Lateral prefrontal cortex contributes to fluid intelligence via multi-network connectivity

Our ability to effectively adapt to novel circumstances – as measured by general fluid intelligence – has recently been tied to the global connectivity of lateral prefrontal cortex (LPFC). Global connectivity is a broad measure that summarizes both within-network and across-network connectivity. We used additional graph theoretical measures to better characterize the nature of LPFC connectivity and its relationship with fluid intelligence. We specifically hypothesized that LPFC is a " connector " hub with across-network connectivity that contributes to fluid intelligence independently of within-network connectivity. We verified that LPFC was in the top 10% of brain regions in terms of across-network connectivity, suggesting it is a strong connector hub. Importantly, we found that LPFC across-network connectivity predicted individuals' fluid intelligence, and that this correlation remained statistically significant when controlling for global connectivity (which includes within-network connectivity). This supports the conclusion that across-network connectivity independently contributes to the relationship between LPFC connectivity and intelligence. These results suggest LPFC contributes to fluid intelligence by being a connector hub with truly global multi-system connectivity throughout the brain.

[1]  Jonathan D. Power,et al.  Evidence for Hubs in Human Functional Brain Networks , 2013, Neuron.

[2]  Jonathan D. Power,et al.  Multi-task connectivity reveals flexible hubs for adaptive task control , 2013, Nature Neuroscience.

[3]  Michael W. Cole,et al.  Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence , 2012, The Journal of Neuroscience.

[4]  Andrew R. A. Conway,et al.  Journal of Experimental Psychology : General Neural Mechanisms of Interference Control Underlie the Relationship Between Fluid Intelligence and Working Memory Span , 2011 .

[5]  S. Petersen,et al.  Concepts and principles in the analysis of brain networks , 2011, Annals of the New York Academy of Sciences.

[6]  Michael W. Cole,et al.  Prefrontal Dynamics Underlying Rapid Instructed Task Learning Reverse with Practice , 2010, The Journal of Neuroscience.

[7]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[8]  Hang Joon Jo,et al.  Mapping sources of correlation in resting state FMRI, with artifact detection and removal , 2010, NeuroImage.

[9]  Walter Schneider,et al.  Identifying the brain's most globally connected regions , 2010, NeuroImage.

[10]  Noah A. Shamosh,et al.  Intellect as distinct from Openness: differences revealed by fMRI of working memory. , 2009, Journal of personality and social psychology.

[11]  Keith A. Johnson,et al.  Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease , 2009, The Journal of Neuroscience.

[12]  T. Braver,et al.  Anxiety and cognitive efficiency: Differential modulation of transient and sustained neural activity during a working memory task , 2008, Cognitive, affective & behavioral neuroscience.

[13]  Abraham Z. Snyder,et al.  A method for using blocked and event-related fMRI data to study “resting state” functional connectivity , 2007, NeuroImage.

[14]  Karl J. Friston,et al.  The prefrontal cortex shows context-specific changes in effective connectivity to motor or visual cortex during the selection of action or colour. , 2004, Cerebral cortex.

[15]  R. Guimerà,et al.  The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[16]  M. Newman A measure of betweenness centrality based on random walks , 2003, Soc. Networks.

[17]  Jeremy R. Reynolds,et al.  Neural Mechanisms of Transient and Sustained Cognitive Control during Task Switching , 2003, Neuron.

[18]  E. Miller,et al.  An integrative theory of prefrontal cortex function. , 2001, Annual review of neuroscience.

[19]  J. Raven The Raven's Progressive Matrices: Change and Stability over Culture and Time , 2000, Cognitive Psychology.

[20]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[21]  J. Talairach,et al.  Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging , 1988 .

[22]  Raymond B. Cattell,et al.  A CHECK ON THE THEORY OF FLUID AND CRYSTALLIZED INTELLIGENCE WITH DESCRIPTION OF NEW SUBTEST DESIGNS , 1978 .