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Issue Date: August 2016
Published Online: August 01, 2016
Updated: January 01, 2021
Brain–Behavior Relationships Measuring Attention Differences Among Children With Autism and Age-Matched Peers
Author Affiliations
  • Developmental FX
  • Colorado State University
Article Information
Autism/Autism Spectrum Disorder / Pediatric Evaluation and Intervention / Basic Research
Research Platform   |   August 01, 2016
Brain–Behavior Relationships Measuring Attention Differences Among Children With Autism and Age-Matched Peers
American Journal of Occupational Therapy, August 2016, Vol. 70, 7011505097. https://doi.org/10.5014/ajot.2016.70S1-RP401D
American Journal of Occupational Therapy, August 2016, Vol. 70, 7011505097. https://doi.org/10.5014/ajot.2016.70S1-RP401D
Abstract

Date Presented 4/10/201

Children with high-functioning autism have different brain processing and brain–behavior relationships than typically developing peers. Results may inform how occupational therapists select therapeutic approaches and stimulate adaptive responses during therapy for improving everyday activities.

Primary Author and Speaker: Emily Marshall

Contributing Authors: Mary Khetani, Blythe LaGasse, Mei-Heng Lin, Jewel Crasta, William J. Gavin, Patricia Davies

RESEARCH QUESTION: Is there a relationship between the neural and behavioral measures of attention among children with high-functioning autism (HFA) and typically developing peers?
RATIONALE: Children with HFA have challenges in attention and auditory processing. These attentional deficits have been associated with difficulties in orientation and habituation and can create challenges in performance and participation in everyday tasks. Few studies have assessed relationships between neural and behavioral measures, yet the benefits of doing so are invaluable. Neural measures obtained from electroencephalography (EEG) and event-related potentials (ERP) have associations with functional behaviors. For example, the N1 ERP component has been related to early sensory processing and selective attention to stimuli, and the N2 ERP is associated with cognitive processing. These ERP components can be compared with clinical assessments to illustrate brain–behavior relationships.
DESIGN: A cross-sectional quasi-experimental quantitative study design with convenience sampling procedures was used to compare two groups.
PARTICIPANTS: Participants included 20 children with HFA between ages 6 and 12 yr and 22 age- and gender-matched typically developing peers.
METHOD: Participants completed the Test of Everyday Attention for Children (TEA–Ch). The TEA–Ch is a standardized assessment of attention containing nine subtests that measure three subtypes of attention: sustained, selective, and control/shift. The EEG session required the children to complete a passive listening orientation and habituation paradigm. This task consists of three trains of eight tones each. The first train contains eight identical tones, and the second and third have a deviant tone at the fourth and fifth positions, respectively. This paradigm provides measures of habituation and auditory processing of novel and deviant tones through measures of N1 and N2 ERP amplitudes. Habituation is reduction of attention to continually repeated stimuli. In our study, habituation was measured as N1 and N2 reduction from Tone 2 to Tone 8. To assess orienting, N1 and N2 were measured at Tone 1 in the train of eight identical tones.
ANALYSIS: Mann–Whitney U and two-way analyses of variance were used to evaluate group differences, and hierarchical regression analyses were used to evaluate brain–behavior relationships.
RESULTS: Results of the TEA–Ch indicated significant difficulties in attention control/shift and sustained attention abilities in children with HFA compared with the control group. EEG measures suggested similar habituation abilities as well as auditory processing to novel and deviant tones between groups. Analysis of brain–behavior relationships indicated a significant association between attention control/shift and N2 amplitudes for the first tone in the series with eight identical tones for the control group. In contrast, in the HFA group, there was a significant relationship between attention control/shift and N1 amplitudes for the first tone in the series with eight identical tones.
DISCUSSION: Results indicate that brain–behavior relationships differed between children with HFA and the control group. In the HFA group, ERP components associated with sensory processing related better with behavioral measures of attention, whereas for the control group, this relationship was defined by more cognitive-based ERP components.
IMPACT: This study adds to the understanding of differences in brain processing and brain–behavior relationships between groups. It also may inform how occupational therapists select therapeutic approaches, scaffold attention demands, and stimulate the adaptive response during interventions focused toward improving everyday task performance.