Temporal dynamics of dual-task interference in the brain in a simulated driving environment

Area of Science:

• Cognitive Neuroscience
• Human-Computer Interaction
• Psychology

Background:

• Dual-task interference arises from the brain's limited cognitive resources.
• Understanding the temporal dynamics of this interference is crucial for optimizing task design.

Purpose of the Study:

• To investigate the time course of dual-task interference using electroencephalography (EEG) and advanced analytical techniques.
• To differentiate the impact of interference on decision-making and motor execution stages.

Main Methods:

• Electroencephalography (EEG) combined with multivariate pattern analysis (MVPA) and drift-diffusion modeling (DDM).
• Participants performed single and dual-tasks (tone discrimination and simulated driving lane-change) with varying stimulus onset asynchrony (SOA).
• MVPA temporal and conditional generalization, alongside searchlight analysis, were employed to examine neural pattern stability and information localization.

Main Results:

• Dual-task interference, particularly with short SOA, increased reaction times by altering decision and post-decision processes (DDM).
• MVPA revealed reduced decoding accuracy and disrupted neural pattern stability as early as ~250 ms in short SOA conditions.
• A bottleneck in later processing stages (~450 ms) and reduced task-specific information in perceptual to motor regions were observed.

Conclusions:

• Tasks are processed partially in parallel during early perceptual and decision stages (~first 100 ms).
• Later processing stages (>~450 ms) exhibit serial competition for motor output, leading to performance decrements.
• Findings elucidate the temporal unfolding of cognitive bottlenecks in dual-task scenarios.