Neural signatures of engagement in driving: comparing active control and passive observation

Understanding how the human brain differentiates between active engagement and passive observation is a fundamental question in cognitive neuroscience. Using a matched-stimulus driving paradigm to isolate engagement from sensory input, we recorded whole-brain EEG while participants performed a manual control task and passively viewed a replay of their own performance. Manual control elicited distinct spectral signatures, including stronger frontal midline theta power and, paradoxically, greater occipital alpha power, consistent with heightened cognitive control and active attentional filtering. While a classifier could distinguish these states with high within-subject accuracy, performance declined in cross-subject validation, highlighting inter-individual variability. These findings delineate the distinct neural signatures of active versus passive engagement under controlled conditions. This work establishes a foundational neurophysiological baseline that can inform research on cognitive state monitoring and the design of neuroadaptive systems in complex human-machine interaction.

Authors

Institutions

Publication Details

Journal
Frontiers in Neuroscience
Published
2025-11-06
DOI
https://doi.org/10.3389/fnins.2025.1698625
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Neural signatures of engagement in driving: comparing active control and passive observation

Yasuharu Koike, Hiroyuki Kambara, Zixin Li
Frontiers in Neuroscience
EEG and Brain-Computer Interfaces
article

Neural signatures of engagement in driving: comparing active control and passive observation

Yasuharu Koike, Hiroyuki Kambara, Zixin Li
article en

Abstract

Understanding how the human brain differentiates between active engagement and passive observation is a fundamental question in cognitive neuroscience. Using a matched-stimulus driving paradigm to isolate engagement from sensory input, we recorded whole-brain EEG while participants performed a manual control task and passively viewed a replay of their own performance. Manual control elicited distinct spectral signatures, including stronger frontal midline theta power and, paradoxically, greater occipital alpha power, consistent with heightened cognitive control and active attentional filtering. While a classifier could distinguish these states with high within-subject accuracy, performance declined in cross-subject validation, highlighting inter-individual variability. These findings delineate the distinct neural signatures of active versus passive engagement under controlled conditions. This work establishes a foundational neurophysiological baseline that can inform research on cognitive state monitoring and the design of neuroadaptive systems in complex human-machine interaction.

Frontiers in NeuroscienceVol. 19
Tokyo Polytechnic University (JP), Institute of Science Tokyo (JP), National Institute of Information and Communications Technology (JP)
Japan Agency for Medical Research and Development, Japan Society for the Promotion of Science
Openalex Percentile: Top 67%
EEG and Brain-Computer Interfaces
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.

Neural signatures of engagement in driving: comparing active control and passive observation — Yasuharu Koike, Hiroyuki Kambara, et al. · Frontiers in Neuroscience (2025) | TGRS Research Map | TGRS