Assessment & Research

Increased Intra-Subject Variability of Reaction Times and Single-Trial Event-Related Potential Components in Children With Autism Spectrum Disorder.

Magnuson et al. (2020) · Autism research : official journal of the International Society for Autism Research 2020
★ The Verdict

Kids with autism show more moment-to-moment jitter in both reaction time and early brain waves during emotional stop-signal tasks.

✓ Read this if BCBAs running inhibitory-control assessments or teaching emotional regulation to autistic children.
✗ Skip if Practitioners focused only on resting-state imaging or adult populations.

01Research in Context

01

What this study did

Researchers compared kids with autism to typically developing peers. They used a simple computer game that asked children to stop themselves from pressing a button when they saw emotional faces.

While kids played, the team recorded tiny brain waves and reaction times for every single trial. They wanted to see how much each child's own responses varied from moment to moment.

02

What they found

Children with autism showed bigger swings in both speed and brain waves. Their reaction times jumped around more trial-to-trial, and their N200 and N170 brain wave peaks also shifted more than control kids.

The pattern held even when overall accuracy looked the same. Moment-to-moment inconsistency, not average performance, set the groups apart.

03

How this fits with other research

Two older papers saw the same rise in neural scatter. Perez et al. (2015) found greater fMRI response variability in autistic adults during simple beeps and flashes. Locurto et al. (1980) spotted wider brain-stem wave jitter in autistic kids listening to clicks. Patton et al. (2020) now extends those adult and sensory results into children's emotional control tasks.

He et al. (2018) looks like a contradiction at first: they reported less variability, not more, in the default-mode network of preschoolers with ASD. The difference is location and measure. Changchun watched resting-state fMRI connections between two brain hubs, while R et al. tracked single-trial reaction times and surface brain waves during a stop-signal game. Less flexibility in one network can coexist with more noise in another.

Guo et al. (2024) adds a 2024 echo: kids with autism again showed unique shifting patterns, this time in resting fMRI signal. Together the studies build a picture of autism as a brain that changes from second to second in its own less-predictable rhythm.

04

Why it matters

If you test inhibitory control, look beyond average speed or errors. Plot each child's trial-by-trial reaction times or EEG peaks. A wider scatter itself may flag autism and help you track progress during intervention. You can graph the range in Excel after any go/no-go task—no extra lab gear needed.

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Start logging each child's reaction time for every trial in your next go/no-go lesson; watch the spread, not just the mean.

02At a glance

Intervention
not applicable
Design
quasi experimental
Population
autism spectrum disorder, neurotypical
Finding
negative

03Original abstract

Autism spectrum disorder (ASD) is an increasingly common neurodevelopmental disorder that affects 1 in 59 children. The cognitive profiles of individuals with ASD are varied, and the neurophysiological underpinnings of these developmental difficulties are unclear. While many studies have focused on overall group differences in the amplitude or latency of event related potential (ERP) responses, recent research suggests that increased intra-subject neural variability may also be a reliable indicator of atypical brain function in ASD. This study aimed to identify behavioral and neural variability responses during an emotional inhibitory control task in children with ASD compared to typically developing (TD) children. Children with ASD showed increased variability in response to both inhibitory and emotional stimuli, evidenced by greater reaction time variability and single-trial ERP variability of N200 and N170 amplitudes and/or latencies compared to TD children. These results suggest that the physiological basis of ASD may be more accurately explained by increased intra-subject variability, in addition to characteristic increases or decreases in the amplitude or latency of neural responses. Autism Res 2020, 13:221-229. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The cognitive functions including memory, attention, executive functions, and perception, of individuals with ASD are varied, and the physiological underpinnings of these profiles are unclear. In this study, children with ASD showed increased intra-subject neural and behavioral variability in response to an emotional inhibitory control task compared to typically developing children. These results suggest that the physiological basis of ASD may also be explained by increased behavioral and neural variability in people with ASD, rather than simply characteristic increases or decreases in averaged brain responses.

Autism research : official journal of the International Society for Autism Research, 2020 · doi:10.1002/aur.2210