Logo image
Uncovering the Interplay of Oscillatory Processes During Creative Problem Solving: A Dynamic Modeling Approach
Journal article   Open access   Peer reviewed

Uncovering the Interplay of Oscillatory Processes During Creative Problem Solving: A Dynamic Modeling Approach

Yuhua Yu, Yongtaek Oh, John Kounios and Mark Beeman
Creativity research journal, v ahead-of-print(ahead-of-print)
17 Feb 2023
url
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10745236View
Accepted (AM)Open Access (License Unspecified) Open

Abstract

To solve a new problem, people spontaneously engage multiple cognitive processes. Previous work has identified a diverse set of oscillatory components critical at different stages of creative problem solving. In this project, we use hidden state modeling to untangle the roles of oscillation processes over time as people solve puzzles. Building on earlier work, we further developed analytical methods, such as incorporating source separating techniques and identifying the optimal number of states using cross-validation. We extracted brain states characterized by spatio-spectral topographies from time-resolved EEG spectral powers. The data driven approach allowed us to infer the dynamic, trial-by-trial, state sequences, and provided a comprehensive depiction of how various oscillation components interact recurrently throughout the trial. The properties of the states suggest their dissociable cognitive functions. For example, we identified three states with dominant activation in alpha bands but having distinct spatial distributions. People were differentially engaged in these states depending on the stages (e.g., onset or response) and outcomes of the trials (solved with insight or analysis). The current approach, applicable to many tasks requiring extended trial duration, can potentially reconcile findings from previous EEG studies and drive new hypotheses to further our understanding of the complex creative process.

Metrics

7 Record Views
6 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#4 Quality Education

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Psychology, Educational
Psychology, Multidisciplinary
Logo image