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Running Head: Hearing one’s own name in children with autism
Title: Intact neural responding to hearing one’s own name in
children with autism
Author information
Rachida El Kaddouri¹, Annabel D. Nijhof¹, Marcel Brass²,³, Jan R. Wiersema¹
¹ = Department of Experimental Clinical and Health Psychology, Ghent University, Belgium
² = Department of Experimental Psychology, Ghent University, Belgium
³ = Department of Psychology & Berlin School of Mind and Brain & Cluster, Humboldt-Universität
zu Berlin, Germany
Acknowledgments
Rachida El Kaddouri was supported by the Special Research Fund of Ghent University (project
number BOF.DOC.2015.0096.01). Annabel D. Nijhof was supported by an FWO fellowship (grant
number FWO19/PDJ/025). There are no conflicts of interest associated with this publication.
2
Abstract
Purpose
Diminished responding to one’s own name is one of the strongest and earliest predictors of
autism. However, research on the neural correlates of this response in autism is scarce. Here
we investigate neural responses to hearing the own name in school-aged children with and
without autism.
Methods
Thirty-four children with autism and 33 without autism (ages 7-13) were presented with three
categories of names (own name, close other’s name and unknown other name) as task-
irrelevant deviant stimuli in an auditory oddball paradigm, while EEG was recorded.
Results
In line with previous findings, parietal P3 amplitudes for the own name were enhanced
compared with a close other’s name. Older children showed a stronger self-specific effect than
younger children. However, this self-preferential effect was not different between groups,
despite the fact that parents of children with autism reported significantly less own-name
responsiveness in daily life. Neither the N1 component or SON negativity showed self-specific
effects.
Conclusion
In school-aged children, only the parietal P3 component, and not the N1 or SON negativity,
appears to be enhanced for the own name as compared to a close other’s name. Age seems to
have an effect on the own name modulation of the P3 amplitude, which may explain the
relatively small overall effect size. Against expectations, groups did not differ on this self-
specific effect. Further research into neural and behavioral responses to hearing one’s own
name in autism, across different age groups, is warranted.
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INTRODUCTION
There has been extensive research on how people respond to their own name, as it is a
unique stimulus that strongly relates to the self, but also has an ostensive nature. Names are
among the most salient social cues (Hatch et al., 2021; Miller et al., 2017), and particularly the
own name has a preferential status that is characterized by attention-grabbing features. Self-
preferential effects are particularly strong in contexts without competing auditory/visual
information; so strong in fact, that even in an altered state of consciousness, such as during
sleep, minimally conscious state or vegetative state, individuals still show a neural response to
their own name (Di et al., 2007; Fischer et al., 2008; Perrin et al., 1999, 2006). Typically
developing 5-month-old infants already have the capacity to separate speech from different
speakers and recognize the sound pattern of their own name in a noisy context (Mandel et al.,
1995; Newman, 2005; Parise et al., 2010; Zhang et al., 2018), and at the age of 6 months,
infants start to recognize their own name as a socially meaningful cue to guide their attention
(Parise et al., 2010; Zhang et al., 2018).
Being able to detect social signals directly related to the self is crucial in socio-
communicative development, as it plays an important role in for example joint attention,
initiating and maintaining social interaction, language learning and the development of the self
(Key et al., 2016; Nowicka et al., 2016). Furthermore, it has been argued that also later in life,
a bias in processing self-specific information leads to a stronger sense of self, which in turn is
assumed to help one build more accurate models of the social world (Mitchell, 2009; Nijhof &
Bird, 2019). For this reason, the reaction to the own name has been investigated in populations
with socio-communicative deficits, such as individuals with autism spectrum disorder
(henceforth: autism
1
) or with elevated likelihood for autism. Autism is a neurodevelopmental
1
We use an abbreviated version of the diagnostic term, and refer to a person with a diagnosis of autism
spectrum disorder, as a person with (a diagnosis of) autism. With this, we do not intend to take a stance
5
disorder characterized by qualitative difficulties in social interaction and communication, as
well as by restricted, repetitive patterns of behavior, interests and/or activities (American
Psychiatric Association, 2013). Early detection of autism allows for the implementation of
targeted and timely intervention, leading to better outcomes (Makrygianni & Reed, 2010;
Moore & Goodson, 2003). One of the strongest and earliest predictors of autism is a diminished
response to the own name (Baranek, 1999; Marschik et al., 2017; Miller et al., 2017; Nadig et
al., 2007; Werner et al., 2000; Zhang et al., 2018). This response has been investigated
experimentally (Imafuku et al., 2014; Mandel et al., 1995; Mandel-Emer & Jusczyk, 2003;
Miller et al., 2017; Nadig et al., 2007), as well as through retrospective studies examining home
videos (Baranek, 1999; Webb & Jones, 2009; Werner et al., 2000; Zhang et al., 2018) and
prospective studies (Miller et al., 2017; Nadig et al., 2007; Zhang et al., 2018; Zwaigenbaum
et al., 2005). However, a failure to respond to the own name is neither universal in, nor specific
to autism (Nadig et al., 2007; Zhang et al., 2018).
To better understand the cognitive processes underlying the hearing of one’s own name,
several studies have investigated the neural correlates associated with this, by looking at event-
related potentials (ERPs). The ERP component most reliably related to the response to the own
name, and to self-other distinction processes in general, is the parietal P3, also referred to as
parietal positivity (PP) or P3b (Berlad & Pratt, 1995; Cygan et al., 2014; Folmer & Yingling,
1997; Holeckova et al., 2006; Knyazev, 2013; Kotchoubey & Pavlov, 2017; Perrin et al., 1999;
Polich, 2007; Tacikowski et al., 2014; Tamura et al., 2016). It is associated with top-down
attention allocation and updating of stimulus representations in working memory (Polich,
2007). Although found and reported less consistently, some studies also report another ERP
component to be specifically influenced by the processing of a ‘subject’s own name’ (SON),
in the ongoing person-first versus identity-first debate, in which there is currently no consensus (De Laet et al.,
2023). We acknowledge and respect different language preferences to refer to a person with a diagnosis of
autism spectrum disorder.
6
called the SON negativity (Eichenlaub et al., 2012; Tateuchi et al., 2012, 2015; Thomas et al.,
2019). This component is characterized by an enhanced frontocentral negative deflection
following the P2. It is specifically found for the own name compared to other familiar or
unfamiliar names, and is considered to be an index of pre-attentive auditory detection of the
own name (Tateuchi et al., 2012, 2015; Thomas et al., 2019). Finally, some studies showed
modulation of the amplitude of the N1, an early negative component associated with early
sensory processing. However, findings suggest that this component is sensitive to familiarity
effects rather than to own-name processing specifically (Höller et al., 2011; Müller & Kutas,
1996; Nijhof et al., 2018). Neural responses have been found to be subject to maturation, which
affects their timing and amplitude (Overbye et al., 2018; van Dinteren et al., 2014), but
depending on paradigm characteristics, P3, SON and N1 components have been observed in
adults as well as in children (Davies et al., 2010).
To the best of our knowledge, there are only four studies that investigated ERP
correlates to hearing one’s own name in individuals with autism or children at elevated
likelihood of autism (Arslan et al., 2020; Nijhof et al., 2018; Schwartz et al., 2020; Thomas et
al., 2019). Firstly, Arslan and colleagues (2020) presented the participants’ own name and an
unfamiliar name to infants with low and elevated likelihood for autism at the age of 10 and 14
months. The elevated-likelihood group exhibited attenuated frontal positive-going activity in
response to their own name as compared to the unfamiliar name, and as compared to the low-
risk group, at the age of 14 months (Arslan et al., 2020). A second study was conducted by
Thomas and colleagues (2019) in children between 3 and 5 years old with and without a
diagnosis of autism. Their experiment consisted of six different sound stimuli: the own name
spoken by the parent and by the researcher, a nonsense name spoken by the parent and by the
researcher, and a familiar and unfamiliar music fragment. They concluded that the SON
negative-going component exists in 3- to 5-year-old children across both groups, providing
7
evidence that children orient their attention to and selectively process their own name,
regardless of the speaker. Although no significant effect of name or interaction between name
and group was found on the N1, in the (larger) neurotypical group, N1 amplitude for nonsense
names was marginally greater than for the own name. This suggests that typically, own versus
unknown names may already be processed differently at the early stages of auditory processing.
A third study investigated the neural correlates of hearing one’s own name in adults with and
without autism (Nijhof et al., 2018). An auditory oddball paradigm was used, comparing the
neural response to the own name, a familiar name and an unknown name. An enhancement of
the parietal P3 (referred to as late parietal positivity or PP in their study) was found specifically
for the own name in the neurotypical group, while this was absent in the autism group (Nijhof
et al., 2018). Further, enhanced N1 amplitudes where found for both the own and familiar name
as compared to the unknown name, reflecting a familiarity effect, which did not differ between
groups. Finally, a study by Schwartz and colleagues (2020) compared minimally/low verbal
and verbal adolescents with and without autism when hearing their own versus unknown other
names, both in a quiet and in a multispeaker setting. In the quiet setting, neurotypical
adolescents showed stronger early frontal negative responses to their own than the unknown
name. Although neither autism group showed a significant difference in neural response
between the two names, the interaction between condition and group was not significant. In the
multispeaker setting, however, the difference between own and unknown name was
significantly larger in the neurotypical than the minimally/low verbal group with autism. Late
parietal responses, although not significantly different between groups in either setting, were
associated with auditory filtering abilities.
In short, the current ERP literature on own-name processing in relation to autism is
mixed. Although own-name effects are reported, findings of group differences in these effects
are less consistent. Not all studies investigate and report all relevant components (P3, SON,
8
N1), most sample sizes are small, and highly varying age groups have been studied, making it
harder to generalize across studies. In addition, to the best of our knowledge, the neural
responses to hearing one’s own name have not yet been studied in middle childhood (school-
aged children of 7 to 13 years old) in relation to autism. Important socio-communicative,
cognitive and self-related development take place around this age (Harter, 1999; McHale et al.,
2003), with the self becoming more interpersonally grounded around age 8-10 (Harter, 2006).
In addition, the auditory system further matures (Ponton et al., 2000), which may affect
findings for specific components.
Given findings of a diminished behavioral response to the own name in young children,
and diminished neural responses in adults with autism (Nijhof et al., 2018; Schwartz et al.,
2020), research on this topic in children in this transitional developmental period will further
elucidate how self-related processing differs in autism across the lifespan. Only two studies
report results from school-aged typically developing children (Bathelt et al., 2017; Key et al.,
2016). Key and colleagues (2016) studied children between 4 and 12 years old and found an
enhanced parietal P3 response to own and close other names (with no difference in amplitude
between these conditions), but not to stranger names. These results indicate that in contrast to
studies in adults, where a self-specific effect was found for the parietal P3 (Nijhof et al., 2018;
Tateuchi et al., 2012), in school-aged children the parietal P3 seems to differentiate between
familiar and unfamiliar names (familiarity effect), but not between their own name and the
name of a close other (Key et al., 2016). In the study of Bathelt and colleagues (2017), children
between 8 and 13 years old (with and without congenital visual impairment) were tested to
investigate neural differences when hearing ‘Hey’ followed by their own name or an unfamiliar
name. The main finding was that children in the typically-sighted group showed larger SON
negativity amplitudes for the own name stimuli, while this was not observed in the group of
children with visual impairment. No P3 effects were reported. A final limitation of both this
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study, and of the two studies in children with or at elevated likelihood of autism (Arslan et al.,
2020; Thomas et al., 2019), is that no familiar other name was included. Thus, these studies do
not allow to distinguish self-specific effects from general effects of familiarity (Amodeo et al.,
2023), while this contrast has been found to be crucial in previous self-processing studies in
autism (Amodeo et al., 2024; Cygan et al., 2014; Nijhof et al., 2018, 2024).
Taking into account the lack of convergence across studies and the mentioned
limitations, together with the lack of a study on middle childhood in autism, the aim of the
current study was to investigate all three reported ERP correlates of hearing the own name (P3,
SON, N1) in a sample of children between 7 and 13 years old with and without autism. We
decided to use an auditory oddball paradigm similar to the one employed by Nijhof and
colleagues (2018), in which names are task-irrelevant, and in which the own name, a familiar
name and an unknown name are presented, allowing to investigate both self-specific and
familiarity effects. Based on their findings, our main hypothesis was to find an enhancement
of the parietal P3 component for the own name compared to the other names in typically
developing children, and this effect to be diminished in the autism group. Note however that
Key and colleagues (2016), although within another paradigm, did not find a self-specific effect
for the P3 in children aged 4 to 12, but rather a familiarity effect. Furthermore, we tested
whether we could confirm a familiarity effect on the N1 amplitude, while we did not expect
groups to differ on this (Nijhof et al., 2018). Moreover, we investigated the presence of the
SON negativity for the own name (Thomas et al., 2019), exploring whether this effect is self-
specific by including a close-other name, while also investigating potential group differences.
Further, we also included parent reports on their child’s responsiveness to hearing their own
name in daily life. This allows associating the neural correlates of own-name processing with
behavioral indices. This was also done in the study by Schwartz and colleagues (2020), who
used an auditory filtering subscale and found that this positively correlated with the amplitude
10
of the late positive response to the own name. Additionally, parents reported on their child’s
autism characteristics, again allowing us to explore potential associations with neural
correlates.
METHODS
Participants
In this study, 35 children with autism (22 boys; Mage = 10.64; SD = 1,89) and 35 children
without autism (21 boys; Mage = 10.24; SD = 1.49) between 7 and 13 years old participated.
The children were recruited via social media, paper announcements and rehabilitation centers,
and some already participated in earlier studies of our research group. Inclusion criteria for
both groups were an age between 7 and 13 years old, and an IQ score of 80 or higher. Children
in the typically-developing (TD) group were excluded if they reported a history of neurological
or psychiatric disorders, or had any siblings or parents with autism. Further, they would be
excluded if they scored 15 or more on the Social Communication Questionnaire (SCQ; Rutter
et al., 2003), but there were no scores higher than 14. In the autism group, four children had
comorbid Attention-Deficit/Hyperactivity Disorder (ADHD), four children had a learning
disability (dyslexia or dyscalculia) and four children had comorbid Developmental
Coordination Disorder (DCD). All children had normal or corrected-to-normal vision. The
children and their parents all gave written informed consent prior to the study and received
financial compensation for their participation. This study was approved by the local ethics
committee of the Faculty of Psychology and Educational Sciences of Ghent University.
Children in the autism group were included on the basis of a DSM-IV-based autism-
related diagnosis, or a diagnosis of Autism Spectrum Disorder (DSM-5, American Psychiatric
Association (APA), 2013), given by a multidisciplinary team prior to participation. This
diagnosis was verified by a trained psychologist using Module 3 of the Autism Diagnostic
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Observation Schedule (ADOS-2; Lord et al., 2012). The ADOS-2 is a semi-structured,
standardized assessment of social interaction and communication that allows to assess autism
characteristics across age, developmental level and language skills (Lord et al., 2012). The
ADOS-2 scores were based on the scores on the subscales ‘Social Affect’ and ‘Restricted
Repetitive Behaviors’. In our sample, 13 children with autism scored less than six on the
ADOS-2 comparison score (i.e., more than one point below the ADOS-2 cut-off score), a non-
spectrum classification. This is potentially due in part to compensation strategies learned during
the therapy and interventions some of these children already received, as many children in our
autism sample were recruited through rehabilitation centers and/or received special education.
However, excluding these children did not significantly alter any findings of main or
interaction effects (see Supplementary Information).
All children had IQ scores above 80, evaluated by an abbreviated version of the
Wechsler Intelligence Scale for Children–Third edition–NL (WISC-III-NL; Grégoire, 2000;
Dutch translation by Kort et al., 2005). Eighteen children with autism had an IQ test less than
two years ago at the moment of participation in the study. In the TD group, six children
participated in another study where the same abbreviated version of the WISC-III was used.
For these 24 children, IQ testing was not repeated. IQ scores did not significantly differ
between groups (Autism: MIQ = 105.18; SD = 14.71; TD: MIQ = 108.86; SD = 9.28; t(65) =
0.96, p = .34).
Participants were excluded if they had less than 25 of 30 artifact-free trials left in either
of the name conditions. For this reason, three of the 70 children were excluded (one with
autism, two without autism). The final sample thus consisted of 34 children with autism (21
boys; Mage = 10.18; SD = 1.48) and 33 children without autism (20 boys; Mage = 10.76; SD =
1.86). An overview of all group characteristics of the final sample is displayed in Table 1.
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Stimuli and Task
The task was presented on a 24-inch desktop computer using Presentation Software,
version 18.1 (Neurobehavioral Systems Inc., San Francisco, CA). The auditory stimuli were
presented binaurally with EEG-compatible insert earphones (ER-RC, Etymotic research,
MedCaT).
The children were asked to carry out an auditory oddball task (Nijhof et al., 2018) that
consisted of 300 trials presented in two blocks of 150 trials. There were five different auditory
stimuli: 66% standard sounds (198 trials), 10% own name trials (30 trials), 10% close other
name trials (30 trials), 10% unknown name trials (30 trials) and 4% target sounds (12 trials).
Between the trials there was a silent inter-stimulus interval (ISI) jittered between 1075 ms and
1425 ms in steps of 25 ms, with an average ISI of 1250 ms. The trials were presented semi-
randomly: each non-standard stimulus was followed by at least one standard stimulus. To
control for the overall level of alertness, the children were instructed to listen carefully to all
the stimuli and to press the spacebar only when the target sound was presented. They were told
that there would also be other auditory stimuli, but that these were task-irrelevant. In advance,
children had to fill out a form to indicate their own first name, the name of a close other and an
unknown name. For the close other name, they were asked to give the name of someone whose
name they often hear, for example a brother, a sister, a cousin or a friend. For the unknown
name, they were provided with a list of seven gender-matched names that were one to three
syllables long. For each name they had to indicate if they knew someone with that name (either
in real life or fictional) and which name was the most unfamiliar. The researcher selected a
name that they were not familiar with and that had approximately the same length as their own
name. The name stimuli were all uttered by the same female voice and normalized to the same
volume. The names were between 346 ms and 792 ms long, and length did not significantly
differ between conditions or groups (all p-values > .56; note however that some of the stimulus
13
files were deleted after use in the experiment, for 8 children with autism and 5 in the TD group).
The standard stimulus was a high-frequency tone (1000 Hz) that lasted 500 ms, while the target
stimulus was a low-frequency tone (35 Hz) that lasted 228 ms.
Questionnaires
Three questionnaires were administered. Firstly, the Social Communication
Questionnaire (Rutter et al., 2003) is a screening questionnaire for caregivers assessing social-
communicative skills, with higher scores indicating more social-communicative difficulties.
Mean score in the autism group was 15.4 (SD: 6.0), which was 5.1 (SD: 3.7) in the TD group.
Secondly, the Social Responsiveness Scale (SRS-2; Constantino & Gruber, 2012), again filled
out by the caregiver, identifies social difficulties associated with autism. Again, higher scores
indicate more social difficulties. The mean T-score for children with autism was 93.6 (SD:
15.1), and 51.7 (SD: 8.2) for the typically developing children. Finally, we administered the
Short Sensory Profile – Revised Dutch edition (SSP-NL; Rietman, 2013), a caregiver-report
questionnaire on processing sensory information in daily life. For the scope of the current
study, we were particularly interested in a specific item from the Auditory Filtering subscale,
asking caregivers to rate how often the child does not respond to the own name (item 26), on a
scale of 1 to 5. Here, a lower score means the child does not respond to the own name more
often. Mean score for autism was 2.7 (SD: 1.0), and 3.8 (SD: 0.8) for the TD group.
Procedure
Parents received the questionnaires and the form to indicate the names prior to the test
sessions. If needed, there was a first separate session during which the ADOS-2 (autism group
only) and an abbreviated version of the WISC-III were administered. The short version of the
WISC-III consists of Similarities, Picture Arrangement, Block Design and Vocabulary
14
(Grégoire, 2000). This first session lasted between 60 and 120 minutes (depending on whether
the ADOS-2 needed to be administered). During the second test session, four tasks were
conducted, of which three were administered with electroencephalography (EEG). Children
carried out the first task during preparation of the EEG cap. The three following tasks were
presented while EEG was administered. The auditory oddball paradigm was always presented
as the third of the four tasks. The other tasks are not relevant for the scope of this study and
will be discussed elsewhere. This session, including breaks, took approximately 120 minutes
in total.
EEG/ERP recording and pre-processing
EEG activity was recorded continuously using 64 actiCAP active electrodes
(actiCHamp, EasyCap) placed in actiCHamp electrode caps appropriately sized for the
children’s heads. The reference electrode was placed at Fz and the ground electrode at Fpz.
The signal was digitized at a 1000 Hz sampling rate with BrainVision Recorder software
(version 1.21.0304, Brain Products, Gilching, Germany). A high-pass filter of 0.1 Hz, a low-
pass filter of 70 Hz and a notch filter at 50 Hz were applied within Brain Vision Analyzer
software (version 2.2, Brain Products, Gilching, Germany). The data were re-referenced
against the average reference. Data were segmented in epochs of 1200 ms after stimulus onset
with a 100 ms pre-stimulus baseline, time-locked to the beginning of each trial. The data were
corrected for eye blinks and eye movement artifacts using the algorithm proposed by Gratton
and colleagues (1983). Electrodes FT9 and FT10 were used to correct for horizontal ocular
artifacts and two additional Ag/AgCl sintered ring electrodes were positioned above and below
the left eye to correct for vertical ocular artifacts. Segments with voltage steps greater than 50
µV/ms, amplitudes exceeding -100 µV or +100 µV over an epoch of 200 ms, or activity below
0.5 µV were rejected. The remaining segments were averaged and baseline-corrected per
15
condition, per participant. Based on collapsed scalp topographies across groups and conditions
(‘collapsed localizer approach’, Luck & Gaspelin, 2017), we identified the three components
that correspond to those reported in previous literature on the neural response to the own name
(i.e., N1, SON and P3). Electrodes that showed maximum activity based on visual inspection
of these collapsed topographies in the expected time windows were included in the analyses.
The N1 component was identified in the 120 – 180 ms time window positioned at electrodes
CP3, CPz and CP4. The SON negativity was defined as the mean amplitude between 270 and
350 ms post stimulus onset at the Cz electrode. Finally, the P3 component was quantified as
the mean amplitude between 450 and 700 ms post stimulus onset at Pz.
Statistical analysis
Behavioral data
All spacebar responses within 1500 ms of the target sound (slightly more liberal than
the 1000 ms of Nijhof et al., 2018, given the participants in the current study were children)
were considered correct; responses that were slower or absent were considered errors.
EEG/ERP measures
ERP segments were removed if they contained too many artifacts or if the spacebar was
pressed in response to the name. The percentage of included trials was high for the three name
conditions (Own name: MCON = 88.99%; MASD = 87.55%; Close Other name: MCON = 88.59%;
MASD = 88.82%; Unknown name: MCON = 89.09%; MASD = 89.22%), and did not significantly
differ between groups (Own name: t(65) = 0.69; p = .50; Close Other name: t(66) = -0.10; p =
.92; Unknown name: t(66) = -0.06; p = .96).
Preprocessed data were exported from BrainVision Analyzer 2 and imported into IBM
SPSS 25 statistics (SPSS Inc., Chicago, IL, USA) for statistical analysis. For each component,
16
a 2 x 3 repeated-measures ANOVA was carried out, each time with Group (Autism vs TD) as
a between-subjects factor and Name (Own, Close Other, Unknown) as a within-subjects factor.
For the N1 a supplementary within-subjects factor Electrode (CP3, CPz, CP4) was added, as
the CP3 and CP4 electrodes might account for potential laterality effects. For the P3 component
and the SON negativity, planned contrasts were carried out exploratively, to directly compare
the response to the own name to the close other name (and the interaction with group). This
contrast is considered the purest reflection of the hypothesized self-specific effect (as the own
name also differs from the unknown name in familiarity), and responses to the unknown name
may obscure any differences between the own and close other’s name. Estimates of effect size
were reported using partial eta squared (ƞp
²) (0.01 = small, 0.06 = medium and 0.14 = large
effect; (Cohen, 1988; Richardson, 2011). We controlled for multiple comparisons by means of
a Bonferroni correction. Because the primary goal was to investigate the presence or absence
of group differences in the neural response to one’s own name, results of repeated-measures
ANOVAs were also analyzed within a Bayesian framework using JASP 0.18.1 (https://jasp-
stats.org) to examine the strength of the evidence in favor of the null and alternative hypotheses.
A Bayes Factor (BF10) approaching zero indicates that the data provide more evidence in favor
of the null hypothesis (H0) than the alternative hypothesis (H1), a value of 1 indicates that H0
and H1 are equally likely given the data, and values above 1 indicate greater support for H1.
By convention, values below one third and above 3 are taken as evidence in favor of H0 and
H1, respectively, whereas values between these values are judged to provide insufficient
evidence to favor either hypothesis.
To correlate amplitude differences with other variables, difference scores per
participant were calculated for each component by subtracting the average amplitude for the
close other name from the average amplitude for the own name. Pearson correlations were
performed to explore the association between the neural response to the own name (own name
17
– close other name) and autism characteristics as measured with the SCQ and SRS-2. To
investigate the link between the child’s neural responding to its own name and as reported by
the parents, a Pearson correlation was performed between the P3 amplitude (own name – close
other name) and the reaction to own name as reported by the parents on item 26 of the SSP-
NL.
RESULTS
ERP Results
Accuracy
There was a high number of correct and timely responses to the target trials in both
groups (Autism group: 81.37%; TD group: 81.57%), with no significant difference between
the two groups (t(65) = 0.04; p = .97).
P3 component
A 2 x 3 repeated measures ANOVA with Group (Autism vs TD) as between-subjects
factor and Name (Own, Close Other, Unknown) as within-subjects factor was carried out for
the P3 amplitudes (see Figure 1). We found a non-significant main effect of Name (F(2,130) =
2.56, p = .081, ƞ𝑝
2 = .04, BF10 = 0.51). There was also no significant main effect of Group
(F(1,65) = 0.05, p = .83, ƞ𝑝
2 = .001, BF10 = 0.23), nor was the interaction between Name and
Group significant (F(2,130) = 0.001, p = .99, ƞ𝑝
2 = .00, BF10 = 0.09). Planned contrasts for
Name and Name x Group were carried out. The contrast between Own versus Close Other
name was found to be statistically significant, F(1,65) = 4.46, p = .04, ƞ𝑝
2 = .06, BF10 = 1.66,
with significantly larger P3 amplitudes for the own compared to the close other name (M = .87;
SD = .41; 95% CI [.05, 1.69]). However, the interaction with Group was not significant
18
(F(1,65) = 0.00, p = .98, ƞ𝑝
2 = .00, BF10 = 0.26), indicating no difference for this self-
preferential effect between groups.
SON negativity
A 2 x 3 repeated measures ANOVA with Group (Autism vs TD) as between-subjects
factor and Name (Own, Close Other, Unknown) as within-subjects factor was carried out for
the SON (see Figure 2). No significant main or interaction effects were found (Name: F(2,130)
= 0.29, p = .75, ƞ𝑝
2 = .01, BF10 = 0.07; Group: F(1,65) = 1.69, p = .20, ƞ𝑝
2 = .03, BF10 = 0.61;
Name x Group: F(2,130) = 1.07, p = .35, ƞ𝑝
2 = .02, BF10 = 0.21). Planned contrasts between
Own and Close Other name for the Name and Name x Group effects were also not significant,
F(1,65) = 0.48, p = .49, ƞ𝑝
2 = .01, BF10 = 0.22, and F(1,65) = 0.35, p = .55, ƞ𝑝
2 = .01, BF10 =
0.30, respectively.
N1 component
A 2 x 3 x 3 repeated measures ANOVA with Group (Autism and TD) as between-
subjects factor and Name (Own, Close Other, Unknown) and Electrode (CP3, CPz, CP4) as
within-subjects factors was carried out for the N1 (see Figure 3). The main effects of Name
(F(2,130) = 1.48, p = .23, ƞ𝑝
2 = .02, BF10 = 0.16) and Group (F(1,65) = 0.53, p = .47, ƞ𝑝
2 = .01,
BF10 = 0.28) were not significant, nor were the interaction effects between Name x Group
(F(2,130) = 0.48, p = .62, ƞ𝑝
2 = .007, BF10 = 0.11), Electrode x Group (F(2,130) = 0.88, p =
.42, ƞ𝑝
2 = .01, BF10 = 0.13), Electrode x Name (F(4,260) = 0.85, p = .49, ƞ𝑝
2 = .01, BF10 =
0.03), or Electrode x Name x Group (F(4,260) = 0.64, p = .63, ƞ𝑝
2 = .01, BF10 = 0.05). Only a
significant main effect of Electrode was found (F(2,130) = 23.28, p < .001, ƞ𝑝
2 = .26, BF10 >
999), indicating a right-lateralized N1 (CP4 > CPz > CP3).
Autism characteristics
19
The own-name effect on neither the P3, nor the SON negativity correlated significantly
with the total scores of the SCQ (P3: r = .07; p = .55; SON: r = .12; p = .34) or SRS-2 (P3: r =
-.06; p = .66; SON: r = .10; p = .45) across groups. These correlations were also not significant
within groups (all p-values > .33).
Relation with Age
Our main hypothesis was that children with autism would show a diminished
amplification of the parietal P3 amplitude in response to hearing their own name. Because,
contrary to our expectations, we did not find a Name x Group interaction, and because previous
studies across different age groups have reported inconsistent results, we explored whether age
effects may offer an explanation. For this, correlational analyses were carried out (see Figure
4 for a scatterplot). The difference in P3 amplitude between Own and Close Other name
correlated with age across groups (r = .26; p = .03). When split per group, the magnitudes of
the correlations were similar (although non-significant) for the two groups (Autism: r = .31; p
= .07; TD: r = .23; p = .20; Fisher’s z = 0.34, p = .37).
Parent-reported own name response
Reported behavioral responsiveness to the own name was significantly lower in the
autism group than in the TD group (item 26 of the SSP-NL; t(64) = 5.50; p < .001). However,
the score on this item was not significantly correlated with (Own-Close Other) differences in
P3, SON negativity or N1 amplitudes across or within groups (all correlations: -.23 < r < 0;
all p-values > .06).
20
DISCUSSION
The main objective of the current study was to investigate the neural responses, by
means of ERPs, to hearing the own name in children between 7 and 13 years old with and
without a formal diagnosis of autism. Based on previous literature, three ERP components were
studied: the parietal P3, the SON negativity and the N1. We also investigated parents’ report
of their child’s responsiveness to hearing their own name, as well as of autism characteristics,
and their association with neural correlates of name processing.
Based on Nijhof and colleagues (2018), our main hypothesis was a smaller
enhancement of the parietal P3 for own names relative to the close other name in children with
autism. We additionally expected that children with autism would show less responsiveness to
their own name as reported by their parents (Dawson et al., 2004; Lord et al., 2012). The parent
reports indeed revealed that children with autism respond significantly less to hearing their own
name compared to children without autism. On the neural level, as expected, we found that the
parietal P3 amplitude was enhanced for the own name compared to the close other name,
indicating a self-specific effect, although the effect size was relatively small compared to
earlier studies. Contrary to our expectations, no difference between groups for this effect was
found, suggesting unaltered self-referential processing in children with autism. The same
effects were investigated for other ERP components. A negative-going component was found
in the SON time window, but this was not specific to the own name, nor did it differ between
groups. Finally, with respect to the N1, no condition effect or group difference was found.
Several studies have established the presence of a more prominent parietal P3
component as a neural correlate of hearing one’s own name compared to other names in adults
(Eichenlaub et al., 2012; Nijhof et al., 2018; Tateuchi et al., 2012). However, in the few studies
that included children, the P3 component was not always investigated (Bathelt et al., 2017;
21
Thomas et al., 2019). The study of Key and colleagues (2019) failed to find a self-specific
effect for the P3, but did find a familiarity effect, as demonstrated by enhanced P3 amplitudes
for the own and close other name compared to repeated and single presentations of unknown
names in typically developing children between 4 and 12 years old. However, in line with
previous findings in adults (Nijhof et al., 2018; Peters et al., 2017), we found a self-specific
effect for the P3, with larger amplitudes for the own name compared to the close other name.
Thus, the self-specific P3 effect we find is more in line with adult studies than with the
familiarity effect as found in younger children (Key et al., 2016). This indicates that age may
play a role in the neural response to the own name, and indeed, our study suggests a relation
between age and the P3 amplitude amplification for own name, regardless of group. Older
children seemed to be better at differentiating between their own and a close other’s name than
younger children, as there was a positive correlation between age and the P3 amplitude
difference between own name and close other name. It is important to note that these age-
related effects were specific to the own-name response, as the P3 component has been found
to show maturational changes around middle childhood (Overbye et al., 2018; van Dinteren et
al., 2014). Thus, findings suggest that the parietal P3 can be used as a neural correlate for own-
name processing in middle childhood, although it should be taken into account that amplitude
differences are age-dependent: in younger children, the P3 showed a familiarity effect rather
than a self-specific effect (Key et al., 2016).
The few studies investigating SON negativity (Bathelt et al., 2017; Thomas et al., 2019)
provided evidence for its presence in typically developing children, reflected in enhanced
frontocentral negative amplitudes for the own name compared to other names. The current
study did not replicate these findings. However, previous studies did not include the name of a
close other (only of unfamiliar others), and found effects can thus not be claimed to be self-
specific (Amodeo et al., 2023). Our results indeed indicate the presence of a negative
22
frontocentral component, but we found this not to be own-name specific, and it did not differ
between groups. Further research on the presence of the SON negativity in middle childhood
as a valid marker of own-name processing is therefore warranted.
The final component investigated in the current study, the N1, to the best of our
knowledge has rarely been investigated in children in the context of auditory own-name
processing. The study of Bathelt and colleagues (2017) found a preferential effect for the own
name compared to unknown names in the N1 in children between 8 and 13 years old, indicating
an automatic capture of attention that does not require conscious awareness. Our study could
not replicate these results, nor did we find a familiarity effect as was found in the study on the
neural processing of one’s own name in adults with and without autism (Nijhof et al., 2018).
Against expectations, no group differences were found regarding the neural correlates
associated with hearing one’s own name in the current study, which was substantiated by
Bayesian analyses. This suggests that children with autism in the age range as included in the
current study show similar neural responses to the own name as children without autism, at
least on the ERP components investigated here. Different explanations are possible. Firstly,
since the own name is considered a highly significant social cue, of great importance in socio-
communicative and self-development (Nowicka et al., 2016; Zhang et al., 2018), it could be
that the neural response to the own name is affected by the level of autism characteristics.
Nonetheless, additional performed correlational analyses did not support this assumption; no
relation between autism characteristics and the difference in neural response between own and
close other name was found in the autism group. Another possible explanation could be found
in how detecting and diagnosing autism has evolved over the years, with the possibility of
earlier and more targeted interventions. Previous studies indicate that younger children and
adults with autism show a diminished neural response to hearing their own name (Nijhof et al.,
2018; Thomas et al., 2019). It could be that the adults with autism for whom a diminished
23
response to own name was found, did not receive the same interventions as the children tested
in the current study, given strong increases in the types and number of randomized clinical
trials of early interventions over the past decades (French & Kennedy, 2018; Sandbank et al.,
2021). They may have received later diagnoses as well as different or no interventions, making
direct comparisons across age groups harder. The same can be said for the younger children in
the study of Thomas and colleagues (2019) who are just starting interventions and may not
experience a similar benefit yet. We acknowledge that this is speculative, and that prospective
longitudinal research is necessary to test this hypothesis. In addition, autism is an heterogenous
condition, and our results should be replicated within other samples of children with autism of
different ages, before firm conclusions can be made.
Further, the discrepancy between the parents’ reports and ERP findings needs further
clarification. In line with previous behavioral research, parents of children with autism reported
significantly less responsiveness in their child when calling their name than parents of children
without autism (Zhang et al., 2018). Although both neural and behavioral indices are used as
measures of responsiveness to hearing the own name, they may reflect distinct processes. The
ERP response to the own name reflects activity in the child’s brain on a task in which no
behavioral response to hearing the own name is required, in a lab context. In contrast, parent
reports are based on the actual behavioral response of the child when being called by their own
name in daily life. In the latter situation, there is a clear intent to initiate an interaction with the
child and thus a behavioral response from the child would be expected. This daily-life response
comprises of more than the child’s brain being able to attend to the own name as reflected in
the ERP response, as the child must also act on this. Therefore, it may be that the initial
attention-enhancing brain response in our sample of children with autism is intact, potentially
due to effects of interventions as reasoned above, but that this does not always result in an
appropriate behavioral response. Furthermore, in everyday life, one’s own name usually
24
appears within an environment that is much more noisy than the isolated lab context, and thus
needs to compete against more distracting stimuli. Indeed, Schwartz et al. (2020), who tested
response to own name in a quiet as well as a multispeaker environment, reported a positive
correlation between the late positive response to the own name in the multispeaker setting with
parent-reported auditory filtering abilities. An alternative explanation for our findings is that
parents may have overrepresented their child’s difficulty with responding to the own name at
this age, because of difficulties at an earlier age. We are aware that these explanations are
speculative, and future systematic research (also comparing response to name in conditions
with and without noise) is warranted. In the light of the current findings, we strongly advise
future studies to also include a behavioral measure of responsiveness to the own name.
There are some limitations associated with this study. Firstly, while only children with
a formal clinical autism diagnosis received from a multidisciplinary team were included, 13 of
the 34 children in the autism group scored more than one point below the cut-off score on the
ADOS-2 that was administered during the research, which may have affected the results.
However, due to interventions it is not uncommon that children in this age range perform better
during ADOS testing. In addition, we explored whether excluding those children from the
analyses would change the relevant findings, which was not the case. Furthermore,
correlational analyses did not show associations with autism characteristics. Secondly, we
included only children within the normal range of intellectual abilities. This affects the
generalizability of our results to the whole population of children with autism in middle
childhood. Finally, parental ratings on daily life responsiveness to hearing the own name were
used as a measure of behavioral response to the own name. Future studies might consider
adding a more direct measure (behaviorally coding the reaction to the own name during a task
that requires such a response) in combination with recordings of brain activity.
25
In conclusion, this study set out to investigate the neural responses to hearing the own
name in children with and without autism in middle childhood. We found that in this age group,
only the parietal P3 component, and not the N1 or SON negativity, appears to be enhanced for
the own name as compared to other names. Against expectations, groups did not differ on this
effect. An additional finding is that age seems to have a significant effect on the own name
modulation of the P3 amplitude, with older children showing a stronger self-specific effect than
younger children. This age effect could however not explain the absence of group effects for
the neural correlates of own name processing. Further research is warranted to understand the
discrepancy with earlier ERP findings in autism studies that included other age groups. A novel
finding that requires attention is that despite intact neural processing of the own name, parents
of children with autism did report less responsiveness when their children were called by their
name. To better understand altered own-name processing in autism, future ERP studies are
advised to include behavioral indices as well.
26
REFERENCES
American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental
Disorders (5th ed.). Author.
Amodeo, L., Goris, J., Nijhof, A. D., & Wiersema, J. R. (2024). Electrophysiological
correlates of self-related processing in adults with autism. Cognitive, Affective and
Behavioral Neuroscience, 24(3), 582–598. https://doi.org/10.3758/s13415-024-01157-0
Amodeo, L., Nijhof, A. D., Brass, M., & Wiersema, J. R. (2023). The Relevance of
Familiarity in the Context of Self-Related Information Processing. Quarterly Journal of
Experimental Psychology. https://doi.org/10.1177/17470218231154884
Arslan, M., Warreyn, P., Dewaele, N., Wiersema, J. R., Demurie, E., & Roeyers, H. (2020).
Development of neural responses to hearing their own name in infants at low and high
risk for autism spectrum disorder. Developmental Cognitive Neuroscience, 41, 100739.
https://doi.org/10.1016/j.dcn.2019.100739
Baranek, G. T. (1999). Autism during infancy: A retrospective video analysis of sensory-
motor and social behaviors at 9-12 months of age. Journal of Autism and Developmental
Disorders, 29(3), 213–224. https://doi.org/10.1023/A:1023080005650
Bathelt, J., Dale, N., & De Haan, M. (2017). Event-related potential response to auditory
social stimuli, parent-reported social communicative deficits and autism risk in school-
aged children with congenital visual impairment. Developmental Cognitive
Neuroscience, 27(February), 10–18. https://doi.org/10.1016/j.dcn.2017.07.003
Berlad, I., & Pratt, H. (1995). P300 in response to the subject’s own name.
Electroencephalography and Clinical Neurophysiology, 96, 472–474.
Cohen, J. (1988). Statistical power analysis for the social sciences (2nd editio). Academic
Press.
Constantino, J., & Gruber, C. (2012). Social Responsiveness Scale - Second Edition (SRS-2).
Western Psychological Services.
Cygan, H. B., Tacikowski, P., Ostaszewski, P., Chojnicka, I., & Nowicka, A. (2014). Neural
Correlates of Own Name and Own Face Detection in Autism Spectrum Disorder. PLoS
ONE, 9(1), e86020. https://doi.org/10.1371/journal.pone.0086020
Davies, P. L., Chang, W.-P., & Gavin, W. J. (2010). Middle and late latency ERP
components discriminate between adults, typical children, and children with sensory
processing disorders. Frintiers in Integrative Neuroscience, 4 (16).
https://doi.org/10.3389/fnint.2010.00016
Dawson, G., Toth, K., Abbott, R., Osterling, J., Munson, J., Estes, A., & Liaw, J. (2004).
Early social attention impairments in autism: social orienting, joint attention, and
attention to distress. Developmental Psychology, 40(2), 271–283.
https://doi.org/10.1037/0012-1649.40.2.271
27
Di, H. B., Yu, S. M., Weng, X. C., Laureys, S., Yu, D., Li, J. Q., Qin, P. M., Zhu, Y. H.,
Zhang, S. Z., & Chen, Y. Z. (2007). Cerebral response to patient’s own name in the
vegetative and minimally conscious states. Neurology, 68(12), 895–899.
https://doi.org/10.1212/01.wnl.0000258544.79024.d0
Eichenlaub, J. B., Ruby, P., & Morlet, D. (2012). What is the specificity of the response to
the own first-name when presented as a novel in a passive oddball paradigm? An ERP
study. Brain Research, 1447, 65–78. https://doi.org/10.1016/j.brainres.2012.01.072
Fischer, C., Dailler, F., & Morlet, D. (2008). Novelty P3 elicited by the subject’s own name
in comatose patients. Clinical Neurophysiology, 119(10), 2224–2230.
https://doi.org/10.1016/j.clinph.2008.03.035
Folmer, R. L., & Yingling, C. D. (1997). Auditory P3 Responses to Name Stimuli. Brain and
Language, 56(2), 306–311.
French, L., & Kennedy, E. M. M. (2018). Annual Research Review: Early intervention for
infants and young children with, or at-risk of, autism spectrum disorder: a systematic
review. In Journal of Child Psychology and Psychiatry and Allied Disciplines (Vol. 59,
Issue 4, pp. 444–456). Blackwell Publishing Ltd. https://doi.org/10.1111/jcpp.12828
Grégoire, J. (2000). L’évaluation clinique de l’intelligence de l’enfant: Théorie et pratique du
WISC-III. Mardaga.
Harter, S. (1999). The construction of the self: A developmental perspective. Guilford Press.
Holeckova, I., Fischer, C., Giard, M. H., Delpuech, C., & Morlet, D. (2006). Brain responses
to a subject’s own name uttered by a familiar voice. Brain Research, 1082(1), 142–152.
https://doi.org/10.1016/j.brainres.2006.01.089
Höller, Y., Kronbichler, M., Bergmann, J., Crone, J. S., Ladurner, G., & Golaszewski, S.
(2011). EEG frequency analysis of responses to the own-name stimulus. Clinical
Neurophysiology, 122(1), 99–106. https://doi.org/10.1016/j.clinph.2010.05.029
Imafuku, M., Hakuno, Y., Uchida-Ota, M., Yamamoto, J. ichi, & Minagawa, Y. (2014).
“Mom called me!” Behavioral and prefrontal responses of infants to self-names spoken
by their mothers. NeuroImage, 103, 476–484.
https://doi.org/10.1016/j.neuroimage.2014.08.034
Key, A. P., Jones, D., & Peters, S. U. (2016). Response to own name in children: ERP study
of auditory social information processing. Biological Psychology, 119, 210–215.
https://doi.org/10.1016/j.biopsycho.2016.07.016
Knyazev, G. G. (2013). EEG correlates of self-referential processing. Frontiers in Human
Neuroscience, 7(June), 264. https://doi.org/10.3389/fnhum.2013.00264
Kort, W., Schittekatte, M., Dekker, P. H., Verhaeghe, P., Compaan, M., Bosmans, M., &
Vermeir, G. (2005). Wechsler Intelligence Scale for Children Derde Editie NL:
Handleiding. Harcourt Test Publishers.
28
Kotchoubey, B., & Pavlov, Y. G. (2017). Name conditioning in event-related brain potentials.
Neurobiology of Learning and Memory, 145(September), 129–134.
https://doi.org/10.1016/j.nlm.2017.09.009
Lord, C., Rutter, M., DiLavore, P. C., Risi, S., Gotham, K., & Bishop, S. (2012). Autism
Diagnostic Observation Schedule, Second Edition (ADOS-2) Manual (Part I): Modules
1–4. Western Psychological Services.
Luck, S. J., & Gaspelin, N. (2017). How to get statistically significant effects in any ERP
experiment (and why you shouldn’t). Psychophysiology, 54(1), 146–157.
https://doi.org/10.1111/psyp.12639
Makrygianni, M. K., & Reed, P. (2010). A meta-analytic review of the effectiveness of
behavioural early intervention programs for children with Autistic Spectrum Disorders.
Research in Autism Spectrum Disorders, 4(4), 577–593.
https://doi.org/10.1016/j.rasd.2010.01.014
Mandel, D. R., Jusczyk, P. W., & Pisoni, D. B. (1995). Infants’ recognition of the sound
patterns of their own names. Psychological Science, 6(5), 314–317.
https://doi.org/10.1111/j.1467-9280.1995.tb00517.x
Mandel-Emer, D., & Jusczyk, P. W. (2003). What’s in a Name?: How Infants Respond to
Some Familiar Sound Patterns. In: Huston D, Seidl A, Hollich G, Johnson E, Jusczyk A,
Eds.
Marschik, P. B., Pokorny, F. B., Peharz, R., Zhang, D., O’Muircheartaigh, J., Roeyers, H.,
Bölte, S., Spittle, A. J., Urlesberger, B., Schuller, B., Poustka, L., Ozonoff, S., Pernkopf,
F., Pock, T., Tammimies, K., Enzinger, C., Krieber, M., Tomantschger, I., Bartl-
Pokorny, K. D., … Kaufmann, W. E. (2017). A Novel Way to Measure and Predict
Development: A Heuristic Approach to Facilitate the Early Detection of
Neurodevelopmental Disorders. Current Neurology and Neuroscience Reports, 17(5).
https://doi.org/10.1007/s11910-017-0748-8
McHale, S. M., Dariotis, J. K., & Kauh, T. J. (2003). Social Development and Social
Relationships in Middle Childhood. In Handbook of Psychology (pp. 271–282). John
Wiley & Sons, Inc. https://doi.org/10.1002/0471264385.wei0610
Miller, M., Iosif, A. M., Hill, M., Young, G. S., Schwichtenberg, A. J., & Ozonoff, S. (2017).
Response to Name in Infants Developing Autism Spectrum Disorder: A Prospective
Study. Journal of Pediatrics, 183, 141-146.e1.
https://doi.org/10.1016/j.jpeds.2016.12.071
Mitchell, J. P. (2009). Inferences about mental states. Philosophical Transactions of the
Royal Society B: Biological Sciences, 364(1521), 1309–1316.
https://doi.org/10.1098/rstb.2008.0318
Moore, V., & Goodson, S. (2003). How Well Does Early Diagnosis of Autism Stand the Test
of Time? Autism, 7(1), 47–63. https://doi.org/10.1177/1362361303007001005
Müller, H. M., & Kutas, M. (1996). What’s in a name? Electrophysiological differences
between spoken nouns, proper names and one’s own name. Neuroreport, 8(1), 221–225.
https://doi.org/10.1097/00001756-199612200-00045
29
Nadig, A. S., Ozonoff, S., Young, G. S., Rozga, A., Sigman, M., & Rogers, S. J. (2007). A
prospective study of response to name in infants at risk for autism. Archives of Pediatric
and Adolescent Medicine, 161(4), 378–383. https://doi.org/161/4/378
[pii]\r10.1001/archpedi.161.4.378
Newman, R. S. (2005). The cocktail party effect in infants revisited: Listening to one’s name
in noise. Developmental Psychology, 41(2), 352–362. https://doi.org/10.1037/0012-
1649.41.2.352
Nijhof, A. D., & Bird, G. (2019). Self‐processing in individuals with autism spectrum
disorder. Autism Research, 12(11), 1580–1584. https://doi.org/10.1002/aur.2200
Nijhof, A. D., Catmur, C., Brewer, R., Coll, M. P., Wiersema, J. R., & Bird, G. (2024).
Differences in own-face but not own-name discrimination between autistic and
neurotypical adults: A fast periodic visual stimulation-EEG study. Cortex, 171, 308–
318. https://doi.org/10.1016/j.cortex.2023.10.023
Nijhof, A. D., Dhar, M., Goris, J., Brass, M., & Wiersema, J. R. (2018). Atypical neural
responding to hearing one’s own name in adults with ASD. Journal of Abnormal
Psychology, 127(1), 129–138. https://doi.org/10.1037/abn0000329
Nowicka, A., Cygan, H. B., Tacikowski, P., Ostaszewski, P., & Kuś, R. (2016). Name
recognition in autism: EEG evidence of altered patterns of brain activity and
connectivity. Molecular Autism, 7(1), 38. https://doi.org/10.1186/s13229-016-0102-z
Overbye, K., Huster, R. J., Walhovd, K. B., Fjell, A. M., & Tamnes, C. K. (2018).
Development of the P300 from childhood to adulthood: a multimodal EEG and MRI
study. Brain Structure and Function, 223(9), 4337–4349.
https://doi.org/10.1007/s00429-018-1755-5
Parise, E., Friederici, A. D., & Striano, T. (2010). “Did you call me?” 5-month-old infants
own name guides their attention. PLoS ONE, 5(12).
https://doi.org/10.1371/journal.pone.0014208
Perrin, F., García-Larrea, L., Mauguière, F., & Bastuji, H. (1999). A differential brain
response to the subject’s own name persists during sleep. Clinical Neurophysiology,
110(12), 2153–2164. https://doi.org/10.1016/S1388-2457(99)00177-7
Perrin, F., Schnakers, C., Schabus, M., Degueldre, C., Goldman, S., Brédart, S., Faymonville,
M. E., Lamy, M., Moonen, G., Luxen, A., Maquet, P., & Laureys, S. (2006). Brain
response to one’s own name in vegetative state, minimally conscious state, and locked-
in syndrome. Archives of Neurology, 63(4), 562–569.
https://doi.org/10.1001/archneur.63.4.562
Peters, S. U., Katzenstein, A., Jones, D., & Key, A. P. (2017). Distinguishing response to
names in Rett and MECP2 Duplication syndrome: An ERP study of auditory social
information processing. Brain Research, 1675, 71–77.
https://doi.org/10.1016/j.brainres.2017.08.028
Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical
Neurophysiology, 118(10), 2128–2148. https://doi.org/10.1016/j.clinph.2007.04.019
30
Ponton, C. W., Eggermont, J. J., Kwong, B., & Don, M. (2000). Maturation of human central
auditory system activity: evidence from multi-channel evoked potentials. Clinical
Neurophysiology, 111(2), 220–236. https://doi.org/10.1016/S1388-2457(99)00236-9
Richardson, J. T. E. (2011). Eta squared and partial eta squared as measures of effect size in
educational research. Educational Research Review, 6(2), 135–147.
https://doi.org/10.1016/j.edurev.2010.12.001
Rutter, M., Bailey, A., & Lord, C. (2003a). The social communication questionnaire:
Manual. Western Psychological Services.
Rutter, M., Bailey, A., & Lord, C. (2003b). The social communication questionnaire:
Manual. Western Psychological Services.
Sandbank, M., Bottema-Beutel, K., & Woynaroski, T. (2021). Intervention
Recommendations for Children with Autism in Light of a Changing Evidence Base. In
JAMA Pediatrics (Vol. 175, Issue 4, pp. 341–342). American Medical Association.
https://doi.org/10.1001/jamapediatrics.2020.4730
Schwartz, S., Wang, L., Shinn-Cunningham, B. G., & Tager-Flusberg, H. (2020). Neural
Evidence for Speech Processing Deficits During a Cocktail Party Scenario in Minimally
and Low Verbal Adolescents and Young Adults with Autism. Autism Research, 13(11),
1828–1842. https://doi.org/10.1002/aur.2356
Tacikowski, P., Cygan, H. B., & Nowicka, A. (2014). Neural correlates of own and close-
other ’ s name recognition : ERP evidence. Frontiers in Human Neuroscience, 8, 1–10.
https://doi.org/10.3389/fnhum.2014.00194
Tamura, K., Mizuba, T., & Iramina, K. (2016). Hearing subjects own name induces the late
positive component of event-related potential and beta power suppression. Brain
Research, 1635, 130–142. https://doi.org/10.1016/j.brainres.2016.01.032
Tateuchi, T., Itoh, K., & Nakada, T. (2012). Neural mechanisms underlying the orienting
response to subject’s own name: An event-related potential study. Psychophysiology,
49(6), 786–791. https://doi.org/10.1111/j.1469-8986.2012.01363.x
Tateuchi, T., Itoh, K., & Nakada, T. (2015). Further characterization of “subject’s own name
(SON) negativity,” an ERP component reflecting early preattentive detection of SON.
BMC Research Notes, 8(195), 1–5. https://doi.org/10.1186/s13104-015-1150-8
Thomas, R. P., Wang, L. A. L., Guthrie, W., Cola, M., McCleery, J. P., Pandey, J., Schultz,
R. T., & Miller, J. S. (2019). What’s in a name? A preliminary event-related potential
study of response to name in preschool children with and without autism spectrum
disorder. PLoS ONE, 14(5), 1–16. https://doi.org/10.1371/JOURNAL.PONE.0216058
van Dinteren, R., Arns, M., Jongsma, M. L. A., & Kessels, R. P. C. (2014). P300
development across the lifespan: A systematic review and meta-analysis. PLoS ONE,
9(2). https://doi.org/10.1371/journal.pone.0087347
Webb, S. J., & Jones, E. J. H. (2009). Early Identification of Autism. Infants & Young
Children, 22(2), 100–118. https://doi.org/10.1097/IYC.0b013e3181a02f7f
31
Werner, E., Dawson, G., Osterling, J., & Dinno, N. (2000). Brief report: Recognition of
autism spectrum disorder before one year of age: A retrospective study based on home
videotapes. Journal of Autism and Developmental Disorders, 30(2), 157–162.
https://doi.org/10.1023/A:1005463707029
Zhang, D., Roche, L., Bartl-Pokorny, K. D., Krieber, M., McLay, L., Bölte, S., Poustka, L.,
Sigafoos, J., Gugatschka, M., Einspieler, C., & Marschik, P. B. (2018). Response to
name and its value for the early detection of developmental disorders: Insights from
autism spectrum disorder, Rett syndrome, and fragile X syndrome. A perspectives paper.
Research in Developmental Disabilities, 82(October 2017), 95–108.
https://doi.org/10.1016/j.ridd.2018.04.004
Zwaigenbaum, L., Bryson, S., Rogers, T., Roberts, W., Brian, J., & Szatmari, P. (2005).
Behavioral manifestations of autism in the first year of life. International Journal of
Developmental Neuroscience, 23, 143–152.
https://doi.org/10.1016/j.ijdevneu.2004.05.001
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Figure Caption Sheet
Figure 1.
Grand average waveforms for the P3 component at Pz, and the topographies for the P3 time
window (450 – 700ms) specifically for the own name, per group (top = Typically developing,
bottom = Autism group).
Figure 2.
The SON negativity at Cz for the different names, and the topographies for the SON
negativity (270 – 350 ms) specifically for the own name, per group (top = Typically
developing, bottom = Autism group).
Figure 3.
The N1 component at CP3, CPz and CP4 for the different names, and the topographies for the
N1 time window (120 – 180ms) specifically for the own name, per group (top = Typically
developing, bottom = Autism group).
Figure 4.
Correlation between age and the self-specific P3 amplitude effect (Own – Close Other). The
typically developing group is represented by blue triangles and the autism group by red dots.
Regression lines per group are noted.
33
Figures
34
35
Tables
Table 1
Characteristics of the final autism and typically developing group
Autism group (N=
34)
Typically developing
group (N= 33)
Mean
SD
Mean
SD
p
Age
10.18
1.48
10.76
1.86
.161
IQ (WISC-III-NL)
105.18
14.71
108.00
8.48
.341
SCQ (total)
15.35
6.03
5.13
3.74
<.001
SRS-2 (total)
97.41
24.12
28.59
13.77
<.001
SSP-NL (auditory
filtering)
13.88
4.45
21.44
5.05
<.001
SSP-NL (item 26)**
2.65
0.98
3.84
0.77
<.001
ADOS-2
5.68
2.50
N.A.*
N.A.*
N.A.*
Note. *N.A. = Not applicable; the ADOS-2 was not administered to children in the typically
developing group. **Item 26 of the SSP-NL: Does not respond when his/her name is called,
while knowing there are no hearing difficulties (1 = always, 5 = never).
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