Eric Courchesne

Unusual brain growth patterns in early life in patients with autistic disorder An MRI study

Objective: To quantify developmental abnormalities in cerebral and cerebellar volume in autism. Methods: The authors studied 60 autistic and 52 normal boys (age, 2 to 16 years) using MRI. Thirty autistic boys were diagnosed and scanned when 5 years or older. The other 30 were scanned when 2 through 4 years of age and then diagnosed with autism at least 2.5 years later, at an age when the diagnosis of autism is more reliable. Results: Neonatal head circumferences from clinical records were available for 14 of 15 autistic 2- to 5-year-olds and, on average, were normal (35.1 ± 1.3 cm versus clinical norms: 34.6 ± 1.6 cm), indicative of normal overall brain volume at birth; one measure was above the 95th percentile. By ages 2 to 4 years, 90% of autistic boys had a brain volume larger than normal average, and 37% met criteria for developmental macrencephaly. Autistic 2- to 3-year-olds had more cerebral (18%) and cerebellar (39%) white matter, and more cerebral cortical gray matter (12%) than normal, whereas older autistic children and adolescents did not have such enlarged gray and white matter volumes. In the cerebellum, autistic boys had less gray matter, smaller ratio of gray to white matter, and smaller vermis lobules VI–VII than normal controls. Conclusions: Abnormal regulation of brain growth in autism results in early overgrowth followed by abnormally slowed growth. Hyperplasia was present in cerebral gray matter and cerebral and cerebellar white matter in early life in patients with autism.

Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects

OBJECTIVES Electrical potentials produced by blinks and eye movements present serious problems for electroencephalographic (EEG) and event-related potential (ERP) data interpretation and analysis, particularly for analysis of data from some clinical populations. Often, all epochs contaminated by large eye artifacts are rejected as unusable, though this may prove unacceptable when blinks and eye movements occur frequently. METHODS Frontal channels are often used as reference signals to regress out eye artifacts, but inevitably portions of relevant EEG signals also appearing in EOG channels are thereby eliminated or mixed into other scalp channels. A generally applicable adaptive method for removing artifacts from EEG records based on blind source separation by independent component analysis (ICA) (Neural Computation 7 (1995) 1129; Neural Computation 10(8) (1998) 2103; Neural Computation 11(2) (1999) 606) overcomes these limitations. RESULTS Results on EEG data collected from 28 normal controls and 22 clinical subjects performing a visual selective attention task show that ICA can be used to effectively detect, separate and remove ocular artifacts from even strongly contaminated EEG recordings. The results compare favorably to those obtained using rejection or regression methods. CONCLUSIONS The ICA method can preserve ERP contributions from all of the recorded trials and all the recorded data channels, even when none of the single trials are artifact-free.

Hypoplasia of Cerebellar Vermal Lobules VI and VII in Autism

Autism is a neurologic disorder that severely impairs social, language, and cognitive development. Whether autism involves maldevelopment of neuroanatomical structures is not known. The size of the cerebellar vermis in patients with autism was measured on magnetic resonance scans and compared with its size in controls. The neocerebellar vermal lobules VI and VII were found to be significantly smaller in the patients. This appeared to be a result of developmental hypoplasia rather than shrinkage or deterioration after full development had been achieved. In contrast, the adjacent vermal lobules I to V, which are ontogenetically, developmentally, and anatomically distinct from lobules VI and VII, were found to be of normal size. Maldevelopment of the vermal neocerebellum had occurred in both retarded and nonretarded patients with autism. This localized maldevelopment may serve as a temporal marker to identify the events that damage the brain in autism, as well as other neural structures that may be concomitantly damaged. Our findings suggest that in patients with autism, neocerebellar abnormality may directly impair cognitive functions that some investigators have attributed to the neocerebellum; may indirectly affect, through its connections to the brain stem, hypothalamus, and thalamus, the development and functioning of one or more systems involved in cognitive, sensory, autonomic, and motor activities; or may occur concomitantly with damage to other neural sites whose dysfunction directly underlies the cognitive deficits in autism.

Why the frontal cortex in autism might be talking only to itself: local over-connectivity but long-distance disconnection.

Although it has long been thought that frontal lobe abnormality must play an important part in generating the severe impairment in higher-order social, emotional and cognitive functions in autism, only recently have studies identified developmentally early frontal lobe defects. At the microscopic level, neuroinflammatory reactions involving glial activation, migration defects and excess cerebral neurogenesis and/or defective apoptosis might generate frontal neural pathology early in development. It is hypothesized that these abnormal processes cause malformation and thus malfunction of frontal minicolumn microcircuitry. It is suggested that connectivity within frontal lobe is excessive, disorganized and inadequately selective, whereas connectivity between frontal cortex and other systems is poorly synchronized, weakly responsive and information impoverished. Increased local but reduced long-distance cortical-cortical reciprocal activity and coupling would impair the fundamental frontal function of integrating information from widespread and diverse systems and providing complex context-rich feedback, guidance and control to lower-level systems.

Impairment in shifting attention in autistic and cerebellar patients

MRI and autopsy evidence of early maldevelopment of cerebellar vermis and hemispheres in autism raise the question of how cerebellar maldevelopment contributes to the cognitive and social deficits characteristic of autism. Compared with normal controls, autistic patients and patients with acquired cerebellar lesions were similarly impaired in a task requiring rapid and accurate shifts of attention between auditory and visual stimuli. Neurophysiologic and behavioral evidence rules out motor dysfunction as the cause of this deficit. These findings are consistent with the proposal that in autism cerebellar maldevelopment may contribute to an inability to execute rapid attention shifts, which in turn undermines social and cognitive development, and also with the proposal that the human cerebellum is involved in the coordination of rapid attention shifts in a fashion analogous to its role in the coordination of movement.

Analysis and visualization of single-trial event-related potentials

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single‐trial multichannel EEG data from event‐related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra‐brain sources. Both the data and their decomposition are displayed using a new visualization tool, the “ERP image,” that can clearly characterize single‐trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye‐movement artifacts. Results show that ICA can separate artifactual, stimulus‐locked, response‐locked, and non‐event‐related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single‐trial EEG records, (2) identification and segregation of stimulus‐ and response‐locked EEG components, (3) examination of differences in single‐trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between‐subject component stability of ICA decomposition of single‐trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event‐related potentials, and event‐modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event‐related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Hum. Brain Mapping 14:166–185, 2001.

Mapping Early Brain Development in Autism

Although the neurobiology of autism has been studied for more than two decades, the majority of these studies have examined brain structure 10, 20, or more years after the onset of clinical symptoms. The pathological biology that causes autism remains unknown, but its signature is likely to be most evident during the first years of life when clinical symptoms are emerging. This review highlights neurobiological findings during the first years of life and emphasizes early brain overgrowth as a key factor in the pathobiology of autism. We speculate that excess neuron numbers may be one possible cause of early brain overgrowth and produce defects in neural patterning and wiring, with exuberant local and short-distance cortical interactions impeding the function of large-scale, long-distance interactions between brain regions. Because large-scale networks underlie socio-emotional and communication functions, such alterations in brain architecture could relate to the early clinical manifestations of autism. As such, autism may additionally provide unique insight into genetic and developmental processes that shape early neural wiring patterns and make possible higher-order social, emotional, and communication functions.

Cerebral Lobes in Autism: Early Hyperplasia and Abnormal Age Effects

Metabolic, functional, behavioral, and histologic studies suggest that the structure of the cerebrum may be abnormal in autism. In a previous cross-sectional study we found abnormal enlargement of cerebral cortex and cerebral white matter volumes in autistic 2- and 3-year-olds and abnormally slow rates of volume change across later ages. In the present study, we assessed whether these volume abnormalities are limited to particular cerebral regions or are pervasive throughout the cerebrum. We used magnetic resonance imaging (MRI) to quantify volumes of cerebral lobes (frontal, temporal, parietal, and occipital regions), using classic sulcal boundaries to define regions. We examined 38 boys with autism and 39 normal control boys between the ages of 2 and 11 years. Several regions showed signs of gray matter and white matter hyperplasia in 2- and 3-year-old patients (as much as 20% enlargement), but there appeared to be an anterior to posterior gradient in the degree of hyperplasia. The frontal lobe showed the greatest enlargement while the occipital lobe was not significantly different from normal. Gray and white matter differences were not found in the older children. By examining the relationships between regional volumes and subject age, we found that frontal, temporal, and parietal white matter volumes, as well as frontal and temporal gray matter volumes, changed at significantly slower rates in autism patients than in controls across the 2- to 11-year-age range. For example, frontal lobe white matter volume increased by about 45% from 2-4 years of age to 9-11.5 years, but by only 13% in autistic patients. Mechanisms that might account for early hyperplasia are discussed as they might relate to the regional differences in degree of abnormality. For instance, possible influences of neurotrophic factors, or of abnormal afferent activity from other affected brain regions are considered.

When Is the Brain Enlarged in Autism? A Meta-Analysis of All Brain Size Reports

BACKGROUND Multiple studies have reported increased brain size in autism, while others have found no difference from normal. These conflicting results may be due to a lack of accounting for age-related changes in brain enlargement, use of small sample sizes, or differences in data acquisition methods. METHODS Reports of autism head circumference (HC), magnetic resonance imaging (MRI), and post-mortem brain weight (BW) that met specific criteria were identified and analyzed. Percent difference from normal values (%Diff) and standardized mean differences (SMD) were calculated to compare brain size across studies and measurement methods. Curve fitting, analysis of variance, and heterogeneity analyses were applied to assay the effects of age and measurement type on reported brain size in autism. RESULTS A fitted curve of HC and MRI %Diff values from 15 studies revealed a largely consistent pattern of brain size changes. Specifically, brain size in autism was slightly reduced at birth, dramatically increased within the first year of life, but then plateaued so that by adulthood the majority of cases were within normal range. Analysis of variance of MRI and post-mortem %Diff values by age group (young child, older child, adult) and measurement type (MRI, BW) revealed a significant main effect of both age and measurement type, with the youngest ages (2-5) showing the greatest deviation from normal. Random effects heterogeneity analysis revealed a significant effect of age on HC and MRI SMD. CONCLUSIONS These findings reveal a period of pathological brain growth and arrest in autism that is largely restricted to the first years of life, before the typical age of clinical identification. Study of the older autistic brain, thus, reflects the outcome, rather than the process, of pathology. Future research focusing on this early process of brain pathology will likely be critical to elucidate the etiology of autism.

Evidence of linkage between the serotonin transporter and autistic disorder

The serotonin transporter gene (HTT) is a primary candidate in autistic disorder based on efficacy of potent serotonin transporter inhibitors in reducing rituals and routines. We initiated a candidate gene study of HTT in trios consisting of probands with autistic disorder and both parents. Preliminary transmission/disequilibrium test (TDT) analysis with 86 families revealed no evidence for linkage or linkage disequilibrium between autistic disorder and a polymorphism in the second intron of HTT. However, preferential transmission of a short variant of the HTT promoter was found in the same 86 trios (TDT χ2 = 4.69, 1 d.f., P = 0.030). In further analyses, we considered haplotypes of the HTT promoter variant and second intron locus as alleles in a multiallelic TDT. Results confirmed the significance of the effect of this region (TDT χ2 = 11.85, 4 d.f., P = 0.018). This provides preliminary evidence of linkage and association between HTT and autistic disorder.