The impact of acute high-intensity activity on perceptual decision-making dynamics

This study investigates the acute impact of high-intensity activity on perceptual decision-making, using computational modeling to assess changes during and after physical activity. Participants performed a two-alternative forced choice perceptual decision-making task at rest (pre- and post-exercise) and during six of eight 5-min cycling bouts (totaling 47 min) under dual-task condition, while maintaining an average intensity of 86 ± 7% of their maximum heart rate. Drift diffusion modeling was applied to accuracy and reaction time data to estimate changes in evidence accumulation (drift rate), decision threshold (boundary separation), and nondecision processes (t<sub>er</sub>). Results revealed improved post-exercise performance, characterized by shorter nondecision time, potentially reflecting a transient improvement in motor or perceptual efficiency. During ongoing physical activity, results indicate that exercise is associated with a decrease in nondecision time and an increase in the efficiency of evidence accumulation, while response caution remains stable. These findings provide novel insights into how sustained high-intensity exercise modulates perceptual decision-making dynamics under physiological stress.

Authors

Institutions

Publication Details

Journal
Cognitive Affective & Behavioral Neuroscience
Published
2025-12-05
DOI
https://doi.org/10.3758/s13415-025-01372-3
Citations
1
Primary Topic
Heart Rate Variability and Autonomic Control
Type
article
Field-Weighted Citation Impact
1.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The impact of acute high-intensity activity on perceptual decision-making dynamics

Thibault Gajdos, Dorian Giraud, Karen Davranche, Arnaud Hays
1 citations
Cognitive Affective & Behavioral Neuroscience
Heart Rate Variability and Autonomic Control
1.39
article

The impact of acute high-intensity activity on perceptual decision-making dynamics

Thibault Gajdos, Dorian Giraud, Karen Davranche, Arnaud Hays
article en
1 citations

Abstract

This study investigates the acute impact of high-intensity activity on perceptual decision-making, using computational modeling to assess changes during and after physical activity. Participants performed a two-alternative forced choice perceptual decision-making task at rest (pre- and post-exercise) and during six of eight 5-min cycling bouts (totaling 47 min) under dual-task condition, while maintaining an average intensity of 86 ± 7% of their maximum heart rate. Drift diffusion modeling was applied to accuracy and reaction time data to estimate changes in evidence accumulation (drift rate), decision threshold (boundary separation), and nondecision processes (t<sub>er</sub>). Results revealed improved post-exercise performance, characterized by shorter nondecision time, potentially reflecting a transient improvement in motor or perceptual efficiency. During ongoing physical activity, results indicate that exercise is associated with a decrease in nondecision time and an increase in the efficiency of evidence accumulation, while response caution remains stable. These findings provide novel insights into how sustained high-intensity exercise modulates perceptual decision-making dynamics under physiological stress.

Cognitive Affective & Behavioral Neuroscience
Centre National de la Recherche Scientifique (FR), Université de Toulon (FR), Aix-Marseille Université (FR), Institut Universitaire des Systèmes Thermiques Industriels (FR)
Openalex Percentile: Top 13%
Heart Rate Variability and Autonomic Control
1.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.