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RESEARCH ARTICLE
Auditory language comprehension among children and adolescents
with autism spectrum disorder: An ALE meta-analysis of fMRI
studies
Zihui Hua | Jun Hu | Huanke Zeng | Jiahui Li | Yibo Cao | Yiqun Gan
School of Psychological and Cognitive
Sciences & Beijing Key Laboratory of Behavior
and Mental Health, Peking University, Beijing,
China
Correspondence
Yiqun Gan, School of Psychological and
Cognitive Sciences, Peking University,
5 Yiheyuan Road, Beijing 100871, China.
Email: ygan@pku.edu.cn
Funding information
National Natural Science Foundation of China,
Grant/Award Number: 32171076; National
Social Science Fund of China, Grant/Award
Number: 20BSH139
Abstract
Difficulties in auditory language comprehension are common among children and
adolescents with autism spectrum disorder. However, findings regarding the
underlying neural mechanisms remain mixed, and few studies have systematically
explored the overall patterns of these findings. Therefore, this study aims to sys-
tematically review and meta-analyze the functional magnetic resonance imaging
evidence of neural activation patterns while engaging in auditory language com-
prehension tasks among children and adolescents with autism. Using activation
likelihood estimation, we conducted a series of meta-analyses to investigate neural
activation patterns during auditory language comprehension tasks compared to
baseline conditions in autism and non-autism groups and compared the activation
patterns of the groups, respectively. Eight studies were included in the within-
group analyses, and seven were included in the between-group analysis. The
within-group analyses revealed that the bilateral superior temporal gyrus was acti-
vated during auditory language comprehension tasks in both groups, whereas the
left superior frontal gyrus and dorsal medial prefrontal cortex were activated only
in the non-autism group. Furthermore, the between-group analysis showed that
children and adolescents with autism, compared to those without autism, showed
reduced activation in the right superior temporal gyrus, left middle temporal
gyrus, and insula, whereas the autism group did not show increased activation in
any of the regions relative to the non-autism group. Overall, these findings con-
tribute to our understanding of the potential neural mechanisms underlying diffi-
culties in auditory language comprehension in children and adolescents with
autism and provide practical implications for early screening and language-related
interventions for children and adolescents with autism.
Lay Summary
By synthesizing previous fMRI research findings, we compared brain activity of
children and adolescents with and without autism during auditory language com-
prehension. We found that certain brain regions were active in both groups, while
others were only active in non-autistic individuals. Furthermore, certain brain
areas were less active in the autism group. These findings contribute to our under-
standing of the challenges of children and adolescents with autism in comprehend-
ing spoken language.
KEYWORDS
ALE meta-analysis, auditory language comprehension, autism, children and adolescents, fMRI
Zihui Hua and Jun Hu contributed equally to this study.
Received: 29 July 2023 Accepted: 23 October 2023
DOI: 10.1002/aur.3055
© 2023 International Society for Autism Research and Wiley Periodicals LLC.
Autism Research. 2023;1–15. wileyonlinelibrary.com/journal/aur 1
INTRODUCTION
Autism is a neurodevelopmental condition characterized
by challenges in social communication and social interac-
tion as well as restricted, repetitive patterns of behavior,
interests, or activities (American Psychiatric
Association, 2013). The prevalence of autism has been
consistently rising worldwide, with one in every 36 chil-
dren aged 8 years having autism, according to data pub-
lished by the Centers for Disease Control and Prevention
in the United States (Maenner et al., 2023). Children and
adolescents with autism commonly manifest difficulties
in auditory language comprehension (i.e., verbal compre-
hension; Carlsson et al., 2013; Mody & Belliveau, 2013),
which refers to their ability to understand spoken lan-
guage (McDuffie, 2013). Given the crucial role of audi-
tory language comprehension skills in children’s
cognitive, social, emotional, and academic development,
impairments in verbal comprehension can significantly
interfere with the overall functioning and well-being of
children and adolescents with autism (Brignell
et al., 2018; Schlichting et al., 1995). From this perspec-
tive, exploring the mechanisms underlying auditory lan-
guage comprehension in children and adolescents with
autism has important implications for education and
interventions. Some studies using neuroimaging tech-
niques such as functional magnetic resonance imaging
(fMRI) have indicated the potential neural basis of audi-
tory language comprehension difficulties in autism
(e.g., Colich et al., 2012; Lai et al., 2012). However, the
findings remain mixed and few studies have systemati-
cally examined the overall patterns of these findings. The
present study seeks to bridge this gap by performing a
meta-analysis of fMRI studies on auditory language
comprehension among children and adolescents with
autism.
Verbal comprehension difficulties are one of the most
common co-occurring features of autism (Carlsson
et al., 2013) and have been consistently reported in chil-
dren and adolescents with autism in previous studies
employing parent-reported scales, standardized assess-
ments, and behavioral tasks (e.g., Chan et al., 2005;
Hudry et al., 2010). For example, children with autism
have shown lower performance than age-matched chil-
dren without autism on the Token Test, during which
they were asked to perform various verbal commands
(Chan et al., 2005). Caregivers of children with autism
have reported lower scores on the receptive subscale of
the MacArthur-Bates Communication Development
Inventory (MCDI) and the Vineland Adaptive Behavior
Scale (VABS) receptive subscale (Hudry et al., 2010)
compared to neurotypical age norms. Children and ado-
lescents with autism also obtained lower scores than their
age-matched peers without autism on the standardized
and norm-based Peabody Picture Vocabulary Test
(PPVT; Kover et al., 2013; Plesa Skwerer et al., 2015).
Despite rich evidence showing impaired auditory lan-
guage comprehension in children and adolescents with
autism compared with their peers without autism, tradi-
tional assessments of auditory language comprehension
could merely demonstrate the outcome of the complex
process of comprehending verbal information, and these
tasks were unable to identify the specific stage in which
their performance is impaired in that chain
(Norbury, 2017). Multiple alternative explanations exist
for their impaired performance in traditional auditory
language comprehension assessments, such as reduced
attention to auditory stimuli, poor instruction following,
delayed motor skills, and a lack of engagement in social
contexts. The lack of clarity regarding the specific under-
lying processes that lead to difficulties in auditory lan-
guage comprehension hinders the development of
interventions aimed at improving auditory language com-
prehension skills in children and adolescents with autism.
Therefore, more advanced methods are required to
explore the underlying mechanisms to facilitate targeted
and effective interventions.
Neuroimaging techniques, such as fMRI, serve as
important tools to investigate the underlying mechanisms
of auditory language comprehension difficulties in chil-
dren and adolescents with autism. Several fMRI studies
using tasks that involve listening to human speech during
wakefulness have revealed different patterns of brain acti-
vation in children and adolescents with autism compared
to their non-autism counterparts (e.g., Colich et al., 2012;
Karten & Hirsch, 2014; Lai et al., 2012), indicating the
potential neural basis of verbal comprehension difficul-
ties in autism. For example, Lai et al. (2012) have found
reduced activation in the left inferior frontal gyrus (IFG)
of children and adolescents with autism when listening to
pre-recorded parental speech, relative to an age-matched
comparison group. Similarly, Colich et al. (2012) have
found reduced overall activation in canonical language
regions, including the IFG, middle and superior temporal
gyri (MTG and STG), and supramarginal gyrus (SMG),
while processing auditory narratives in children and ado-
lescents with autism compared to their non-autism coun-
terparts. In addition to differences in positive blood
oxygen level-dependent (BOLD) responses, reduced inhi-
bition (i.e., negative BOLD responses) of multiple regions
such as the precuneus (PC) and inferior temporal gyrus
(ITG) were also revealed in children and adolescents with
autism compared to comparison groups during passive
listening and spoken narratives (Karten & Hirsch, 2014).
However, the findings of previous fMRI studies have
been mixed regarding the brain regions involved and how
they differ between autism and non-autism groups, and
the specific tasks used varied across these studies, render-
ing it necessary to systematically examine existing rele-
vant fMRI studies to determine a consistent pattern to
their findings. Previous systematic reviews of fMRI stud-
ies examining auditory/language-related processes in
2HUA ET AL.
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individuals with autism have included participants across
all age ranges (e.g., Herringshaw et al., 2016; Philip
et al., 2012; Tryfon et al., 2018). However, as childhood
and adolescence are critical periods for both language
development (Friedmann & Rusou, 2015) and autism
screening and interventions (Hyman et al., 2019), it is
necessary to specifically investigate auditory language
comprehension in individuals with autism within these
two developmental periods. Moreover, previous relevant
systematic reviews have included evidence from
non-speech-sound perception tasks, visual language pro-
cessing tasks, expressive language tasks, and tasks con-
ducted during natural sleep (e.g., Philip et al., 2012;
Tryfon et al., 2018), which fall outside the scope of com-
prehending auditory language information. To synthesize
findings on the process of auditory language comprehen-
sion specifically, it is necessary to ensure that evidence
from the tasks mentioned above is excluded. This step is
crucial to prevent the findings from being confounded by
other auditory/language-related cognitive processes.
Therefore, fMRI studies have revealed different pat-
terns of brain activation in individuals with autism com-
pared to those without autism during auditory language
comprehension tasks, suggesting a neural basis of audi-
tory language comprehension difficulties commonly man-
ifested in autism. However, the findings of fMRI studies
examining auditory language comprehension in autism
remain mixed, and few studies have synthesized these
findings, limiting the understanding of the underlying
mechanisms of the commonly revealed language
comprehension difficulties in individuals with autism. No
meta-analytic studies thus far have specifically examined
children and adolescents with autism regarding their neu-
ral activation patterns during auditory language compre-
hension, despite the crucial role played by the early
stages in language development. Furthermore, previous
relevant meta-analyses have included evidence of tasks
outside the scope of auditory language comprehension,
with no studies specifically focusing on this important
cognitive process. Therefore, the current study aims to
complement the previous work by conducting an activa-
tion likelihood estimation (ALE) meta-analysis of fMRI
studies using tasks involving the auditory language com-
prehension process in children and adolescents with
autism. Distinct from previous relevant meta-analyses,
evidence from tasks that did not involve comprehending
auditory language information (i.e., non-speech sound
perception tasks, expressive language tasks, and tasks
conducted during natural sleep) as well as tasks that
simultaneously presented visual language were excluded
so as to minimize confusion introduced by auditory/lan-
guage-related cognitive processes outside the scope of
the current study. Our meta-analysis aims to identify
(a) commonly activated brain regions involved in
auditory language comprehension in children and adoles-
cents with and without autism and (b) the differences in
brain activation patterns during auditory language
comprehension between children and adolescents with
and without autism. We expect both children and adoles-
cents with autism to exhibit brain activation in regions
related to receptive language processing, such as the STG
(H1). However, children and adolescents with autism
may show a reduced number or area of activated regions
compared with their non-autism counterparts (H2). We
also expect children and adolescents with autism to
exhibit reduced intensity of activation in commonly acti-
vated areas compared to their non-autism counter-
parts (H3).
METHOD
This meta-analysis was conducted between April and
May 2023 and was registered in the International Pro-
spective Register of Systematic Reviews (PROSPERO)
under the registration number CRD42023413187. A
comprehensive literature search was conducted based on
the Preferred Reporting Items for Systematic Reviews
and Meta-Analyses (PRISMA) 2020 statement (Page
et al., 2021). The studies included in this meta-analysis
used fMRI tasks involving comprehensible speech listen-
ing to examine the neural correlates of auditory language
comprehension in children and adolescents with and
without ASD.
Search strategy and inclusion criteria
We conducted a computerized literature search using the
following keyword combinations through PubMed, Web
of Science, Scopus, MEDLINE, and PsycINFO:
(1) “autis*”OR “Asperger*”OR “ASD,”AND
(2) “fMRI”OR “functional magnetic resonance imaging”
OR “BOLD”OR “Blood Oxygen Level-Dependent,”
AND (3) “children”OR “adolescent*”OR “infant”OR
“toddler”OR “preschooler,”AND (4) “language compre-
hension”OR “speech”OR “voice”OR “auditory.”
The inclusion criteria for studies used in this review
are as follows: (1) primary research studies published as
peer-reviewed articles in English with original data;
(2) task fMRI studies; (3) studies in which participants
received auditory language stimuli (i.e., speech or vocal
sound with meanings) during the scan while being awake
(they may or may not have received visual stimuli at the
same time, as long as the visual stimuli were not text);
(4) studies including a sample of individuals with autism
or individuals with high autism symptomology/broader
autism phenotype (BAP)/increased likelihood of autism;
(5) studies that include a non-autism comparison group
for comparison (e.g., a neurotypical group for whom neu-
rodevelopmental conditions have been ruled out);
(6) studies that reported coordinates for brain activation
or deactivation in the standard anatomical reference
space (Talairach/Tournoux; Montreal Neurological
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Institute [MNI]); (7) studies that used whole-brain-level
analysis to obtain activation results; (8) studies that are
not interventional clinical trials/treatment effects; and
(9) studies conducted on human participants under the
age of 18.
During the preliminary screening of the records we
obtained in the initial literature search, we identified six
systematic review articles. Although these records per se
were excluded in our meta-analysis, they could have
included relevant research articles that were omitted in our
initial search. We further examined these six systematic
review articles based on the following criteria: (1) the study
synthesized findings of fMRI studies of ASD and (2) the
study examined language-related functions of ASD. Three
relevant systematic review articles were identified
(Herringshaw et al., 2016; Philip et al., 2012; Tryfon
et al., 2018). For each review, we examined its summary
table of included studies, which listed relevant characteris-
tics of each study. Studies in which the mean age of partic-
ipants was above 18 were removed, resulting in a total of
32 studies identified from prior relevant reviews. These
32 studies were then merged into the full record list gener-
ated from the initial literature search (n=795) and under-
went duplication removal, initial screening, and eligibility
examination, as shown in Figure 1.
Five researchers were assigned to search five data-
bases, with each responsible for one database. Two of
them were additionally responsible for retrieving records
from previous relevant meta-analytic studies. The initial
set included 827 studies from the five databases and
relevant systematic review articles up to April 20, 2023.
Duplicate records were removed using EndNote X9 soft-
ware, leaving 292 records for screening. These records
were divided into five equal parts, with each researcher
responsible for one part. They independently reviewed
titles and abstracts and excluded records that failed to
meet the inclusion criteria, resulting in 166 remaining
records. These records were then equally divided into five
parts and assigned to five researchers for full-text assess-
ment of eligibility. In cases of uncertainty, discussions
were held among the five researchers to determine inclu-
sion or exclusion. For articles that were excluded, specific
reasons were stated in the Excel sheet. Finally, two pri-
mary researchers independently examined the remaining
full-text articles for inclusion. Again, disagreements were
addressed by discussion and if necessary, a psychological
expert was consulted.
Nine of 827 articles met the above inclusion criteria
(see Table 1), with eight of them included in the within-
group analyses and seven of them included in the
between-group analysis. The flowchart in Figure 1shows
the literature search and selection processes. We collated
and recorded the following details for each study: first
author, year of publication, experimental task, experi-
mental contrasts, number of participants, age range of
participants, gender ratio, toolbox for fMRI analysis,
and statistical threshold. Two researchers independently
extracted and coded information from the included litera-
ture. The other two researchers extracted the peak coor-
dinates under different conditions reported in the
FIGURE 1 Flowchart representing
the literature search process. n=number
of publications.
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TABLE 1 Complete list and relevant characteristics of whole-brain fMRI studies included in the ALE analyses.
First author
and year
Experiment Participants fMRI
Task Contrast(s) N
Age range/
mean (SD)
Autism sex
(M:F) Toolbox
Statistical
threshold
Colich et al.,
2012
Distinguish
speech
remarks in
cartoons
Ironic/sincere
scenarios
versus baseline
15 autistic,
15 non-
autistic
14.27 ± 2.5
(autistic),
13.15 ± 2.2
(non-
autistic)
13:2 FSL Cluster-level
corrected,
p< 0.05
Doyle-
Thomas
et al., 2013
Auditory/visual/
audiovisual
emotion
identification
Audiovisual versus
visual
18 autistic,
16 non-
autistic
14.94 ± 1.55
(autistic),
14.69 ± 1.70
(non-
autistic)
18:0 Brain
VoyagerQX
FDR
corrected,
p< 0.05
Hubbard
et al., 2012
Watch co-speech
gesture
videos
Speech versus no
speech
10 autistic,
10 non-
autistic
13 ± 3.2
(autistic),
12 ± 1.6
(non-
autistic)
10:0 SPM Voxel-wise
threshold
(t> 2.55,
p< 0.01),
cluster-level
corrected
(p< 0.05)
Leipold
et al.,
2023
Passive speech
stimulation
Neutral versus
environmental
sound, sad
versus neutral,
happy versus
neutral
22 autistic,
21 non-
autistic
10.73 ± 1.66
(autistic),
10.71 ± 1.38
(non-
autistic)
16:6 SPM Cluster
threshold
p< 0.005,
spatial
extent of 70
voxels,
FWE
corrected
(α≤0.05)
with Monte
Carlo
simulations
Wang et al.,
2007
Distinguish
speech
remarks in
cartoons
Sincere comments
versus ironic
tone
17 autistic,
18 non-
autistic
7–17 (autistic),
9–15 (non-
autistic)
17:0 SPM Cluster-level
threshold
(t> 2.57,
p< 0.05),
spatial
extent of
115 voxels
Lai et al.,
2012
Passive speech
stimulation
Speech versus
baseline
12 autistic,
12 non-
autistic
7.01–22.47
(autistic),
4.19–17.78
(non-
autistic)
10:2 FEAT Voxel-wise
threshold
(Z> 1.6,
p< 0.05),
cluster-level
corrected
(p< 0.05)
Wang et al.,
2006
Distinguish
speech
remarks in
cartoons
Event knowledge
+prosodic
cues versus
rest, event
knowledge only
versus rest,
prosodic cues
only versus rest
18 autistic,
18 non-
autistic
7.4–16.9
(autistic),
8.1–15.7
(non-
autistic)
18:0 SPM Voxel-wise
corrected
(p< 0.01),
cluster-level
corrected
(p< 0.05)
Groen et al.,
2010
Passive listening:
implicit
auditory
stimulus
paradigm
Speech versus
noise
16 autistic,
26 non-
autistic
15.3 ± 1.6
(autistic),
15.7 ± 1.7
(non-
autistic)
12:4 SPM Cluster-level
corrected,
p< 0.05
(Continues)
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included literature (autism and non-autism for the
within-group analysis, autism > non-autism and non-
autism > autism for the between-group analysis) for sub-
sequent ALE analysis. Any disagreements were resolved
through discussion with a third researcher.
As can be seen in Table 1, the nine included studies
include a variety of tasks from passive speech stimulation
to active processing of pragmatic features of spoken lan-
guage, such as irony. We combined evidence of these var-
ied tasks in our analysis based on the following two
rationales: First, although the tasks themselves varied in
their specific formats, they all tapped into common
underlying mechanisms involved in auditory language
comprehension as they all required participants to listen
to and understand speech stimuli. Similar approaches of
task inclusion can be seen in previous relevant meta-
analytic studies (Herringshaw et al., 2016; Philip
et al., 2012; Tryfon et al., 2018). Second, the inclusion of
a range of tasks can provide a more comprehensive view
of auditory language comprehension in children and ado-
lescents with autism and potentially add to ecological
validity, given the high complexity of real-life auditory
language input received by children and adolescents
(McMillan & Saffran, 2016). In the real-life process of
auditory language comprehension, children and adoles-
cents engage in a wide range of listening activities, from
passively listening to the TV news to actively decoding
complex social cues during social communications. In
laboratory settings, passive listening tasks may highlight
more basic and automatic aspects of the process
(Giordano et al., 2014), while active tasks involving pro-
cessing pragmatic features may emphasize higher-order
aspects (Colich et al., 2012; Tesink et al., 2009). Combin-
ing these varied tasks could potentially offer a more
holistic understanding of how children and adolescents
with autism process auditory language information in
real-life.
Data analysis
Meta-analyses were performed using the GingerALE
3.0.2 software (Eickhoff et al., 2009,2012; Turkeltaub
et al., 2011),andALEwasusedtoestimatethe
probability of the coactivation of various brain regions
in a given task state. After merging spatial probability
distributions, a “Modeling Activation (MA)”map was
created. Using the union of each MA map, we calcu-
lated the ALE value for each voxel in the brain. We
manually fed the peak coordinates of the autism and
non-autism groups for each study into GingerALE.
The coordinates of the Talairach space were converted
into MNI space using the GingerALE “convert foci”
tool. To examine the neural differences across a wide
range of auditory processing tasks, we first performed
a meta-analysis of peak coordinates in a list of partici-
pants’fMRI tasks for auditory language comprehen-
sion (see Table 1).
We conducted two separate meta-analyses of audi-
tory language comprehension tasks versus rest/
baseline for autism and non-autism groups. Further-
more, for the meta-analysis and validation of the
directions of differences between groups, we sepa-
rately calculated the coordinates under two compari-
son conditions: autism > non-autism and non-
autism > autism. Eight studies were included in the
within-group analyses, and seven were included in the
between-group analysis. To limit the occurrence of
false positives and artifactual results, a threshold
using 5000 permutations was used to estimate a
cluster-level family-wise error (cFWE) correction of
p<0.05usingacluster-formingthresholdof
p< 0.001 (Eickhoff et al., 2012,2016,2017). The
MRIcronGL software was used to visualize the ALE
maps (https://www.nitrc.org/projects/mricrogl/).
RESULTS
Within-group ALE clusters during auditory
language comprehension
For the within-group analysis of the autism group, one
article was excluded because it did not provide activation
coordinates for comparisons between task and baseline
conditions within the autism group (Leipold et al., 2023).
Thus, eight independent studies with a total of 121 partici-
pants with autism were included; these studies reported
TABLE 1 (Continued)
First author
and year
Experiment Participants fMRI
Task Contrast(s) N
Age range/
mean (SD)
Autism sex
(M:F) Toolbox
Statistical
threshold
Green et al.,
2018
Distinguish
speech
remarks in
cartoons
Instructions no
tactile versus
baseline
15 autistic,
16 non-
autistic
14.09 ± 2.70
(autistic),
14.97 ± 2.44
(non-
autistic)
11:4 FSL Cluster
corrected
threshold at
Z> 2.3,
p< 0.01
6HUA ET AL.
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contrasts between the auditory language comprehension
conditions and baseline conditions with 94 foci (see
Table 2). As shown in Table 2, the concurrently activated
regions were the bilateral STG (Left: ALE peak at MNI
(64, 34, 8), ALE value =0.018, volume =4528 mm
3
;
Right: ALE peak at MNI (60, 0, 6), ALE
value =0.014, volume =2000 mm
3
; Right: ALE peak at
MNI (64, 28, 10), ALE value =0.016, volume =
840 mm
3
; see Figure 2).
For the within-group analysis of the non-autism group,
the same article was excluded as it also did not provide acti-
vation coordinates for task versus baseline comparisons
within the non-autism group (Leipold et al., 2023).
Therefore, eight independent studies with a total of 131 par-
ticipants without autism were included; these studies reported
contrasts between the auditory language comprehension con-
ditions and baseline conditions with 132 foci (see Table 2).
AsshowninTable2, the concurrently activated regions were
the bilateral STG (Left: ALE peak at MNI (64, 28, 6),
ALE value =0.013, volume =1344 mm
3
;Right:ALEpeak
at MNI (46, 26, 8), ALE value =0.017,
volume =1168 mm
3
), the left superior frontal gyrus (SFG;
ALE peak at MNI (10, 58, 28), ALE value =0.018,
volume =1168 mm
3
), and the left dorsal medial prefrontal
cortex(dmPFC;ALEpeakatMNI(2,52,24),ALE
value =0.011, volume =1168 mm
3
;seeFigure2).
TABLE 2 ALE results: Significant peaks of activation across ALE meta-analyses.
Cluster
Peak voxel coordinates
Cluster size (mm
3
) Maximum Z-value ALE value Anatomical labelXYZ
Autistic (foci =94, k=8, n=122)
164 34 8 4528 5.19 0.018 STG, L (BA22)
52 20 4 5.11 0.017
54 28 2 4.72 0.015
58 12 2 4.48 0.014
26006 2000 4.37 0.014 STG, R (BA22)
54 82 4.26 0.013
60 18 0 3.90 0.012
36428 10 840 4.87 0.016 STG, R (BA41)
62 30 2 3.34 0.009 STG, R (BA22)
Non-autistic (foci =132, k=8, n=134)
164 28 6 1344 4.05 0.013 STG, L (BA22)
62 24 2 4.04 0.013
50 18 4 3.19 0.009
260 46 1272 5.71 0.022 STG, L (BA22)
34626 8 1168 4.77 0.017 STG, R (BA41)
46 36 2 3.27 0.009
410 58 28 1168 4.89 0.018 SFG, L (BA9)
2 52 24 3.58 0.011 dmPFC, L (BA9)
55412 0 1104 4.35 0.015 STG, R (BA22)
52 20 8 3.78 0.012
648 30 8 896 4.31 0.015 STG, L (BA41)
Non-autistic > autistic (foci =57, k=7, n=222)
15020 6 1344 5.63 0.021 STG, R (BA22)
54 28 2 4.57 0.015
256 34 0 888 4.13 0.013 MTG, L
46 30 2 3.83 0.011 Insula, L (BA22)
64 28 0 3.72 0.010 MTG, L
Autistic > non-autistic (foci =26, k=7, n=240)
No significant cluster
Note: ALE clusters were thresholded at p< 0.001 for a cluster forming at voxel level and p< 0.05 for FWE-corrected multiple comparisons. k=the number of studies;
n=the number of participants. Coordinates are in MNI space.
Abbreviations: dmPFC, dorsal medial prefrontal cortex; L, left hemisphere; MTG, middle temporal gyrus; R, right hemisphere; SFG, superior frontal gyrus; STG,
superior temporal gyrus.
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Between-group comparisons during auditory
language comprehension
In the meta-analyses for non-autism > autism compari-
sons, two articles were excluded because they did not pro-
vide activation coordinates for between-group
comparisons of the tasks that were relevant to our current
study, although they did provide between-group compari-
sons for other less relevant tasks (Green et al., 2018;
Groen et al., 2010). Ultimately, seven independent stud-
ies reporting contrasts between the autism group and
non-autism group were included (see Table 2). Specifi-
cally, the non-autism > autism contrast included 57 foci
and a total of 222 participants (112 with autism,
110 without autism), and the autism > non-autism con-
trast included 26 foci and a total of 240 participants
(116 with autism, 124 without autism). As shown in
Table 2, according to the results of the non-
autism > autism contrast, participants with autism
showed reduced activation in the right STG (ALE
peak at MNI (50, 20, 6), ALE value =0.021,
volume =1344 mm
3
), left MTG (ALE peak at MNI
(56, 34, 0), ALE value =0.013, volume =888 mm
3
),
and insula (ALE peak at MNI (46, 30, 2), ALE
value =0.011, volume =888 mm
3
;seeFigure3)when
compared with their counterparts without autism. How-
ever, according to the results of the autism > non-autism
contrast, the autism group did not show increased acti-
vation in any of the regions compared to the non-autism
group (foci =26, k=7, n=240).
DISCUSSION
This study examined the functional neural basis of audi-
tory language comprehension in children and adolescents
with and without autism using an ALE meta-analysis of
qualifying fMRI studies. The utilization of the ALE
method provides quantitative, spatially consistent, and
statistically rigorous integration of existing fMRI find-
ings. The study was prospectively registered and adhered
to the PRISMA 2020 statement (Page et al., 2021)to
ensure the transparency, quality, and reliability of our
meta-analysis. We conducted within-group analyses
between the auditory language comprehension condition
and the baseline condition for the autism and non-autism
groups and between-group comparisons of their activa-
tion patterns. Overall, both the autism and non-autism
groups showed brain activation during auditory language
comprehension in the bilateral STG; however, in the
non-autism group, the left SFG/dorsal medial frontal
cortex (dmPFC) was activated. Between-group compari-
sons revealed that the autism group displayed reduced
activation in the right STG, left MTG, and insula relative
FIGURE 3 Significant non-
autistic > autistic ALE results under
auditory language comprehension task
versus baseline. Cluster-level FWE-
corrected at p< 0.05 with a cluster-forming
threshold of p< 0.001 using 5000
permutations. Coordinates are in MNI
space.
FIGURE 2 Significant ALE results
under auditory language comprehension
task versus baseline for autistic and non-
autistic groups respectively. Cluster-level
FWE-corrected at p< 0.05 with a cluster-
forming threshold of p< 0.001 using 5000
permutations. Coordinates are in MNI
space.
8HUA ET AL.
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to the non-autism group in auditory language compre-
hension tasks, whereas no differences were found in the
reverse comparison.
In agreement with our first hypothesis, we found an
overlap in activation across participants with and without
autism in the bilateral STG. Our results are consistent
with findings from other ALE meta-analyses that found
largely overlapping patterns of language-related activa-
tion in autism and non-autism groups, particularly in the
bilateral STG (Tryfon et al., 2018). The STG is a region
of the brain located in the temporal lobe above the lateral
sulcus. It performs various functions related to hearing
and language processing, including recognizing complex
sounds, distinguishing language from other sounds, and
processing speech (Yi et al., 2019). More specifically, the
STG helps in processing auditory information, particu-
larly complex sounds such as music and speech. It sepa-
rates different frequencies and allows the identification of
discrete acoustic units, such as phonemes, in spoken
words (Zhang et al., 2016). The STG also plays a funda-
mental role in speech perception by analyzing the sounds
that make up speech (Ramos Nuñez et al., 2020). This
area recognizes the structure of speech units such as
words and syllables. Based on these two sensory pro-
cesses, the STG supports semantic processing, helps map
the meaning of linguistic input to concepts, and is
involved in understanding social information communi-
cated through speech, such as emotional tone
(Frühholz & Grandjean, 2012), sarcasm, and humor.
Thus, the overlap in bilateral STG activation across the
autism and non-autism groups suggests that auditory lan-
guage comprehension processing may rely on shared neu-
ral mechanisms.
Consistent with our second hypothesis, we found that
the non-autism group exhibited additional activation of
the left SFG/dmPFC during auditory language compre-
hension tasks. The SFG is part of the prefrontal cortex,
which is responsible for various essential functions such
as decision-making, working memory, and attention con-
trol (du Boisgueheneuc et al., 2006). Studies have shown
that the SFG plays a crucial role in executive functions
(Aron et al., 2003; Taylor et al., 2004), including plan-
ning, problem-solving, reasoning, and self-control. In
addition, the dmPFC is critically involved in social pro-
cessing, particularly in understanding and interpreting
others’intentions and emotions (Campbell et al., 2015;
Lewis et al., 2011; Mitchell, 2009); moreover, it plays a
special role in encoding key features of the structure of
the social environment (Klein-Flügge et al., 2022). The
activation of this brain region may be because some stud-
ies (Groen et al., 2010; Wang et al., 2006) included social
interaction information in the auditory language compre-
hension task. In real-life scenarios, accurate interpreta-
tion of social information often plays a critical role in
understanding auditory language, as the same literal con-
tent can convey completely different meanings in differ-
ent social contexts. This empirical evidence shows that
children and adolescents with autism may have difficulty
mobilizing different cognitive functions to integrate pho-
nological comprehension and contextual cues to under-
stand communicative intentions.
In line with our third hypothesis, between-group com-
parisons revealed that children and adolescents with
autism showed reduced activation of the right STG, left
MTG, and insula during auditory language comprehen-
sion tasks compared with their counterparts without
autism. Reduced activation in the right STG in individ-
uals with autism relative to their counterparts without
autism was also found in an ALE meta-analysis of a simi-
lar topic conducted by Philip et al. (2012), which included
all types of auditory and language fMRI tasks, and
another similar ALE meta-analysis conducted by Her-
ringshaw et al. (2016), which included participants of all
ages with autism. Notably, these two meta-analytic stud-
ies also found reduced activation in the left STG of indi-
viduals with autism compared to individuals without
autism, while in our study, no significant group difference
in the activation of the left STG was found. This could be
because our study focused specifically on auditory lan-
guage comprehension and children/adolescents with
autism.
While both the left and right STG have been sug-
gested to be important in speech perception (Price, 2012),
previous studies have indicated their different roles. Spe-
cifically, whereas the left STG is more responsible for the
phonetic and phonological processing of speech, the right
STG is more involved in the acoustic analysis of speech
and voice sensitivity (Lattner et al., 2005; Obleser
et al., 2008; Turkeltaub & Coslett, 2010; Zhang
et al., 2010). The right STG is, therefore, more sensitive
to prosody, which refers to the variations in tone, pitch,
and rhythm in speech that convey the emotional state
and intentions of the speaker (Alba-Ferrara et al., 2012;
Turkeltaub & Coslett, 2010; Zhang et al., 2017). In our
study, children and adolescents with autism showed no
significant differences in the activation of the left STG
and showed reduced activation of the right STG. These
results indicate that children and adolescents with autism
might be able to process phonetic and phonological infor-
mation in speech as their counterparts without autism do,
but they might experience difficulties in processing the
acoustic properties of speech and understanding the emo-
tive information and intentions conveyed through speech,
which consequently leads to difficulties in comprehending
auditory language.
The between-group ALE analysis also revealed
reduced activation of the left MTG in children and ado-
lescents with autism relative to their counterparts without
autism. Although a group difference in the activation of
the left MTG has not been indicated in previous
between-group ALE analyses of language processing in
individuals with autism (Herringshaw et al., 2016; Philip
et al., 2012; Tryfon et al., 2018), this may be attributed to
our more specific focus on auditory language
HUA ET AL.9
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comprehension and children/adolescents with autism. In
addition, the qualitative analysis of Tryfon et al. (2018)
found additional activation in the left MTG in the non-
autism group compared to the autism group, indicating a
potential association between this brain region and audi-
tory language processing challenges in autism. The left
MTG was found to function as a focal point and play a
central role in the language comprehension network with
extensive structural and functional connectivity, and
damage to this region leads to severe and persistent lan-
guage comprehension impairments (Turken &
Dronkers, 2011). Specifically, the left MTG is involved in
the ventral pathway that is responsible for mapping
sounds onto meaning (Hickok & Poeppel, 2007). The
hypoactivation of the left MTG in children and adoles-
cents with autism might suggest difficulties in coordinat-
ing and integrating the substages required to reach
language comprehension, such as connecting auditory
information with semantic meaning.
Furthermore, we found reduced insula activation in
children and adolescents with autism compared to their
counterparts without autism, which is consistent with the
findings of Herringshaw et al. (2016). The insula plays a
diverse range of roles in humans, encompassing sensory
and emotional processing as well as higher-level cognitive
functions (Uddin et al., 2017). Specifically, the insula is
involved in sound detection, and damage to this area
leads to central auditory deficits or abnormalities (Uddin
et al., 2017). The insula also plays a critical role in emo-
tional stimulus processing (Pugnaghi et al., 2011; Tayah
et al., 2013). Thus, our findings further suggest that the
auditory language comprehension difficulties exhibited
by children and adolescents with autism may also corre-
late with impaired perception of the acoustic properties
of speech and the emotive content conveyed through
speech.
We did not find regions of increased activation in the
autism group compared to the non-autism group, which
is consistent with the findings of similar ALE
meta-analyses conducted by Herringshaw et al. (2016)
and Tryfon et al. (2018), both of which examined audi-
tory language tasks in individuals with autism. Although
the ALE meta-analysis conducted by Philip et al. (2012)
has found relative overactivation in the right precentral
gyrus in children and adolescents with autism, it should
be noted that their analysis also included studies examin-
ing non-speech sound perception and visual language
processing, which were outside the scope of the current
meta-analysis.
The current study complements previous research on
auditory language processing in children with autism and
contributes to a better understanding of the possible neu-
ral mechanisms underlying the commonly exhibited diffi-
culties in auditory language comprehension in children
and adolescents with autism. Compared to existing rele-
vant meta-analyses, our study is unique in its focus on
child and adolescent participants. By narrowing down
the age range to this critical period for language develop-
ment and autism intervention, our findings are better
positioned to offer insights that can inform early identifi-
cation of autism as well as targeted intervention strate-
gies. Our study also uniquely focused on the process of
auditory language comprehension by excluding tasks
related to non-speech sound perception, expressive lan-
guage, tasks during natural sleep, and visual language
processing. This approach allowed for a more targeted
analysis of this critical aspect of language processing in
autism. The results of this study have several theoretical
implications. First, our within-group findings align with
prior research, particularly Herringshaw et al. (2016) and
Tryfon et al. (2018), in underscoring the pivotal role of
the bilateral STG in auditory language comprehension
across both children and adolescents with and without
autism. This consistency in neural activation patterns
across groups implies a shared neurobiological basis for
auditory language comprehension. Second, our within-
group results reveal a less distributed pattern of brain
activation during auditory language comprehension, as
indicated by fewer activated brain regions during speech
processing, suggesting that the development of the neural
network responsible for auditory language processing
may be delayed in children and adolescents with autism.
Third, the results of the between-group comparisons
highlight three potential underlying mechanisms for the
auditory language comprehension challenges exhibited
by children and adolescents with autism: (a) the presence
of abnormalities in early acoustic or auditory processing
of speech in children and adolescents with autism may
impede their ability to extract basic linguistic information
from auditory language stimuli, (b) difficulties in under-
standing the emotional information and intentions con-
veyed through speech (i.e., prosody) could contribute to
the challenges in interpreting nuanced social cues in audi-
tory language, and (c) challenges in coordinating and
integrating the individual stages needed to achieve
auditory language comprehension, such as connecting
auditory information with semantic meanings, may hin-
der their development of auditory language comprehen-
sion skills (see Table 3for a summary of the main
findings and theoretical implications).
Furthermore, the findings of this study have several
practical implications. First, the early identification and
prognosis prediction of autism have long been challeng-
ing due to the lack of objective methods (Lai et al., 2020).
Recent studies have investigated the possibility of using
neuroimaging methods, such as fMRI, to assist in these
processes (Haweel et al., 2021). As several brain regions
were found in our study to display distinct activation pat-
terns between children/adolescents with and those with-
out autism during auditory language comprehension
tasks, future clinical studies should explore the potential
of these brain regions to serve as biomarkers of autism
and its co-occurring language difficulties to facilitate
early identification and prognosis prediction. Second, the
10 HUA ET AL.
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TABLE 3 Summary of main findings and theoretical implications.
Significant clusters Brain regions Main functions Theoretical implications
Autism Bilateral STG Hearing and language
processing
Shared neural mechanisms of
auditory language comprehension in
autistic and non-autistic
children/adolescents
Non-autism
Bilateral STG
Left SFG/dmPFC Executive functions &
social processing
Autistic children/adolescents may
have difficulty mobilizing executive
functions to integrate phonological
comprehension and contextual cues.
Non-autism >
Autism
Right STG
Acoustic analysis of
speech and voice
sensitivity; prosody
perception
Autistic children/adolescents might
have difficulty processing the
acoustic properties of speech and
understanding the emotions and
intentions conveyed through speech
Left insula Sound detection &
emotional processing
Left MTG
Focal point of the
language comprehension
network; mapping sounds
onto meaning
Autistic children/adolescents might
have difficulty coordinating and
integrating the substages required to
reach language comprehension
Bila
t
e
ra
l
B
il
a
t
e
ra
l
Le
f
t SFG
ff
R
ight S
T
Le
f
t
ff
i
ns
u
Le
f
t MTG
f
f
Abbreviations: dmPFC, dorsal medial prefrontal cortex; MTG, middle temporal gyrus; SFG, superior frontal gyrus; STG, superior temporal gyrus.
HUA ET AL.11
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findings of our study shed light on the potential underly-
ing mechanisms of auditory language comprehension dif-
ficulties in children and adolescents with autism, which
provide implications for interventions focusing on lan-
guage difficulties in this population that might be exam-
ined in future clinical studies. Specifically, given the
highly important role of the STG in hearing and lan-
guage processing (Yi et al., 2019), speech perception
(Ramos Nuñez et al., 2020), and semantic processing
(Frühholz & Grandjean, 2012) and the role of music
intervention in promoting social communication in chil-
dren with autism (Sharda et al., 2018), the increasing acti-
vation of STG regions by song and rhythm training
might be considered a potential treatment target for
children and adolescents with autism. Similarly, the acti-
vation of the SFG/dmPFC regions, for example, via
high-frequency transcranial magnetic stimulation (Burke
et al., 2019), may improve patients’social processing
involved in understanding and interpreting the present
mentation of oneself or others.
Further interpretation of our results requires caution
given the following limitations of our meta-analysis.
First, the number of experiments included in our analysis
failed to reach the recommended number for ALE analy-
sis (n=17–20; Eickhoff et al., 2016; Müller et al., 2018).
The limited number of experiments might have led us to
miss small or medium effect size differences between the
autism and non-autism groups. The limited number of
articles included in our study might be because conduct-
ing fMRI studies in awake children/adolescents with
autism has been challenging (Jassim et al., 2021; Lee
et al., 2017) given the susceptibility of this technique to
movement-related artifacts (Patriquin et al., 2013; Tyszka
et al., 2013). Due to the potential sensory discomfort
fMRI exams might induce (e.g., exposure to acoustic
noise; McJury & Shellock, 2000), some participants may
have difficulty remaining still in the scanner, leading to
the removal of their data during subsequent analysis.
Therefore, these technical limitations could have resulted
in a sampling bias in fMRI studies on children/
adolescents with autism, compromising the representa-
tiveness of our findings. For example, children with
autism who have high sensitivity to auditory stimuli
might possess unique neural patterns while processing
auditory language; however, these children might be
underrepresented in fMRI studies of children with autism
due to lower tolerance to scanner noise and a higher like-
lihood of their data being removed. Future studies could
investigate strategies to assist children with autism in
acclimating to the experimental environment and employ
a broader range of research methods to mitigate potential
biases stemming from the technical limitations of fMRI.
Second, our analysis included mixed evidence from both
children and adolescents, exposing the analysis to the
threat of nonlinear developmental trajectories. Nonlinear
trajectories have been frequently reported in studies
investigating the development of brain structures in
typically developing individuals (Kilford & Blakemore,
2020; Tamnes & Mills, 2020). While research on the
developmental trajectories of brain structure and
function in autism remain limited, certain studies have
indicated age-based differences in language-related chal-
lenges associated with autism (e.g., Baxter et al., 2019;
Tang et al., 2023). Given the early onset of autism, it is
anticipated that this condition closely interacts with neu-
ral development and exhibit distinct trajectories as indi-
viduals age. Therefore, incorporating mixed evidence
from both children and adolescents in our meta-analysis
might obscure age-related variations in neural patterns of
auditory language comprehension associated with
autism, hindering a more comprehensive understanding
of neural mechanisms and the development of targeted
interventions. Additional studies that recruit participants
with autism within a narrower age range are necessary to
facilitate subgroup analyses and the identification of
potential age-related trends or variations in future sys-
tematic reviews. Finally, it is essential to consider the
potential impact of inter-subject variance on our findings.
The heterogeneous nature of autism includes various sub-
types and a wide range of symptom profiles (Masi
et al., 2017). These differences in symptom severity, cog-
nitive functioning, and sensory sensitivities can lead to
diverse neural responses during auditory language com-
prehension tasks. This variability can confound the inter-
pretation of group differences in studies involving
individuals with autism (Heller Murray et al., 2022).
Future research should aim to explore various subtypes
of autism and individual differences more comprehen-
sively, considering factors such as age, cognitive abilities,
and sensory sensitivities. Doing so could help gain a dee-
per insight into the neural mechanisms underlying audi-
tory language comprehension in children and adolescents
with autism and tailor interventions to individual needs.
In conclusion, we conducted an ALE meta-analysis of
fMRI studies that investigated auditory language com-
prehension in children and adolescents with autism. Our
results revealed common brain activation in the bilateral
STG in children and adolescents with and without autism
as well as additional activation of the left SFG and
dmPFC in the group without autism during auditory lan-
guage comprehension tasks. Furthermore, we found
reduced activation in the right STG, left MTG, and
insula in the group with autism compared to the group
without autism. Our findings contribute to a better
understanding of the potential neural mechanisms under-
lying difficulties in auditory language comprehension in
children and adolescents with autism and provide practi-
cal implications for early screening and language-related
interventions for these children and adolescents.
FUNDING INFORMATION
This study is supported by National Natural Science
Foundation of China (32171076) and National Social
Science Fund of China (20BSH139).
12 HUA ET AL.
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CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are avail-
able from the corresponding author upon reasonable
request.
ETHICS STATEMENT
Not applicable.
ORCID
Zihui Hua https://orcid.org/0000-0003-1835-5443
Jun Hu https://orcid.org/0000-0001-6450-6754
Yiqun Gan https://orcid.org/0000-0001-9886-6862
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How to cite this article: Hua, Z., Hu, J., Zeng, H.,
Li, J., Cao, Y., & Gan, Y. (2023). Auditory
language comprehension among children and
adolescents with autism spectrum disorder: An
ALE meta-analysis of fMRI studies. Autism
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