In Press: Carol Armstrong, Ed., Handbook of Medical Neuropsychology. New York: Springer Science.

Transcription

1 In Press: Carol Armstrong, Ed., Handbook of Medical Neuropsychology. New York: Springer Science. Autism and Asperger s Syndrome: A Cognitive Neuroscience Perspective Jeanne Townsend, Ph.D., Marissa Westerfield, Ph.D. Department of Neurosciences, University of California, San Diego Table of Contents History and Background Biological Underpinnings Neuroanatomy Postmortem Studies MRI Studies White Matter Connectivity EEG Abnormalities Seizures Diagnosis Screening Guidelines Clinical & Research Criteria Increased Prevalence of Autism It s not the vaccine Neurocognitive Mechanisms Major Cognitive Models Cognitive Profiles Attention Sensation/Perception Language Social/Emotional Treatment Behavioral Pharmacologic Summary & Conclusions 1

2 HISTORY AND BACKGROUND Leo Kanner, an Austrian born American psychiatrist first described autism in His observations of a small group of children with behavioral symptoms of social withdrawal, impaired language/communication and obsession with sameness led to recognition of autism as a specific pervasive developmental disorder. At about the same time Austrian psychiatrist Hans Asperger independently described similar symptoms in a small group of children except that the Asperger children were high functioning with better language and cognitive skills than those described by Kanner 11. Both Kanner and Asperger used the word autistic to describe the pathology in the children they observed a term rooted in the Greek autos (self) and coined by Swiss psychiatrist Eugen Bleuler to describe symptoms in his schizophrenic patients. Before Kanner and Asperger defined autism as a specific disorder, children with autistic symptoms were most likely classed and treated as mentally retarded or, if they were high functioning, perhaps as schizophrenic. The symptoms described by Kanner and Asperger remain the core diagnostic symptoms for autism and associated disorders. Autism Spectrum Disorders (ASD) as specified in the DSM-IV TR (a text revision of the DSM-IV) include autistic disorder (classic autism), Asperger s disorder, pervasive developmental disorder not otherwise specified, Rett s disorder, and childhood disintegrative disorder 8. This chapter is limited to discussion of autistic disorder and Asperger s disorder. BIOLOGICAL UNDERPINNINGS Neuroanatomic Abnormalities. Studies of neuroanatomic abnormality in autism are generally inconsistent and often controversial. There has been a veritable explosion of the number of MRI anatomic studies in the last decade. The methods are quite variable, samples are usually small, and, with a few exceptions, there is little agreement overall. Some newer smoothing and normalization techniques used to process MRI data require, at the very least, the questionable assumption that ASD brains can be warped accurately to a standard normal template. Some studies make strong claims about small structures (e.g., the amygdala) when their image analysis has smoothed across an area that is similar in size to the structure of interest. That is, they very well may have included surrounding tissue in the measurement of the structure of interest. A few things are clear. There is widespread but heterogeneous brain structural abnormality in autism that can be seen on postmortem exam and MRI. Abnormalities are developmental in nature and most likely begin during prenatal or early post-natal brain development. The most common findings are summarized below, but an exhaustive review is beyond the scope of this chapter. The most commonly reported findings include abnormalities in the brainstem, cerebellum, limbic system and overall brain size. 7, 30, 77, 224, 231 Postmortem Studies. Recent reviews of the postmortem literature summarize neuropathology in a total of 58 postmortem cases. The most consistent findings are in the cerebellum and brainstem. Autopsy studies have found reduced numbers of Purkinje neurons in the cerebellar vermis and hemispheres 15, 28, 97, 162, 251, 314. Purkinje neuron loss in autism is patchy, and the amount and distribution of loss across the cerebellar hemispheres and vermis differs from individual to individual. Neural ectopias in the inferior cerebellar peduncle and malformation of the inferior olives, a 2

3 crucial afferent structure of the cerebellum, have also been found 15, 162, 252. In total, cerebellar anatomic abnormality was present in of all 29 (72-86%) cases in which the cerebellum was examined. These findings are from 6 independent lab groups. Abnormality in limbic structures (hippocampus, amygdala, subiculum, entorhinal cortex, anterior cingulate gyrus, mammillary body, septum) was present in a majority of autism cases examined 15, 28, 122, 247. When present, limbic system abnormality involved increased packing density of neurons and reduction in neuron sizes or a reduced number of neurons 272. In total, cerebellar anatomic abnormality was also present in 9 of 14 (64%) cases in which the limbic system was examined. Few abnormalities have been reported in cerebral cortex on postmortem exam. Five groups have examined neocortex in 15 cases and found no differences from controls except for 5 cases in which cells in the anterior cingulate were poorly laminated 161. However, a number of irregularities in cell migration and white matter have been identified including: thickened cortices, high neuronal density, neurons in the molecular layer, irregular laminar patterns (poor grey-white matter boundaries) and ectopias 15. Smaller and less compact minicolumns in frontal and temporal lobes were found in 9 autistic subjects 50. Adult brain weight has been found to be normal or lighter than normal in autism but brain weight from children has been found to be statistically heavier than controls 29. A review of 21 postmortem cases found that compared to a large database of 8000 control cases, 17 were normal weight, 1 was microencephalic and 3 were megaencephalic 73. A more recent review of 55 postmortem autism cases 248 shows highly variable brain weight results. On average, the autism cases were 6% (SD 12%) heavier than age matched controls (a large averaged database). The brains of young children (3-5) were statistically larger than controls but those of older children and adults were not. In the cerebellar nuclei and the inferior olive, Bauman found large neurons in children and small pale neurons in adults 27. This combined with evidence that brain weight may be greater than normal in autistic children and somewhat smaller than normal in adults with autism suggests an on-going neuropathological process in autism 30. MRI Studies. The first quantitative MRI studies identified abnormally reduced 110, 220 size of cerebellar hemispheres and sub-regions within the vermis in autistic children and adults 66, 67. From that time until 2003, twelve additional studies with a total of several hundred subjects from seven independent labs reported significantly reduced 48, 60-62, 70, 74, 131, 153, 154, 180, 264, 322 size in one or another sub-region of the vermis or hemispheres 74, or in overall cerebellar gray matter 208. In some few cases, cerebellar size reduction was so substantial that it could be detected by visual inspection 214. Similar hypoplasia in the brainstem has also been reported 131. While postmortem findings are highly consistent regarding cerebellar and brainstem abnormality, a number of MRI studies have failed to find cerebellar hypoplasia in autistic subjects e.g., 101, 137, 243. Some have reported larger than normal overall cerebellar volume in autism 127, 281, but these effects are related to overall larger brain size and not to specific cerebellar overgrowth. Unlike postmortem studies, MRI studies usually employ group analysis rather than a case by case comparison. So, the critical issues are statistical power, sample heterogeneity and the nature of the control sample. For example, while Purkinje cell loss manifests as a dramatic effect on postmortem exam, it is reflected only in small volume changes on MRI (around 10% in the posterior vermis 3

4 much less in the whole cerebellum). So, power is a huge issue. Most samples are quite small (under 20), and variability in measures is nearly always quite large. Additionally, if the brain is large as is commonly reported in autism (see below), the cerebellum will be proportionally large and hypoplastic regions of the cerebellum will not be reflected in absolute numbers. There is also some evidence of association of verbal IQ and cerebellar measures (e.g., some have reported that the size of the cerebellar vermis is normal or larger than normal in those with high verbal IQ 72, 127 ). It is generally the case that studies finding no difference in cerebellar vermal measures have studied autism samples with normal or above normal verbal IQ. Reduced parietal volume in adults 69 has been reported. Consistent with parietal volume loss are reports of reduced thickness of the posterior corpus callosum 91, 201, 242, 264. There are reports of abnormal frontal gyrification patterns 129 and sulcal shifting in frontal and temporal cortex 181. MRI studies have also found the following in autistic patients: reduced amygdala or hippocampal volume 12, 133, 153, 238 ; enlarged amygdala or hippocampal volume 139, 271 ; reduced cross-sectional area of the dentate gyrus 265. Some of the variability in these findings may be age-related with young children showing enlarged limbic regions 271, 281 but adolescents-adults showing no difference 132, 244, 264 or smaller limbic regions 12, 238. Increased total brain area or volume has also been reported in autism these findings are generally consistent in young children but more varied in older children and adults. For example, total brain volume was found to be enlarged in autism in young children (age 4) 281 and in children younger than Cortical volume was enlarged in autism in young (age 2-3) but not in older children 49, 74. Increased total brain volume (total gray and white matter only) has been reported in adults with autism 128 as has increased intracranial volume (total gray and white matter and CSF) 240, 241. Enlarged or normal head circumference has been reported in both children and adults 13, 76, 77, 81, reviews: 248 ). However, such findings are not consistent, and decreased gray matter overall has also been reported in children (age 7-11) 133, as has normal total brain area or volume in ASD adults 12, 208, 222, 257. For an excellent review of brain size studies see 135. Enlarged brain volume in children but not adults on MR studies would be consistent with postmortem findings of increased brain weight in children with autism but normal or lighter brain weight in adults (see postmortem section above). Some of the most interesting and promising neuroanatomic findings are those that suggest developmental progression of autism that may guide improved understanding of the origins and potential intervention. The general finding is that of early brain overgrowth followed by slowed or no growth. Consider the following: Young children show enlarged limbic regions 271, 281 but adolescents and adults show no difference 132, 244, 264 or smaller limbic regions 12, 238. Brain overgrowth in cerebrum (particularly in frontal regions) during the first five post-natal years is followed by abnormally slowed brain growth 48, 49, 74, 75. Brain size (indexed by head circumference) is normal or slightly small at birth, undergoes abnormal growth and enlargement during the first five years, is stable and generally found to be normal in adults (review: 248 ). Carper and colleagues reported enlarged frontal, parietal and temporal cortices in young (2-5) but not older children with autism with an association between the size of the posterior cerebellar vermis and abnormal enlargement of frontal lobes 48, 49. In this study, 4

5 children with the greatest cerebellar hypoplasia had the greatest overgrowth of frontal cortex. This suggests growth dysregulation in autism in which brain overgrowth (particularly in frontal regions) during the first five post-natal years is followed by abnormally slowed brain growth 48, 49, 74, 75. White Matter Connectivity. Important for understanding function in autism is that abnormal growth patterns suggest an associated abnormal connectivity during critical periods of development 1, 33, 209. There is some neuroanatomic evidence from white matter studies to support this model. For example, Barnea-Goraly 19 reported reduced fractional anisotropy (FA) in regions adjacent to ventromedial prefrontal cortex, the anterior cingulate, temporal-parietal junctions, superior temporal sulcus, temporal lobes approaching the amygdala, occipitotemporal tracts and in the genu and body of the corpus callosum. The authors suggest these findings are consistent with compromised white matter integrity in brain systems associated with social cognition. Lee and colleagues also found evidence on diffusion tensor imaging of white matter abnormality in temporal lobe regions that might be expected to affect language and social communication 175. Nordahl and colleagues have reported abnormal cortical folding in children and adolescents with autism that is consistent with abnormal patterns of brain development and subsequent abnormalities of connectivity in frontal and parietal cortex 224. Recent work by Lewis and colleagues has provided evidence for the relationship between early brain overgrowth in autism and reduced long-distance white matter connectivity. Based on Ramón y Cajal s hypothesis that neural circuit design is under pressure to minimize cellular costs and conduction delays, and evidence that larger brain size is associated with reduced long-range connectivity across species 141, 249, 321, Lewis and colleagues hypothesized that the early brain overgrowth in autism would result in reduced longrange connectivity Lewis and Elman used neural network modeling to examine this hypothesis, and demonstrated that increased conduction delays presumably associated with early brain overgrowth lead to reduced long-range structural and functional connectivity, and also poorer performance 186. Their results provide theoretical support for a tie between the early brain overgrowth and reduced connectivity in autism. Using diffusion tensor imaging (DTI) with tractography, Lewis demonstrated that in healthy young adults, a larger brain is associated with reduced long-range connectivity 189. New studies by Lewis and colleagues have subsequently provided the first direct evidence of structural reduction in long-range connectivity in adults with autism. These studies used DTI with tractography in adults with autism to demonstrate reduced longrange frontal lobe interhemispheric connections via the anterior corpus callosum 187, 188. The anterior of the callosum is a particular focus of development during the period of maximal brain overgrowth in autism, and so this finding is consistent with the hypothesized impact of the early brain overgrowth on connectivity. In summary, developmental growth patterns reported from imaging 49, 74 and postmortem studies 29 are consistent with an on-going pathologic process 30 that involves early overgrowth followed by slowed growth during maturation. These abnormal developmental patterns may result in abnormal white matter connectivity 1, 33, 209 and an accelerated loss of brain tissue with aging 30. EEG Abnormalities and Seizures. The most common medical condition associated with autism is epilepsy, and even in the absence of epilepsy there may be an elevated incidence of epileptiform abnormalities in the EEG. Epileptiform abnormalities 5

6 in individuals with ASD are most often multifocal, and there is considerable disagreement in the literature over the distribution of these abnormalities 47, 156, 297. Studies with large sample sizes (more than 100 subjects) have reported epilepsy rates that range from 0% to 39% 80, 126, 156, 166, 259, 300, 305. Fombonne 103 compared data from eleven epidemiological surveys published between 1966 and 2001 that included information about rates of medical conditions associated with autism and found that the rate of epilepsy ranged from 0-26%, with 16.8% being the median rate. The wide range of rates is probably attributable to widely varying population samples, and in some cases, varying definitions of epilepsy. While there is a peak onset of epilepsy in early childhood, and a possible second peak of onset in adolescence 306, epilepsy can develop in autism anytime during childhood and adolescence (with some less common instances of onset in adulthood as well). Epilepsy in autism is more common in the severely impaired. Unsurprisingly, there is a higher incidence of epileptiform EEG activity than of epilepsy itself in autism although the reported rate of EEG abnormality is even more variable than that of epilepsy. The epilepsy studies cited above show a reported range of % of EEG abnormalities in non-epileptic ASD individuals. A new study by Chez et al 59 found EEG abnormalities in 60.7% of 889 ASD patients. Samples in these studies could either be biased toward finding epileptiform EEG, as in studies where patients who were suspected of having seizures were more likely to have EEG recordings 299, or biased against finding epileptiform EEG, as in studies where children who had ever had a seizure were excluded 16. Small 279 found that the observation of abnormal EEG activity in autistic children increased with repeated EEG; and others reported an increased chance of observing abnormal EEG during sleep recordings 58, 300. For a detailed review of methodological issues see Kagan-Kushnir et al In any case, there does appear to be a strong relationship between the presence of epileptiform activity in the EEG and epilepsy. Tuchman found that 59% of autistic children with epilepsy had epileptiform EEG abnormalities, while only 8% of those without epilepsy showed epileptiform EEG 300. Hara 126 followed 130 autistic patients over a ten-year period, and showed that EEG abnormalities were observable in 73% of epileptic cases, and all but two of those patients displayed abnormalities before developing seizures. In contrast, EEG abnormalities were observable in only 21% of the non-epileptic cases. There has been some question about whether epilepsy or epileptiform EEG is associated with regressive autism. Approximately 30% of autistic children undergo a developmental regression by twenty-four months of age, losing previously acquired language and social skills 194, 300. Kobayashi 169 reported that epilepsy was twice as prevalent in children that had regressed than in those that had not. Tuchman, however, found no relationship between epilepsy and language regression, although their data did suggest a link between epileptiform EEG activity in non-epileptic children and regression 300. Using the potentially more sensitive MEG technique, Lewine found EEG abnormalities in the majority, 68%, of autistic children with a history of regression, but this number may be inflated as the authors note that all of the study participants had been referred because of unusual behavioral episodes that might be indicative of a seizure disorder 183. Other studies have found no evidence for any association between regression and abnormal EEG 16, 59. One study found that epileptiform EEG could be improved or normalized with antiepileptic medication, but the value of this is unclear as there have been no systematic clinical trials evaluating the effects on development of epilepsy, behavior or cognition of autistic individuals following such treatments 59. 6

7 DIAGNOSIS Screening Guidelines. Increased awareness of autism in the general public has resulted in increased recognition of symptoms in infants and toddlers. The majority (80%) of parents of children with ASD recognize symptoms in the first two years of life and approximately 30% recognize symptoms before their child is 12 months old 56. Concerns most commonly reported by parents are speech and language delays, abnormal social behavior, problems with attention and disruption of sleep and eating 84. In 25-30% of children, ASD manifests as a regression of communication and social skills after months of apparently normal development 300, 301, 312. There is reasonable evidence that ASD can be reliably diagnosed in the second year of life 54, 55 and some possibility that there are much earlier behavioral markers associated with ASD. A large prospective study of high-risk infants with ASD siblings found reliable markers in infants less than 12 months who were later diagnosed with ASD 323. These behaviors included abnormalities in eye contact, visual attention, imitation, social smiling, orienting to name, temperament and unusual sensory behaviors. A comprehensive review of studies reporting on early development in ASD suggests that these behaviors do provide stable markers for diagnosis of ASD under the age of two 324. A review of findings from studies of infants who are at high risk for ASD because they have a diagnosed sibling has provided some surprising information about early signs and symptoms of autism 256. Prospective studies of infants who met the diagnosis of ASD by age three suggests that many critical diagnostic symptoms are not present in early infancy, but develop gradually over the first 2-3 years of life. For example, at six months of age, ASD infants showed abnormal motor development and unusual visual interests, but normal social behavior. A family physician or pediatrician is frequently the first to be consulted when parents are concerned about symptoms of autism. If neurological signs, such as seizures, are among the symptoms of concern, the child may be referred to a pediatric neurologist. The American Academy of Pediatrics has provided guidelines for the diagnosis and ongoing care management for children with Autism Spectrum Disorders 123, 144, 223. The Council on Children with Disabilities has provided a screening tool for identification of children at risk for ASD 64. Routine screenings to identify at risk children are recommended at 9-, 18-, 24- and 30-month visits. The screening instrument and updated recommendations are available on-line from the American Academy of Pediatrics ( Clinical and Research Criteria. Clinical criteria for the diagnosis of autism are based on the DSM-IV TR and ICD10 specifications 8, 319. The three diagnostic domains in which symptoms are evaluated are social relationships, language and symbolic capacity, and repetitive behaviors. Criteria for a diagnosis of autism require impaired behavior in each of these domains. While the clinical diagnosis is most commonly based on the DSM criteria and expert judgment, there are a number of assessment instruments used to enhance the specification of clinical features in research and treatment settings. The current gold standard for diagnostic instruments are the Autism Diagnostic Interview, Revised, (ADI-R), and the Autism Diagnostic Observation Schedule, (ADOS) 192, 193, 263. These instruments score impairment in a number of domains and have excellent reliability and validity. Both instruments are, however, relatively expensive, require extensive training for the test administrator and a lengthy administration time. A number of additional assessments are commonly used to evaluate clinical features of 44 autism. For example, the Scales of Independent Behavior-Revised (SIB-R) assess adaptive functioning. The Social Responsiveness Scales (SRS) 63 provide measures of 7

8 social function and social communication including social awareness, social information processing, capacity for reciprocal social communication, social anxiety/avoidance, and autistic preoccupation/traits. The Childhood Autism Rating Scale (CARS) is broadly used as a measure of symptom severity 268. For a brief review of additional assessment and screening instruments, see 87, 317. Autism is associated with other psychiatric and medical conditions including in a small percentage, Fragile X (1%) and tuberous sclerosis ( %) 104. The diagnosis of other psychiatric conditions in ASD is controversial, but there seems to be an elevated rate of depression and anxiety disorders in Asperger patients while the there is no elevation in the rate of schizophrenia (for a review see Volkmar et al. 307 ). Increased Prevalence of Autism: It s not the vaccine. Is the prevalence of autism increasing? Considerable media attention has been devoted to a potential increase in the prevalence of autism and autism spectrum disorders over the past couple of decades. Speculation about reasons for such an increase in the rate of autism has included most prominently a concern over the role of environmental factors, particularly childhood vaccination. A comprehensive review by Canadian psychiatrist and epidemiologist Eric Fombonne compiled survey data from 14 different countries over the last several decades to track changing rates of autism 103. Fombonne reported that early surveys using Kanner s strict diagnostic criteria estimated rates of autism at 3.8 per 10,000 while later surveys using DSM-IV 8 and ICD diagnostic criteria estimated autism rates at 20 per 10,000. A Finnish study reviewed by Fombonne illustrates the result of using less strict diagnostic criteria. Using Kanner s criteria, this survey estimated autism prevalence at 2.3 per 10,000 while the prevalence in the exact same large sample using DSM-IV and ICD-10 criteria was estimated to be nearly 3 times larger--7.6 per 10, In spite of growing evidence that increased rates of autism most likely reflect changes in diagnostic criteria and an increased awareness of the symptoms of pervasive developmental disorders and not an epidemic rise in autism, concerns have persisted that environmental factors are responsible for the purported rate increase. The major focus of these hypotheses have been the measles-mumps-rubella (MMR) vaccine and a mercury-based preservative (thimerosal) used in many other childhood vaccines 35, 37, 310. Numerous studies have found no evidence for the association of these vaccines and the increased rate of autism in this country or world wide (review: 105 ). Some of the strongest evidence that there is no such association comes from large ecological studies showing the rise in incidence of autism has occurred in countries where the vaccines in question were not used, or that there is no difference in the incidence of autism in vaccinated and unvaccinated children, or that the rate has continued to increase after discontinuation of the vaccine (e.g., 10, 140, 267 ). There is also no biological evidence to support these allegations (for reviews see: 17, 18 ). An unfortunate result of these unsupported speculations can be seen in recent outbreaks of measles in unvaccinated children in Europe, Japan and the US 233. Morton Gernsbacher and her colleagues have provided a thoughtful analysis of some of the reasons for this disconnection between scientific evidence and popular perception 113. Is there a true increase in the prevalence of autism? Probably not. The diagnosis has become increasingly inclusive, and the signs and symptoms are more commonly recognized by parents and physicians. Do autism and related autism spectrum disorders pose an important public health problem? Absolutely. As many as 1 in 150 children have 8

9 some form of pervasive developmental disorder that affects their ability to learn and to function in a social environment. Early diagnosis and treatment is crucial. NEUROCOGNITIVE MECHANISMS Major Cognitive Models. Several major current models attempt to explain neuropsychological function in autism (for reviews see: Baron-Cohen et al ; Russell 261 ; Hill and Frith 136 ; Levy 182 ). The Theory of Mind (TOM) deficits model, proposes that the origin of social communication in autism is an impaired ability to attribute feelings and thoughts to others that is to understand ones own or another s state of mind. This model was first tested by Baron-Cohen 20 and has subsequently been tested many times. The results are robust and many (though not all) children with autism consistently show TOM deficits. These deficits are, however, not necessarily specific to autism and are found in other disorders as well 275. Executive Function Deficits 230, 260 are impairments typically associated with frontal lobe function. These deficits include planning, set shifting, perseveration, working memory and control of action and inhibition. Children and adults with autism have been shown to be impaired on a variety of executive function tasks 136. The Weak Central Coherence model is based on the bias in autism to process details that results in enhancement of segments of information at the expense of context (reviewed in the sensory/perception section below). This model suggests a weakened ability to integrate or bind details into a coherent whole that affects many domains of behavior in autism 108, 109, 125. Although all of the major cognitive models of autism have been associated with underlying neural systems, they are largely descriptive and none explains all of the clinical symptoms. All are important, however, as frameworks within which to advance research and develop treatment interventions. Some newer explanatory models incorporate development and underlying neural mechanisms. Brock has proposed a temporal binding deficit which postulates that many features of autism, such as superiority in processing of detail (local processing) and disadvantage in global processing necessitating integration of information either over space (visuo-spatial perception) or context (integration of words into meaningful sentences), can be explained by a failure of temporal integration, or binding, between cortical areas 42. A related and promising model of abnormal functional connectivity based on developmental neuroanatomic findings is considered by some to be a logical extension of the weak central coherence model 23, 33, 34 and may provide an explanatory base for many of the neuropsychological and social deficits in autism. Abnormal brain overgrowth in early development (discussed in the previous section) may result in abnormal white matter under- and over-connectivity 1, 33, 186, 209. Excessive short-distance and reduced long-distance pathways that would result in a failure to integrate processing across brain systems could predict many of the neuropsychological processing abnormalities to be discussed below. There is growing evidence in support of such abnormal functional connectivity in autism. The first of these studies was conducted by Horwitz and colleagues more than two decades ago 138. This early positron emission tomography (PET) study demonstrated that in subjects with autism there was reduced correlation in resting cerebral metabolism in brain regions that serve directed attention including frontal and parietal cortex and the thalamus. These authors were the first to suggest the failure of integrated long-distance communication in the autistic brain. Modern FMRI studies have also begun to provide evidence for reduced long-distance connectivity in autism. Just and colleagues found decreased functional connectivity 9

10 during a language task among brain region pairs including mid-range (occipito-temporal, occipito-parietal) and long-distance (e.g., occipito-frontal) connections 147. FMRI studies of working memory, spatial attention and selective attention suggest dependence upon short-distance local connections (e.g., processing of visual features) rather than integration of attention and verbal networks during these tasks 32, 124, 170, 250. In a study of executive function, Just et al. found reduced synchrony between frontal and parietal regions suggesting a cortical underconnectivity that would result in deficits in neural and cognitive integration 148. A recent study of resting state EEG in autism also demonstrated patterns that suggest increased short-range and reduced long-range functional connectivity 221. See Figure 1. This study, the first to use reference independent dense array EEG coherence to examine functional connectivity in autism, is of particular importance as EEG coherence directly reflects synchrony in oscillations of cortical neural cell assemblies (i.e., a direct functional connection in real time). Figure 1 From: Figure 3, Murias et al., This figure shows resting EEG alpha band coherence in electrode pairs where coherence was significantly greater for controls than ASD subjects. The authors conclude that the findings shown here suggest weak functional connections between frontal cortex and other cortices which is consistent with long-range underconnectivity 147. Theta band coherence (not shown here) was consistent with short-range over-connectivity, particularly in left hemisphere frontal and temporal cortex which is consistent with increased short-range fibers 134 and may reflect a local processing bias in autism 33. Red lines represent electrodes that are less than 10 cm apart (short-range), blue lines represent electrodes that are cm apart and gray lines represent electrodes that are more than 20 cm apart (long-range). Cognitive Profiles Attention. Attentional dysfunction is a prominent feature of autism, first noted by Kanner in his early descriptions of the disorder 152. While attentional dysfunction is not a criterion for clinical diagnosis of autism, visual attention dysfunction and problems with orienting have been identified as potential markers in early diagnosis 256, 323, 324. Although individuals with autism have performed in the normal range on standardized tests that measure some static aspects of attention 215, 216, experimental tasks requiring dynamic manipulation of attention have typically found attentional dysfunction manifested in numerous ways review: 5. Focused or sustained attention has generally been found to be intact in autism (except that it may be over-focused ), but more complex attentional operations including orienting or shifting, divided and shared or joint attention have been found to be impaired (for reviews see: 5, 68, 190 ). Disruption of basic attentional mechanisms may underlie clinical symptoms of autism such as language acquisition and social communication. For example, a study done by Keehn and Joseph 157 found that children with ASD were not responsive to the onset of targets during visual search. This 10

11 inattention to novel information was significantly related to greater sociocommunicative impairment in children with ASD. Courchesne and colleagues found that adolescents with autism were slow to shift attention between auditory and visual information 71. Akshoomoff examined these same attentional skills in children with acquired cerebellar damage and found similar results 2. While typically developing children were able to shift attention between auditory and visual information almost instantaneously, children with autism (and those with cerebellar lesions) required more than two seconds to re-orient attention. The involvement of the cerebellum in shifting attention in particular and in cognition in general remains controversial 106, 115, 290. However, a functional imaging study using a task patterned after the Courchesne et al task reported cerebellar activation associated with non-spatial cross-modal attention shifts 174. Allen et al found that distinct regions of the cerebellum were associated with motor response (anterior cerebellum ipsilateral to responding hand) and attention shifts (lateral cerebellar hemispheres) 4. Slowed manipulation of attentional resources would particularly interfere with dynamic social interactions. Interestingly, a recent study has demonstrated that slowing facial movement and vocalizations significantly improved emotional expression recognition and imitation in autistic children 288. An inability to follow the rapid ebb and flow of normal social interaction would also interfere with the expression of joint or shared attention a skill that may be a prerequisite for language acquisition and a skill that is impaired in autism 200, 253, 298. Dawson has demonstrated that children with autism have difficulty orienting to social stimulation and that this deficit is correlated with deficits in shared attention 83. Spatial attention is particularly affected in autism. Adults and children with autism have been reported to have: difficulty disengaging attention from a spatial focus and shifting to a new location 155, 308, 309 ; slowed shifting of spatial attention 130, 294, 295 ; difficulty adjusting an attentional lens 46, 203 ; and abnormal distributions of visual attention reflecting a narrow spotlight-like spatial focus 293. Recently, Keehn and colleagues 158 utilized the 95, 96 Attention Network Test to investigate the efficiency of alerting, orienting, and executive control networks in children and adolescents with ASD. The authors report that the ASD group evidenced reduced efficiency of the orienting network compared to the TD group. Landry and Bryson found severe impairment in disengagement of attention from a spatial focus in the majority of children with autism spectrum disorder tested 173. This study employed a comparison group of children with Down syndrome in whom attentional disengagement was normal. The authors have proposed that such visual attention problems represent a developmental spatial neglect syndrome in autism 45. Evidence for neuroanatomic abnormalities of parietal cortex in at least a subset of individuals with autism suggests a possible anatomic substrate for spatial neglect 69. A study that used electrophysiological markers of visual attention distribution illustrates the importance of the underlying anatomic abnormalities to understanding patterns of behavior in autism. A group of adults with autism who had abnormal widening of parietal sulci showed abnormally focused (spotlight) attention while those with no parietal abnormality showed abnormally broad attentional focus 293. The group with excessively focused attention showed faster behavioral response and earlier and larger eventrelated potential (ERP) components associated with visual stimuli at their attended focus. This spotlight attention is consistent with earlier clinical observations of stimulus 11

12 over-selectivity and over-focused attention 195, 197. While this sort of spotlight focus may produce superior performance within the attentional spotlight, there is a cost. Gating of surrounding visual information prohibits rapid response to information outside the attentional spotlight. In view of recent models of over- and under-connectivity, this study may provide an example of neural enhancement that results from a local processing bias. These results are also interesting in the context of a recent study that found an association between behavioral measures sensory over-reactivity and over-focused attention in children with autism 190. Electrophysiological (ERP) responses during spatial attention processing in autism and in patients with acquired cerebellar lesions demonstrated deficits in attention orienting that may represent dysfunction in long-range cerebello-frontal attention pathways 296. In a task that required attention orienting to peripheral space, an electrophysiological marker thought to index attention orienting was significantly delayed and reduced over frontal cortex in adults with autism, and the latency delay was significantly associated with the size of the posterior cerebellar vermis. See Figure 2. Figure 2 From: Figure 3 (Left) and Figure 5 (Right), Townsend et al., The plot on the left shows the distribution of a late cognitive ERP component that indexes spatial attention orienting. The attention orienting brain response is significantly delayed in ASD subjects over frontal cortex, which is consistent with slowed orienting of visual spatial attention. The plot on the right shows a significant correlation in normal control subjects during the same task for the same frontal attention orienting ERP component as in the plot on the left. A greater latency delay over frontal cortex is associated with smaller posterior cerebellar vermal lobules (VI-VII). These data combined with previous data showing similarly disrupted responses in patients with cerebellar lesions and significant correlations in ASD subjects with greater spatial attention orienting delay associated with smaller posterior vermal lobules (VI-VII) 295 suggest disruption in ASD in a fronto-cerebellar network for control of visual spatial attention. Neuroanatomic studies have identified developmental structural abnormalities in both the cerebellum and frontal cortex 27, 48, 70, 75. An fmri study of spatial attention in autism has implicated both parietal and cerebellar dysfunction 124. Haist et al found abnormal activation in both superior and inferior parietal regions during spatial attention shifts in 12

13 adults with autism. Reduced activation in dorsolateral prefrontal cortex and the posterior cerebellar vermis in the autism subjects suggested a dysfunctional cerebello-frontal attention system. An fmri study of visual-spatial processing in autism also found evidence for dysfunction in fronto-parietal networks 277. These studies suggest that both a frontal-cerebellar network that supports spatial attention orienting and a posterior network that supports disengaging of spatial attention may be impaired in autism. Disruption of these long-range attention networks would also be consistent with a model of reduced long-distance connectivity. Sensation/Perception. Abnormal responses to sensory stimuli are a commonly reported feature of autism, and as such they form a component of the diagnosis on a number of standardized assessments. For example, the evaluation of sensory responses comprises 3 out of 15 items on the Childhood Autism Rating Scale 268. Abnormalities in sensory responses are evaluated in some detail by the Diagnostic Interview of Communication and Social Behavior (DISCO) 176, 316 and the Sensory Profile (SP) 90. The DISCO is based on clinical observation and evaluates the proximal sensory abnormalities (e.g., smell, taste, touch) most commonly reported as clinical symptoms in autism 315. The SP assessment represents a more even distribution across all sensory systems. Second-hand or observational reports of sensory sensitivities are plentiful, with parents and/or observers documenting greater proportions of sensory-seeking or sensorydefensiveness behaviors in autistic individuals than in either normal or other clinical controls 163, 177, 217, 254. Behaviors exhibited by individuals with autism can include an unusual interest in bright lights or shiny objects, twisting or flicking hands or objects near the eyes, negative reactions (including covering the ears) to loud sounds, an unusual tendency to explore objects or people by smelling them, discomfort during grooming or dental work, frequent twirling or spinning, and indifference to heat, pain, or cold. The less-frequent self-reports corroborate the observational findings, with autistic individuals reporting more sensory distortions than typically developing controls 82, 217. There is some indication that sensory abnormalities abate with age 163, 164, although Minshew and colleagues found increased numbers of sensory abnormalities in autistic individuals compared to normal controls at all ages in a sample ranging from 8-54 years 217. Despite the seemingly indisputable association of sensory processing abnormalities with autism, the basic mechanisms underlying these sensory sensitivities are not at all clear. Rogers and Ozonoff 255 point out that [t]here is a widely held assumption that sensory and repetitive behaviors are closely related [and] that either repetitive behaviors have sensory origins or that both types of symptoms are driven by chronic hypo- or hyperarousal. Rogers and Ozonoff compiled a comprehensive review of studies through 2003 in order to evaluate evidence for abnormalities in general arousal levels, in arousal to specific stimuli, or in habituation to stimuli as an explanation for the unusual response to sensory stimuli found in autism. They concluded that there was no reliable support for a general heightened level of arousal in autism, although there was some consistent support for under-arousal to stimuli. Either way, the idea of motor stereotypies functioning to regulate levels of stimulation and/or arousal levels appeared to be unsupported. While the majority of sensory-perception studies have investigated auditory and visual processing (reviewed below), some research on the tactile modality suggests that there are multiple mechanisms to consider regarding somatosensory response in autism. Both 13

14 O Riordan et al 226 and Cascio et al 51 found that high-functioning individuals with autism were not different from normal controls in their ability to detect light pressure against the skin. However, additional findings from the Cascio study were that autistic adults had lower detection thresholds for vibrotactile stimuli on their forearms (but not the palm), and that they had lower hot and cold pain thresholds overall. Guclu et al s 121 finding that high-functioning autistic children and typically developing children had similar detection thresholds for vibrotactile stimuli on the fingers is consistent with the Cascio results. Tommerdahl et al 292 recently reported that the improved tactile spatial localization that accompanies adaptation to a long-duration (5 sec) vibrotactile stimulus in normal adults is absent in high-functioning autistic adults. The authors suggest that the lack of improvement in autistic subjects implies abnormal corticocortical connectivity. Studies of visual perception in autism have found evidence for superior performance in some tasks and impaired performance in others. A review by Dakin and Frith compiles evidence that in ASD simple lower order visual perceptual processing is enhanced while more complex higher order processing is impaired 78. See Figure 3. Figure 3 From: Figure 2, Dakin and Frith, Figures show examples of tasks in which ASD subjects showed superior processing of detail (local processing bias) and superior performance as a result of suppressing or ignoring context. Ignoring Context Superior Processing of Details Immune to Many Visual Illusions, Happe, 1996 Superior Performance on Block Design (WISC), Shah & Frith, 1993 Single Feature Better at Visual Search, O Riordan, 2001 Conjunction Superior Detection of Embedded Figures, Jolliffe & Baron-Cohen, 1997; Shah & Frith, 1983 Superior Orientation Discrimination Bertone et al, 2005 Superior Copy of Impossible Figures, Mottron et al, 1999 ASD subjects have demonstrated superior processing of detail: on block design subtests from the WISC 274 ; on detection of embedded figures 142, 145 ; visual search for simple or conjoined features 227, 228, 245 ; and on reproduction of impossible figures 43, 218. In processing higher order (or integrated) information, ASD subjects have demonstrated impaired use of context in orientation discrimination 36 and in visual illusion 125 (although note that a subsequent study 258 using different illusions and methods did not replicate this finding). Studies that have attempted to gather objective measures of auditory perception have found superior pitch discrimination and categorization abilities in high-functioning individuals with autism compared to normal control subjects 40, 226, though it is not yet known whether this enhanced processing is a characteristic of lower-functioning autism 14

15 as well. Researchers have also attempted to trace early auditory transmission along the 65, 120, 172, 207, 278, brainstem by measuring the brainstem auditory evoked potential (BAEP) 287, 318, examine subcortical sensory gating by measuring pre-pulse inhibition as indexed by the P50 wave 160, 225, 235, and assess processing in auditory cortical areas by 53, 159, measuring early electroencephalographic or magnetoencephalographic potentials 289. Results in each of these areas have been contradictory, with inconsistent findings possibly stemming from differences between the presence or absence of mental retardation in the various autistic samples, other issues relating to study controls, or methodological differences between studies. The majority of attempts to reconcile the variety of findings in autism studies of sensory perception have generally agreed that auditory and visual perception of simple or low level information is superior, while perception of more complex of higher level information is impaired in autism. The Dakin and Frith review of visual perception studies concludes that there is robust evidence for superior local processing in autism 78. They caution however that the evidence for reduced global processing is less convincing. A review of auditory perceptual studies concluded that the variability in results could be explained by the complexity of the material and the tasks 266. Samson and colleagues found that studies using low-level auditory stimulation (e.g., pure tones) and simple tasks (e.g., detection, identification, chord disembedding) reported superior behavioral results and shorter latency brain responses in ASD subjects while studies using more complex material and tasks reported poor behavioral performance and abnormal brain responses in ASD subjects. The authors suggest that the neural complexity required to perform the higher level tasks may be deficient in autism. Mottron and colleagues have proposed an Enhanced Perceptual Functioning processing model in which the general profile of visual and auditory perceptual processing (enhanced low level processing and impaired complex processing) can be explained by over-dependence on low level sensoryperceptual processing. There is some support for this model from recent functional MR studies. Two separate studies used embedded figure tasks to examine task-associated brain activation in autism and control subjects 202, 250. Both reported that in autism subjects there was increased activation in early visual brain regions and reduced activation in the frontal and parietal regions that were robustly activated in control subjects. While there is as yet little consensus regarding the specific underlying explanatory model for the sensory-perceptual profile in autism, findings reviewed here seem at least generally compatible with local (sensory) functional over-connectivity and long-range (association) under-connectivity e.g., 23. Language. Language impairment is a defining feature of autism. Language profiles are considered increasingly relevant for differentiation of sub-phenotypes and understanding the neurobiological bases of this disorder. Lack of delay in language acquisition is the major defining feature that differentiates Asperger s syndrome from autism. The level of language impairment correlates with severity of autistic symptoms, especially when combined with higher-level, non-verbal abilities 14, 285. Currently, some experts in the field believe that children with autism are language impaired as well as autistic. At the same time, there is a considerable variability both with respect to the level of language impairment and the impairment profile. A recent review of language studies in autism 286 suggests that, while language deficits in autism range from no functional language to normal standardized scores on language measures, all affected children can be assigned into three main language impairment subtypes: those scoring within the normal range of standardized tests of language (about 25%), those scoring more than one or two standard deviations below the mean across most of language 15

16 tests (about 50%), and those with borderline language abilities with an inconsistent pattern across the tests (about 25%). Universal and specific language deficits in autism reside in higher order syntactic and pragmatic domains. However, a majority of the children in the language impaired group also show phonological short-term memory problems as well as morphological deficits. During pre-school age, children with autism generally fall into two broad subtypes: those with prevailing phonology (perception and production of speech sounds) and grammar deficits; and those with prevailing pragmatic and semantic deficits In the latter group, the major weaknesses include word retrieval and sentence comprehension 3. Several behavioral studies found relatively normal single-word semantic processing in children and adolescents in autism, when stimuli were presented in the visual modality 93, 151, 291. However, higher level semantic processing may not be intact. Behaviorally and with ERPs it has been shown that children with autism have difficulty integrating semantic information, for example, using semantic context in stimulus pairs and sentences 88, 89, 107, 146, 280, 302. In an ERP study, Dunn et al. 88, 89 tested the hypothesis that compared to typically developing peers, language processing in high-functioning verbal children with autism is less influenced by semantic context. They found that in autistic children an electrophysiological index of semantic processing (the N400) was not modulated by word category, providing support for diminished context effect. Siegal and Blades 276 have suggested that auditory processing might be a key factor in these deficits. The few studies that have used event-related potentials to examine auditory phoneme discrimination in autism 52, 117, 178 have reported that automatic within-modality auditory phoneme discrimination is not impaired in high-functioning children with this disorder. However, a study on low-functioning adults with autism found that an ERP index of this process, the mismatch negativity (MMN), is impaired even for simple tone contrast 98. An FMRI study done by Just et al. 147 found that, during sentence comprehension, individuals with autism showed more net activation in Wernicke s area, but less net activation in Broca s area, than their controls. This finding was interpreted as an overreliance on local, word-level, processing during language comprehension (hyperactivation in Wernicke s area) with diminished semantic and syntactic integration abilities (hypo-activation in Broca s area). Further, this study found decreased functional connectivity among all brain region pairs that yielded significant connectivity measures, including mid-range (inferior temporal-inferior extrastriate; inferior parietal lobe-inferior extrastriate) and long-distance (e.g., calcarine-inferior frontal gyrus; dorso-lateral prefrontal cortex inferior extrastriate) connections. Interestingly, the ordering of the pairs of brain regions by the amount of power in their connection was the same in autistic and control groups. The authors conclude that this suggests a quantitative rather than qualitative impairment in cross-region functional connectivity in autism, reflecting a more general problem with long-distance under-connectivity that affects the wide-spread networks of language processing. See Figure

17 Figure 4 From: Figure 3, Just et al., The plot shows similar patterns of functional connectivity from fmri BOLD activations during sentence comprehension. Mid- and long-range connectivity is reduced in ASD subjects for these regions representing language processing networks. However, the pattern of results suggests quantitative but not qualitative differences. L = Left; R = Right; CALC = calcarine fissure; DLPFC = dorsolateral prefrontal cortex; FEF = frontal eye fields; IES = inferior extrastriate; IFG = inferior frontal gyrus; IPL = intraparietal sulcus; IT = inferior temporal; TRIA = triangularis; OP = occipital pole; SMFP = superior medial frontal paracingulate. An earlier positron-emission tomography (PET) study on neural organization of language in autism 219 found: reversed hemispheric dominance during verbal auditory stimulation; a trend towards reduced activation of auditory cortex during non-verbal acoustic stimulation; and reduced cerebellar activation during nonverbal auditory perception and expressive language. These results are compatible with the downstream effects of cerebellar abnormality on perceptual and language processing in autism and also with a model of reduced long-range cortical-subcortical connectivity. The cerebellum has been associated with verbal IQ and a variety of language functions including lexical retrieval, verb and antonym generation, grammatical morphology, syntactic comprehension and discrimination review: 94, 99, 100, 111, 149, 204, 205, 320. Converging lines of evidence indicate that normal development entails not only emerging specialization of but also integration among the neural processors, from the lower to the highest information processing levels 26, 42, 92. The more specialized systems become during maturation, the more critical integration among them becomes. Balance between these two types of fundamental processes is essential for engendering functionally efficient and adaptive behavior. In particular, normal acquisition and use of language are contingent on multi-level integrative mechanisms. These include audio-visual and motor integration at the sensory and phonetic levels of processing during formation of native language-specific phonetic representations 57, since normally developing infants learn through the exposure to audio-visual speech. Vocabulary acquisition, in addition, involves integration across somato-sensory and motor modalities, through which environmental experience about objects and actions is received. In order to form lexical representations of objects/events, stable integrative links among the constituent sensory-motor parts must be built. Non-lexical mental representations of objects, events, and relations among them can only be represented by flexible, dynamic, temporary integration of lower level sensory and category information 24. During language processing, an online integration of semantic word or intuitive representations of 17

18 meaning must be accomplished 171. In autism, these many processes might be perturbed by insufficient integration among the neural processors that serve different functions. Social/Emotional. Social dysfunction in autism is a critical diagnostic feature. Difficulties with social function are among the most troublesome of behavioral symptoms and are among those problem behaviors most frequently targeted by clinical interventions. The majority of current studies have focused on eye gaze and face processing. However, there is little consistency in results from these studies, and little or no consensus regarding the mechanisms that may underlie clinical social dysfunction in autism. Individuals with autism have been found to exhibit atypical gaze patterns when looking at human faces. While typically developing children and adults spend more total time fixated on eyes than on other features like noses and mouths, autistic children and adults do not appear to afford special status to the eyes. Study results differ, however, depending on whether static or dynamic images are used and as a function of task requirements (review: 41 ). Some studies that track eye movements over photographs of faces report that people with autism spend less time on the eyes than typically developing control subjects 79, 234, 283. However, other studies have found no difference in viewing patterns 262, 303, 304. One study with ASD children found that neither ASD children nor typically developing children spent more time fixating on the eyes than the nose or mouth 9. These researchers subsequently grouped the eyes, nose, and mouth into an 'internal' face zone and an 'external' zone (the rest of the head). Fixation times to these zones were not different for any of their participant groups, although all groups spent more time on the 'internal' zone compared to the 'external' zone. Conclusions from studies finding a gaze preference biased away from the eyes often infer that this pattern of processing represents avoidance of the eyes. There is, however, no direct evidence that this is the case. There is rather an indication from these studies that people with autism merely attend to other core features of the face, not necessarily that they avoid looking at the eyes. For example, a study by Spezio and colleagues found that high-functioning subjects with autism performed as well as control subjects on an emotion identification task, although their judgments were determined using a very different processing strategy 282. As in previous studies, the autism subjects spent approximately equal time looking at each of the three major facial features (left eye, right eye, mouth) while control subjects spent significantly more time looking at the two eyes (see Figure 5). The processing bias in autism observed in these studies is consistent with the more general visual perceptual bias for detailed processing described in the earlier section on perception. A recent review of the face processing literature suggests that these perceptual processing abnormalities in ASD may be quite general and independent of social function 31. A comprehensive review of face processing studies by Jemel et al concludes that overall the findings support a locally oriented perception of faces with generally no deficit in perception of global features or face identity and emotion recognition

19 Figure 5 From: Figure 1, Spezio et al., Top figures (A & B) show that high-functioning autistic subjects process each of the major facial features equally, while control subjects spend significantly more time processing the eyes. Bottom figures (C & D) show subtracted images that highlight processing differences between HFA and Controls. Additional evidence that abnormal face processing patterns in autism may not reflect gaze avoidance comes from a recent study by Rutherford and Towns 262 which demonstrates that task requirements can influence gaze patterns. This study used a more difficult task than the studies cited above, in which people with autism were asked to view photographs of faces and choose a label that described the emotion (simple or complex) expressed in the picture (the previous studies asked participants to either identify pictures as familiar or unfamiliar, or whether a face showed emotion or was neutral). Rutherford and Towns demonstrated that under these more demanding conditions, people with autism did look more at eyes than at the mouth, and that the ratio of attention to these features did not differ from that of controls. Another study that used an explicit attention-directing task instruction ( look at the eyes or look at the mouth ) found normal performance of autism subjects on a face processing task 191. The gaze patterns of people with autism appear to change when dynamic images are used. Klin and colleagues 167, 168 have shown that when video clips of faces are used, people with autism fixate on the mouths one and a half times as much than they do eyes. In contrast, typically developing controls fixate on the eyes three times more than they do mouths. The authors hypothesize that their autistic participants are attempting to integrate sound with vision, and focus on the mouth in order to integrate speech sounds. However, the authors acknowledge that motion alone may account for their results. Additionally, these studies used no control for attention, and as the studies described above suggest, manipulating attentional bias may drastically alter results. The other major thrust of social research in autism is functional imaging studies that examine activation in brain systems associated with face processing. In typical function these networks include the fusiform gyrus, the superior temporal sulcus, the amygdala and prefrontal cortex 116, 143. The first study to report abnormal BOLD activation during face processing in autism concluded that the patterns seen in the autism subjects were more typical of object than face perception 270. A flood of subsequent fmri studies reported various abnormalities but particularly reduced activation of the fusiform face area and the amygdala 23, 31, 116, 134, 143. A study by Dalton and colleagues combined 19

20 functional MR with eye-tracking and found that in autism activation in the amygdala and fusiform was significantly correlated with the amount of time gaze was fixated on the eyes of the stimulus 79. Dalton et al hypothesized that their results suggested an increased emotional response associated with eye fixation. However, many other studies reported contradictory findings demonstrating normal fusiform activation in a variety of tasks, and normal amygdala activation when familiar faces were viewed 239. Normal activation of the amygdala under some task conditions demonstrates that while individuals with autism may commonly use alternative face processing strategies and atypical brain systems, typical social networks including the fusiform and the amygdala can be employed by individuals with autism, and are recruited during some social processing tasks. Similar to a number of findings in face processing studies, an fmri study of voice processing in autism showed activation in the superior temporal sulcus in control subjects during voice processing compared to non-vocal sounds, but no preferential activation of this region in the majority of autism subjects 114. The authors conclude that this may reflect an attentional bias toward non-vocal sounds and that these findings, like those from face processing studies, may reflect abnormal functioning of a social brain network. There is some support for this model from structural data reviewed previously suggesting white matter abnormalities in temporal lobe regions that could affect language and social communication 175, and in reduced functional connectivity among temporal and other cortical and subcortical regions 147, 221. Interestingly, functional abnormalities observed in both face and voice processing can be normalized by attentional manipulation as can be seen in a recent FMRI study done by Wang and colleagues 311. In this study children with autism and typically developing controls viewed cartoon scenarios accompanied by spoken remarks. The vignette ending was either sincere or ironic. The child s task was to determine whether the speaker meant what he said. Children with autism performed the task as well as controls, and BOLD activation patterns during face and voice processing were similar in the two groups except that control children showed robust activation of medial prefrontal cortex while children with autism showed none. However, when task instructions were changed to call explicit attention to the face or the voice, both groups showed activation in medial prefrontal regions. See Figure 6. These findings suggest that abnormalities observed in social brain networks may reflect a processing bias that favors non-social information, but this bias can be altered by simple attention-directing instructions. 20

21 Figure 6 From: Figure 2, Wang et al., The top figure shows lack of frontal activation in ASD during face and prosody processing. Bottom figure shows normal frontal activation in ASD during the same task when attention was explicitly directed to the face or voice. Yellow arrows mark medial prefrontal cortex; Green arrows mark left inferior frontal gyrus. TREATMENT Autism is a lifelong disorder. There is no cure and no treatment for autism per se, but there are many effective educational, behavioral and pharmacological treatments for specific symptoms that may not only reduce symptoms but also improve overall function. Several recent reviews summarize the most common behavioral and pharmacologic treatments 86, 206, 229, 273. The American Academy of Pediatrics provides comprehensive guidelines for both medical and non-medical management of children with ASD 223. Behavioral. While there is general agreement that early, intensive intervention is crucial, individual variability in symptom patterns and in response means that there is no one-size-fits-all approach. Behavioral interventions can be roughly grouped into three 21