Artigo
Artigo
Artigo
705
pISSN: 0513-5796, eISSN: 1976-2437
Yonsei Med J 56(3):705-711, 2015
2
Division of Child and Adolescent Psychiatry, Department of Psychiatry and Institute of Behavioral Science in Medicine,
Yonsei Autism Laboratory, Yonsei University College of Medicine, Seoul;
3
Department of Art Therapy, Daegu Cyber University, Daegu;
4
Department of Psychiatry, Konyang University College of Medicine, Daejeon, Korea.
Receievd: October 10, 2014 Purpose: We aimed to determine whether Autism Spectrum Disorder (ASD)
Revised: December 11, 2014 would show neural abnormality of the social reward system using functional MRI
Accepted: December 15, 2014 (fMRI). Materials and Methods: 27 ASDs and 12 typically developing controls
Corresponding author: Dr. Keun-Ah Cheon,
(TDCs) participated in this study. The social reward task was developed, and all
Division of Child and Adolescent Psychiatry,
Department of Psychiatry and Institute of
participants performed the task during fMRI scanning. Results: ASDs and TDCs
Behavioral Science in Medicine, with a social reward learning effect were selected on the basis of behavior data.
Yonsei Autism Laboratory, We found significant differences in brain activation between the ASDs and TDCs
Yonsei University College of Medicine, showing a social reward learning effect. Compared with the TDCs, the ASDs
50-1 Yonsei-ro, Seodaemun-gu,
showed reduced activity in the right dorsolateral prefrontal cortex, right orbitofron-
Seoul 120-752, Korea.
tal cortex, right parietal lobe, and occipital lobe; however, they showed increased
Tel: 82-2-2228-1633, Fax: 82-2-313-0891
E-mail: kacheon@yuhs.ac activity in the right parahippocampal gyrus and superior temporal gyrus. Conclu-
sion: These findings suggest that there might be neural abnormality of the social
∙ The authors have no financial conflicts of reward learning system of ASDs. Although this study has several potential limita-
interest. tions, it presents novel findings in the different neural mechanisms of social re-
ward learning in children with ASD and a possible useful biomarker of high-func-
tioning ASDs.
INTRODUCTION
it is also helpful for observing the brain activities of sub- cent psychiatric clinic in Severance Children’s Hospital af-
jects while the subjects perform certain task stimuli.3 Previ- filiated with Yonsei University College of Medicine and
ous studies have taken multiple approaches to examining from an ongoing community epidemiological study in the
social brain abnormalities in ASDs. Many researchers have city of Goyang in South Korea. We initially enrolled and
demonstrated aberrant neural mechanism in social cogni- scanned 45 children (39 boys, 6 girls); however, six boys
tion of those with ASD in facial processing studies using met at least one exclusion criterion. Accordingly, we ana-
fMRI.4-6 Other prior studies have examined differences of lyzed the data of 39 subjects (27 ASDs, mean age 9.9±2.5;
functional connectivity between ASDs and a healthy con- 12 TDCs, mean age 9.2±1.8) (Table 1). For all children
trol group. They reported that ASDs showed significantly with ASD, the ASDs diagnosis was obtained independently
reduced functional connectivity compared to TDCs.7-9 by two child and adolescent psychiatrists based on the Di-
ASDs are known to be less reinforced by positive social agnostic and Statistical Manual of Mental Disorders, 4th
reward such as praise or smiling toward them. Some re- Edition, Text Revision (DSM-IV-TR) criteria.15 The follow-
searchers reported that deficit in social reward leaning would ing characteristics were exclusionary for ASDs: 1) a past or
result in qualitative impairment of social function in chil- present history of brain damage or convulsive disorder; 2)
dren with ASD.10 There have been few functional studies intellectual disability or language delay; and 3) comorbid
related to the reward system of a social learning mechanism child and adolescent psychiatric disorders. All TDCs were
of ASDs. One previous study reported that the lateral pre- screened by two child and adolescent psychiatrists with as-
frontal cortex was involved in the integration of cognitive sessments including a psychological assessment and a neuro-
and motivational information and made accurate reward-re- logical examination. None of the TDCs had a past or current
lated decisions in complicated circumstances.11 Another developmental, medical, or psychiatric diagnosis. Partici-
study demonstrated that children with ASD fewer frontos- pants were not sedated for the MRI scanning, and none were
triatal responses to social rewards than TDCs. These de- taking any psychoactive medications on the day of the scan-
creased responses suggested the neural impairment of so- ning. This study was approved by the respective Institutional
cial learning in children with ASD.12 There have been sev- Review Boards for research with human subjects at Yonsei
eral attempts to find social brain abnormalities in Asian University Severance Hospital, where this study was per-
children with ASD,13,14 however none of these have includ- formed, and at the Gachon Neuroscience Research Institute
ed a functional brain imaging study using Korean subjects in Incheon, South Korea, where all subjects were scanned.
with ASD. All subjects and their parents were given a full description
In this study, we aimed to demonstrate a neural mecha- of the study and provided prior written informed assent and
nism related to a reward system during a social learning task consent, respectively.
with Korean children with ASD. We postulated two hypothe-
ses. The first hypothesis was that social reward learning in Screening and diagnostic tools
children with ASD would be less complete than in the
healthy controls. The second hypothesis was that the neural Social Responsiveness Scale (SRS)-Korean version
mechanisms of social reward systems would differ between The SRS-K was used to screen those with ASD and TDCs
children with ASD and TDCs and that the social reward before the confirmative diagnostic procedure. The severity
leaning process of an aberrant neural system in children with of autism symptoms was quantified by the SRS, which con-
ASD could contribute to the social deficit of ASDs. Both sists of a 65-item rating scale commonly used with clinical
ASDs and TDCs were asked to perform a social learning and general populations. Measurements of social impair-
task during a functional MRI scan in this study. During the ments of children were reported by their parents or teachers
task, subjects sought the correct answers using social cues. in their social situations. All items were rated between 0
and 3 and consisted of social awareness, characteristic autis-
tic preoccupations/traits, social information processing, social
MATERIALS AND METHODS anxiety/avoidance, and capacity for reciprocal social re-
sponses. The SRS is designed to determine a singular scale
Subjects score that presents the severity of social implements in those
ASDs and TDCs were recruited from a child and adoles- with ASD.16 The English version of the SRS strongly corre-
lates with DSM-IV-TR criteria scores estimated from the Korean Educational Development Institute-Wechsler
Autism Diagnosis Interview-Revised (ADI-R). It also shows Intelligence Scale for Children-Revised-III (KEDI-WISC)
high test-retest reliability and separates children who show All children with ASD and TDCs were measured for full
pervasive developmental disorders from children who show scale, performance, and verbal IQ [full-scale IQ (FIQ), per-
other psychiatric disorders.17 We completed the translation formance IQ (PIQ), and verbal IQ (VIQ)].
and back-translation of the English version of the SRS and
gathered the screening data of approximately 1280 children. Scanning procedures
In male children, the recommended cut-off score (above 70) We performed our experiment using a 3-Tesla MRI scanner
of American children corresponded to the 97th percentile (MAGNETON Verio, Siemens, Muenchen, Germany). Func-
scores in the Korean sample. This indicated an 83% positive tional and anatomical images were acquired through differ-
predictive value of ASDs diagnoses (in submission). ent MRI sequences. Functional images were obtained with a
gradient echo single-shot echo planar image sequence [repeti-
Autism Diagnosis Interview-Revised-Korean version tion time (TR)=2000 ms; echo time (TE)=30 ms; in-plane
(ADI-R-K) and Autism Diagnostic Observation Schedule- resolution=3.4×3.4 mm2; slice thickness=3 mm]. After ac-
Korean version (ADOS-K) quiring a functional image, we also scanned a T1 weighted
The ADI-R-K and ADOS-K were used in the diagnosis of image to acquire an anatomical image with specific scan pa-
ASDs. The ADI-R18 is an interview of caregivers and is rameters (TR=1900 ms; TE=2.93 ms; in-plane resolu-
common and semi-structured. The ADI-R provides algo- tion=1×1 mm2; slice thickness=1 mm). T1 weighted and
rithms for the 10th revision of the International Statistical functional images had the same orientation for better co-
Classification of Diseases and Related Health Problems registration in three-dimensional space (3D-space).
(ICD-10) and DSM-IV-TR for definitions of autism. In this
interview, more than 100 items cover information about lan- Experimental design
guage, communication, play, social development, develop- An auditory discrimination task was used, where subjects
mental milestones, and unusual behaviors and interests. had to judge the direction of the presented auditory stimulus.
ADI-R diagnostic criteria require a specified threshold on Linear frequency modulated (FM) tones with a duration of
four algorithm domains: communication, repetitive behav- 600 ms served as acoustic stimuli. The FM tones differed in
iors, social interaction, and age at which certain symptoms direction of frequency modulation (20 upward/ascending,
start. The ADOS19 is also a common diagnosis tool that 20 downward/descending) and in center frequency (Fc=
contains a semi-structured assessment of social interaction, 1100‒3000 Hz in steps of 100 Hz), with starting and ending
communication, play, and imaginative use of materials in frequencies calculated by Fc (Hz)±Fc (Hz)/2×Δt (s). A total
subjects with ASD. Compared with the ADI-R, which esti- of 73 FM tones were presented pseudo-randomly in an
mates current and earlier development of ASDs, the ADOS event-related design with a jittered intertrial interval of 6, 8,
estimates the current status. In the ADOS, planned social and 10 s. At the beginning of each trial, subjects were
activities are created in which a range of social initiations shown a real facial image (front view) of an unknown male
and responses are likely to appear, and communication op- person in color with a neutral facial expression. The same
portunities are designed to elicit a range of interchanges. image was used as a control for the whole experiment. Af-
This includes play situations to allow observations of a range ter the presentation of this image, which jittered at intervals
of imaginative activities and social role-play. It also provides of 6, 8, and 10 s, subjects were required to judge the direc-
standard contexts of materials, structured activities, and less tion of acoustic stimuli by pressing the correct button. They
structured interactions for understanding ASDs. The ADOS were asked to press either the right or left button; however,
includes four modules which are appropriate for children they needed to guess which one for ascending or descend-
and adults at different developmental and language levels. ing stimulus at first trial in which they did not receive any
The ADI-R and ADOS have long been the gold standard cues for the answer. Immediately following the button press,
for autism diagnosis.18,19 We also translated and back-trans- either a positive or negative emotion shown on a real facial
lated the ADI-R and ADOS and estimated their validities image of an unknown female person was presented to al-
in Korean children (personal communication, Dr. Y.S. Kim, low the subjects to determine whether their response was
December 2009). correct. The image was a frontal view with the hand in ei-
ther a thumbs-up (in the case of positive emotion in the ance (ANOVA) with a random effect included in Brain Voy-
face) or thumbs-down (negative) position. ager QX. All regions of interest (ROIs) were selected based
on a threshold of p<0.05. Beta values of ROIs were extracted
Data analysis and analyzed using a two-way ANOVA to confirm the statis-
tical significance of all ROIs.
Behavior data analysis
The correct answer was defined as “1,” and the wrong an-
swer was defined as “0”. From the first trial to the last trial,
RESULTS
all correct answers were added to the next trial. These accu-
mulative correct answers were calculated as percentage val- Table 1 showed no significant differences of age, FIQ, and
ues. If the accumulative accuracy curve showed an increas- PIQ; however, slightly significant differences of VIQ and
ing pattern (i.e., the gradient value of the curve was greater SRS scores between the ASDs and TDCs were found (inde-
than zero by a regression analysis, and the final accuracy pendent t-test, p<0.05). Two ASDs (ASDs with social reward
was above 50%), it was defined as a learning effect of so- learning effect and ASDs without social reward learning ef-
cial reward. fect) also showed no significant differences of age, FIQ, PIQ,
VIQ, SRS scores, and ADI-R scores, except for the ADI-re-
Functional data analysis stricted repetitive behavior (RRB) score and ADOS scores
Functional data were analyzed using Brain Voyager QX (independent t-test, p<0.05).
(Brain Innovation B.V., Maastricht, the Netherlands). Ana-
tomical data were preprocessed by a spatial normalization Behavior results of the subjects
(Talairach transformation). Functional data were prepro- 20 children in total showed a social reward learning effect
cessed using slice-timing correction, head-motion correction, during the social reward task (Fig. 1). 15 children in the ASDs
and temporal filtering. These functional data were co-regis- (55.6%) and 5 children in the TDCs (41.7%) showed a social
tered with each of the normalized anatomical images. We reward learning effect in the behavior result (p<0.001).
performed an individual analysis of selected subjects in the
first step and a group analysis in the subsequent step. The ac- Comparison of fMRI results between ASDs and TDCs
tivation map was made by the contrast of all feedback phases showing a social reward learning effect
>base phase (non-feedback phase). In the group analysis, The fMRI results of the 20 children who showed social re-
several brain regions were found using an analysis of vari- ward learning effects were analyzed. ASDs with a social re-
ward learning effect showed more increased responses in the ASDs with a social reward learning effect in several areas,
right parahippocampal gyrus (PG) [F(1,18)=7.166; p<0.05] including the right dorsolateral prefrontal cortex (DLPFC) [F
and in the right superior temporal gyrus (STG) [F(1,18)= (1,18)=5.959; p<0.05], right orbitofrontal cortex (OFC)
10.622; p<0.01] than TDCs with a social reward learning ef- [F(1,18)=8.834; p<0.01), right parietal lobe [F(1,18)=6.464;
fect (Fig. 2). On the other hand, TDCs with a social reward p<0.05], and occipital lobe [F(1,18)=7.616; p<0.05] (Fig. 2,
learning effect showed significantly more responses than Table 2).
100 100
90 y=0.3491x+61.291 90 y=0.3491x+61.291
80 80
Accumulative accuracy
Accumulative accuracy
70 70
y=0.4907x+47.095
60 60
50 50
y=-0.0356x+55.951
40 40
30 30
20 ASD 20 LE
10 TDC 10 nLE
0 0
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73
Trials Trials
A B
Fig. 1. Behavioral results of the subjects. (A) Comparison between the ASDs and TDCs who showed a social reward learning effect. There was no signifi-
cant difference between the two groups. (B) Comparison between different ASDs subgroups. LE, subgroup with a social reward learning effect; nLE, sub-
group without a social reward learning effect; ASD, Autism Spectrum Disorder; TDC, typically developing control.
ASD>TDC
TDC>ASD
B
Fig. 2. Different brain activation maps of ASDs and TDCs with a social reward learning effect. (A) Different brain activation maps of the ASDs> the TDCs con-
trast. The parahippocampal gyrus and superior temporal cortex were observed (ANOVA analysis with random effect GLM, p<0.01, uncorrected). (B) Different
brain activation maps of the TDCs> the ASDs contrast. The dorsolateral prefrontal cortex, orbitofrontal cortex and parietal lobe were observed (ANOVA analy-
sis with random effect GLM, p<0.01, uncorrected). ANOVA, analysis of variance; GLM, general linear model; ASD, Autism Spectrum Disorder; TDC, typically
developing control; PG, parahippocampal gyrus; STG, superior temporal gyrus; DLPFC, dorsolateral prefrontal cortex; OFC, orbitofrontal cortex.
Table 2. Comparison of Activated Brain Areas during the Task in the ASDs and TDCs with a Social Reward Learning Effect
Talaiach coordinates
Comparison Hemisphere Region BA z-value p value
x y z
Right Parahippocampal gyrus BA19 23 -50 0 7.166 0.015
ASD>TDC
Right Superior temporal gyrus BA41 46 -36 9 10.622 0.004
Right Occipital lobe BA18 -6 -89 -13 7.616 0.013
Right Dorsolateral prefrontal cortex BA9 26 32 25 5.959 0.025
TDC>ASD
Right Orbitofrontal cortex BA11 33 41 -6 8.834 0.008
Right Parietal lobe BA7 24 -57 43 6.464 0.020
ASD, Autism Spectrum Disorder; TDC, typically developing control; BA, brodmann area.
By two-way analysis of variance with a random effect.
social reward system in children with ASD. 11. Sakagami M, Watanabe M. Integration of cognitive and motiva-
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Y Acad Sci 2007;1104:89-107.
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ACKNOWLEDGEMENTS and social understanding in individuals with autism: evidence
from fMRI and ERP measurements. Soc Cogn Affect Neurosci
2014;9:1203-13.
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