Examining reaction time variability on the stop-signal task in the ABCD study
DOI: 10.1017/s1355617722000431
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Summary
This study investigates reaction time variability (RTV) in children using data from the Adolescent Brain Cognitive Development (ABCD) study, aiming to clarify the interrelationships between different computational models of RT and to examine sex differences and time-on-task effects. RTV is a marker for impaired attention and is associated with various psychiatric disorders, yet prior research has rarely examined how Gaussian, ex-Gaussian, and diffusion model (DM) parameters relate to one another in childhood populations. The authors sought to determine if computational models could better elucidate the mechanisms underlying performance changes over time and group differences than standard descriptive statistics. The researchers analyzed trial-level data from the stop-signal task (SST) for 8,916 children aged 9–10 years. They excluded participants with poor accuracy or extreme stop probabilities. Using the integration method, they calculated stop-signal reaction times. For Go-trials, they estimated Gaussian indices (mean RT, standard deviation, coefficient of variation), ex-Gaussian parameters (mu, sigma, tau), and DM parameters (drift rate, boundary separation, non-decision time) using Fast-DM software. Parameter recovery simulations confirmed that the available trial counts allowed for good to excellent estimation of these parameters. The study examined correlations among these indicators, temporal patterns of performance, and sex-based differences. Results indicated no one-to-one correspondence between DM and ex-Gaussian parameters. Drift rate was most strongly associated with the standard deviation of RT and tau, while non-decisional processes correlated most strongly with mean RT, mu, and sigma. Performance worsened over time, driven primarily by a decrease in drift rate, suggesting a decline in the efficiency of information accumulation rather than just increased impulsivity. Regarding sex differences, boys were faster and less variable than girls. Computational modeling revealed that this difference was likely attributable to girls’ wider boundary separation, indicating a more cautious response strategy, rather than slower processing speed. Standard models might incorrectly interpret this caution as slowed processing. The findings demonstrate that computational approaches are crucial for understanding the cognitive mechanisms behind RTV in children. The intercorrelations among model parameters in children mirror those observed in adults, validating the use of these models in developmental psychopathology. Importantly, the study highlights that standard RT metrics can be misleading; for instance, they may suggest girls have slower processing speeds when they actually employ a different speed-accuracy trade-off strategy. These results underscore the value of using computational models to disentangle distinct cognitive processes, such as information accumulation efficiency versus response caution, which is essential for identifying accurate risk markers for psychopathology and understanding sex-specific cognitive profiles.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-20 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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- Empirical Findings: behavioral performance data