Heterogeneity in the patterns of neural abnormality in autistic spectrum disorders: evidence from ERP and MRI.
Autistic spectrum disorder (ASD) refers to a heterogeneous group of social communication problems. Research into the neural basis of ASD has revealed abnormalities in a number of different regions of the brain. However, the literature is highly inconsistent. One possible explanation for these discrepancies is differences in intelligence. Children with ASD and below average intelligence may be hypothesised to show additional or different neural abnormalities. This possibility was explored using structural magnetic resonance imaging (MRI) and event-related potentials (ERP). Two groups of children with ASD were studied, those with average or above average intelligence (high ASD group) and those with below average intelligence (low ASD group). The structural MRI data were analysed using voxel-based morphometry (VBM). Using the family-wise error threshold, results showed bilateral abnormality common to the two ASD groups in the cerebellum, fusiform gyrus and frontal cortex. In addition, a number of regions were found to be significantly different in the two ASD groups: regions of the cerebellum showed increased grey matter density bilaterally in the high ASD group, but decreased grey matter density bilaterally in the low ASD group. Further, compared to the high ASD group, additional bilateral abnormalities were found in the postcentral gyrus and regions of the dorsolateral prefrontal cortex in the low ASD group. Using the less stringent false discovery rate (FDR) threshold, differences were also seen in the medial temporal lobes. ERPs also showed differences between the two ASD groups. Whereas the ERPs of the high ASD group were not significantly different from those of the controls, the low ASD group had delayed novelty P3a responses and reduced amplitude target P3b components. These data provide convergent ERP and MRI evidence for the heterogeneity of neural abnormality in ASD in relation to variations in intelligence.
Salmond
Claire H
CH
Developmental Cognitive Neuroscience Unit, Institute of Child Health, University College London, London, UK. claire.salmond@iop.kcl.ac.uk
Vargha-Khadem
Faraneh
F
Gadian
David G
DG
de Haan
Michelle
M
Baldeweg
Torsten
T
D000293:Adolescent; D000704:Analysis of Variance; D001321:Autistic Disorder / Q000145:classification / Q000473:pathology / Q000503:physiopathology*; D001921:Brain / Q000002:abnormalities / Q000502:physiology* / Q000503:physiopathology; D001931:Brain Mapping; D016022:Case-Control Studies; D002648:Child; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D016555:Matched-Pair Analysis; D046709:Pattern Recognition, Physiological / Q000502:physiology; D012016:Reference Values; D012720:Severity of Illness Index; D018709:Statistics, Nonparametric; D014705:Verbal Behavior / Q000502:physiology*