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Neurosci Biobehav Rev. 2018 Sep;92:318-337. doi: 10.1016/j.neubiorev.2018.06.009. Epub 2018 Jun 23.

Meta-analytic evidence for a core problem solving network across multiple representational domains.

Author information

1
Department of Physics, Florida International University, Miami, FL, USA.
2
Department of Psychology, Florida International University, Miami, FL, USA.
3
Institute for Systems Neuroscience, Medical Faculty, Heinrich Heine University Dusseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Center Jülich, Jülich, Germany.
4
Department of Teaching and Learning, Florida International University, Miami, FL, USA; Department of Physics, Drexel University, Philadelphia, PA, USA; Department of Education, Drexel University, Philadelphia, PA, USA.
5
Department of Physics, Florida International University, Miami, FL, USA. Electronic address: alaird@fiu.edu.

Abstract

Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development.

KEYWORDS:

Activation likelihood estimation (ALE); Cognitive control; Domain-generality; Domain-specificity; Functional neuroimaging; Meta-analysis; Problem solving; Reasoning

PMID:
29944961
DOI:
10.1016/j.neubiorev.2018.06.009
[Indexed for MEDLINE]

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