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      The inferior parietal lobule and temporoparietal junction: A network perspective

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      Neuropsychologia
      Elsevier BV

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          Evidence for a frontoparietal control system revealed by intrinsic functional connectivity.

          Two functionally distinct, and potentially competing, brain networks have been recently identified that can be broadly distinguished by their contrasting roles in attention to the external world versus internally directed mentation involving long-term memory. At the core of these two networks are the dorsal attention system and the hippocampal-cortical memory system, a component of the brain's default network. Here spontaneous blood-oxygenation-level-dependent (BOLD) signal correlations were used in three separate functional magnetic resonance imaging data sets (n = 105) to define a third system, the frontoparietal control system, which is spatially interposed between these two previously defined systems. The frontoparietal control system includes many regions identified as supporting cognitive control and decision-making processes including lateral prefrontal cortex, anterior cingulate cortex, and inferior parietal lobule. Detailed analysis of frontal and parietal cortex, including use of high-resolution data, revealed clear evidence for contiguous but distinct regions: in general, the regions associated with the frontoparietal control system are situated between components of the dorsal attention and hippocampal-cortical memory systems. The frontoparietal control system is therefore anatomically positioned to integrate information from these two opposing brain systems.
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            Multi-task connectivity reveals flexible hubs for adaptive task control

            Extensive evidence suggests the human ability to adaptively implement a wide variety of tasks is preferentially due to the operation of a fronto-parietal brain network. 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. We utilized recent advances in characterizing brain network organization and dynamics to identify mechanisms consistent with the flexible hub theory. We found that the fronto-parietal network’s brain-wide functional connectivity pattern shifted more than other networks’ across a variety of task states, and that these connectivity patterns could be used to identify the current task. Further, these patterns were consistent across practiced and novel tasks, suggesting 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 generally.
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              Individual variability in functional connectivity architecture of the human brain.

              The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here, we used repeated-measurement resting-state functional MRI to explore intersubject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Intersubject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Neuropsychologia
                Neuropsychologia
                Elsevier BV
                00283932
                October 2017
                October 2017
                : 105
                :
                : 70-83
                Article
                10.1016/j.neuropsychologia.2017.01.001
                28057458
                5374da62-2d40-48da-a2d5-29211bf61fd8
                © 2017
                History

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