期刊
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
卷 92, 期 -, 页码 318-337出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neubiorev.2018.06.009
关键词
Problem solving; Reasoning; Cognitive control; Functional neuroimaging; Meta-analysis; Activation likelihood estimation (ALE); Domain-generality; Domain-specificity
资金
- National Science Foundation [REAL DRL-1420627, 1631325]
- National Institute of Drug Abuse [U24-DA039832, U01-DA041156, K01-DA037819]
- National Institute of Mental Health [R56-MH097870]
- Direct For Education and Human Resources
- Division Of Research On Learning [1420627] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1631325] Funding Source: National Science Foundation
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.
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