Neural responses to affective and cognitive theory of mind in children and adolescents with autism spectrum disorder

Accepted Manuscript Title: Neural Responses to Affective and Cognitive Theory of Mind in Children and Adolescents with Autism Spectrum Disorder Author: Eunjoo Kim Sunghyon Kyeong Keun-Ah Cheon Bumhee Park Maeng-Keun Oh Ji Won Chun Hae-Jeong Park Jae-Jin Kim Jae-Jin Kim Dong-Ho Song PII: DOI: Reference:

S0304-3940(16)30231-2 http://dx.doi.org/doi:10.1016/j.neulet.2016.04.026 NSL 31976

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Neuroscience Letters

Received date: Revised date: Accepted date:

2-9-2015 31-3-2016 11-4-2016

Please cite this article as: Eunjoo Kim, Sunghyon Kyeong, Keun-Ah Cheon, Bumhee Park, Maeng-Keun Oh, Ji Won Chun, Hae-Jeong Park, Jae-Jin Kim, Jae-Jin Kim, Song Dong-Ho, Neural Responses to Affective and Cognitive Theory of Mind in Children and Adolescents with Autism Spectrum Disorder, Neuroscience Letters http://dx.doi.org/10.1016/j.neulet.2016.04.026 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Neural Responses to Affective and Cognitive Theory of Mind in Children and Adolescents with Autism Spectrum Disorder

Eunjoo Kim a, Sunghyon Kyeonga, Keun-Ah Cheona, Bumhee Parkb, Maeng-Keun OhC, Ji Won Chund , Hae-Jeong ParkC, Jae-Jin Kima, and Dong-Ho Song a* a

Department of Psychiatry and Institute of Behavioral Science in Medicine, Yonsei

University College of Medicine, Seoul, Korea b

Department of Statistics, Hankuk University of Foreign Studies, Yongin, Korea

c

Department of Diagnostic Radiology, Division of Nuclear Medicine, Yonsei University

College of Medicine, Seoul, Korea d

Department of Psychiatry, Seoul St. Mary’s Hospital, The Catholic University of Korea

College of Medicine, Seoul, Korea

*Corresponding author

Dong-Ho Song, M.D., Ph. D. Department of Psychiatry and Institute of Behavioral Science in Medicine Yonsei University College of Medicine 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 150-752, Republic of Korea Tel: +82-2-2228-1620, Fax: +82-2-313-0891, e-mail: [email protected]

Highlights

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We examined the neural correlates of cognitive and affective theory of mind (ToM) in children and adolescents with ASD.

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Cognitive ToM was related to greater activation of the medial prefrontal cortex, superior temporal gyrus and anterior cingulate cortex in ASD group.

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Affective ToM was related to greater activation in the insula and other subcortical regions in both ASD and TDC group.



Greater activation of m PFC/ACC regions was associated with a lesser symptom severity in ASD participants.

Abstract Children and adolescents with Autism Spectrum Disorder (ASD) are characterized by an impaired Theory of Mind (ToM). Recent evidence suggested that two aspects of ToM (cognitive ToM versus affective ToM) are differentially impaired in individuals with ASD. In this study, we examined the neural correlates of cognitive and affective ToM in children and adolescents with ASD compared to typically developing children (TDCs). Twelve children and adolescents with ASD and 12 age, IQ matched TDCs participated in this functional MRI study. The ToM task involved the attribution of cognitive and affective mental states to a cartoon character based on verbal and eye-gaze cues. In cognitive ToM tasks, ASD participants recruited the medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and superior temporal gyrus (STG) to a greater extent than did TDCs. In affective ToM tasks, both ASD and TDC participants showed more activation in the insula and other subcortical regions than in cognitive ToM tasks. Correlational analysis revealed that greater activation of the mPFC/ACC regions was associated with less symptom severity in ASD patients. In sum,

our study suggests that the recruitment of additional prefrontal resources can compensate for the successful behavioral performance in the ToM task in ASD participants.

Keywords: affective ToM; cognitive ToM; Autism spectrum disorder; functional MRI; Theory of mind

Introduction

Children and adolescents with Autism Spectrum Disorder (ASD) are characterized by an impairment of Theory of Mind (ToM) abilities, which contribute to their characteristic deficit in social interaction and communication [1]. ToM refers to the ability to infer other people’s mental states, and it underlies human ability to explain and predict the behavior of ourselves and others by attributing to them independent mental states, such as beliefs, desires, emotions or intentions [2]. It has been suggested that ToM functions might involve the ability to share attention by following the gaze of another agent, the ability to represent goal-directed actions and the ability to distinguish between actions of the self and others [2,3]. Numerous neuroimaging studies of ToM reported that a network of functionally related regions are involved in the ToM, and the key regions recruited by ToM processes in the healthy brain comprises medial prefrontal cortex (mPFC), superior temporal sulcus (STS), the temporoparietal junction (TPJ), the anterior temporal poles (TP) and precuneus [3,4]. In ASD patients, these ToM-related brain regions have been reported to show aberrant activation during ToM tasks. These include inferior frontal cortex (IFC) [5], mPFC, STS, TP [1] and anterior insula [6,7]. However, ToM is a broad concept encompassing various subcomponents, making it one that requires various different cognitive abilities [8]. Therefore, depending on which

ToM task is used and which aspect of ToM is focused on, each research on ToM of ASD patients reported somewhat different results [9]. To provide the explanation for these inconsistencies, recent studies have investigated subcomponents of ToM, and one important differentiation is that of ‘affective’ ToM (inference about other people’s emotional states and feelings)’ versus ‘cognitive’ ToM (inference regarding other people’s thoughts and beliefs). These two aspects of ToM are said to be mediated by overlapping but dissociable brain networks in healthy controls and a variety of psychiatric populations [10-12]. Prior neuroimaging studies in healthy population suggested that both cognitive and affective ToM conditions were associated with neural responses in the common ToM network in both adults and adolescents [3,13]. The presence of reciprocally interconnected limbic-paralimbic and neocortical areas of the ToM network implies that there is an interacting functions of the brain where emotion and cognition can mutually affect each other [10]. The anterior cingulate cortex (ACC) is one candidate brain region where such an interaction between cognition and emotion may occur [14]. By contrast, other studies have suggested that distinct brain regions are implicated in distinct subcomponents of ToM, and that emotional and cognitive components of ToM may involve dissociable circuits within the larger ToM network [8,15,16]. Cognitive components have been proposed to involve brain regions, such as mPFC, STS and TP, and affective components have been linked to the ventromedial PFC (vmPFC), orbitofrontal cortex (OFC), and IFC, together with limbic structures and the insula [11,17,18]. In addition, studies investigating developmental trajectories of ToM subtypes have found that during an affective ToM task, adolescents displayed a greater vmPFC activation than did adults [19]. This agerelated changes in ToM abilities has been found to be largely mediated by age-related developments or declines of executive function, such as inhibitory control and perspective taking, especially prominent on the second-order ToM tasks [20].

With respect to ASD, behavioral data suggested that ‘cognitive’ and ‘affective’ ToM is differentially impaired in individuals with ASD, but the results have been inconsistent [21]. One study suggested that only affective ToM is impaired in ASD [22], while other studies reported that only cognitive ToM is impaired in ASD [23,24]. However, to date, few neuroimaging studies examined the neural circuitry underlying cognitive and affective TOM separately in children and adolescents with ASD. Therefore, the main objective of the present study was to examine the neural bases of affective vs cognitive theory of mind, using functional magnetic resonance imaging (f MRI) in children and adolescents with ASD, compared to TDC. Our key hypothesis were that 1) children and adolescents with ASD would show differences of activation in brain regions involved in ToM during the ToM tasks, relative to TDCs, and 2) Cognitive and affective ToM might activate similar structure in brain, but affective ToM might recruit additional regions functionally related to the integration of cognitive and affective information, such as the mPFC, insula, and some subcortical para-limbic regions.

2. Methods

2.1. Participant recruitment and assessment

15 ASD subjects with normal intelligence and 14 typically developing controls (TDCs) were recruited from the Severance hospital Child and Adolescent Psychiatry clinic and from the local community. All subjects were age 7-18 years and right-handed. Diagnosis was performed by a child and adolescent psychiatrist according to the standard Diagnostic and Statistical Manual of Psychiatric Disorders-IV [25].

In addition to clinical diagnosis, we

used the Autism Diagnostic Interview-Revised (ADI-R) [26] and the Autism Diagnostic Observational Schedule (ADOS) [27] to confirm the diagnosis. ASD subjects with comorbid

ADHD, depressive disorder, anxiety disorder and tic disorder were also included. Stimulant medication is discontinued 24 hour prior to the experiment, but other medications are continued. Those subjects with a neurological condition, IQ less than 80, presence of metallic implants or braces were excluded. TDCs were determined to have no DSM-IV diagnosis through structured interview with the parents. This study was approved by the Institutional Review Board of Yonsei University College of Medicine. All participants gave written informed assent or consent.

2.2. Behavioral task A Korean modified version of the ‘Yoni’ task [28] was used as a behavioral task and it was adapted for the f MRI environment as an event-related paradigm (Figure 1). Yoni task is based on a task previously described by Baron-Cohen [29] and measures the ability to judge mental states based on verbal and eye gaze cues. The detailed description of the task is provided in Supplementary Information. There are two main conditions ; ‘cognitive’ and ‘affective’ conditions. These two conditions involved mental inferences; in the cognitive ToM conditions, both Yoni’s facial expression and the verbal cue are emotionally neutral (eg. ‘Yoni is thinking of the toys that X wants’). In the affective ToM conditions, both cues provide affective information (eg. ‘Yoni loves the toys that X loves’ ). The physical condition required a choice based on a physical attribute of the character (‘Yoni has the toys that X has’) served as a control for errors made due to attention and working memory deficits. Only second order ToM items from the original Yoni task were selected, since previous study reported that second order ToM task evokes more activation in the ToM network than first order ToM task [30]. In the second order ToM task, the four stimuli in the corners consist of faces and an inference regarding the interaction between Yoni’s and the other stimuli’s mental

state is necessary. Each of 3 conditions consisted of 24 stimuli, so total of 72 items in 1 run out of 2 runs, and the total task duration was 9 min 46 sec. All items were presented in randomized order for a maximum of 5.5 sec during which the subjects had to answer by tapping a button on the square number keyboard on both hands as fast as possible. There was baseline screen of 500 msec duration with fixation cross in the center between each event. Before experiment, all subjects received a training to the task with 15 items not included in the test. Performance was rated for accuracy and reaction time (RT), and accuracy and RT of ASD and TDC group were subjected to statistical analysis in SPSS 20. 2.3. Assessment of ToM abilities: Interpersonal Reactivity Index (IRI) Four aspects of empathic abilities were assessed using the Interpersonal Reactivity Index (IRI) [31]. These scales assess both the cognitive and affective components of empathy separately, and were validated with other measures of empathy. Specifically, cognitive empathy in IRI is a similar concept to ‘affective theory of mind’ in our study, referring to the ability to understand emotions of other people, rather than other types of mental states (e.g. lying). Affective empathy in the IRI refers to ‘empathic concern’ or the capacity to share another’s emotions. This instrument consist of four seven-item subscales: Perspective Taking (PT), Fantasy Scale (FS), Empathic Concern (EC) and Personal Distress (PD) (Details of the subscales are described in Supplementary Information). Of those scales, the PT scale best operationalizes cognitive empathy, and emotional empathy was assessed using the mean score of the EC and the PD subscales, following the prior study by Dziobek et al [23]. The IRI has good internal consistency, with alpha coefficients ranging from 0.68 to 0.79 [31].

2.4. Functional MRI acquisition and imaging data analysis Participants were scanned on a Philips Achieva 3.0 T MR scanner (Philips Medical

Systems, Best, The Netherlands). E-Prime was used to present the task to the subjects during scanning. Functional MRI data comprised 293 volumes acquired with a T2-weighted single shot echo planar imaging (EPI) sequence, using a sense-8 head coil. Each participant was axially scanned using the following parameters: voxel size=2.75×2.75×4.0mm3, matrix = 80×80, repetition time (TR) = 2000 ms, echo time (TE) = 30ms, field of view (FOV) = 220mm. Slices were acquired interleaved with a thickness=4mm (no gap), and a slice number = 31. Data were preprocessed and analyzed using SPM8 (Wellcome Department of Imaging Neuroscience; http://www.fil.ion.ucl.ac.uk/spm/). Standard pre-processing was applied with slice time correction, realignment to the first volume to correct for inter-scan motion artifacts. After realignment, a mean EPI image was created, which was co-registered with the structural T1 image. Subsequently, images were spatially normalized to the standard stereotactic space defined by the Montreal Neurological Institute (MNI) template. Functional images were then smoothed with a 3D isotropic 6-mm full width/half-maximum (FWHM) Gaussian kernel. Low-frequency noise was removed by applying a high-pass filter (cut-off of 128s) to the f MRI time-series at each voxel. For the group level inference between ASD and TDC groups, we set a cluster level criterion with a voxel level threshold, uncorrected p < 0.001 at the whole brain level, and with an extent threshold of 35 contiguous voxels using SPM 8. This criteria is equivalent to p < 0.05 corrected by cluster level for multiple comparisons as estimated by 10,000 Monte Carlo simulations [32]. The contrasts we performed were: Cognitive ToM (COG) > Physical Control (PHY), Affective ToM (AFF) > PHY, COG> AFF and AFF > COG. To further explore the relationship between brain function in regions showing the difference between the ASD and TDC groups and ToM abilities and clinical symptoms, correlation analyses were also conducted between blood-oxygen-level-dependent (BOLD) signal estimates associated with the contrasts of interest and (i) IRI cognitive and affective empathy subscales across the

two groups (ii) ADOS social subscale within the ASD group only. Coordinates were reported in MNI (Montreal Neurological Institute) space and brain regions were identified with the Anatomical Automatic Labelling Toolbox for SPM.

3. Results 3.1. Demographic and clinical characteristics of ASD and TDC Of the total 29 participants, 5 participants (3 ASD, 2 TDCs) were excluded due to excessive motion ( > 3.5 mm of deviation or rotation from the estimated center of mass) during fMRI scanning. This left 12 ASD participants (11 males, mean age 12.4 years, SD = 2.3) and 12 age and IQ matched TDCs (12 males, mean age 11.7 years, SD = 2.1) to be included for statistical analysis. Participants’ demographic and clinical characteristics are provided in Table 1. There were no group differences in full scale IQ as measured by the KWISC-III (p = 0.34). In terms of comorbidities, ASD participants included one participant with ADHD; 2 with ADHD and tic disorder; 1 with ADHD, obsessive-compulsive disorder, and tic disorder; and 1 with ADHD and depressive disorder NOS. Four out of 12 ASD participants were taking medication (risperidone, sertraline for obsessive-compulsive disorder and tic disorder; aripiprazole for tic disorder; escitalopram for depression; fluoxetine and methylphenidate for depression and ADHD). The severity of ADHD symptoms were mild (the mean scores of ADHD rating scale = 19 ) in 5 patients who are comorbid with ADHD, and only one patient required a stimulant medication to manage his ADHD symptoms.

3.2. Behavioral performance and Interpersonal Reactivity Index (IRI) subscales To rule out the possibility that ToM performance could be related to demographic variables such as age and IQ, the correlation between scores on the TOM tasks and these variables were examined, but the results revealed no significant correlation between these

variables. Since there was a significant performance difference of ASD and TDC groups (p=0.02) on the PHY condition, it was used as a covariate in the analysis of accuracy. A multivariate ANOVA was conducted for the COG and AFF conditions to examine whether the two groups differed significantly from each other on cognitive and affective response accuracy. This analysis revealed that the difference of accuracy between the groups was not significant (Hotelling’s Trace; F [1, 20]=0.59, NS). This result indicates that the ASD group showed similar performance to TDC group on both affective and cognitive ToM measurements. With regard to mean reaction time (RTs), excluding missing trials, multivariate ANOVA was conducted for the COG, AFF, PHY condition, but did not yield significant group effect, indicating that there were no differences in RTs of COG or AFF conditions between the groups (Table 2). The analysis of Interpersonal Reactivity Index (IRI) subscales, using independent sample t-test, revealed that the ASD group scored significantly lower on the empathic concern (EC) subscale compared to TDCs (p < 0.01). There were no significant group differences in any of the other IRI subscales, and cognitive ToM and affective ToM scores were not significantly different between the two groups (Table 3).

3.3. Imaging data analysis

3.3.1. Brain regions showing significant group differences between ASD and TDC group

Regions reaching cluster-level significance at p < 0.001 uncorrected, k>35 between ASD and TDC groups are shown in Table 4 and Figure 2. In cognitive ToM tasks (COG> PHY), ASD group recruited a region within the bilateral medial frontal gyrus (BA 9,10) and the right superior temporal gyrus (BA 22), and the left anterior cingulate gyrus to a greater

extent, compared to TDC group. In affective ToM tasks (AFF > PHY), right medial frontal gyrus (BA 10) and superior frontal gyrus (BA 9) were engaged to a greater degree relative to TDC group, when the threshold was lowered to p < 0.005 uncorrected, k > 73 at the cluster level. (This criteria is equivalent to p < 0.05 corrected by cluster level for multiple comparisons as estimated by 10, 000 Monte Carlo simulations [32]. Neither AFF > COG nor COG > AFF contrasts did not survived the statistical threshold of p < 0.001, uncorrected.

3.3.2. Brain regions showing a significant effect of condition (COG, AFF) in ASD group

There was a significant effect of the cognitive ToM condition (COG > PHY) in bilateral prefrontal regions (right medial frontal gyrus, left middle frontal gyrus, precentral gyrus: BA 6, 9) and the bilateral inferior frontal gyrus (BA 46, 47), middle temporal gyrus (BA 39), right precuneus (BA 19), and left cingulate gyrus (BA 32). The affective ToM (AFF > PHY) contrast showed activations in the right inferior and middle frontal gyrus ( BA 9, 45, 46, superior temporal gyrus (BA 22), middle and medial frontal gyrus (BA 6), middle temporal gyrus (BA 37, 19) bilaterally, anterior cingulate, and cerebellum. These activations are presented in Supplementary Table 1 and Figure 2. In the AFF > COG condition, the right insula (BA 13), middle frontal gyrus, and precentral gyrus (BA 4) showed significant activation differences, but the reverse contrast COG > AFF did not show any significant activation differences.

3.3.3. Brain regions showing a significant effect of condition (COG, AFF) in TDC group

There was no significant COG > PHY contrast in the TDC group, except for at one left sub-gyral region at a threshold of p < 0.001, uncorrected, although when the threshold was lowered to uncorrected p < 0.005, k > 35, ToM related regions such as the mPFC and STG were activated in the cognitive ToM condition. The affective ToM condition (AFF >

PHY contrast) showed significantly greater activation in bilateral thalamus, precentral gyrus (BA 6), precuneus (BA 7), insula, and middle and inferior frontal gyrus (BA 9). For the AFF > COG contrast, significant activations were found in right putamen and left insula (Supplementary Table 2).

3.4. The relationship between autistic symptomatology and brain activation

Correlational analyses explored the relationship between patterns of brain activation to the contrasts of interest (COG > PHY, AFF > PHY ) in brain regions showing significant group differences, and the severity of symptoms of the ASD group (ADOS social and communication subscale scores). ADOS scores were missing for 3 subjects with ASD, and thus, 9 ASD participants were included in this correlational analysis. The results of our analysis revealed that signal intensities in the mPFC and ACC were inversely correlated with symptoms of reciprocal social interaction as measured by the ADOS social subscale (mPFC: r = -0.71, p = 0.03, ACC: r = -.66, p = 0.05, Figure 4) in COG > PHY contrast, but not in AFF > PHY contrast. Correlation analysis of ADOS communication subscale and brain activation for both contrasts was performed, but turned out to be non-significant (p > 0.05).

3.5. The correlation between IRI subscale scores and signal intensity across groups Correlation analysis between signal intensities in brain areas in COG and AFF ToM contrasts and IRI subscale scores were conducted across the whole sample (Table 4). The analyses were constrained to brain areas where significant group x condition interaction differences are present, as shown in Figure 2. For the AFF > PHY contrasts, there was a negative relationship between IRI empathic concern subscale score and the BOLD response in the mPFC and STG. For COG > PHY contrasts, there was also a negative relationship between IRI cognitive (perspective taking) subscale and affective ToM score and signal

intensity in the mPFC. In some mPFC areas, IRI cognitive and affective empathy subscale scores correlated with the BOLD response in both cognitive and affective ToM tasks.

4. Discussion

The present study examined the neural correlates underlying the cognitive and affective ToM in children and adolescents with ASD. To our knowledge, this is the first study to examine the contrast between neural correlates of these two subtypes of ToM in children and adolescents patients with ASD. The comparison between brain activation in the ASD and TDC groups revealed some interesting results. First, ToM-related regions, such as the mPFC and STG, and cognitive control regions, such as mPFC and ACC, showed an increased activation in the ASD group relative to the TDC group in the cognitive ToM condition. Group differences were also found in the medial and superior frontal cortices for the affective ToM condition. In contrast, no brain regions showed greater activation in the TDC group. This finding is consistent with recent results that show a hyper-activation of ToM-related brain regions in ASD [33,34], although other studies have also reported under-activation or negligible activation differences of the ToM network in ASD participants [1,35-37]. One possible explanation for variable findings of over- versus under-activation in ASD patients is the different task characteristics of each study. For example, one task-specific factor that may potentially influence brain activation is the use of implicit versus explicit tasks [38,39]. In an implicit task, participants are not explicitly instructed to engage ToM processes, which could result in their failure to engage ToM processes, and a subsequent under-activation of ToM-related regions [30]. However, the Yoni task employed in our study is an explicit task and involved complex cognitive functions, such as the processing of verbal cues, eye gaze, and the capacity for ToM. This task thus places higher demands on attention

and working memory, because several cues must be processed simultaneously [30]. The cognitive components of ToM (eg. mentalizing and cognitive control) may become more automated and require fewer neural resources in TDCs. In contrast, ASD-associated increases in brain activation may result from a greater effort or compensatory strategies to solve the cognitive or emotional requirement of the ToM task, hence over-activating the ToM network. Such increase in PFC activation might be an evidence of impaired ToM circuitry [30]. Indeed, data from other disorders validated the possibility that psychopathological states may be associated with hyperactivation of relevant brain regions [34]. Alternatively, ASD patients may have taken a more cognitive approach to the ToM task, thus increasing the recruitment of cognitive control regions such as mPFC or ACC. Previous studies have indicated an abnormal engagement of cognitive control regions in social contexts in ASD patients [40]. Considering the lack of significant differences in behavioral task performance between the two groups, this compensatory mechanism seems to be working to a satisfactory level in our task. Another possible explanation for the increased ToM–related activation in ASD is that our participants were mainly adolescents. Studies of typically developing adolescents have revealed there to be an increased activation of mPFC compared to adult participants [41,42]. If ToM development is substantially delayed in ASD [43], this may be reflected in the neural response, leading to increases rather than decreases in ToM-related brain activity during adolescence [44]. However, this assumption is speculative and requires further longitudinal investigation. Based on prior findings regarding ToM subtypes (cognitive vs affective ToM), our second objective was to investigate these two concepts at the neural level. We found that cognitive and affective ToM tasks engaged similar areas of brain, including the prefrontal cortex and superior temporal gyrus, and mPFC. This result contrasts with previous studies

that have reported vmPFC involvement in affective but not cognitive ToM [11,45]. However, these findings have received mixed support from fMRI studies, which suggest that the mPFC may not be affect specific, but is related to various executive function [42]. In addition, in the affective ToM condition, activation of additional brain areas (the insula and precentral gyrus in ASD group, the putamen and insula in TDC group) was observed; ASD and TDC participants engaged these brain areas to a greater extent during affective ToM tasks compared to Cognitive ToM Tasks. While data on the recruitment of subcortical structures in ToM tasks has thus far been scarce, several neuroimaging studies have reported the activity of these structures during ToM tasks [13,46,47]. Specifically, it has been reported that ToM tasks related to identifying emotional state recruit emotion-related brain regions such as the amygdala, anterior insula, and thalamus [48]. The involvement of the subcortical structures in affective ToM processing provide evidence of their role in facilitating the interaction between cortical and subcortical information [49]. Greater insula activation was observed in AFF > COG contrast, especially in the ASD group. This result suggests that our ASD group depended more on increased insula activation during the affective ToM task relative to the cognitive ToM task. The insula is comprised of sub-regions with distinct functional and anatomical boundaries: anterior regions are involved in processing emotion, empathy and some cognitive functions, and posterior regions are involved in internal awareness of bodily sensations, including emotional arousal [50-53]. The insula is also known to be related to dispositional differences in empathy [54], and a recent meta-analysis has identified the insula region as a common loci of dysfunction in ASD patients [55]. Additionally, in the TDC group, the AFF > COG contrast showed increased activation in the putamen. One prior study, also employing Yoni’s task, found similar patterns of activation in the basal ganglia (BG), the simulation of an emotional state on perceiving the

same emotion in another [47,49]. Our result is consistent with previous findings that simulating mental states of others is associated with affective ToM [56]. Alternatively, the BG might be involved in affective ToM due to their role in emotion recognition and facial expression decoding [57]. Finally, exploratory correlational analysis revealed there to be an inverse relationship between autistic symptoms of social impairment and fMRI functional response for COG > PHY contrasts, which suggests that greater activation of mPFC/ACC regions was associated with a lesser symptom severity in ASD patients. ACC activation is known to be associated with effortful control of attention, cognition, and emotion in situations that involve selecting among competing responses [14]. Moreover, the differentiation of self-other agency (i.e. me versus not-me) is registered in different regions of the medial cingulate gyrus. We interpreted this hyper-activation of mPFC/ACC in the context of a compensatory mechanism, in line with similar previous reports [14]. In other words, ASD individuals with less severe symptoms were able to engage such compensatory mechanisms to a greater degree than those with more severe symptoms, especially in cognitive ToM task. The correlation between self-reported empathic abilities measured by the IRI and BOLD response across ASD and TDC groups showed a significant correlation of IRI cognitive empathy subscale with the BOLD response of affective ToM tasks (Table 4). One of the possible explanation for this correlation is that ‘affective ToM’ and ‘cognitive empathy’ are often defined in similar ways in relevant literatures, as the ability to explain, predict, and interpret another’s emotions accurately [58]. Additionally, the negative correlation between the IRI empathy subscale and contrasts of interest in cross-group was mainly driven by the TDC group, and the brain activation of the TDC individuals with lower levels of cognitive and affective empathy was greater than those with higher levels of empathy. This result suggests that in frontal control regions such as the mPFC, TDC participants with low

empathy scores may have taken a more cognitive approach to the task, increasing the contribution of these cognitive control regions [59]. On the other hand, in some PFC and STG areas, both IRI cognitive and affective empathy subscale scores correlated with the BOLD response in both cognitive and affective ToM tasks. This suggests that cognitive and affective ToM conditions may be associated with neural responses in the common ToM network [3,13]. The presence of reciprocally interconnected limbic-paralimbic and neocortical areas of the ToM network supports that there is an interacting function of the brain, whereby emotion and cognition can mutually affect each other [10]. The above study should be interpreted with caution in the context of following limitations. The majority of participants except one ASD patient were boys and only ASD participants with normal IQ were included to this study, and thus, the present results cannot be generalized to girls or ASD participants with low IQ. However, this data is nonetheless valuable, since ASD is more common in males, and there are differences in structural brain development between males and females during adolescence [59]. Therefore, averaging results across both males and females might produce noisy data that cannot represent the characteristics of either sex. Small sample size is a major limitation, which may have led to a reduced power in detecting brain activations in both group. Also, the significant differences were observed only at an uncorrected level (uncorrected p < 0.001). However, prior report suggested that this criteria is equivalent to p < 0.05 corrected by cluster level for multiple comparisons as estimated by 10,000 Monte Carlo simulations [32]. Age effects were not explored in our analysis, because there was no significant age difference between ASD and TDC groups, and the age range of the participants was not broad, mostly ranging from 11 to 14 years old. However, age can be one of the major factors affecting brain activation pattern in adolescent period. Furthermore, in several participants, ASD was comorbid with other psychiatric disorders, especially ADHD, and this may have contributed to differences in task

performance and resultant brain activation. However, the severity of ADHD was mild in our ASD subjects, and only one participants was treated with stimulant medication for ADHD symptoms. Also, behavioral performance was similar between two groups. Therefore, probably it is less likely that our results were mainly driven by the ADHD symptoms of our participants. Another limitation of this study might be the Yoni task itself. There was no performance difference between ASD and TDC groups on the ToM tasks in our study, which is somewhat different findings from the prior studies reporting impaired performance on ToM tasks in ASD patients compared to TDCs. This discrepancy might result from the limited ecological validity inherent to laboratory behavioral tasks of ToM. However, while Yoni task appears to be too simple to operationalize such a complex concept as ToM, the task has been validated and shown to be positively correlated with verbal measures of ToM, such as false belief stories [9]. Nonetheless, this task cannot disentangle which components of ToM processing (e.g. basic processing of affective cues, emotional contagion, more conscious affect sharing) might be driving the group differences in the reported regions of the significant activation difference. Future studies should aim to disentangle these processes for more complete understanding of ToM processing.

5. Conclusions Despite these limitations, our study provides useful insight into the neural correlates of ToM processing in children and adolescents with ASD. In sum, our findings extend those of other studies, demonstrating the neural bases of cognitive and affective ToM in ASD patients. From a clinical perspective, our data suggest that the recruitment of additional prefrontal resources can compensate for the successful performance in the ToM task at behavioral level. The results of this study provide the rationale for strengthening prefrontal functions, such as cognitive control, as an intervention strategy for enhancing ToM abilities in ASD patients.

Also, the recruitment of subcortical para-limbic structures in affective ToM tasks compared to cognitive ToM tasks, suggests that the intervention geared toward improving emotion-related functioning may be effective for the enhancement of affective ToM abilities in children and adolescents with ASD.

Authors contributions EK proposed the idea of this study. EK, JC, BP, JK, and HP participated in the design of the study. EK and DS evaluated the subjects participating in this study and collected clinical data from the participants. EK, JC, SK, BP and MO carried out MRI data collection and statistical analysis. EK, SK and KC drafted the manuscript. EK and SK completed to write the final manuscript. All authors read and approved the final manuscript. Disclosures None of the authors has commercial or financial interests invested in this study.

Acknowledgements This work was supported by research grants from the Yonsei University Professor Research Support Fund and the Yonjung Research Award.

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Figure Legends Figure 1. Examples of task stimulus of the Yoni ToM task adapted from Shamay-Tsoory et al. (2007) for each condition; text was written in Korean, but has been translated into English in these examples.

Figure 2. Brain regions showing significant activation differences between the ASD and TDC groups, at p < 0.001, uncorrected at the cluster level for contrasts Cognitive ToM > PC, Affective ToM > PC

Figure 3. Main effects relative to PC for (A) Affective ToM and (B) Cognitive ToM (C) Affective ToM > Cognitive ToM at p < 0.001, uncorrected in ASD group.

Figure 4. The relationship between autistic symptomatology and brain activation in the mPFC/ACC. Correlation scatterplots show individual participant's signal intensity values in the mPFC/ACC in COG > PHY contrast and ADOS social subscale scores. R values reflect correlation coefficients.

Table 1. Demographic and clinical characteristics for ASD and TDC participants ASD (n = 12)

TDC (n = 12)

Age (SD)

12.4 (2.3)

11.7 (2.2)

0.48

IQ (SD)

107.3 (13.9)

112.5 (12.3)

0.34

Verbal IQ (SD)

107.3(13.3)

116.3 (12.9)

0.12

Performance IQ (SD)

103.9(15.4)

103.1(10.8)

0.89

ADOS social

7.8 (3.2) range: 4-13

ADOS communication

4.3 (1.5) range: 3-7

Medication (yes/no)

4/12

0/12

Comorbidity (yes/no)

5/12

0/12

p

ASD: Autism Spectrum Disorder; SD: standard deviation; IQ: intelligence quotient; TDC: Typically Developing Control; ADOS social: ADOS reciprocal social interaction *p < 0.05: significant difference

Table 2. Means and standard deviations for reaction time (RT: ms) and percentage correct data for the Yoni task, presented by Condition and Group ASD (n = 12)

TDC (n = 12)

F

p

Affective TOM

2826 (466)

2695(390)

.54

0.47

Cognitive TOM

2923 (465)

2849 (378)

.17

0.68

Physical control

1780 (403)

1776 (342)

.00

0.98

Affective TOM

79.2 (14.7)

84.2 (11.9)

0.80

0.38

Cognitive TOM

71.0 (17.4)

80.4 (13.1)

2.1

0.15

Physical control

90.1 (7.6)

96.0 (3.3)

6.1

0.02*

Mean RT (SD)

Percentage correct (SD)

RT: reaction time; SD: standard deviation, ASD: Autism Spectrum Disorder, TDC: Typically Developing Controls

Table 3. The comparison of scores on the IRI subscales between ASD and TDC groups ASD (n = 12)

TDC (n = 12)

p

21.3 (4.3)

24.5 (4.3)

.09

21.8 (3.7)

26.5 (3.0)

.01*

Personal Distress (PD)

20.3 (4.8)

19.7 (4.8)

.73

Cognitive TOM (PT) Affective TOM( EC+ PD)

21.3 (4.3)

24.5 (4.3)

.09

42.2 (7.1)

46.7 (6.8)

.12

Perspective Taking (PT) Empathic Concern (EC)

Table 4. The correlation between IRI subscale scores and signal intensity in each brain regions across ASD and TDC groups

Contrast Name

mPFC (22,34,36) r p

mPFC (12,48,10) r p

STG (48,-18,2) r p

IRI (Cognitive ToM) COG > PHY

-0.05

0.834

-0.57*

0.004

-0.30

0.157

AFF > PHY

-0.44*

0.031

-0.54*

0.006

-0.52*

0.010

COG > PHY

-0.03

0.895

-0.42*

0.042

-0.31

0.14

AFF > PHY

-0.26

0.218

-0.36

0.087

-0.43*

0.038

COG > PHY

-0.20

0.351

-0.60*

0.002

-0.29

0.169

AFF > PHY

-0.43*

0.036

-0.55*

0.006

-0.37

0.079

-0.18

0.404

-0.48*

0.018

-0.38

0.069

IRI (Affective ToM)

IRI (Perspective taking)

IRI (Empathic concern) COG > PHY

AFF > PHY -0.51* 0.011 -0.48* 0.018 -0.48* 0.017 mPFC: medial prefrontal cortex, STG: superior temporal gyrus, IRI: Interpersonal reactivity index, ToM: theory of mind, COG: cognitive ToM, AFF: affective ToM, PHY: physical control, * p < 0.05, significant correlation