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      Situating the left-lateralized language network in the broader organization of multiple specialized large-scale distributed networks

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          Abstract

          Using procedures optimized to explore network organization within the individual, the topography of a candidate language network was characterized and situated within the broader context of adjacent networks. The candidate network was first identified using functional connectivity and replicated across individuals, acquisition tasks, and analytical methods. In addition to classical language regions near the perisylvian cortex and temporal pole, regions were also observed in dorsal posterior cingulate, midcingulate, and anterior superior frontal and inferior temporal cortex. The candidate network was selectively activated when processing meaningful (as contrasted with nonword) sentences, whereas spatially adjacent networks showed minimal or even decreased activity. Results were replicated and triplicated across two prospectively acquired cohorts. Examined in relation to adjacent networks, the topography of the language network was found to parallel the motif of other association networks, including the transmodal association networks linked to theory of mind and episodic remembering (often collectively called the default network). The several networks contained juxtaposed regions in multiple association zones. Outside of these juxtaposed higher-order networks, we further noted a distinct frontotemporal network situated between language regions and a frontal orofacial motor region and a temporal auditory region. A possibility is that these functionally related sensorimotor regions might anchor specialization of neighboring association regions that develop into a language network. What is most striking is that the canonical language network appears to be just one of multiple similarly organized, differentially specialized distributed networks that populate the evolutionarily expanded zones of human association cortex.

          NEW & NOTEWORTHY This research shows that a language network can be identified within individuals using functional connectivity. Organizational details reveal that the language network shares a common spatial motif with other association networks, including default and frontoparietal control networks. The language network is activated by language task demands, whereas closely juxtaposed networks are not, suggesting that similarly organized but differentially specialized distributed networks populate association cortex.

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          The organization of the human cerebral cortex estimated by intrinsic functional connectivity.

          Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
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            Advances in functional and structural MR image analysis and implementation as FSL.

            The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right. In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB's Software Library (FSL).
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              The brain's default network: anatomy, function, and relevance to disease.

              Thirty years of brain imaging research has converged to define the brain's default network-a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.
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                Author and article information

                Journal
                J Neurophysiol
                J Neurophysiol
                jn
                J Neurophysiol
                JN
                Journal of Neurophysiology
                American Physiological Society (Bethesda, MD )
                0022-3077
                1522-1598
                1 November 2020
                23 September 2020
                23 September 2020
                : 124
                : 5
                : 1415-1448
                Affiliations
                [1] 1Department of Psychology, Center for Brain Science, Harvard University , Cambridge, Massachusetts
                [2] 2Department of Neurology and Neurological Sciences, Stanford University , Stanford, California
                [3] 3The Computational, Cognitive, and Clinical Neuroimaging Laboratory, Hammersmith Hospital Campus, Imperial College London , London, United Kingdom
                [4] 4Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
                [5] 5Department of Radiology, Harvard Medical School , Boston, Massachusetts
                [6] 6Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts
                Author notes
                Correspondence: R. M. Braga ( rbraga@ 123456stanford.edu ).
                Author information
                https://orcid.org/0000-0001-7562-0755
                Article
                JN-00753-2019 JN-00753-2019
                10.1152/jn.00753.2019
                8356783
                32965153
                87d666da-4ac4-4b23-926c-b890970c0a3e
                Copyright © 2020 the American Physiological Society

                Licensed under Creative Commons Attribution CC-BY 4.0: © the American Physiological Society.

                History
                : 17 December 2019
                : 23 July 2020
                : 21 August 2020
                Funding
                Funded by: HHS | National Institutes of Health (NIH) 10.13039/100000002
                Award ID: P50MH106435
                Award Recipient : Randy L Buckner
                Funded by: HHS | National Institutes of Health (NIH) 10.13039/100000002
                Award ID: S10OD020039
                Award Recipient : Randy L Buckner
                Funded by: National Science Foundation (NSF) 10.13039/100000001
                Award ID: DGE-1745303
                Award Recipient : Lauren M DiNicola
                Funded by: HHS | NIH | National Institute of Mental Health (NIMH) 10.13039/100000025
                Award ID: K99MH117226
                Award Recipient : Rodrigo M Braga
                Funded by: Wellcome Trust (Wellcome) 10.13039/100004440
                Award ID: 103980/Z/14/Z
                Award Recipient : Rodrigo M Braga
                Categories
                Research Article
                Higher Neural Functions and Behavior

                Neurology
                broca’s area,distributed association networks,intrinsic functional connectivity,language,wernicke’s area

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