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Resting-state brain oscillations predict trait-like cognitive styles
Journal article   Open access   Peer reviewed

Resting-state brain oscillations predict trait-like cognitive styles

Brian Erickson, Monica Truelove-Hill, Yongtaek Oh, Julia Anderson, Fengqing Zoe Zhang and John Kounios
Neuropsychologia, v 120
Nov 2018
DOI: https://doi.org/10.1016/j.neuropsychologia.2018.09.014
PMID: 30261163
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.1016/j.neuropsychologia.2018.09.014View
Accepted (AM)Open Access (Publisher-Specific),  Open

Abstract

Adolescent Adult Brain - physiology Electroencephalography Female Humans Male Personality - physiology Problem Solving - physiology Reaction Time Rest Signal Processing, Computer-Assisted Young Adult
Anecdotal reports suggest the existence of individual differences in peoples' cognitive styles for solving problems, in particular, the tendency to rely on insight (the "aha" phenomenon) versus deliberate analytical thought. We hypothesized that such stable individual differences exist and are associated with trait-like individual differences in resting-state brain activity. We tested this idea by recording participants' resting-state electroencephalograms (RS-EEGs) on 4 occasions over approximately 7 weeks and then tasking them with solving anagrams and compound remote associates problems that are solvable by either strategy. We found that peoples' tendency to solve problems consistently by insight or by analysis spans both tasks and time. Moreover, we discovered trait-like individual differences in the balance between frontal and posterior resting-state brain activity and in temporal-lobe hemispheric asymmetries that predict, at least weeks in advance, the tendency to solve by insight versus analysis. The discovery of an insight-analytic dimension of cognitive style and its neural basis in resting state brain activity suggests new avenues for the development of neuroscience-based methods for intellectual, educational, and vocational assessment.

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30 citations in Web of Science
34 citations in Scopus

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Web of Science research areas
Behavioral Sciences
Neurosciences
Psychology, Experimental
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