2013/08/07 春野

Multi-task connectivity reveals flexible hubs for adaptive task control.
Cole MW, Reynolds JR, Power JD, Repovs G, Anticevic A, Braver TS.
Nat Neurosci. 2013 Sep;16(9):1348-55.

Introduction

• Decades of neuroimaging studies suggested that a core set of brain regions is centrally involved in implementing a wide variety of distinct task demands, including lateral prefrontal cortex (LPFC), posterior parietal cortex (PPC), anterior insula and medial prefrontal cortex.
• Here, authors focus on the fronto-parietal network (FPN). A fundamental mystery is that the FPN is most active during novel and non-routine tasks that the system could not have been shaped by practice.
• They examined the hypothesis that FPN is composed of “flexible hubs”: brain regions that flexibly and rapidly shift their brain-wide functional connectivity by combining functional connectivity, graph theory and machine learning.

What will be done in this paper?

• They show FPN involves greater variable connectivity across networks and across tasks than other networks.
• These connectivity changes maps systematically to the currently implemented task components.
• They examined compositional coding by first testing whether connectivity patterns encoded the similarity relationships between tasks, and then testing whether these distributed connectivity patterns can be used to reliably decode which task was being performed.

Discussion

• The FPN had the highest GVC, an index of global variable connectivity, of all the major brain networks. This pattern was robust (i.e., individual FPN region, connectivity measures and the participation coefficient).
• Brain-wide FPN functional connectivity patterns across 64 task states encoded the similarity relationships between tasks.
• A limitation is the inclusion of only the major brain networks, and subcortical networks were not included.

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