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Accepted (AM)Open Access (License Unspecified), Open
Journal article
EEG Spectral-power Volatility Predicts Problem-solving Outcomes
Journal of cognitive neuroscience, p1
03 Mar 2024
PMID: 38437171
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Temporal variability is a fundamental property of brain processes and is functionally important to human cognition. This study examined how fluctuations in neural oscillatory activity are related to problem-solving performance as one example of how temporal variability affects high-level cognition. We used volatility to assess step-by-step fluctuations of EEG spectral power while individuals attempted to solve word-association puzzles. Inspired by recent results with hidden-state modeling, we tested the hypothesis that spectral-power volatility is directly associated with problem-solving outcomes. As predicted, volatility was lower during trials solved with insight compared with those solved analytically. Moreover, volatility during prestimulus preparation for problem-solving predicted solving outcomes, including solving success and solving time. These novel findings were replicated in a separate data set from an anagram-solving task, suggesting that less-rapid transitions between neural oscillatory synchronization and desynchronization predict better solving performance and are conducive to solving with insight for these types of problems. Thus, volatility can be a valuable index of cognition-related brain dynamics.
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Details
- Title
- EEG Spectral-power Volatility Predicts Problem-solving Outcomes
- Creators
- Yuhua Yu - Northwestern University, Evanston, ILYongtaek Oh - Drexel UniversityJohn Kounios - Drexel UniversityMark Beeman - Northwestern University, Evanston, IL
- Publication Details
- Journal of cognitive neuroscience, p1
- Grant note
- T32 NS047987 / NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:001199555100009
- Scopus ID
- 2-s2.0-85190483399
- Other Identifier
- 991021860639504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Neurosciences
- Psychology, Experimental