PLoS ONENeurosciencePeer-reviewed journal article
Neurocognitive Dynamics of Preparatory and Adaptive Cognitive Control: Insights from Mass-Univariate and Multivariate Pattern Analysis of EEG data
José C. García AlanisiD, Malte Rudo GüthiD, Mira‐Lynn ChavanoniD, Martin PeperiD
Abstract
Cognitive control encompasses a set of basic perceptual and reasoning processes that help us align thoughts and actions with goals. While a growing body of research indicates that these processes can be independently engaged and tuned to fit different tasks (e.g., behavioural preparation vs behavioural adaptation), the dynamic interplay of these processes and their functional timing within the information stream, remains elusive. In this study, we used a combination of mass-univariate and multivariate pattern analysis to examine electroencephalography data from 52 participants, recorded during performance of the Dot Pattern Expectancy Task (DPX), a task designed to assess both preparatory and adaptive cognitive control. Contrary to the notion of isolated neural signatures for either cognitive control mode, our data indicates that cognitive control engages a sequence of distinct yet partially overlapping brain activation patterns. Preparatory cue-stimuli evoked early transient occipital-parietal amplitude responses that were followed by enhanced sustained central-parietal and fronto-central amplitude responses. Similarly, adaptive probe-stimuli evoked enhanced early transient occipital-parietal amplitude responses, but these were followed by enhanced transient, fronto-central and central parietal amplitude responses. Moreover, we found significant relationships between the magnitude of the central-parietal and fronto-central amplitude response pattern and behavioural performance in the DPX. This research not only extends prior work but also offers valuable insights into the functional timing and organisation of the neurocognitive processes underpinning both preparatory and adaptive cognitive control.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 2
- FWCI
- 0.48
- Field percentile
- top 39%
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