Investigating the involvement of cognitive control processes in innovative and adaptive creativity and their age-related changes.

ERP Figural TTCT aging cognitive control creativity innovative/adaptive task-switching

Journal

Frontiers in human neuroscience
ISSN: 1662-5161
Titre abrégé: Front Hum Neurosci
Pays: Switzerland
ID NLM: 101477954

Informations de publication

Date de publication:
2023
Historique:
received: 31 08 2022
accepted: 09 01 2023
entrez: 23 2 2023
pubmed: 24 2 2023
medline: 24 2 2023
Statut: epublish

Résumé

Based on the two-factor model of creativity, two distinct types of creative problem solving can be differentiated: innovative ("do things differently") and adaptive ("do things better"). Flexible cognitive control is a crucial concept in connection with both general and specific styles of creativity: innovative problem-solving benefits from broader attention and flexible mental set shifting; while adaptive creativity relies on focused attention and persistent goal-oriented processes. We applied an informatively cued task-switching paradigm which is suitable for measuring different cognitive control processes and mechanisms like proactive and reactive control. We hypothesized that adaptive creativity is connected to effective proactive control processes, while innovative creativity is based on reactive task-execution. As we have found no previous evidence how age-related changes in cognitive control affects creative cognition; we also examined the effect of healthy aging on different problem-solving styles in an explorative way. Our participants, 37 younger (18-30 years) and 37 older (60-75 years) adults, were divided into innovative and adaptive creative groups according to the Torrance Test of Creative Thinking's Figural Subtest (Hungarian version). Our results showed that among younger adults the adaptively creative group had larger cue-locked CNV component (effective preparatory activity connected to proactive control), while the innovatively creative group had a larger target-locked P3b component (effective target evaluation and categorization in line with reactive control) which supports a functional difference in the two creative styles. By contrast, in older adults innovative problem-solving showed larger mixing costs (less effective maintenance and selection of task sets), and the lack of trial type effect on target-locked N2b (target-induced goal reactivation and less effective conflict resolution); while adaptive problem-solving caused them to make fewer errors (accuracy-oriented behavior). All in all, innovative and adaptive creativity is based on distinct cognitive control mechanisms in both age-groups, but their processing level is affected by age-related changes.

Identifiants

pubmed: 36816501
doi: 10.3389/fnhum.2023.1033508
pmc: PMC9932509
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1033508

Informations de copyright

Copyright © 2023 Nagy, Czigler, Csizmadia, File, Fáy and Gaál.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Boglárka Nagy (B)

Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.
Department of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary.

István Czigler (I)

Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.

Petra Csizmadia (P)

Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.
Department of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary.

Domonkos File (D)

Institute of Psychology, Eötvös Loránd University, Budapest, Hungary.

Nóra Fáy (N)

Independent Researcher, Budapest, Hungary.

Zsófia Anna Gaál (ZA)

Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary.

Classifications MeSH