VOLUME 16 | NUMBER 9 | SEPTEMBER 2013 nature neurOSCIenCe a r t I C l e S Following decades of research involving hundreds of human neuro imaging studies, a consensus view has emerged suggesting that a core set of brain regions is centrally involved in implementing a wide variety of distinct task demands [1] [2] [3] . This functional system includes portions of lateral prefrontal cortex (LPFC), posterior parietal cortex (PPC), ante rior insula cortex and medial prefrontal cortex, and has been variously termed the cognitive control network or system 2 , the multipledemand system 1 and the taskpositive network 4 . We focused on a major com ponent of this system (consisting primarily of LPFC and PPC), the FPN. A fundamental mystery surrounding this system, and the FPN in particular, is how it can meaningfully contribute to such a wide variety of task demands. This computational mystery is compounded by the fact that the FPN is most active 1,5 during the implementation of novel and nonroutine tasks that, by definition, the system could not have been shaped by practice or evolution to specifically implement. We examined the hypothesis that the FPN is capable of such func tional adaptation because it is composed of flexible hubs: brain regions that flexibly and rapidly shift their brainwide functional connectivity patterns to implement cognitive control across a variety of tasks 5, 6 . We tested this hypothesis using recent methodological advances in human neuroimaging, including multitask cognitive testing 7 , task state functional connectivity 8 , graph theory 9 and machine learning 10 , that allowed us to test for flexible hub properties in the FPN. In par ticular, our central approach was to adapt functional magnetic reso nance imaging (fMRI) methods that are typically used to characterize functional connectivity during the resting state (that is, patterns of interregion temporal correlations) to determine whether such func tional connectivity patterns are reliably modulated across a large set of cognitive task states. The flexible hub account builds on the previously described guided activation framework 11 (which was derived in turn from the biased competition account 12 ). The guided activation framework describes how topdown signals originating in LPFC (representing current task goals) may implement cognitive control by biasing information flow across multiple largescale functional networks. The guided activation framework was developed primarily to explain how current cognitive goals overcome conflict from previous habits. The flexible hub theory builds on the guided activation theory by extending this mechanism to account specifically for novel task control and by broadening this mechanism to the entire FPN, rather than restricting it to the LPFC portion of the network. We distinguished the FPN from other brain networks that may also be involved in cognitive control functions. This is based on recent analyses using graph theory that suggest that at least five distinct subnetworks are associated with cognitive control 9,13 : the FPN, the cinguloopercular control network, the salience network, the ventral attention network and the dorsal attention network. We focused on the FPN for two reasons. First, the FPN includes the LPFC (the focus of the guided activation theory) as a central component. Second, the flexible hub theory predicts that most adaptive taskcontrol flexible hubs likely exist in the FPN, as evidence suggests that the FPN is espe cially active (relative to other networks) during situations requiring highly adaptive task control 5, 14 . Notably, the flexible hub theory expands on the guided activa tion framework by proposing two specific systemslevel neural mechanisms that may enable adaptive task control: global variable connectivity and compositional coding (Fig. 1) . Global variable con nectivity refers to the possibility that some brain regions flexibly shift their functional connectivity patterns with multiple brain networks across a wide variety of tasks. Compositional coding refers to the possibility of a systematic relationship between connectivity patterns and task components (for example, rules), allowing wellestablished Extensive evidence suggests that the human ability to adaptively implement a wide variety of tasks is preferentially a result of the operation of a fronto-parietal brain network (FPN). We hypothesized that this network's adaptability is made possible by flexible hubs: brain regions that rapidly update their pattern of global functional connectivity according to task demands. Using recent advances in characterizing brain network organization and dynamics, we identified mechanisms consistent with the flexible hub theory. We found that the FPN's brain-wide functional connectivity pattern shifted more than those of other networks across a variety of task states and that these connectivity patterns could be used to identify the current task. Furthermore, these patterns were consistent across practiced and novel tasks, suggesting that reuse of flexible hub connectivity patterns facilitates adaptive (novel) task performance. Together, these findings support a central role for fronto-parietal flexible hubs in cognitive control and adaptive implementation of task demands. npg
However, with the incremental discovery in adaptability, flexibility, and environmentally dependent modality of the brain REF , the concept of brain mechanisms transformed into the internal connection of the brain networks.
Multi-task connectivity reveals flexible hubs for adaptive task control
Nature Neuroscience
Nature Neuroscience
Medicine Psychology