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      The brain’s default network: updated anatomy, physiology and evolving insights

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      Nature Reviews Neuroscience
      Springer Science and Business Media LLC

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          Abstract

          Discoveries over the past two decades demonstrate that regions distributed throughout the association cortex, often called the default network, are suppressed during tasks that demand external attention and are active during remembering, envisioning the future and making social inferences. This Review describes progress in understanding the organization and function of networks embedded within these association regions. Detailed high-resolution analyses of single individuals suggest that the default network is not a single network, as historically described, but instead comprises multiple interwoven networks. The multiple networks share a common organizational motif (also evident in marmoset and macaque anatomical circuits) that might support a general class of processing function dependent on internally constructed rather than externally constrained representations, with each separate interwoven network specialized for a distinct processing domain. Direct neuronal recordings in humans and monkeys reveal evidence for competitive relationships between the internally and externally oriented networks. Findings from rodent studies suggest that the thalamus might be essential to controlling which networks are engaged through specialized thalamic reticular neurons, including antagonistic subpopulations. These association networks (and presumably thalamocortical circuits) are expanded in humans and might be particularly vulnerable to dysregulation implicated in mental illness.

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          Searching for a baseline: functional imaging and the resting human brain.

          Functional brain imaging in humans has revealed task-specific increases in brain activity that are associated with various mental activities. In the same studies, mysterious, task-independent decreases have also frequently been encountered, especially when the tasks of interest have been compared with a passive state, such as simple fixation or eyes closed. These decreases have raised the possibility that there might be a baseline or resting state of brain function involving a specific set of mental operations. We explore this possibility, including the manner in which we might define a baseline and the implications of such a baseline for our understanding of brain function.
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            Situating the default-mode network along a principal gradient of macroscale cortical organization.

            Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface-and are precisely equidistant-from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.
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              Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization.

              Resting state functional connectivity MRI (fcMRI) is widely used to investigate brain networks that exhibit correlated fluctuations. While fcMRI does not provide direct measurement of anatomic connectivity, accumulating evidence suggests it is sufficiently constrained by anatomy to allow the architecture of distinct brain systems to be characterized. fcMRI is particularly useful for characterizing large-scale systems that span distributed areas (e.g., polysynaptic cortical pathways, cerebro-cerebellar circuits, cortical-thalamic circuits) and has complementary strengths when contrasted with the other major tool available for human connectomics-high angular resolution diffusion imaging (HARDI). We review what is known about fcMRI and then explore fcMRI data reliability, effects of preprocessing, analysis procedures, and effects of different acquisition parameters across six studies (n = 98) to provide recommendations for optimization. Run length (2-12 min), run structure (1 12-min run or 2 6-min runs), temporal resolution (2.5 or 5.0 s), spatial resolution (2 or 3 mm), and the task (fixation, eyes closed rest, eyes open rest, continuous word-classification) were varied. Results revealed moderate to high test-retest reliability. Run structure, temporal resolution, and spatial resolution minimally influenced fcMRI results while fixation and eyes open rest yielded stronger correlations as contrasted to other task conditions. Commonly used preprocessing steps involving regression of nuisance signals minimized nonspecific (noise) correlations including those associated with respiration. The most surprising finding was that estimates of correlation strengths stabilized with acquisition times as brief as 5 min. The brevity and robustness of fcMRI positions it as a powerful tool for large-scale explorations of genetic influences on brain architecture. We conclude by discussing the strengths and limitations of fcMRI and how it can be combined with HARDI techniques to support the emerging field of human connectomics.
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                Author and article information

                Journal
                Nature Reviews Neuroscience
                Nat Rev Neurosci
                Springer Science and Business Media LLC
                1471-003X
                1471-0048
                September 6 2019
                Article
                10.1038/s41583-019-0212-7
                31492945
                954374d9-6681-4824-ab7a-53c7f30a6454
                © 2019

                http://www.springer.com/tdm

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