Research and understanding of autism spectrum disorder (ASD) have evolved in recent decades. In this piece, we explore research findings using one representative article from each decade from 1990 to 2020.
The rate of identifying people as being on the autism spectrum disorder spectrum has been increasing in recent years — and so has the language we use to describe it and the practices we use to work with it.
In 2016, one in 54 eight year-olds were estimated to be on the autism spectrum in the United States. That year, ASD was found to be 4.3 times more prevalent in boys than girls (Maenner, et. al, 2020).
According to the DSM-V (American Psychiatric Association, 2013), ASD is a neurodevelopmental disorder impacting human development, which in turn can have wide-ranging social, academic, occupational, and personal functioning impacts on the child. As such, understanding ASD through interactions of theoretical, empirical, and interdisciplinary methods is key to creating appropriate learning environments for this population.
We chose three articles to track neurological theories, research, and technological developments related to the ASD population without intellectual impairment from 1991 to the present. Shifts in language and study construction, parameters, and methodology were observed.
As noted below, language used by researchers in the field evolved from terms with negative implications to more neutral terms describing ASD differences compared to other groups over the three decades. Minshew and Goldstein (1998) used terms such as “abnormalities,” “deficits,” and “non-mentally retarded” in their paper, likely reflecting prevalent cultural views on ASD. From the 2000s onward, as exampled by the Iarocci et al. (2006) and Shyman (2017) papers, the same three terms used by Minshew and Goldstein changed to “atypical,” “differences,” and “high-functioning,” reflecting a less pathologizing and more neurodiversity-centered viewpoint. The articles also illuminated a need to focus more on information processing rather than input differences when studying how this population responds to stimuli.
Articles
Minshew and Goldstein (1998) reviewed various neurobehavioral models of ASD from the 1960s until the mid-1980s and found that most of these models focused on a single primary cognitive domain deficit. Later research investigated multi-domain cognitive functioning within the same research sample, allowing for patterns of deficits to be observed. No deficits in attention, sensory perception, simple memory, simple language, rule learning, or visuospatial areas were found in this study compared to typically developing controls. On the other hand, motor, complex memory, complex language, and reasoning were found to be significantly at “deficit” from the controls. Minshew and Goldstein (1998) proposed that this pattern of intact basic skills and impairment in advanced cognitive abilities may be reflective of an underlying complex information processing model of ASD. In the decade following the Minshew and Goldstein (1998) paper, Iarocci et al. (2006) conducted two experiments comparing high-functioning ASD children (8-10 years) with two groups of typically developing children that had comparable non-verbal mental ages (NVMA) and verbal mental ages (VMA). The authors were interested to see if there were any differences in neutral, global (long range), or local (short range) visual attention processing when tasks were under expectancy (structural or implicit) bias conditions. In experiment 1, they found no significant differences between groups when searching for visual targets (four-dot configurations on a computer screen) in local or global spatial structural conditions. In experiment 2, 20 high-functioning ASD children, including the 12 from experiment 1, were again matched with VMA and NVMA children. ASD children were found to be most able to tune toward implicit bias conditions among the three groups, reacting fastest according to changes in the likelihood of global or local targets over the three sets of 40 experimental trials, compared to VMA or NVMA. On the other hand, ASD children were least sensitive to structural global bias. In the third and most recent article, Shyman (2017) presented a selective literature review from 2004 and later in which he describes structural and functional differences in the brain regions supporting emotional processing in ASD individuals and the implications for neuroeducation. He presented research using rating scales, fMRI (functional magnetic resonance imaging), MRI (magnetic resonance imaging), an oxytocin trial, eye-gaze measurement technology, blood oxygen level-depend (BOLD) signals, self-reporting, and video and picture viewing that all showed differences in ASD emotional processing. Shyman (2017) also identified the amygdala as one of the central neurological structures linked to differences in emotional processing. He proposed that teachers, neuroscience researchers, publishers and media, educational policy makers, and university teacher educators are the five key groups required to work together in order to further communicate, identify, and apply research findings to enhance education and intervention for ASD students, through the inclusion of social-emotional approaches. Based on my personal educational journey with my twice-exceptional autistic son, private schools that identify as catering to students with learning differences do seem to be more attuned to the importance of social-emotional factors on behavior and learning.Findings
The articles also illuminate movement toward using research paradigms more reflective of real-world situations rather than stimuli that are laboratory based, whose findings may or may not translate to real world situations. The Iarocci et al. (2006) empirical research paper is a good example of a stimuli delivered in a laboratory setting. There will need to be greater leaps taken in order to generalize their findings on how visual processing is occurring when viewing realistic everyday visual stimuli. Research literature reported by Shyman (2017) investigating emotional processing used more realistic stimuli such as videos and pictures of social interactions or faces expressing emotions. It is likely that the nature of the research subject (emotional processing) required more realistic stimuli. Applicability of complex information processing to explain ASD across the whole spectrum was not addressed by the three articles. Additionally, the articles did not elucidate how gender, racial, and cultural factors, in addition to changing diagnostic criteria for ASD, impact our understanding of ASD. [perfectpullquote align=”full” bordertop=”false” cite=”” link=”” color=”” class=”” size=””]Teachers, neuroscience researchers, publishers and media, educational policy makers, and university teacher educators are the five key groups required to work together in order to further communicate, identify, and apply research findings to enhance education and intervention for ASD students, through the inclusion of social-emotional approaches.[/perfectpullquote] It is reasonable to infer from the Shyman (2017) paper that greater awareness and understanding for the need of interdisciplinary (neuroscience, education, psychology) and inter-group (teachers, researchers, policy makers) collaboration is beginning to be acknowledged. All the different stakeholders are required in order to guide research with the goal of practical applications in real life. We need researchers to not only clarify different theoretical models of ASD, but also to prioritize and design research that may be applicable to impact educational policies, practice, and related services such as therapeutic services. Following three decades of study in high-functioning ASD populations, using the information processing model to understand ASD continues to receive research support as more domains are investigated. The information processing areas that were covered in the three articles included physical brain structures and functional domains such as attention, sensory perception, motor, simple language, complex language, simple memory, complex memory, visual task bias, global-local visual processing, reasoning, visual-spatial and emotional. The general consensus seems to support differences in information processing and not input differences as one key element in understanding ASD in high-functioning children, adolescents and adults. Such understanding may require refinement, modification, or a different model as future studies include gender, cultural, socio-economic, and racial components into the experimental design. References American Psychiatric Association. (2013). Neurodevelopmental Disorders. In Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596.dsm01 Iarocci, G., Burack, J. A., Shore, D. I., Mottron, L., & Enns, J. T. (2006). Global-local visual processing in high functioning children with autism: Structural vs. implicit task biases. Journal of Autism & Developmental Disorders, 36(1), 117. doi:10.1007/s10803-005-0045-2 Maenner, M., Shaw, K., Baio, J. et. al. (2020). Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016. Surveillance Summaries, 69(4);1–12. doi: http://dx.doi.org/10.15585/mmwr.ss6904a1external icon. Minshew, N. J., & Goldstein, G. (1998). Autism as a disorder of complex information processing. Mental Retardation & Developmental Disabilities Research Reviews, 4(2), 129. doi:10.1002/(SICI)1098-2779(1998)4:2<129::AID-MRDD10>3.0.CO;2-X Shyman, E. (2017). Please wait, processing: A selective literature review of the neurological understanding of emotional processing in ASD and its potential contribution to neuroeducation. Brain Sciences, 7(11). doi:10.3390/brainsci7110153
