Meta-analytic evidence for a core problem solving network across multiple representational domains. (September 2018)

• Record Type: Journal Article
• Authors: Bartley, Jessica E.; Boeving, Emily R.; Riedel, Michael C.; Bottenhorn, Katherine L.; Salo, Taylor; Eickhoff, Simon B.; Brewe, Eric; Sutherland, Matthew T.; Laird, Angela R.
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 92(2018)
• Page Start: 318
• Page End: 337
• Publication Date: 2018-09
• Subjects: Problem solving -- Reasoning -- Cognitive control -- Functional neuroimaging -- Meta-analysis -- Activation likelihood estimation (ALE) -- Domain-generality -- Domain-specificity; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2018.06.009
• Languages: English
• ISSNs: 0149-7634

Abstract

Highlights: Identified meta-analytic brain networks associated with diverse problem solving tasks. A shared managerial and attentional network supports generalized problem solving. Problem solving within content areas engages representationally specific sub-networks. Problem solving relies on cooperation between sub-network and whole-brain systems. 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.