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Jointly modeling behavioral and EEG measures of proactive control in task switching
Frini Karayanidis1, Guy E Hawkins1, Aaron S W Wong1
1School of Psychological Sciences, University of Newcastle, Newcastle, New South Wales, Australia.
Psychophysiology
|January 12, 2023
Summary
We linked brain activity, specifically electroencephalography (EEG) signals during the cue-target interval, to decision-making adjustments in a task-switching study. Findings suggest current cognitive models need refinement for complex task-switching.
Area of Science:
- Cognitive Neuroscience
- Computational Neuroscience
Background:
- Task-switching involves cognitive control processes.
- Understanding the neural basis of decision-making adjustments is crucial.
Purpose of the Study:
- To investigate the link between electroencephalography (EEG) signals and response criterion adjustments in a cued-trials task-switching paradigm.
- To test if event-related potentials (ERPs) during the cue-target interval (CTI) correlate with decision-making parameters.
Main Methods:
- Implemented joint modeling of behavioral data and single-trial EEG.
- Utilized a diffusion decision model (DDM) to derive response criterion.
- Examined three joint models varying in complexity of cognitive control parameters.
Main Results:
- A significant link was found between response criterion and pre-target negativity amplitude in EEG.
- Switch and task preparation parameters improved ERP waveform modeling but not the criterion-EEG link.
- The criterion-EEG link was strongest just before target onset.
Conclusions:
- Joint modeling successfully linked latent decision parameters with EEG data in task-switching.
- Current cognitive models may require customization to fully capture task-switching complexities.
- This study highlights the need for more nuanced models of proactive cognitive control.
