasticity (Bavelier &
Neville, 2002).

In sighted individuals, person (Mathias & von Kriegstein,
2014), emotion (Collignon et al., 2008), and speech recog-
nition (van Wassenhove, 2013) are part of cognitive oper-
ations that benefit from the ability to efficiently bind facial

and vocal stimuli ( Yovel & Belin, 2013). It has recently
been suggested that face–voice interactions might rely on
direct functional and structural links between face-selective
regions in the visual cortex (e.g., FFA) and voice-selective
regions in the auditory cortex (e.g., temporal voice area
[TVA]; Blank, Anwander, & von Kriegstein, 2011). Prefer-
ential responses to voices in face-selective regions, and
vice versa, have however never been demonstrated in
sighted individuals. In blind individuals, the ability to ex-
tract crucial social information, such as the speaker’s iden-
tity, emotional state, and speech, relies almost uniquely
on voice perception. It could therefore be hypothesized
that regions typically responsive to faces in sighted indi-
viduals would display a preferential response to voices in
blind individuals due to the enhancement/unmasking of
preexisting connections between these two cortical sys-
tems (Blank et al., 2011). Recent findings in congenitally
deaf individuals support this hypothesis by demonstrating
the presence of cross-modal face-selective responses in this
population within regions of the temporal cortex that are
typically tuned to voices in hearing participants (Benetti
et al., 2017).

In the present study, we used fMRI to characterize
brain responses to object sounds, voices, and the scram-
bled version of these stimuli in early blind and sighted
individuals. We relied upon a factorial design that allowed
us to directly contrast brain responses to familiar object
sounds and voices. The voice and object stimuli were con-
trolled for global energy (Belin et al., 2000, 2002), but not
for other low-level auditory cues that differ between voices
and objects, such as the spectral content of the sounds
(Belin et al., 2000, 2002). Control for these low-level cues
is provided by the scrambling (see Methods) of the two cat-
egories of stimuli. Therefore, by relying on directional
contrasts between sound categories and between each
category and its scrambled control condition, we assessed
categorical preference while controlling for differences in
the spectral content of the sounds and their global energy
(see Rossion et al., 2012; Andrews, Clarke, Pell, & Hartley,
2010, for similar methodology in the visual literature).
Sighted individuals were also tested in a visual experiment
involving pictures of faces, objects, and scrambled pictures
to assess the spatial correspondence between putative
VOTC responses to auditory stimuli, on the one hand,
and categorical responses elicited by visual material, on
the other hand.

Our goals were threefold: (1) to test the existence of a
double dissociation between voice- and object-selective
regions in temporal auditory cortices while controlling
for differences in low-level properties of these sounds
(Giordano et al., 2013; Leaver & Rauschecker, 2010),
(2) to investigate the existence of categorical responses
to voices and sounds of objects in the VOTC and to
elucidate whether these putative responses are unique
to blind individuals (due to cross-modal plasticity) or
whether they are also observable in sighted individuals,
and (3) to explore the differences in the functional

Dormal et al.

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connectivity profile of domain-selective regions between
blind and sighted individuals.

METHODS

Participants

Thirty-three participants were recruited for this study.
Sixteen early blind participants (EB; five women, age
range = 23–62 years, mean = 45, SD = 12 years; Table 1)
and 15 sighted control participants (SC; five women, age
range = 22–61 years, mean = 41.9, SD = 11.8 years) took
part in the auditory experiment. Participants were
matched for age, sex, handedness, educational level,

and musical experience. Seventeen sighted participants
(including the 15 that participated in the auditory exper-
iment) were also tested in an independent visual experi-
ment (seven women, age range = 22–61 years, mean =
40.7, SD =11.6 years). At the time of testing, the blind
participants were either totally blind or had only rudimen-
tary sensitivity for brightness differences and no pattern
vision. In all cases, blindness was attributed to peripheral
deficits with no neurological impairment (Table 1). All
the procedures were approved by the research ethical
and scientific boards of the “Centre for Interdisciplinary
Research in Rehabilitation of Greater Montreal” and the
“Quebec Bio-Imaging Network.” Experiments were under-
taken with the consent of each participant.

Table 1. Characteristics of the Blind Participants

Participant

Age

Sex

Handedness

EB01

EB02

EB03

EB04

EB05

EB06

EB07

EB08

EB09

EB10

EB11

EB12

EB13

EB14

EB15

EB16

A(R)

Residual
Vision

None

Educational
Level

Musical
Experience

Onset

Etiology

1 y

Glaucoma

Leber’s congenital
amaurosis

Retinopathy of
prematurity

University

High school

10 m (OS)/
3.5 y (OD)

Retinoblastoma

Cegep

None

Leber’s congenital

University

None

2 m

None

amaurosis

Electrical burn of
optic nerves

Glaucoma

Retinopathy of
prematurity

High School

University

High School

Major eye infection

University

Congenital cataracts

Cegep

Glaucoma and

microphtalmia

Retinopathy of
prematurity

University

Chorioretinal atrophy
(Toxoplasmosis)

Retinopathy of
prematurity

Cegep

Yes

Handedness was assessed using an adapted version of the Edinburgh inventory. Blind and sighted participants were classified as musicians if
they had practiced a musical instrument or had vocal training for at least 2 years on a regular basis (at least 2 hours a week). A = Ambidextrous;
M = male; F = female; DL = diffuse light; m = months; y = years; OS = left eye; OD = right eye; Cegep = 2 years of education between high school and
university.

Journal of Cognitive Neuroscience

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Experimental Design and Stimuli

Participants in both groups were scanned in an auditory
run and were blindfolded throughout the fMRI acquisi-
tion. Sighted participants were additionally scanned in a
visual run on a separate day. To familiarize the partici-
pants to the fMRI environment, participants underwent
a training session in a mock scanner while listening to
recorded scanner noise. To ensure that all object sounds
were clearly recognized, participants were familiarized
to all stimuli before practicing the tasks in the mock
scanner. In the scanner, auditory stimuli were delivered
by means of circumaural, fMRI-compatible headphones
(Mr Confon, Magdeburg, Germany). Visual stimuli were
projected on a screen at the back of the scanner and
visualized through a mirror (127 mm × 102 mm) that was
mounted at a distance of approximately 12 cm from the
eyes of the participants.

Auditory Stimuli

Auditory stimuli consisted of four different categories:
human voices, object sounds, and their respective scram-
bled versions (hereafter V, O, SV, SO, respectively; Fig-
ure 1). All sounds were monophonic, 16-bit, and sampled
at 44.1 Hz. Voices and object sounds were cut at 995 msec
(5 msec fade-in/fade-out). A 5-msec silence was added
at the beginning of the stimuli to prevent clicking.

Human voices consisted of eight exemplars of each of
five vowels (“a,” “e,” “i,” “o,” “u”), pronounced by 40 dif-
ferent speakers (half were male; Figure 1A). Object
sounds consisted of 40 sounds of man-made artifacts
(Figure 1B). In line with previous studies (Lewis et al.,
2005, 2012; Lewis, Talkington, et al., 2011), object sounds
included a range of nonverbal sounds of nonliving ob-
jects, namely, human action sounds (lighting a match,
jingling coins, hammering a nail, water flushing in the
sink, jigsaw, manual saw, typing on a writing machine
(2), dropping ice cubes in a glass, broom falling on the
floor, pouring water in a glass, velcro, jingling keys, plate
breaking, zipper, cleaning brush), bells and musical
instruments (christmas bells, shop bell, door bell, piano,
flute, drums, maracas, trumpet, guitar, tom tom, bicycle
bell, harp), and automated machinery (car horn, train
horn, helicopter, cuckoo clock, phone tone, motorcycle,
gun bursts, printer, automatic camera, police car, tractor,
hair dryer). These sounds were selected from a larger
sample of 80 sounds in a pilot study based on
the recognition performance of 10 sighted participants.
In this pilot study, participants were asked to name
each sound and rate it on a scale from 1 to 10 according
to how much the sound was characteristic (representa-
tive) of the object. The 40 sounds with the highest rates
(all above 7) were selected for the fMRI experiment.
Before the actual fMRI experiment and before practic-
ing the repetition task (see Paradigm section) in the sim-
ulator, all participants were familiarized to each of the

object sounds: They were asked to name each object
after listening to its sound. Recognition accuracy during
familiarization was at ceiling and was therefore not
monitored.

Scrambled versions of the vocal and object sounds
were obtained using MATLAB (The MathWorks, Inc.,
Natick, MA; Figure 1C and D). Scrambling was inspired
by the method of Belin and colleagues (2000, 2002) but
differed in that the scrambling of amplitude and phase
components was conducted separately within frequency
windows (here 700 Hz) instead of time windows. Each
vocal and object sound was submitted to a fast Fourier
transformation, and the resulting components were
separated into frequency windows of ∼700 Hz based
on their center frequency. Scrambling was then per-
formed by randomly intermixing the magnitude and
phase of each Fourier component (Belin et al., 2000,
2002) within each of these frequency windows sepa-
rately. The inverse Fourier transform was then applied
on the resulting signal. The output was a sound of the
same length of the original sound with similar energy
within each frequency band (Figure 1A–D, power spec-
trum, and E, decibel level). For scrambled vocal sounds
only, the envelope of the original voice was further ap-
plied on the output signal (Figure 1C). This was not done
for scrambled object sounds because the application of
the original envelope in this case led to recognition of
many scrambled object sounds despite the scrambling
(Figure 1D). Hence, for these sounds, a 5-msec ramp
was applied in the beginning and at the end, and a 5-msec
silence was added at the beginning. Following standard
practice, voices, object sounds, and their scrambled ver-
sions were equalized in root mean square level (Giordano
et al., 2013; Belin et al., 2000, 2002).

Measures of spectral content (FC and FCSD) and spec-
tral structure (HNR) were extracted for each sound using
Praat as described in Leaver and Rauschecker (2010)
and are depicted in Figure 1F. FC reflects the center of
gravity of the spectrum, an approximation of overall
frequency content, and FCSD is its standard deviation
across the spectrum. HNR measures the ratio of the
strength of the periodic and aperiodic (noisy) components
of a signal.

The scrambling method used in this study has the
important advantage of altering the perception of the
stimuli as object- and voice-like (sound examples are
provided as supplemental material) while leaving the fre-
quency spectrum of the original sound relatively unaffected
(Figure 1). Temporal structure is relatively preserved only
in the case of scrambled voices by application of the orig-
inal sound envelope (Figure 1C). In contrast, harmonicity,
typically higher for vocal stimuli, is altered by scrambling
(Figure 1F, HNR).

This factorial design thus allows for control of the fre-
quency spectrum of objects and voices by contrasting
these sounds to their scrambled versions. This is crucial,
considering recent evidence that occipital regions in

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congenitally blind participants respond differently to dis-
tinct auditory frequencies ( Watkins et al., 2013). Beyond
controlling for low-level parameters of the sounds, this
paradigm further allows for the assessment of the degree
to which low-level parameters contribute to a given cate-
gorical response (i.e., as it is the case for instance when a
larger categorical response for voices relative to objects is
also found when contrasting the corresponding scram-
bled control sounds; Table 2).

Visual Stimuli

In this experiment, stimuli consisted of four different
categories: pictures of faces, objects, and their phase-
scrambled version (hereafter F, O, SF, SO, respectively;
Rossion et al., 2012). The face category consisted of full
front pictures of 50 different faces (half male; between
170 and 210 pixels width and 250 pixels height) that were
cropped for external features and embedded in a white
rectangle (220 pixels width × 270 pixels height). Similarly,
the objects category consisted of pictures of 50 different
objects (170–210 pixels width × 250 pixels height) in-
serted in a white rectangle (220 pixels width × 270 pixels
height). The phase-scrambled pictures were used to con-
trol spatial frequencies and pixel intensity in each color
channel (RGB) in the face and in the object categories.
Phase-scrambled pictures were created using a Fourier
phase randomization procedure by replacing the phase
of each original image by the phase of a uniform noise
allowing for amplitude to be conserved in each frequency
band (Sadr & Sinha, 2004).

Pictures of objects consisted of the following items:
fan, lamp, hat, garbage, coins, bag, balloon, stroller, glass,
jeans, pair of boots, jewel, small bell, sofa, door, present,
hairdryer, vase, hourglass, frame, headphones, key, clip-
board, wine barrel, guitar, mug, toothbrush, tennis racket,
alarm clock, tap, wardrobe, gloves, car tire, scissors, adjust-
able wrench, lens, screw, drum, trumpet, water gallon, light
bulb, bucket, rugby ball, padlock, ring, paper bag, pepper,
apple, plastic bag, ruby.

Paradigm

Both the auditory and the visual experiments consisted
of a single run lasting about 18 min and with 10 repeti-
tions of each of the four conditions that alternated in
blocks of 21 sec. Blocks were separated by a 7-sec baseline
(silence and white fixation cross on a black background
in the auditory and visual experiment, respectively). In
each block, 20 items (sounds, pictures) were presented
with a 50-msec ISI. Participants were instructed to detect
a repetition in the stimuli (the same sound or picture
presented twice in a row) by pressing a key with the right
index finger. Emphasis was put on accuracy rather than
speed. The number of repetitions within each block was
unpredictable (i.e., two to four repetitions), thus ensuring

that participants kept attending to the stimuli throughout
the block. Within each condition, there were four blocks
with one repetition, four blocks with two repetitions, and
two blocks with three repetitions, for a total of 18 targets
per condition. This design aimed at matching as best
as possible attention, arousal, and motor components
between conditions.

Behavioral Analysis

Behavioral performance in the auditory experiment was
analyzed by submitting accuracy scores (hits − false
alarms) to a mixed 2 Group (blind, sighted; between-
subject factor) × 4 Condition ( V, O, SV, SO) ANOVA. In
the visual experiment, a repeated-measures ANOVA was
conducted with Condition (faces, objects, scrambled
faces, scrambled objects) as a within-subject factor. A
Greenhouse–Geisser correction was applied to the de-
grees of freedom and significance levels whenever an
assumption of sphericity was violated.

MRI Data Acquisition

fMRI series were acquired using a 3-T TRIO TIM system
(Siemens, Erlangen, Germany), equipped with a 12-channel
head coil. Multislice T2*-weighted fMRI images were
obtained with a gradient echo-planar sequence using axial
slice orientation (repetition time = 2200 msec, echo time =
30 msec, flip angle = 90°, 35 transverse slices, 3.2 mm slice
thickness, 0.8 mm interslice gap, Field of View = 192 ×
192 mm2, matrix size = 64 × 64 × 35, voxel size = 3 × 3 ×
3.2 mm3). Slices were sequentially acquired along the
z-axis in feet-to-head direction. The four initial scans were
discarded to allow for steady state magnetization. The
participants’ head was immobilized using foam pads. A
structural T1-weigthed 3-D magnetization-prepared rapid
gradient echo sequence (voxel size = 1 × 1 × 1.2 mm3,
matrix size = 240 × 256, repetition time = 2300 msec,
echo time = 2.91 msec, inversion time = 900 msec, Field
of View = 256; 160 slices) was also acquired for all
participants.

fMRI Analysis

Functional volumes from the auditory and visual experi-
ments were preprocessed and analyzed separately using
SPM8 ( Welcome Department of Imaging Neuroscience,
London, UK; www.fil.ion.ucl.ac.uk/spm/software/spm8/ ),
implemented in MATLAB R2008a (The MathWorks, Inc.).
Preprocessing included slice timing correction of the
functional time series (Sladky et al., 2011), realignment
of functional time series, coregistration of functional
and anatomical data, creation of an anatomical template
using DARTEL (a template including participants from
both groups in the auditory experiment and a template

Journal of Cognitive Neuroscience

Volume 30, Number 1

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Figure 1. Stimuli in the auditory experiment. Top: Sound properties in a representative 21-sec block in the (A) voice and (B) object sounds
conditions and in their respective (C and D) scrambled conditions. Graphs represent sound amplitude as a function of time and frequency
spectrum as a function of time. Red dashed lines indicate the occurrence of a target sound. (E) Bode magnitude plot expressing the
magnitude in decibels as a function of frequency for the four blocks depicted in the top part of the figure. (F) Measures of spectral content
(FC and FCSD) and spectral structure (HNR) are plotted in color for each stimulus. Scrambling leaves the frequency spectrum relatively
unaffected while altering harmonicity.

including sighted participants only in the visual experi-
ment; Ashburner, 2007), spatial normalization of ana-
tomical and functional data to the template, and spatial
smoothing (Gaussian kernel, 8 mm FWHM). The creation
of a study-specific template using DARTEL was performed
to reduce deformation errors that are more likely to arise
when registering single-participant images to an unusually
shaped template (Ashburner, 2007). This is particularly
relevant when comparing blind and sighted participants,

given that blindness is associated with significant changes
in the structure of the brain itself, particularly within the
occipital cortex ( Jiang et al., 2009; Park et al., 2009; Pan
et al., 2007).

Activation Analyses

The analysis of fMRI data, based on a mixed effects model,
was conducted in two serial steps, accounting for fixed

Dormal et al.

and random effects, respectively. In the auditory exper-
iment, changes in brain regional responses were esti-
mated for each participant by a general linear model
including the responses to each of the four conditions
( V, O, SV, SO). These regressors consisted of boxcar
function convolved with the canonical hemodynamic
response function. The movement parameters derived
from realignment of the functional volumes (translations
in x, y, and z directions and rotations around x, y, and
z axes) and a constant vector were also included as covar-
iates of no interest. High-pass filtering was imple-
mented in the design matrix using a cutoff period of
128 sec to remove low-frequency noise and signal drift
from the time series. Serial correlations in fMRI signal
were estimated using an autoregressive (Order 1) plus
white noise model and a restricted maximum likelihood
algorithm. Linear contrasts tested the main effect of each
condition ([V], [O], [SV], [SO]) and the contrasts be-
tween conditions ([V > O], [O > V], [V > SV], [O >
SO]) and generated statistical parametric maps [SPM
(T)]. These summary statistics images were then further
spatially smoothed (Gaussian kernel 6 mm FWHM) and
entered in a second-level analysis, corresponding to a ran-
dom effects model, accounting for intersubject variance.
For each of the above-mentioned contrasts, one-sample t
tests were performed within each group, and two-sample
t tests were performed to compare effects between groups
(EB > SC, SC > EB). Voice-selective voxels were identified
by means of an “AND” conjunction contrast of [V > O] and
[V > SV] (Nichols, Brett, Andersson, Wager, & Poline,
2005). Object-selective voxels were identified by means of
an “AND” conjunction contrast of [O > V] and [O > SO].
These contrasts thus identified voxels responding more to a
category of sound relative to the other and for which this
difference could not be accounted by differences in global
energy or frequency spectrum.

These two conjunction analyses were conducted sepa-
rately for each group (testing for voxels fulfilling these
requirements in each group), jointly between groups
(testing for voxels fulfilling these requirements in both
groups, that is, independently of visual experience; see
Figure 2A and B), and on between-group two-sample
t tests (testing for voxels fulfilling these requirements in
one group more than in the other; Figure 4A).

Preprocessing and statistical analyses of the fMRI data
in the visual experiment were performed as in the audi-
tory experiment, with the exception that random effects
were only calculated based on a one-sample t test (no
group comparison).

Statistical inference was performed at a threshold of
p < .05 after correction for multiple comparisons (family- wise error [FWE] method) over either the entire brain volume or over small spherical volumes (15-mm radius) located in structures of interest (see table legends). Signif- icant clusters were anatomically labeled using a brain atlas (Petrides, 2012). Beta-weight extraction was used for visualization in figure charts only, whereas statistical ana- lyses were performed on the single-voxel data, as per convention. Psychophysiological Analyses Psychophysiological interaction (PPI) analyses were com- puted to identify any brain regions showing a significant change in functional connectivity with seed areas as a function of experimental condition (O, V) and group (EB > SC). Seed areas were selected using a two-step
approach. First, all of the regions that were significant
in the contrasts of interest, namely, regions showing pref-
erential responses to voices and objects in both groups
(Figure 2A and B) and those selectively responding to
object sounds in the blind group only (Figure 4A) were
selected as potential seed areas. Second, among signifi-
cantly active regions, seeds for PPI analyses were selected
based on previous literature (see the list of selected re-
gions in Table 6).

In each participant, the first eigenvariate was extracted
using the single value decomposition of the time series
across the voxels in a 10-mm radius sphere centered on
the peak of activation reported at the group level. New
linear models were generated using three regressors.
The first two regressors were modeled as covariates of
no interest and represented the condition (i.e., psycho-
logical regressor: O > V and V > O) and the raw activity
extracted in the seed area (i.e., physiological regressor),
respectively. The third, psychophysiological regressor,
represented the interaction of interest between the first
(psychological) and the second (physiological) regressor.
To build this third regressor, the underlying neuronal
activity was first estimated by a parametric empirical
Bayes formulation combined with the psychological
factor and subsequently convolved with the hemo-
dynamic response function (Gitelman, Penny, Ashburner,
& Friston, 2003). Thus, variance explained by the psycho-
physiological regressor is above variance explained solely
by the main effects of task (psychological regressor) and
physiological correlation (O’Reilly, Woolrich, Behrens,
Smith, & Johansen-Berg, 2012). Movement parameters and
a constant vector were also included as covariates of no
interest. A significant PPI indicated a change in the regres-
sion coefficients between any reported brain area and
the seed area related to the experimental condition (O >
V, V > O). Next, individual summary statistic images ob-
tained at the first-level (fixed-effects) analysis were spatially
smoothed (6-mm FWHM Gaussian kernel) and entered in
a second-level (random-effects) analysis using a one-
sample t test. Two-sample t tests were then performed to
compare these effects between groups.

Statistical inference was performed as for the activation
analyses with the exception that here we only report
those regions showing a functional connectivity change
in the blind group compared with the sighted group
(EB > SC) and where the effect is driven by the blind
group. For this purpose, small volume correction (SVC)

Journal of Cognitive Neuroscience

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(corrected for multiple comparisons using FWE method
at p < .05) were performed on the between-group func- tional connectivity maps (two-sample t tests thresholded at p(unc) < .001, EB > SC) and inclusively masked by
the functional connectivity map in the blind group (one-
sample t test, p(unc) < .001). RESULTS Behavioral Results Auditory Experiment There was no effect of group ( p > .15), indicating that
overall accuracy (hits − false alarms) did not differ be-
tween blind (mean = 91.58%, SD = 11.22%) and sighted
participants (mean = 86.2%, SD = 9.42%). There was a
significant effect of condition, F(2.23, 64.71) = 4.493, p =
.012, but group did not interact with this effect ( p > .9).
Two-tailed paired t tests, collapsed across groups, revealed
that detecting repetitions in the scrambled objects condition
(mean = 83.87%, SD = 14.79%) was more challenging
than in the other conditions (scrambled voices [SV]:
mean = 90.86%, SD = 12.79%, t(30) = −3.198, p = .003;
objects [O]: mean = 92.29%, SD = 10.21%, t(30) = −3.591,

p = .001; voices [V]: mean = 88.89%, SD = 15.18%, t(30) =
−2.005, p = .05).

Visual Experiment

There was a significant effect of condition (F(3, 48) =
9.663, p < .001). Two-tailed paired t tests revealed that accuracy (hits − false alarms) was lower in the scrambled faces condition (mean = 73.2%, SD = 21.26%) compared with the remaining conditions (faces: mean = 85.29%, SD = 11.44%, t(16) = −2.766, p = .014; objects: mean = 92.16%, SD = 9.43%, t(16) = −4.788, p < .001; scrambled objects: mean = 87.58%, SD = 11.87%, t(16) = −3.507, p = .003) and lower in the face than in the object condition (t(16) = −2.159, p = .046). fMRI Results—Activation Analyses Object and Voice Categorical Responses Common to Early Blind and Sighted Participants Between-group conjunction (AND) analyses identified brain regions commonly responsive in both groups when listening to voices compared with both scrambled voices l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / / 3 0 1 8 6 1 7 8 7 0 5 0 / j o c n _ a _ 0 1 1 8 6 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Figure 2. Categorical responses to (A) voices and (B) object sounds common to blind and sighted participants. For illustration purposes, activity maps are displayed at p(unc) < .005 with k > 90 (A) and p(unc) < .001 with k > 8 (B). Color bar represents t values. (C) Mean activity
estimates (arbitrary units ± SEM ) are plotted for the four auditory conditions in significant peaks depicted in A and B. (D) PPI analyses as a function
of group (blind > sighted) and experimental condition ( V > O and O > V) based on the peaks of activation depicted in A and B. For illustration
purposes, activity maps are displayed at p(unc) < .005 and masked inclusively by the main effect in the blind ( p(unc) < .005). EB = early blind; SC = sighted controls; L = left; R = right; S = sulcus; G = gyrus. See Tables 2 and 6 for a list of brain regions depicted in this figure. Dormal et al. 93 and objects and when listening to objects compared with scrambled objects and voices. Categorical responses to voices common to blind and sighted participants were found in two circumscribed areas within the superior temporal sulci bilaterally (Figure 2A and Table 2). Inspection of the individual data revealed that such responses were present in each single participant (data not shown). Importantly, these areas also strongly responded to low-level characteristics of voices (SV > SO; Table 2).

In both blind and sighted participants, object sounds
preferentially activated large portions of the auditory cortex
bilaterally—although stronger in the left hemisphere—in
the medial part of the transverse temporal gyrus (A1),
extending laterally along the lateral fissure and posteriorly
to the planum temporale (Figure 2B and Table 2). In the
left hemisphere, additional clusters of activation were
found within the inferior frontal gyrus and sulcus and
within the temporal cortex, in the posterior middle tempo-
ral gyrus (pMTG) extending to the inferior temporal sulcus
and fusiform gyrus. Contrary to voice-responsive regions,
there was no contribution of low-level parameters to
the response observed in object-responsive regions,
neither in the sighted group nor in the blind group (no
significant responses in the contrast SO > SV). Object-
selective areas common to both groups in the left-
lateralized inferior frontal gyrus, pMTG, and fusiform
gyrus overlapped with visual-selective areas responsive to

pictures of objects in the sighted group (Figure 3B and
Table 3) (as also confirmed by a conjunction analysis, data
not shown).

Object and Voice Categorical Responses Specific to
Early Blind Participants

Two-sample t tests were then performed to compare these
effects between groups. A conjunction (AND) analysis was
conducted on the two-sample t tests [EB > SC] × [O > V]
and [EB > SC] × [O > SO] to identify regions specifically
activated in the blind group (relative to sighted) for the pro-
cessing of object sounds relative to both scrambled objects
and voices (Figure 4A and Table 4). This analysis revealed
large bilateral activations in the occipital cortex that peaked
in the middle and inferior occipital gyri bilaterally. There
was no contribution of low-level parameters to the categor-
ical response observed for objects (no significant responses
in the contrast SO > SV ). These between-group effects
[EB > SC] were driven by the blind group (Table 4). The
reverse group comparisons [SC > EB] did not reveal any
region that was more strongly responsive in the sighted
to object sounds relative to voices or scrambled objects.

On the lateral portion of the occipitotemporal cortex,
these object-selective responses specific to the blind group
partially overlapped with shape-selective visual cortex
localized in the sighted group using the contrast [O > SO]
(lateral occipital complex [LOC]; Malach et al., 1995;

Figure 3. Objects categorical responses across modalities (visual and auditory) and populations (blind and sighted). (A) Categorical responses to
object sounds common to blind and sighted participants. (B) Categorical responses to pictures of objects in the sighted. For illustration purposes,
activity maps are displayed at p(unc) < .001 with k > 8. Color bar represents t values. Regions in the left inferior frontal gyrus, pMTG, and fusiform
gyrus are responsive across groups in the auditory modality (A) and across the auditory and the visual modalities in the sighted group (A and B).
EB = early blind; SC = sighted controls; L = left; R = right; S = sulcus; G = gyrus; O = objects; V = voices; SO = scrambled objects; SV = scrambled
voices; F = faces; SF = scrambled faces. See Tables 2 and 3 for a list of brain regions depicted in this figure.

Journal of Cognitive Neuroscience

Volume 30, Number 1

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Figure 4. (A) Categorical responses to object sounds specific to the blind. Color bar represents t values. For illustration purposes, activity maps are
displayed at p(unc) < .0001. Mean activity estimates (arbitrary units ± SEM ) are plotted for the four auditory conditions in significant peaks depicted in A. (B) PPI analyses as a function of group (blind > sighted) and experimental condition (O > V) based on the peaks of activation depicted in A. For
illustration purposes, activity maps are displayed at p(unc) < .001 and masked inclusively by the main effect in blind group ( p(unc) < .001). See Tables 4 and 6 for a list of brain regions depicted in this figure. Table 3), as also confirmed by a conjunction analysis (data not shown). A conjunction (AND) analysis was conducted on the two-sample t tests [EB > SC] × [V > O] and [EB > SC] ×
[V > SV] to identify regions specifically activated in the
blind group (relative to the sighted group) for the pro-
cessing of voices relative to both scrambled voices and
objects. This analysis yielded no significant response,
even at a very lenient threshold of p < .01 uncorrected. Considering each of these t tests separately revealed that voices relative to scrambled voices [EB > SC] × [V > SV]
elicited higher responses in the blind group in the fusi-
form gyrus bilaterally (Figure 5 and Table 5). This effect
was driven by the blind group (Table 5). In contrast, voices
compared with objects [EB > SC] × [V > O] did not elicit
any larger activation in the blind group relative to the
sighted group. The reverse group comparisons [SC > EB]
did not reveal any region that was more strongly respon-
sive in the sighted group for voices relative to objects or
scrambled voices.

In summary, voice-selective responses relative to both
object sounds and scrambled voices were limited to the
superior temporal sulci (auditory cortices) in both
groups with no evidence of cross-modal responses in
the VOTC in either group (as also accounted by the indi-
vidual data, data not shown).

Figure 5. Regions showing stronger response to voices relative to
scrambled voices specifically in the blind. For illustration purposes,
activity maps are displayed at p(unc) < .001 with k > 10. Mean activity
estimates (arbitrary units ± SEM ) are plotted for voices and scrambled
voices in significant peaks. EB = early blind; SC = sighted controls;
L = left; R = right; S = sulcus; G = gyrus. See Table 5 for a list of
brain regions depicted in this figure.

Dormal et al.

fMRI Results—Psychophysiological Analyses

PPI analyses were computed to identify any brain regions
showing a significant change in functional connectivity with
specific seed areas as a function of experimental condition
(O > V and V > O) and group (EB > SC; Table 6).

Among the two regions selectively responsive to voices
in both groups (Figure 2A), the left STS displayed an in-
crease in functional connectivity with the right fusiform
gyrus in the blind group during voice processing com-
pared with object sounds processing (Figure 2D, a).

Among the regions that selectively responded to object
sounds in both groups (Figure 2B), several seed areas
located in auditory cortices showed a significant increase
in functional connectivity with ventral occipitotemporal

regions during the processing of object sounds relative
to processing of voices in blind relative to sighted partici-
pants (Figure 2D, c–e). Notably, the left primary auditory
cortex showed increased connectivity with the left inferior
occipital gyrus (Figure 2D, c), the left transverse temporal
gyrus showed increased connectivity with the left inferior
occipital gyrus and the left posterior fusiform gyrus
(Figure 2D, d), whereas the right planum temporale showed
increased connectivity with the right fusiform gyrus
(Figure 2D, e). Regions located in the left inferior frontal
gyrus and the sulcus and those located in the left temporal
cortex (left pMTG and the left inferior temporal sulcus), all
showed an increase in functional connectivity with a cir-
cumscribed region located in the left posterior fusiform
gyrus (Figure 2D, f–i). In addition, the left inferior frontal

Table 2. Categorical Responses to Voices and Object Sounds Common to Blind and Sighted Participants and Responses to Low-level
Properties of Voices Common to Blind and Sighted Participants

Area

x (mm)

y (mm)

z (mm)

Between-group (AND) Conjunction: [V > SV] ∩ [V > O]

R superior temporal S

L superior temporal S

Between-group (AND) Conjunction: [O > SO] ∩ [O > V]

L planum temporale

L transverse temporal G

L transverse temporal S (A1)

R Heschl’s G (A1)

R planum temporale

L inferior frontal G (orbital part)

L inferior frontal G (triangular part)

L inferior temporal S

L pMTG

L collateral S (fusiform G)

L fusiform G

1293

956

176

367

283

Between-group (AND) Conjunction: [SV > SO]

R superior temporal S

L superior temporal S

135

197

−60

−50

−42

−32

−46

−44

−54

−26

−36

−60

−66

−24

−28

−34

−22

−26

−30

−36

−50

−60

−38

−26

−24

−14

−22

−2

−8

−12

−18

−22

3.45

3.23

4.83

4.80

4.79

4.65

4.61

4.02

4.28

4.18

4.02

3.96

4.35

3.36

3.47

3.70

3.51

.022

.04

.013*

.014*

.015*

.026*

.030*

.003

.001

.002

.003

.004

.001

.025

.016

.008

.014

Coordinates reported in this table are significant ( p < .05 FWE) after correction over small spherical volumes (SVC) or over (*) the whole brain. k represents the number of voxels when displayed at p(unc) < .001. V = voices; O = objects; SV = scrambled voices; SO = scrambled objects; L = left; R = right; G = gyrus; S = sulcus. Coordinates used for SVC are as follows (in MNI space): R superior temporal S: [60 −32 4] (Gougoux et al., 2009); L superior temporal S: [−64 −28 2] (Gougoux et al., 2009); R planum temporale: [52 −44 10] (Lewis, Talkington, et al., 2011); L collateral S: [−28 −26 −26] (He et al., 2013); L inferior frontal G (triangular part): [−51 30 3] (Noppeney et al., 2003); L inferior frontal G (orbital part): [−28 34 −6] (Bar et al., 2001); L pMTG/ITG: [−52 −58 −6] (Peelen et al., 2013). Voice-selective regions common to blind and sighted participants are depicted in Figure 2A. Object-selective regions common to blind and sighted participants are depicted in Figures 2B and 3A. 96 Journal of Cognitive Neuroscience Volume 30, Number 1 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / / 3 0 1 8 6 1 7 8 7 0 5 0 / j o c n _ a _ 0 1 1 8 6 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 Table 3. Visually Responsive Regions in the Sighted Area k x (mm) y (mm) z (mm) Z p Shape-selective Regions in Vision: [O > SO]

13013

8510

5739

L collateral S

L fusiform G

L inferior occipital G

L angular G

R inferior temporal G

R parahippocampal G

R middle temporal G

L superior frontal G

L inferior frontal G (orbital part)

L superior frontal G

Object-selective Regions in Vision: [O > SO] ∩ [F > SF]

L collateral S

L fusiform G

R collateral S

R fusiform G

L angular G

L pMTG

L inferior temporal G

L inferior frontal G (orbital part)

1295

809

633

360

148

−34

−46

−38

−46

−56

−48

−18

−48

−38

−30

−4

−32

−30

−38

−42

−58

−56

−30

−34

−54

−46

−82

−66

−70

−24

−74

−14

−66

−34

−50

−26

−46

−76

−82

−58

−60

−18

−10

−6

−14

−10

−22

−18

−14

−10

−18

−14

−22

−12

−6

−10

5.76

5.41

4.96

5.64

4.98

4.77

5.53

5.52

5.24

5.30

5.42

4.98

4.89

4.66

4.86

5.75

4.67

5.20

4.75

3.99

3.51

4.29

4.16

3.77

<.001* .002* .015* .001* .013* .030* .001* .001* .005* .004* .002* .013* .019* .046* .021* .000* .044* .005* .032* .005 .032 .002 .003 .010 Coordinates reported in this table are significant ( p < .05 FWE) after correction over small spherical volumes (SVC) or over (*) the whole brain. k represents the number of voxels when displayed at p(unc) < .001. F = faces; O = objects; SF = scrambled faces; SO = scrambled objects; L = left; R = right; G = gyrus; S = sulcus. Coordinates used for SVC are as follows (in MNI space): L inferior frontal G (orbital part): [−28 34 −6] (Bar et al., 2001); L pMTG/inferior temporal G: [−52 −58 −6] (Peelen et al., 2013), L angular G: [−48 −70 31] (Fairhall & Caramazza, 2013). Object-selective regions in vision are depicted in Figure 3B. sulcus and pMTG showed an increase with the right anterior fusiform gyrus (Figure 2D, f–g), whereas the left inferior temporal sulcus showed an increase with the left inferior occipital gyrus (Figure 2D, h). All reorganized occipital regions that showed a categor- ical response to object sounds only in the blind group (Figure 4A) showed increased connectivity with a circum- scribed region in the left posterior fusiform gyrus (Figure 4B, a–d). In addition, the left middle occipital gyrus showed increased connectivity with the right anterior fusiform gyrus, the right middle occipital gyrus, and the right planum temporale (Figure 4B, a); the left inferior oc- cipital gyrus showed increased functional connectivity with the right inferior occipital gyrus (Figure 4B, b), and the right middle occipital gyrus showed an increase in connec- tivity with the right planum temporale (Figure 4B, c). DISCUSSION This study investigated how visual experience impacts on the neural basis of object sounds and voice processing. Dormal et al. 97 l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . e d u / j / o c n a r t i c e - p d l f / / / / 3 0 1 8 6 1 7 8 7 0 5 0 / j o c n _ a _ 0 1 1 8 6 p d . f b y g u e s t t o n 0 7 S e p e m b e r 2 0 2 3 We used scrambled control sounds to control for low- level differences in the frequency spectrum between these categories of sounds and assess the contribution of low-level parameters to the categorical responses ob- served for object sounds and voices. Double Dissociation for Object Sounds and Voices in the Auditory Temporal Cortices In both blind and sighted groups, a double dissociation was identified in the temporal cortex between separate regions that showed categorical responses to either ob- ject sounds or voices. These findings suggest that the cortical networks for processing these two auditory cate- gories are at least partially separate (Figure 2 and Table 2). In line with previous work, categorical responses to sounds of objects were observed along the lateral fissure bilaterally (Giordano et al., 2013; Lewis et al., 2005, 2012; Lewis, Talkington, et al., 2011), whereas categorical responses to voices were observed within bilateral superior temporal sulci (Belin, Fecteau, & Bédard, 2004; Belin et al., 2000, 2002). These findings support the notion that the audi- tory system—like the visual one—hosts a domain-specific organization where distinct areas preferentially respond to different categories of complex environmental sounds such as voices, animal vocalizations, tools, or musical instruments (Engel et al., 2009; Lewis et al., 2005, 2009; Patterson, Uppenkamp, Johnsrude, & Griffiths, 2002). These results are also in line with neuropsychological evidence demonstrating that lesions to portions of the tem- poral or temporoparietal cortex can lead to auditory agno- sia, an impaired capacity to recognize complex natural Table 4. Categorical Responses to Object Sounds Specific to the Blind Area k x (mm) y (mm) z (mm) Z p x (mm) y (mm) z (mm) Z p Between-group Effects: [EB > SC]

Main Effect in EB

[O > SO]

L inferior occipital G

7443

L middle/inferior occipital G

L fusiform G

R inferior OTC

R inferior occipital G

R fusiform S

6075

[O > V]

L middle occipital G

15494

L middle/inferior occipital G

L superior occipital G

[O > SO] ∩ [O > V]

L middle occipital G

5582

L middle/inferior occipital G

L lingual G

R inferior OTC

R inferior occipital G

R middle occipital G

4821

−26

−36

−26

−28

−26

−36

−20

5.46

.001*

5.45

0.001*

4.86

4.75

4.57

4.52

.011*

.018*

.035*

.042*

[O > SO]
−20

−32

−34

5.57 <.001* 5.32 0.001* 5.22 .002* [O > V]
−24

−26

−94

−84

−68

−66

−82

−56

−94

−78

−94

[O > SO] ∩ [O > V]

5.46

.001*

5.21

0.002*

4.49

4.75

4.40

4.29

.047*

.018*

.001

−24

−30

−20

−94

−80

−72

−76

−82

−4

−18

−6

−4

−20

−4

−6

−4

5.35

.001*

5.14 0.003*

5.82 <.001* 4.54 .039* 4.52 .043* 5.31 .002* 5.39 .001* 5.54 0.001* 5.34 .001* 5.31 .001* 5.14 0.003* 4.83 .013* 4.60 .031* 4.15 .002 3.75 .008 6 0 −14 −4 0 −16 4 −4 26 6 −2 0 −4 −2 10 −92 −82 −68 −66 −84 −54 −92 −78 −94 −92 −82 −74 −66 −80 −86 Coordinates reported in this table are significant ( p < .05 FWE) after correction over small spherical volumes (SVC) or over (*) the whole brain. k represents the number of voxels when displayed at p(unc) < .001. EB = early blind; SC = sighted controls; V = voices; O = objects; SV = scrambled voices; SO = scrambled objects; L = left; R = right; G = gyrus; S = sulcus; OTC = occipitotemporal cortex. For each region significant in the between-group contrasts (left-hand table), corresponding coordinates significant in the main effect in the blind are listed in the right-hand table. None of these regions were activated in the sighted group, indicating that the between-group effects (blind > sighted) are driven by these regions
being responsive only in the blind group. Two regions (underlined in the left-hand table) showed selective deactivation in the sighted group, thus
contributing to the between-group effects observed in the R inferior OTC [34 −68 4] (z = 3.21) and in the L middle occipital G [−24 −84 6] (z =
3.25). Coordinates used for SVC are as follows (in MNI space): R middle occipital G: [44 −74 8] (Gougoux et al., 2009). Regions listed showing
specific responses to objects (relative to both scrambled objects and voices) in blind compared with sighted are depicted in Figure 4A.

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Table 5. Voice-selective Regions Specific to the Blind

Area

x (mm)

y (mm)

z (mm)

x (mm)

y (mm)

z (mm)

Between-group Effects: [EB > SC]

Main Effect in EB

[V > SV]

L lateral occipitotemporal S

147

L fusiform G

R fusiform G

−40

−36

−50

−44

−62

−10

−22

−20

3.89

.006

3.40

.025

3.50

.019

−40

[V > ScrV]
−10

−10

−22

−50

−62

5.96 <.001* 5.96 <.001* 4.54 <.001* [V > O]

No significant voxels

[V > O]

No significant voxels

Coordinates reported in this table are significant ( p < .05 FWE) after correction over small spherical volumes (SVC) or over (*) the whole brain. k represents the number of voxels when displayed at p(unc) < .001. EB = early blind; SC = sighted controls; V = voices; O = objects; SV = scrambled voices; SO = scrambled objects; L = left; R = right; G = gyrus; S = sulcus. For each region significant in the between-group contrast (left-hand table), corresponding coordinates significant in the main effect in the blind group are listed in the right-hand table. None of these regions were activated or deactivated in the sighted group, indicating that the between-group effects (blind > sighted) are driven by these regions being respon-
sive only in the blind group. Coordinates used for SVC are as follows (in MNI space): L fusiform/inferior temporal G: [−46 −48 −16] (Gougoux et al.,
2009); R fusiform G: [34 −52 −16] (Gougoux et al., 2009). Regions more responsive to voices than scrambled voices in the blind group compared
with the sighted group are depicted in Figure 5.

sounds despite preserved speech comprehension and
visual object recognition (for a review, see Goll, Crutch, &
Warren, 2010).

Our paradigm further allowed us to investigate the
contribution of low-level parameters to these categorical
responses. Our scrambling technique preserved the fre-
quency content of the sounds (Figure 1) while altering
harmonic and phase-coupling content that is known to
contribute to the response in voice-selective regions
(Lewis et al., 2009). In this study, higher responses in
voice-selective areas were observed when contrasting
scrambled voices and objects (SV > SO; Table 2). This
finding suggests that the spectral frequency content of
voices participates to the signal attributes that preferen-
tially activate these regions. In other words, the prefer-
ence observed for voices compared with objects in
bilateral STS may emerge, at least partly, from the differ-
ential processing of low-level features that are typical of
these two categories of sounds (for a similar interpreta-
tion in vision, see Andrews et al., 2010). In contrast, low-
level parameters did not contribute to object categorical
responses, as no area in the brain was more largely re-
sponsive to scrambled objects than to scrambled voices.
In contrast to previous findings, no between-group dif-
ferences were observed for these domain-preferential re-
sponses in temporal “auditory” cortex (Hölig, Föcker,
Best, Röder, & Büchel, 2014; Lewis, Frum, et al., 2011;
Gougoux et al., 2009).

Multimodal Object Representations in the Left
Lateral and Ventral Occipitotemporal Cortex

Beyond the auditory cortex, preferential responses to ob-
ject sounds common to both groups were found in left-
lateralized inferior frontal and occipitotemporal regions

including the pMTG, inferior temporal gyrus, and fusi-
form gyrus (Figure 2B and Table 2). These left frontal
and temporal regions have been associated with auditory
object recognition (Lewis et al., 2004) and with semantic
processing of concrete objects (Gold et al., 2006; Gough,
Nobre, & Devlin, 2005; Wheatley, Weisberg, Beauchamp, &
Martin, 2005; Sharp, Scott, & Wise, 2004; for a review, see
Martin, 2007). Of note, in this study, these regions also
responded selectively when sighted participants viewed
pictures of objects (compared with both faces and scram-
bled objects; Figure 3B and Table 3).

In previous studies, similar left frontotemporal regions
were found to be responsive in both early blind and
sighted participants on tasks of action-related semantics
(left inferior frontal [−51 30 3] and left posterior MTG
[−63 −51 −6]; Noppeney et al., 2003), sounds of tools
(left pMTG [−51 −57 3]; Lewis et al., 2005), heard names
of tools (left pMTG [−50 −52 −3]; Peelen et al., 2013)
and places (left parahippocampal gyrus/fusiform [−28
−26 −21]; He et al., 2013), as well as viewing pictures
of corresponding objects in sighted participants (He
et al., 2013; Peelen et al., 2013).

The finding of preferential responses to “objects” inde-
pendent of the input modality (visual and auditory) and
of visual experience in left occipitotemporal regions may
suggest that these regions support a multimodal organi-
zation of object representations (Bi et al., 2016; Fairhall &
Caramazza, 2013). Because all sounds of objects in this
study were highly recognizable, we speculate that these
abstract representations were automatically activated
when participants were listening to these familiar envi-
ronmental sound sources (see Lewis et al., 2004, for sim-
ilar interpretation). In line with previous studies, it is
possible that the left occipitotemporal regions that
showed object-selective responses in this study contain

Dormal et al.

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Table 6. Regions Showing Increased Functional Connectivity with Specific Seed Areas as a Function of Experimental Condition (O >
V and V > O) and Group (Blind > Sighted)

Area

PPI [EB > SC] × [V > O]

x (mm)

y (mm)

z (mm)

Seed areas in voice-selective regions common to EB and SC

L superior temporal sulcus [−60 −28 0]

R anterior fusiform G

−46

−8

3.24

.041

R superior temporal sulcus [62 −24 0]

No significant voxels

PPI [EB > SC] × [O > V]

Seed areas in object-selective regions common to EB and SC

L transverse temporal sulcus (A1) [−42 −22 −2]

L inferior occipital G

L transverse temporal G [−42 −34 18]

L fusiform

L inferior occipital G

R planum temporale [46 −30 16]

R anterior fusiform G

L inferior frontal G [−32 30 −8]

L posterior fusiform G

L inferior frontal S [−46 40 12]

L posterior fusiform G

R anterior fusiform G

L pMTG [−54 −60 2]

R anterior fusiform G

L posterior fusiform G

L inferior temporal S [−44 −50 −12]

L posterior fusiform G

L inferior occipital G

PPI [EB > SC] × [O > V]

Seed areas in object-selective regions specific to EB

L middle occipital G [−26 −92 6]

L posterior fusiform G

R anterior fusiform G

R planum temporale

R middle occipital G

L inferior/middle occipital G [−36 −82 −2]

R inferior occipital G

L inferior temporal/fusiform G

101

160

178

112

−44

−34

−44

−38

−34

−38

−36

−46

−74

−62

−76

−38

−66

−68

−34

−36

−66

−64

−80

−64

−38

−36

−74

−68

−14

−16

−14

−20

−14

−12

−24

−22

−14

−10

−12

−20

−6

3.11

.056#

3.88

3.34

.006

.032

3.18

.052#

3.79

.007

3.71

3.16

3.8

3.57

3.87

3.22

4.07

3.48

3.80

3.46

3.94

3.82

.011

.05#

.008

.017

.006

.044

.003

.021

.008

.022

.005

.008

100

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Table 6. (continued )

Area

R middle occipital G [40 −86 10]

L posterior fusiform G

R planum temporale

R middle/inferior occipital G [36 −80 −2]

L posterior fusiform G

x (mm)

y (mm)

z (mm)

202

−34

−36

−64

−34

−66

−16

4.12

4.11

.002

3.27

.038

Seed areas are the ones resulting from the activation analyses (depicted in Figures 2A and B, 3A, and 4A). Regions showing increased connectivity
with these seed areas in the blind group compared with the sighted group are listed in this table and are depicted in Figures 2D and 4B. Coordinates
reported in this table are significant ( p < .05 FWE) after correction over small spherical volumes (SVC). Marginally significant clusters are indicated with (#). EB = early blind; SC = sighted controls; V = voices; O = objects; L = left; R = right; G = gyrus; S = sulcus. Coordinates used for correction over small spherical volumes are as follows (in MNI space): R fusiform G: [40 −36 −10] (Hölig et al., 2014); L fusiform G: [−36 −63 −18] (Noppeney et al., 2003); L inferior occipital G: [−36 −81 −15] (Noppeney et al., 2003); R planum temporale: [52 −44 10] (Lewis, Talkington, et al., 2011); R middle occipital G: [44 −74 8] (Gougoux et al., 2009). an abstract representation of objects—such as the ob- ject’s meaning and the semantics knowledge associated with it (Bi et al., 2016; Fairhall & Caramazza, 2013; Bracci, Cavina-Pratesi, Ietswaart, Caramazza, & Peelen, 2012; Kassuba et al., 2011; Lewis et al., 2004)—which may de- velop independently of visual experience. An alternative interpretation to multimodality in left occipitotemporal regions is visual mental imagery: The latter could have driven responses to auditory stimuli in the sighted group, as previously demonstrated for the tactile exploration of objects (Lacey, Flueckiger, Stilla, Lava, & Sathian, 2010). In other words, it is possible that similar activation patterns in the blind and sighted groups are related to different cognitive processes. Although no study to date can conclusively rule out visual imagery, we attempted to minimize this potential confound in our task by focusing the participant’s attention on the acous- tical properties of the sounds. Future studies may test more directly whether the format of the representation in this region is identical between auditory and visual stimuli or whether this region still maintains separate representational formats for each modality input despite coding for both. Functional connectivity analyses performed on the left inferior frontal cortex and pMTG showed a unique con- nectivity pattern in the blind group, namely, an increased task-related coupling with a circumscribed region of the left fusiform gyrus. These findings are remarkably similar to the ones reported by Noppeney et al. (2003). These authors found that the left inferior frontal cortex and left pMTG were activated in both early blind and sighted participants on a verbal semantic retrieval task. Yet, func- tional connectivity analyses on both of these regions revealed increased coupling with left-lateralized occipito- temporal areas only in the blind group. Altogether, these findings suggest that early visual deprivation, although preserving the responsiveness of the inferior frontal cor- tex and the left occipitotemporal cortex to object sounds (Figure 2B), impacts on these regions at the network level (Figure 2D). Worth noting, between-group differ- ences in the connectivity profile of regions that show similar task-dependent activity level could support the notion that the cognitive processes underlying the recruit- ment of those regions partially differ between the blind and sighted groups. Cross-modal Categorical Responses to Object Sounds in Posterior Occipital Cortex of the Blind Group A unique pattern of categorical responses to object sounds were found within large portions of the occipital cortex in the blind group, peaking in the middle and in the inferior occipital gyri bilaterally (Figure 4A and Table 4). This suggests a posterior expansion of cortical function related to the representations of object’s sounds in the blind group. These unique object-selective re- sponses in the blind group partially overlapped with por- tions of shape-selective visual cortex localized visually in the sighted group (Malach et al., 1995; Table 3). This runs counter to the notion that object-related responses in the occipital cortex of the blind group rely solely on the pro- cessing of shape information conveyed by objects (either via touch or sensory substitution devices; Amedi et al., 2007, 2010) because our task did not involve shape pro- cessing. In line with the present findings, another study reported a trend for responses to object sounds in LOC in two congenitally blind participants when no imagery of shape was involved (Amedi et al., 2007). Together, these findings suggest that at least portions of LOC in early blind individuals contain representations of object sounds that are not related to shape and that these re- gions reorganize due to the lack of developmental vision as they do not activate in sighted individuals. In this study, cross-modal responses to object sounds in the blind group were most pronounced outside visual re- gions with preferential responses to either shape (LOC, object pictures > scrambled objects) or object (objects >
face) in the sighted group: They extended more posteriorly
in the occipital cortex (compare Figure 3B and Figure 4A).

Dormal et al.

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Similar activation patterns with cross-modal responses ex-
tending posteriorly were reported in a previous study
when congenitally blind participants performed a tactile
recognition task (Amedi et al., 2010).

In this study, an important question pertains to the
cognitive processes or representational format that sup-
ports the categorical responses to sounds of objects
observed in the blind group. It has been proposed that
environmental sounds that are perceived as “object-like,”
such as those produced by automated machinery and
man-made objects (as in this study), share common
acoustical features, which may serve as low-level cues
for their identification in a complex acoustic environment
(Lewis et al., 2012). In this study, none of the reorganized
occipital regions showed stronger responses to scram-
bled objects compared with scrambled voices, running
counter to the assumption that categorical responses to
object sounds are driven by low-level acoustic features
that differentiate object sounds from voices (i.e., fre-
quency spectrum). Instead, we argue that these occipital
regions are an extension of more anterior occipito-
temporal regions that commonly respond to sounds of
objects in both sighted and blind participants (Figure 3)
and support a more abstract representation of an object’s
meaning. Several arguments account for this assumption.
Object-selective cross-modal responses in the blind
group were strongest in the left hemisphere and in the
vicinity of regions previously reported as being respon-
sive when early blind participants (compared with sight-
ed participants) process meaningful speech (sentences
and word lists compared with nonsemantic sentences
and nonword lists; Bedny et al., 2011; Röder et al.,
2002), generate semantically related verb to heard nouns
(Amedi, Raz, Pianka, Malach, & Zohary, 2003; Burton,
Diamond, & McDermott, 2003), and perform semantic
decisions on heard nouns (Noppeney et al., 2003).
Moreover, the functional connectivity pattern of these re-
organized occipital regions in the blind group resembles
to the one observed in the left pMTG and in the inferior
frontal cortex, that is, a systematic increased coupling
with ventral occipitotemporal regions (inferior temporal/
fusiform gyrus), mainly in the left hemisphere. Hence, we
propose that the left pMTG showing object’s sound selec-
tivity in both blind and sighted participants and more pos-
terior occipital regions showing preferential response to
object’s sounds only in the blind group support similar
functions, namely, an abstract representation of object
semantics. Although such representations are shared
across modalities and populations in more anterior occi-
pitotemporal regions, posterior occipital regions might
support similar functions only in the early blind due to
cross-modal plasticity. Future studies may include speech
material to further investigate the complex hierarchy
from sounds to words (Perlovsky, 2011) that may shed light
on the mechanisms that drive the occipital responses to
object sounds observed in early blind participants in
this study.

Lack of Cross-modal Categorical Responses to
Voices in Early Blind or Sighted Participants

In contrast to our observation of categorical responses to
object’s sounds in the occipitotemporal cortex of the
sighted group and, to a much larger extent, of the blind
group, no such categorical responses to voices were ob-
served outside the temporal auditory cortices in either
group. This is unlikely to be related to a lack of sensitivity
of our paradigm to detect voice-selective responses, as
preferential responses to voices compared with both
object sounds and scrambled voices were successfully
identified in bilateral superior temporal sulci in every
participant (data not shown) in both blind and sighted
groups (Figure 2A for group-level statistics).

This lack of reorganization for voices in the VOTC of
the blind group contrasts with recent evidence of cross-
modal face-selective regions in TVAs in congenitally deaf
individuals (Benetti et al., 2017), suggesting that compen-
satory brain plasticity in case of sensory deprivation fol-
lows principles of reorganization that are specific to the
deprived sense. Genetic influence, developmental trajec-
tory, susceptibility to plasticity, and the need for
behavioral compensation are all factors that may poten-
tially influence specific differences between the cross-
modal plasticity observed in blind and deaf individuals
(Frasnelli, Collignon, Voss, & Lepore, 2011).

Our findings suggest that different auditory functions
are not equally susceptible to be supported by the occip-
ital cortex in early visual deprivation. Similarly, we have
previously shown that the spatial processing of sounds
preferentially activates right dorsal regions of the occipi-
tal cortex in early blind participants, whereas pitch process-
ing of sounds does not (Collignon et al., 2011; Collignon,
Lassonde, Lepore, Bastien, & Veraart, 2007). We conclude
that preferential responses to voices over nonvocal audi-
tory objects are confined to the areas of the superior
temporal sulci in early blind participants. Nevertheless,
given that functional connectivity analyses identified
unique patterns of connectivity between the left TVA and
the right fusiform gyrus in the blind group (Figure 2D, a),
it appears that early visual deprivation affects these regions
at the network level. This, however, does not exclude the
possibility that the VOTC supports identification of audi-
tory objects in general—vocal and nonvocal—in the blind
group. For instance, in a recent fMRI study, Hölig et al.
(2014) reported a voice (speaker) congruency effect in
the right anterior fusiform gyrus of congenitally blind
participants, such that this region may have reorganized
to support person identification through the auditory
modality in case of early visual deprivation (Hölig et al.,
2014). However, the absence of another category of
sounds prevents from concluding that this effect rep-
resents a categorical preference for voices, because a
similar congruency effect could have been observed in
the same region for other nonvocal sounds. In our study,
selective responses to voices over scrambled voices were

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found in bilateral fusiform gyri of the blind group (Fig-
ure 5), about 3 cm more posteriorly than the region re-
ported by Hölig et al. (2014). However, responses in
these regions were also significantly larger for object
sounds compared with their scrambled counterpart and,
if anything, significantly larger for object sounds than for
voices. Future studies should further investigate whether
tasks involving the extraction of speaker’s identity from
voices triggers enhanced fusiform activations in early blind
participants when compared with other type of vocal and
nonvocal processing. This may relate to the suggestion
that a specific link exists between the facial and vocal neural
networks for speaker’s identity recognition (von Kriegstein
et al., 2005) and that sensory deprivation could trigger
functionally selective recruitment of the deprived system
through the remaining senses (Benetti et al., 2017; Hölig
et al., 2014).

Similar conclusions about a lack of cross-modal re-
organization of the face processing system in early blind
participants arise from a previous study that investigated
patterns of response elicited during tactile exploration
of face masks and man-made objects in VOTC (Pietrini
et al., 2004; see also Goyal, Hansen, & Blakemore, 2006).
Category-related patterns of response in VOTC were
found in sighted and blind participants for man-made
objects (shoes and bottles), but not for face masks (Pietrini
et al., 2004). Moreover, in the sighted group, category-
related patterns correlated across the visual and the tactile
modality for man-made objects, but not for faces. On the
basis of these observations, the authors concluded that,
although objects’ representations might be supramodal
in the VOTC, face representations are specific to vision.
Similarly, more recent studies reported overlapping re-
sponses to names of nonliving objects in the VOTC of
blind and sighted participants (He et al., 2013; Peelen
et al., 2013), whereas category-related responses to
animals in the VOTC were only observed in the sighted
group and only with visually presented material (He
et al., 2013). It has thus been proposed that selectivity
for nonliving stimuli is multimodal and independent of
visual experience whereas selectivity for living items, par-
ticularly in the lateral fusiform gyrus, is driven by visual
stimulation only (Bi et al., 2016). In this study, the lack of
categorical responses to voices combined with preferen-
tial responses to objects’ sound in VOTC of the blind
and sighted groups are in agreement with this theoretical
framework. These findings also suggest that regions sup-
porting the representation of faces in the sighted indi-
viduals’ brain do not transfer their preferential tuning to
human voices in early blind participants.

This lack of plasticity of the face recognition system is
in line with the high degree of specialization (domain
specificity or modularity) of this system in typically devel-
oped individuals. Studies on the ontogeny of face recog-
nition demonstrate impressive face recognition skills in
newborns within a few days of birth (Johnson, Dziurawiec,
Ellis, & Morton, 1991) and in monkeys raised without any

exposure to faces (Sugita, 2008). A recent study even
showed a visual preference in response to face-like stimu-
lation in human fetuses (Reid et al., 2017). Moreover,
categorical neural responses to faces embedded among
various nonface objects were recently identified in 4-month-
old babies (de Heering & Rossion, 2015). In the nonhuman
primate brain, face-responsive areas contain neurons that
respond selectively to faces (Tsao, Freiwald, Tootell, &
Livingstone, 2006; Desimone, 1991; Gross, Rocha-Miranda,
& Bender, 1972), and these areas have been demonstrated
to be strongly interconnected and isolated from the rest of
the visual recognition system (Moeller, Freiwald, & Tsao,
2008). Together, these characteristics of the face recogni-
tion system could come at the expense of generalization
(to other domains) and plasticity. Some researchers have
proposed that the development of face recognition may
be under high genetic control (Kanwisher, 2010). This
assumption is supported by studies on families with hered-
itary prosopagnosia (Grüter, Grüter, & Carbon, 2008;
Schmalzl, Palermo, & Coltheart, 2008; Duchaine, Germine,
& Nakayama, 2007) and performance of monozigotic rela-
tive to dizigotic twins on a face memory task (Wilmer et al.,
2010). In addition, Polk, Park, Smith, and Park (2007) found
that genetics may play a larger role on neural activity pat-
terns evoked by faces (Polk et al., 2007) compared with the
ones evoked by written pseudowords (Park, Park, & Polk,
2012; Polk et al., 2007; but see Pinel et al., 2014). Hence,
different functional areas in the cortex may result from dif-
ferent neurodevelopmental mechanisms (Kanwisher,
2010). For example, it could be that the selectivity for
word strings of the visual word form area emerges through
learning-dependent mechanisms (Dehaene et al., 2010;
He, Liu, Jiang, Chen, & Gong, 2009) whereas selectivity
for faces in the FFA arises because “the specific instruc-
tions for constructing the critical circuits for face percep-
tion are in the genome” (Kanwisher, 2010). These
different developmental mechanisms for defining func-
tional areas might interact with sensory deprivation and
therefore influence and constrain the process of cross-
modal plasticity. In summary, the finding of cross-modal
categorical responses to objects but not voices in the
occipital cortex of early blind individuals suggests that
cross-modal compensation in the case of early visual dep-
rivation depends on the neural systems investigated and
on the neurodevelopmental mechanisms that underlie
the emergence of these systems.

Acknowledgments

This work was supported by the Canada Research Chair Program
(F. L.), the Canadian Institutes of Health Research (F. L.), the
Belgian National Fund for Scientific Research (G. D.), and a
European Research Council starting grant (MADVIS Grant 337573)
attributed to O. C.

Reprint requests should be sent to Olivier Collignon, Universite
catholique de Louvain, 10, Place du Cardinal Mercier, 1348
Louvain-La-Neuve, Belgium, or via e-mail: olivier.collignon@
uclouvain.be.

Dormal et al.

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