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Articles, Behavioral/Cognitive

Dynamic Network Mechanisms of Relational Integration

Beth L. Parkin, Peter J. Hellyer, Robert Leech and Adam Hampshire
Journal of Neuroscience 20 May 2015, 35 (20) 7660-7673; DOI: https://doi.org/10.1523/JNEUROSCI.4956-14.2015
Beth L. Parkin
2Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, United Kingdom
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Peter J. Hellyer
1The Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, London SW7 2AZ, United Kingdom, and
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Robert Leech
1The Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, London SW7 2AZ, United Kingdom, and
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Adam Hampshire
1The Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, London SW7 2AZ, United Kingdom, and
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Abstract

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support “relational integration” (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional “domain-general” resources when processing more difficult problems in general as opposed to RI specifically. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain-general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.

  • fMRI
  • frontopolar cortex
  • functional networks
  • phase synchrony
  • relational integration
  • rostrolateral prefrontal cortex

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The Journal of Neuroscience: 35 (20)
Journal of Neuroscience
Vol. 35, Issue 20
20 May 2015
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Dynamic Network Mechanisms of Relational Integration
Beth L. Parkin, Peter J. Hellyer, Robert Leech, Adam Hampshire
Journal of Neuroscience 20 May 2015, 35 (20) 7660-7673; DOI: 10.1523/JNEUROSCI.4956-14.2015

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Dynamic Network Mechanisms of Relational Integration
Beth L. Parkin, Peter J. Hellyer, Robert Leech, Adam Hampshire
Journal of Neuroscience 20 May 2015, 35 (20) 7660-7673; DOI: 10.1523/JNEUROSCI.4956-14.2015
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Keywords

  • fMRI
  • frontopolar cortex
  • functional networks
  • phase synchrony
  • relational integration
  • rostrolateral prefrontal cortex

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