Книги по МРТ КТ на английском языке / Functional Neuroimaging in Child Psychiatry Ernst 1 ed 2000

negative information and a 1:3 ratio in right-to-left prefrontal activity during the presentation of the negative backgrounds. However, the next three subjects scanned, either activated the hemispheres equally or showed the reverse pattern. Therefore, while the representation of emotional information is in part served by the prefrontal cortex in both children and adults, the laterality of this representation is less straightforward. Given this variability in pattern of activation across subjects, we have since moved to the presentation of face stimuli rather than pictures from the International AVective Picture System. Face stimuli allow for the control of picture complexity, size, familiarity, etc. across all conditions (e.g., positive, negative, and neutral).

Conclusions

In this chapter, a variety of paradigms have been described for use with developmental populations. These tasks, while

limited primarily to the domain of prefrontal functioning, are quite broad with respect to the type of information processed (e.g., verbal, spatial, response, emotional). Across all four empirical studies described, similar locations of prefrontal activity were observed for school-aged children and adults. However, diVerences were observed in the magnitude of the patterns of activity, both in volume (Casey et al., 1997 a,b,c) and in percentage change (Cohen et al., 1994; Casey et al., 1995). These diVerences may be attributed to overall task diYculty. Even when attempts were made to titrate task diYculty across ages, young children performed less well than the adults. Many of these diVerences may be associated with diVerences in how quickly subjects mastered the tasks. Adults became more proWcient in task performance (e.g., the spatial working memory task) as a function of time on-task in the scanner. The children, by comparison, did not increase their performance with time on task in the scanner. Some of the diYculty for children performing tasks in the scanner may

166B. J. Casey et al.

be the need to lie down, thus blocking a view of their hands. Their motor skills are not as sophisticated and so even with extended practice the children still beneWt from visual feedback on where their hands and Wngers are with respect to the response-recording device. Alternatively, children and adults may diVer in the speed of acquiring new skills. These issues and others raised in the current chapter are just a few to be addressed as we continue to use functional neuroimaging with children. It is clear that innovative methods like fMRI will transform our current understanding of human brain development and hold signiWcant implications for the study of developmental disorders.

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The reader will gain from this section knowledge of the latest research developments and pathophysiologic theories of speciWc child psychiatric disorders and glean from it information on the current status of brain imaging research in child psychiatry. Indeed, this comprehensive review covers practical challenges involved in scanning children, design issues arising from the heterogeneity of child psychiatry disorders, interpretative dilemmae

posed by various imaging paradigms, advances in neurobiological knowledge gained through the use of neuroimaging, and the future potential of functional neuroimaging in child psychiatry. The identiWcation of neural circuits underlying symptoms and vulnerabilities and of their speciWc disruptions in diVerent disorders emerge as a goal worthy of pursuit given its implications for diagnosis and treatment.

DeWnition of autism

Autism is a developmental disorder deWned by the presence of a triad of communication, social, and stereotypical behavioral characteristics with onset before 3 years of age. Previous estimates of the incidence of autism were 2±5 cases per 10000 individuals (for review see Wing, 1993). Recent studies show a higher incidence of autism (approximately 1 in 1000), while the three to four times predominance of the disorder in males has remained constant (Bryson, 1996). Autism was Wrst described by Kanner in 1943 in his landmark paper describing a group of children who showed language abnormalities, impairment in social interactions, and restricted interests and preoccupations. One year later, Asperger (1944) described a similar group of children. The term Asperger's syndrome is now used to describe high-functioning individuals with autistic features but relatively normal communication and cognitive skills (Gillberg, 1989; Volkmar et al., 1996).

Underlying the spectrum of autistic behaviors are undoubtedly multiple etiologies, only a small fraction of which have been so far identiWed. The reliance upon this behavioral deWnition is a consequence of a failure to identify biological markers for the majority of individuals with autistic behavior and is a source of diYculty in the design and reproducibility of functional imaging studies. The inexact nature of the diagnosis of autism and other pervasive developmental disorders is also the source of numerous practical problems for the families of autistic children in identifying appropriate medical, behavioral, and educational interventions necessary to promote optimal development of their children. In spite of the fact that there are various etiologies for autistic behavior, the possibility of a common neurochemical mechanistic feature, shared by multiple causes of autism, cannot be excluded. It is upon this premise that functional neuroimaging of groups of

autistic subjects of unknown etiology are compared with nonautistic control groups in search of common biological substrates to deWne and understand autism better.

Clinical versus research criteria for the diagnosis of autism

The accurate diagnosis of autism and careful description of associated features of the subjects are essential criteria for obtaining meaningful functional imaging data and to allow comparison of results among groups (Table 10.1). The majority of the functional imaging studies published to date have utilized clinical diagnoses of autism based upon DSM-III-R (American Psychiatric Association, 1987), DSMIV (American Psychiatric Association, 1994) or ICD-10 (World Health Organization, 1987) criteria. Various additional psychologic instruments, such as the Childhood Autism Rating Scales (CARS; Schopler et al., 1980), have also been employed. There has been a growing concensus in recent years that the Autism Diagnostic InterviewRevised (ADI-R; Lord et al., 1994) and the Autism Diagnostic Observation Scale (ADOS; Lord et al., 1989) developed by Lord and colleagues represent the gold standard for the diagnosis for autism for research purposes. These are excellent instruments with extensive validation for high-functioning autistic subjects over the age of 4 years (Lord et al., 1997). However, these instruments are overinclusive for lower-functioning individuals, who make up 75% of individuals with a clinical diagnosis of autism. The Prelinguistic Autism Diagnostic Observation Schedule (PL-DOS; DiLavore et al., 1995) was developed by the same group to address younger (less than the age of 6 years) children who have not yet developed phrase-level speech. The problem of stability of diagnosis of young autistic children (Lord and Schopler, 1989) can also be addressed by re-eval- uating the children after several years (Lord, 1995).