Running head: THE TREATMENT OF AUTISM AS AN INFORMATION PROCESSING DISORDER The Treatment of Autism as an Information Processing Disorder Mark Collins University of the Rockies Dr. Robert Wolf August 1, 2010 Abstract This paper examines some of the research and theories related to the neurological, sensorimotor, and memory functions in individuals with autism and autism spectrum disorders. It examines data associated with dysfunction within four neural mechanisms in the brain of those with ASD, along with research findings that have attempted to identify specific areas of brain related to the impairments of learning and memory capabilities.
Furthermore, it explores theories hypothesizing autism as an information processing disorder, and presents the predominant conventional treatment approach, as well as an unconventional methodology utilizing computers. The Treatment of Autism as an Information Processing Disorder The role of neural mechanisms in the brain in autism and autism spectrum disorders (ASD) has changed over the last 40 years as the disorders have become better understood.
Autism was once seen as being basically psychogenic in origin and focused on early developmental and environmental causation (Kanner, 1943), later being discarded in favor of neurobehavioral models in the 1970s and 80s. These theories hypothesized that brain dysfunction was the sponsoring factor related to social, language, and behavioral symptomatology in autism, with ASD in effect being defined as a type of amnesiac disorder (Boucher & Warrington, 1976).
Biopsychological and biological theories are now ascendant, with symptoms related to cognitive and language deficits sponsoring hypotheses attempting to locate the source of motor impairments in the brain. In some senses, researchers have some advantages as the brain physiology in normal individuals is fairly well understood, though there is no one prevailing theory endorsed by all as to how these function in ASD, partially due to the broadness of the diagnostic spectrum and variance in individual’s levels of functioning.
Current thinking regarding biopsychological factors subscribe to the notion that autism is related to functional impairments of the brain, though there is a divergence of opinion as to the responsible systems and mechanisms. Hypotheses postulating that autism as having a varied neurological base seem promising (Deborah, Margaret, Edith, Dorothy, & Lynn, 1984), and this paper examines research studies supporting this contention related to the neurological, sensorimotor, and memory functions of adults and children diagnosed with autism and ASD.
Understanding these mechanisms may lead to a more comprehensive understanding of the disorder, but also how to more effectively apply physical, psychological, and occupational treatment interventions. Neurological Functioning in Autism Genetic Studies For genetic syndromes, the assumption often is that they have a hereditary basis with either a family history of the disorder or family members exhibiting some the features. It is suspected that autism and ASD have a multi-gene basis, with indistinct though notable deficits in families (Spiker 1994).
These include abnormal levels of serotonin, conversation skill deficits and cognitive and language deficits and a high number of affective disorders (Baird & August, 1985). Speculation regarding a multi-gene source is that each gene may exert an indeterminate effect that is interrelated and cumulative in nature. Furthermore, less severe aspects of autism may not be seen as problematic, as in the use of extended selective attention related to visual search and pattern detection (Kinsbourne, 1987).
Dysfunction within four neural mechanisms Abnormalities and dysfunction within four neural mechanisms is hypothesized as having causal significance in terms of autistic behaviors and etiology of autistic spectrum disorders. The first dysfunction involves information processing for ongoing events and long-term memory that is fragmented called canalesthesa. Due to a density of neurons in the hippocampal system, sensory information becomes canalized and improperly integrated, (Bachevalier & Merjanian, 1994). The second dysfunction elates to an impaired functioning of the amygdala (Bachevalier & Merjanian, 1994), which results in an inability to properly assign relevance to other people’s words and actions. The symptomatology in autism related to inappropriate responses to social cues and interactions are associated with the third dysfunction, and are thought to involve processes in the neuropeptide system involving oxytocin and vasopressin in the endogenous (i. e. originating or produced within an organism, tissue, or cell) opiate system and abnormalities in the serotonin production (Chamberlain & Herman, 1990).
Oxytocin and vasopressin are thought to be elements sponsoring social drives and imprinting in lower mammals, and may be associated with similar phenomenon in humans (Carter, DeVries, & Getz, 1995). The fourth identified dysfunction is extended selective attention, where abnormal functioning in the temporal and parietal association regions of the brain result in increased attention to certain objects and activities often described as stereotypical or ritualized behavior (Berthier, 1994). The four dysfunctions and autistic behavior
Many of the diagnostic behaviors in autism involve social communication impairment, including language and speech delays, stereotypical language and behavior, and a lack of social and emotional reciprocity. Waterhouse, Fein, & Modahl (1996) speculate that these impairments result from “the combined effects of asociality, impaired assignment of significance, canalesthesia, and extended selective attention. ” These factors impact the need for social involvement with others as well as the assignment of value accorded to facial expressions and speech.
Furthermore, “canalesthesia and extended selective attention disrupt perceptual integration, fluid shifting of attention, effective working memory, and triggered recall”; all of which are necessary for normal language acquisition, play, and social interactions (Waterhouse, Fein, & Modahl, 1996). There has been extensive research regarding facial recognition in autistic adults and children as many are deficient in this aspect particularly with regards to the identification of facial expression, feature recognition, and memory for faces (Davies, Bishop, Manstead, & Tantam, 1994).
This appears related to a dysfunction in the amygdala that disrupts the assignment of arousal and significance to people’s faces, as well as speech content and intonation (Green et al. , 1995). Non-autistic individuals who have had their amygdalas removed experience both inattention to speech and impaired face recognition (Aggleton, 1992), which seems incongruous as autistics often have superior visual-spatial recognition capabilities.
Typically developing children appear to have innate abilities to imitate others, and gestural imitation is impaired in autistic individuals secondary to an “aberrant attentional system (Smith & Bryson, 1994, p. 268). ” As the facial features and actions of others are not marked by the amygdala as rewarding, autistics often fail to respond to social stimuli and instead will often focus on ordinary objects to a preservative degree. Perseveration, object preoccupation, and stereotypical behavior may be also related to abnormalities in serotonin, dopamine, opiates, and oxytocin production (Panksepp 1992).
This results in a “capture” of repetitive auditory patterns (tapping, clicking, flapping) and visual patterns (spinning objects, rocking) and an extended selective attention arousal loop (Schultz and Berkson, 1995). This extended selective attention loop may be responsible for autistics hypersensitivity to certain sounds, sights, colors, and touch. The impaired amygdala may interpret these sensations as painful or overwhelming, and may be linked to what is known as autistic savantism.
Savants often score highly on specific visual and auditory subtests of IQ testing, and often manifest unique abilities in terms of pattern recognition and remembrance (Young & Nettelbeck, 1995). Other behaviors related to self injury may be related to the oxytocin-opiate system identified earlier as autistics are appear to have a high pain threshold with elevated beta endorphin production (Herman, 1991). Self injurious behavior such as head-banging, hair pulling, biting, tearing out of fingernails etc. ay be related to this as well as seizure activity (Gualtieri, 1989). “Self-injury may be the manifestation of an aftermath state of neural kindling activity (repeated low-level abnormal neural excitation) leading to the onset of seizures” (Sutula, He, Cavazos, & Scott, 1988). There is evidence to support that self injury linked to seizure activity is generated by abnormal neural excitation in the amygdala and hippocampus, and often treated with anticonvulsive drugs (Luiselli, Matson, & Singh, 1992).
The model for the four neural mechanisms is more comprehensive and inclusive than previous theoretical models that tended to focus on one area of dysfunction. The hippocampal and amygdala dysfunction are the only pair of dysfunctions that together might generate diagnosable autistic symptoms. Non-diagnosable symptoms such as social withdrawal, abnormal sleep and eating patterns, pain threshold, and attachment seem influenced by oxytocin-opiate system abnormalities, though no single dysfunction is responsible for all the manifest symptomatology of ASD.
Add to this the individual differences in functioning and variations within the autistic spectrum, and assessment as to the severity and role of each area of dysfunction becomes difficult. Considering the heterogeneity of autistic spectrum disorders and the various associated brain structures, some theorists propose a systemic disruption of functions related to cerebellar, limbic, and cortical structures, as opposed to a specific area or component (Grossberg & Seidman, 2006).
Other areas of the brain related to sensorimotor functions in autism Theories related to dysfunction in the left hemisphere of the brain arose secondary to the notion that impaired language skills that are a hallmark of autistic disorders are related to functioning in this area of the brain (Deborah, Margaret, Edith, Dorothy, & Lynn, 1984). In addition, visual-spatial abilities and nonverbal auditory perception associated with the right hemisphere appear to be intact and even superior to those of typically developing children (Prior, 1979).
In terms of sensorimotor functioning, tests regarding motor and perceptual tasks as well as cognitive measures yielded results that were statistically inconclusive to support the left hemisphere contention. Electrophysiological studies such as EEGs and CAT scans show that most autistic children showed no significant abnormalities related to the left hemisphere, though when present are associated to bilateral hemisphere functioning (Deborah, Margaret, Edith, Dorothy, & Lynn, 1984).
Studies of deprived animals having reduced dendritic branching in the cortex suggest the hypothesis that “a child with attentional, social, and motivational deficiencies such as little or no curiosity, no exploratory behavior, and no selective attention to parent’s voices and faces for the first several years of life may actually develop a dysfunctional cortex” (Volkar& Greenough, 1972). Memory Functioning in Autism The theory of systemic brain dysfunction in autism is supported by esearch regarding memory functioning, which differs markedly between children and adults. Most autistic adults appear to be able to use organizational and contextual strategies in terms of semantic memory processing, whereas children with autism seem to lack this capability. This means that children with autism encode the meaning of words via external cues, but “do not spontaneously use semantic, syntactic, or temporal sequences effectively to facilitate retrieval of information (Tager-Flusberg, 1991).
In essence, explicit memories regarding general facts or information, syntax, and time are not stored, anchored or retrievable as they would be with TD children. This deficit appears to be related to the complexity of the material associated with memorization as opposed to language deficits connected to other forms of cognitive dysfunction (Fein et al. , 1996). Materials requiring low levels of structuring such as numbers were recalled more easily than sentences or stories representative of complex structures.
Assessments of adolescent and adults with autism have presented different results, with participants exhibiting a greater ability than autistic children to utilize associative memory functions requiring high information processing demands, except in subtests regarding facial recognition, spatial working memory, and memories for social situations (Minshew & Goldstein, 2001). Boucher (1981) speculated that children with autism encode less information from social interactions than typically developing (TD) children, and remember less about recent experienced events.
The differing capabilities between autistic adults and children suggest that there may be some potential for learning and adaptation for individuals with the disorder. This underscores the use of current treatment methods that start with rudimentary picture boards for children and progressing towards more complex communicative methodologies such as storytelling as development occurs. Treatment of Autism and ASD Despite the advances in cognitive neuroscience, neurobiology, and the genetics of ASD, it is still unclear which treatments will be most effective partially due to heterogeneity of those afflicted.
Many of the early and current interventions for ASD have a behavioral orientation, targeting the core symptoms related to communication, socialization, and behavior (Dawson, 2008). As with most behavioral strategies, interventions in childhood yields the most optimal results with early detection enabled by the use of neuroimaging methodologies such as functional MRIs, CAT scans, and magneto-encephalographies (Rogers & Vismara, 2008). These methods can also be used to gauge progress in terms of a comparison of the premorbid condition to physiological changes during and after the treatment process.
Once detected, interventions for children with ASD involve comprehensive behavioral treatment programs focusing on specialized education, family therapy, and developing the skills necessary to integrate into the community (O’Roak & State, 2008). Pharmacological and medical interventions for comorbid features may be prescribed, though there are no medical or biological treatments that can address all the impaired neurological deficits and core symptoms described previously.
The most common symptoms and conditions comorbid with ASD are attention deficit-hyperactivity disorder, anxiety disorders, and depression. Atypical antipsychotics such as risperidone have been used to reduce irritability, and SSRI antidepressants can be effective in reducing anxiety and obsessive-compulsive behaviors (Kolevzon, Mathewson, & Hollander, 2006). Although there are a numerous conventional and unconventional treatment methodologies for ASD, detailing the myriad of treatment approaches available fall beyond the scope of this paper.
This study focuses on two treatment approaches reflective of both categories, with behavioral interventions used within a psychosocial context representative of conventional thinking regarding ASD, contrasted with the unconventional and more speculative use of computers for the treatment of autism. Psychosocial treatments Psychosocial treatments for ASD involve a number of approaches involving educational and skills-based training focusing on socialization, play, and language skills as well as behavioral interventions targeting maladaptive behavior and cognitive impairments.
Much of this may occur in the classroom under the auspices of special education, with an effort to mainstream autistic individuals as much as possible. This enhances efforts to improve socialization and play skills in a group setting, and is often augmented with individual therapy. As many of these socialization deficits involve communication, speech and language therapy are necessary adjuncts to the treatment process. For those with verbal apraxia (inability or limited abilities to speak) visual cues involving picture boards help facilitate communication and reduce the individual’s frustration with making their needs known (Paul, 2008).
Behavioral therapy Behavioral interventions based on learning theory and utilizing operant strategies can help shape behavior through the use of positive reinforcement, based on the principles of Applied Behavior Analysis (ABA) (Sebat, et. al. , 2007). ABA and other types of behavioral treatments are highly structured programs, used either on a one-to-one basis or with an integrative approach with other typically developing children to promote attention and allow for the imitation of appropriate behaviors.
These programs have been found to be effective for over half of those involved, and have been the most thoroughly researched and documented of the treatment interventions for ASD (Rogers & Vismara, 2008). The shortcomings to this approach is its cost in terms of time and money, as well as the inability of those with ASD to generalize information gained in a structured session to more widespread social applications.
Developmental approaches using naturalistic strategies have helped to increase knowledge generalization, particularly when there is involvement with parents in the home in conjunction with skills learned in a more structured setting (Howard, et. al, 2005). These approaches often focus on addressing one behavior at a time, with effective outcomes when combined with ABA techniques. The family setting can help promote behavioral changes, providing reinforcement with leisure time activities and an enjoyment of the treatment by parents and child (Howard, et. l. 2005). Alternative views of autistic learning Critics of Applied Behavior Analysis take exception with its reliance on conventional learning theory. Green (1996, p. 24. ) summarizes the procedures as being “derived from the principles of behavior to ‘build socially useful repertoires’ of observable behaviors and reduce or extinguish socially ‘problematic ones,’ has become the basis for an extensive autism intervention literature and service industry. Those challenging ABA types of treatment approaches argue that autistics are not governed by the same learning characteristics as typically developing individuals, and the view that they require explicit training for virtually every human behavior is erroneous (Lovaas & Smith, 2003). In addition, the premise of these behavioral programs that early intervention will interrupt, reverse, or cause autism to deviate in its normal developmental trajectory is seen as faulty, and that researchers have “studied the effectiveness of programs not the appropriateness of various goals” (NRC, 2001).
Training programs that involve older adolescents and adult autistics targeting the core deficits in autism have also been thought to correct faulty autistic neural mechanisms (Tanaka et al. , 2005). Yet though autistics acquired specific training behaviors in terms of labeling pictures expressing facial affect, there was no evidence of neurofunctional changes, whereas untrained autistics have displayed changes in brain activity without the training stimulus (Bolte et al. , 2006).
The only randomized controlled trial of a comprehensive ABA program reported poor short-term results (Smith et al. , 2000, 2001), with data from uncontrolled trials that neither the intensity nor quality of early ABA programs is related to short-term outcomes (Sallows & Graupner, 2005). The repeated performance of tasks associated with ABA testing of perceptual and procedural memory brings about the desired training effect in non-autistics, though not with autistics (Mottron et al. 1999). Autistic learning seems to be a spontaneous mastering of complex material through passive exposure; indeed, autistics have demonstrated superior perceptual abilities than TD individuals in discriminating between similar presented objects and designs, as well as occasions of savantism in certain areas. The bottom line for those contesting the conventional behavioral interventions is that autistic learning is quite different from the learning of non-autistic individuals.
Therefore, new and creative cognitive approaches need to be explored that benefit those with ASD versus the application of learning methods that are appropriate only for typically developing individuals. Computers and autism The use of computers for education and therapeutic benefit for those with ASD seems to hold promise even for individuals at the high end of the spectrum in terms of disability. Murray (1992) contends that “attention tunneling, or monotropism” is an essential feature for those afflicted with autism, and that computers can provide an ideal medium to address eficits in communication and social skills. Computers offer a safe environment well-suited to the monotropic focus of the autistic, which is often fragmented by the polytropic (multiple interests systems) stimulus of the world around them (Murray & Lesser, 1999). With attention tunneling, objects and concepts are isolated and lack a contextual reality, yet ASD clients can learn to function in a computer-generated environment as the device has many monotropic features, as illustrated in the following table. Table 1(Murray & Lesser, 1999). Computers have the following attributes: | |Contained, very clear-cut boundary conditions | |Naturally monotropic | |Context-free | |Rule-governed and predictable thus controllable | |Safe error-making | |Highly perfectible medium | |Possibilities of non-verbal or verbal expression | |It joins the individual’s attention tunnel |
Autism has been defined as “an impairment in integrating elements into wholes (Weak Central Coherence Theory) [or] impaired executive functioning (executive dysfunction theory) (Russell, 2002, p. 295)” This premise is evident in a variety of studies supporting the view that having deficits in integrating material may mean having strengths in other areas (Garner & Hamilton, 2001). This has led to premises involving “local” versus “global” processing of information which ties to the Central Coherence Theory in terms of integration (Russell, 2002). This process of integrating information is seen as dysfunctional in autistics, unless the information is attended to.
It is this focusing of attention which is the essential benefit of computer use for those with ASD, as well as stimulating exploration and forethought, creativity and play, and providing methods for enhancing self-awareness and esteem (Murray & Lesser, 1999). In addition computers often provide tasks that are concrete in nature, free of other stimuli, and possess a system of reinforcement (i. e. games). Promoting an awareness of others is also part of the structure of games with computers essentially mandating when participants take turns. This allows for modeling that can be generalized into other social situations, as well as enhancing an awareness of others’ interests and intentions.
As for communication, computers can prompt spoken input from autistics in a manner that is relevant to the individual’s focused attention. Some autistics hear and understand speech, though they may not respond unless the content reflects a current interest or concern (Murray & Lesser, 1999). Computer graphics and programs with a cooperative design encourage common interest and interaction. Although the interactional give-and-take in a conversation is much more complex, it does require a level of cooperation that can be engendered by a computer program with more clearly defined meanings and contexts. Table 2. illustrates some common elements of communication, and how the computer facilitates this by providing a safe and predictable environment. Table 2. (Murray & Lesser, 1999). Mutual Communication | |Mutual awareness | |Shared attention/common interest | |A means of expression which arouses or expresses the same interests in all | |parties | |Taking turns | |DESIRABLE WORLD |UNDESIRABLE WORLD | |Rules |Few or no universal rules | |Rituals – formal – reliable |Few or no rituals | |Discourse (unless performance or pun) is factual OR ritual |Little or no literal fact | |Highly predictable universe |Blurred distinctions/uncertain boundaries | |Clear distinctions |Substantially unpredictable universe | |Unhurried pace |Rapid pace | |Restricted stimulus environment |Multiple stimulus environment |
Conclusion This paper has examined some of the theories relating to the neurological functions related to autism, as well as an exploration of a conventional and unconventional treatment approach for those with ASD. It has highlighted some of the differences between autistic children and adults within these contexts, with the latter having superior ability linked to cognitive maturation and language skills, both of which are lacking in children with autism (Mandler & Johnson, 1977). This suggests that children in particular have difficulty acquiring information from complex stimuli, affecting and inhibiting the development of social and problem solving skills.
Current research supports the view of autism as a systemic informational processing disorder, involving a variety of functions in the brain as opposed to damage and dysfunction within a specific localized area. These and other studies have instead identified impairments related to reasoning, problem solving, language skills and other complex tasks as being sponsored from other causes than those originally conjectured. The cumulative evidence suggests a generalized informational processing deficit, and that the behavior and acting out frequently manifest in ASD can be better understood as a result and reaction to an overwhelming inundation of information (Williams, Goldstein, & Minshew, 2006).
Advances in cognitive and affective developmental neuroscience, neurobiology, and the genetics of autism spectrum disorder have resulted in improved methods of detection, and sponsored new treatment approaches that show great promise for those afflicted with ASD. Most importantly, this understanding of the interrelated nature of systematic brain dysfunction in autism and ASD provides a basis upon which more effective treatment approaches and methodologies can be formulated and established. | | | | | | | | |References | |Aggleton, J. P. (1992).
The functional effects of amygdala lesions in humans: A comparison with findings from monkeys. In J. P. Aggleton | |(Ed. ), The amygdala: Neurobiological aspects of emotion, memory, and mental dysfunction (pp. 485-503). New York: Wiley-Liss. | |Bachevalier, J. (1994). Medial temporal lobe structures and autism: A review of clinical and experimental findings. Neuropsychology, 32. | |627-648. | |Baird, T. D. , & August, G. J. (1985). Family heterogeneity in infantile autism. Journal of Autism and Developmental Disorders, 15. 315-321 | |Berthier, M. L. (1994). Corticocallosal anomalies in Asperger’s syndrome. American Journal of Roentgenohgy, 162, 236-237. | |Boucher, J. (1981).
Memory for recent events in autistic children. Journal of Autism and Developmental Disorders, 11, 293–302. | |Boucher, J. , & Warrington, E. K. (1976). Memory deficits in early infantile autism: Some similarities to the amnesic syndrome. British Journal| |of Psychology, 67, 73–87. | |Bolte, S. , Hubl, D. , Feineis-Matthews, S. , Prvulovic, D. , Dierks, T. , et al. , (2006). Facial affect | |recognition training in autism: Can we animate the fusiform gyrus? Behavioral | |Neuroscience, 120, 211–216. | |Carter, C. S. , DeVries, A. C, & Getz, L.
L. (1995). Physiological substrates of mammalian monogamy: The prairie vole model. Neuroscience | |Biobehavioral Reviews, 19, 303-314. | |Chamberlain, R. S. , & Herman, B. H. (1990). A novel biochemical model linking dysfunctions in brain melatonin, proopiomelanocortin peptides, | |and serotonin in autism. Biological Psychiatry, 28, 773-793. | |Cohen, D. J. , Caparulo, B. , & Shaywitz, B. A. (1978). Neurochemical and developmental models of childhood autism. In G. Serban (Ed. ), | |Cognitive defects in the development of mental illness (pp. 66-102). New York. | |Davies, S. , Bishop, D. , Manstead, A. S. R. , & Tantam, D. (1994).
Face perception in children with autism and Asperger’s syndrome. Journal of | |Child Psychology and Psychiatry, 35, 1033-1057. | |Dawson G. (2008). Early behavioral intervention, brain plasticity, and the prevention of autism spectrum disorder. Developmental | |Psychopathology, 20:775–803. [PubMed: 18606031] | |Deborah, F. , Margaret, H. , Edith, K. , Dorothy, L. , & Lynn, W. (1984). The question of left | |hemisphere dysfunction in infantile autism. Psychological Bulletin, 95(2), 258-281. | |doi:10. 1037/0033-2909. 95. 2. 58 | |Garner, I. & Hamilton, D. (2001). Evidence for central coherence: Do children with autism experience visual illusions? In Autism: The Search | |for Coherence, pp. 75–85. London: Jessica Kingsley. | |Green, G. (1999). Science and ethics in early intervention for autism. In: Ghezzi, P. M. , Williams, | |W. L. , Carr, J. E. (Eds. ), Autism: Behavior Analytic Perspectives. Context Press, Reno, NV, pp. 29-44. | |Green, L. , Fein, D. , Joy, S. , & Waterhouse, L. (1995). Cognitive functioning in autism: An overview. In E.
Schopler & G. Mesibov (Eds. ), | |Learning and cognition in autism, pp. 13-31. New York: Plenum Press. | |Goldstein, G. , Allen, D. , Minshew, N. , Williams, D. , Volkmar, F. , Klin, A. , et al. (2008). The structure of intelligence in children and | |adults with high functioning autism. Neuropsychology, 22(3), 301-312. doi:10. 1037/0894-4105. 22. 3. 301. | |Goldstein, G. , Allen, D. , Minshew, N. , Williams, D. , Volkmar, F. , Klin, A. , et al. (2008). The structure of intelligence in children and | |adults with high functioning autism. Neuropsychology, 22(3), 301-312. doi:10. 1037/0894-4105. 22. 3. 301. | |Grossberg, S. , & Seidman, D. 2006). Neural dynamics of autistic behaviors: Cognitive, emotional, and timing substrates. Psychological Review,| |113(3), 483-525. doi:10. 1037/0033-295X. 113. 3. 483. | |Gualtieri, C. T. (1989). The differential diagnosis of self-injury in mentally retarded people. Psychopharmacology Bulletin, 23, 358-362. | |Herman, B. H. (1991). Effects of opioid receptor antagonists in the treatment of autism and self-injurious behavior. In J. J. Ratey (Ed. ), | |Mental retardation: Developing Pharmacological Therapies, pp. 107-137. Washington, DC: American Psychiatric Press. | |Howard, J. , Sparkman, C. , Cohen, H. , Green, G. , & Stanislaw, H. (2005).
A comparison of intensive behavior analytic and eclectic treatments | |for young children with autism. Research of Developmental Disabilities; 26:359–383. [PubMed: 15766629] | |Kabot, S. , Masi, W. , & Segal, M. (2003). Advances in the diagnosis and treatment of autism spectrum disorders. Professional Psychology: | |Research and Practice, 34(1), 26-33. doi:10. 1037/0735-7028. 34. 1. 26. | |Kanner, L. (1943). Autistic disturbances of affective contact. Nervous Child, 2, 217-250. | |Kolevzon, A, Mathewson, K. A. , Hollander, E. (2006). Selective serotonin reuptake inhibitors in autism: a review of efficacy and tolerability. | |Journal of Clinical Psychiatry; 67:407–414. PubMed: 16649827] | |Kinsbourne, M. (1987). Cerebral-brainstem relations in infantile autism. In E. Schopler & G. B. Mesibov (Eds. ), Neurobiological issues in | |autism (pp. 107-125). New York: Plenum Press. | |Lahaie, A. , Mottron, L. , Arguin, M. , Berthiaume, C. , Jemel, B. , & Saumier, D. (2006). Face perception in high-functioning autistic adults: | |Evidence for superior processing of face parts, not for a configural face-processing deficit. Neuropsychology, 20(1), 30-41. | |doi:10. 1037/0894-4105. 20. 1. 30. | |Lovaas, O. I. , Smith, T. (2003). Early and intensive behavioral intervention in autism.
In: Kazdin, | |A. E. , Weisz, J. R. (Eds. ), Evidence-based Psychotherapies for Children and Adolescents. | |Guilford, New York. | |Luiselli, J. K. , Matson, J. L. , & Singh, N. N. (Eds. ) (1992). Self-injurious behavior: Analysis, assessment, and treatment. NY: | |Springer-Verlag. | |Mandler, J. , & Johnson, N. (1977). Remembrance of things parsed: Story structure and recall. Cognitive Psychology, 9, 111–151. | |Minshew, N. J. , & Goldstein, G. (2001). The pattern of intact and impaired memory functions in autism. Journal of Child Psychology and | |Psychiatry, 42, 1095–1101. | |Mottron, L. , Belleville, S. , Menard, E. (1999).
Local bias in autistic subjects as evidenced by | |graphic tasks: Perceptual hierarchization or working memory deficit? Journal of Child | |Psychology and Psychiatry 40, 743-55. | |Murray, D. K. C. (1992). Attention tunneling and autism. In Living with Autism: The | |Individual, the Family, and the Professional. Originally presented at the Durham Conference, UK. Proceedings obtainable from Autism Research | |Unit, School of Health Sciences, University of Sunderland, Sunderland SR2 7EE, UK. | |Murray, D. & Lesser, M. (1999). Autism and computing.
Originally presented at the Autism99 online conference organized by the NAS with the | |Shirley Foundation, UK. | |National Research Council, 2001. Educating children with autism. Committee on Educational | |Interventions for Children with Autism. Division of Behavioral and Social Sciences and | |Education. National Academy Press, Washington, DC. | |Oberman, L. , & Ramachandran, V. (2007). The simulating social mind: The role of the mirror neuron system and simulation in the social and | |communicative deficits of autism spectrum disorders. Psychological Bulletin, 133(2), 310-327. doi:10. 1037/0033-2909. 133. 2. 310. | |O’Roak, B. J. , & State, M. W. 2008) Autism genetics: strategies, challenges, and opportunities. Autism Research; 1:4–17. [PubMed: 19360646]. | |Panksepp, J. (1993). Commentary on the possible role of oxytocin in autism. Of Autism and Developmental Disorders, 23, 567-569. | |Paul, R. (2008). Interventions to improve communication in autism. Child Adolescent Psychiatry in Clinical North America; 17:835–856. [PubMed:| |18775373]. | |Rogers S. J. , Vismara, L. A. (2008). Evidence-based comprehensive treatments for early autism. Journal of Clinical Child and Adolescent | |Psychology, 37:8–38. [PubMed: 18444052]. | |Russell, J. (2002). Cognitive Theories of Autism. In J. Harrison & A.
Owen | |(Eds. ) Cognitive Deficits in Brain Disorders. London: Dunitz. | |Sallows, G. O. , Graupner, T. D. (2005). Intensive behavioral treatment for children with | |autism: Four-year outcome and predictors. American Journal on Mental Retardation. 110, | |417-438. | |Schultz, T. M. , & Berkson, G. (1995). Definition of abnormal focused affections and exploration of their relation to abnormal stereotyped | |behaviors. American Journal on Mental Retardation, 99, 376-390. | |Sebat, J. Lakshmi, B. , Malhotra, D. , et al. (2007). Strong association of de novo copy number mutations with autism. Science; 316:445–449. | |[PubMed: 17363630]. | |Smith, I. M. , & Bryson, S. E. (1994). Imitation and action in autism: A critical review. Psychological Bulletin, 116, 259-273. | |Smith, T. , Groen, A. D. , Wynn, J. W. (2000, 2001). Randomized trial of intensive early | |intervention for children with pervasive developmental disorder. American Journal on Mental Retardation, 105, 269-285. | |Spiker, D. , Lotspeich, L. , Kraemer, H. C. , Hallmayer, J. , McMahon, W. , & Peterson, P. B. (1994).
Genetics of autism: Characteristics of | |affected and unaffected children from 37 multiplex families. American Journal of Medical Genetics, 54, 27-35. | |Sutula, T, He, X. , Cavazos, J. , & Scott, G. (1988). Synaptic reorganization in the hippocampus induced by abnormal functional activity. | |Science. 239, 1147-1150. | |Tager-Flusberg, H. (1991). Semantic processing in the free recall of autistic children: Further | |evidence of a cognitive deficit. British Journal of Developmental Psychology, 9, 417– | |430. | |Tanaka, J. , Klaiman, C. , Koenig, K. , Schultz, R. T. (2005).
Plasticity of the neural mechanisms | |underlying face processing in children with ASD: Behavioral improvements following | |perceptual training on faces. International Meeting for Autism Research, Boston, MA. | |Waterhouse, L. , Fein, D. , & Modahl, C. (1996). Neurofunctional mechanisms in autism. Psychological Review, 103(3), 457-489. | |doi:10. 1037/0033-295X. 103. 3. 457. | |Williams D, Goldstein G, & Minshew, N. The profile of memory functions in children with autism. Neuropsychology, 20 (1):21-29. Available from:| |PsycARTICLES, Ipswich, MA. |Volkmar, F. R. , & Greenough, W. (1972). Rearing complexity affects branching of dendrites in the visual cortex of the rat. Science, 176, | |1445-1446. | |Young, R. L. , & Nettelbeck, T. (1995). The abilities of a musical savant and his family. Journal of Autism and Developmental Disorders, 25, | |231-248. | | | | | | | | | | |