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      Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology

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          Abstract

          Understanding central auditory processing critically depends on defining underlying auditory cortical networks and their relationship to the rest of the brain. We addressed these questions using resting state functional connectivity derived from human intracranial electroencephalography. Mapping recording sites into a low-dimensional space where proximity represents functional similarity revealed a hierarchical organization. At a fine scale, a group of auditory cortical regions excluded several higher-order auditory areas and segregated maximally from the prefrontal cortex. On mesoscale, the proximity of limbic structures to the auditory cortex suggested a limbic stream that parallels the classically described ventral and dorsal auditory processing streams. Identities of global hubs in anterior temporal and cingulate cortex depended on frequency band, consistent with diverse roles in semantic and cognitive processing. On a macroscale, observed hemispheric asymmetries were not specific for speech and language networks. This approach can be applied to multivariate brain data with respect to development, behavior, and disorders.

          Abstract

          This study describes the organization of human neocortex on multiple spatial scales, based on resting state intracranial electrophysiology. This provides evidence for hierarchical organization of auditory cortical regions and a limbic stream that parallels the classically described ventral and dorsal auditory processing streams.

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          Most cited references165

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          FSL.

          FSL (the FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural and diffusion MRI brain imaging data, written mainly by members of the Analysis Group, FMRIB, Oxford. For this NeuroImage special issue on "20 years of fMRI" we have been asked to write about the history, developments and current status of FSL. We also include some descriptions of parts of FSL that are not well covered in the existing literature. We hope that some of this content might be of interest to users of FSL, and also maybe to new research groups considering creating, releasing and supporting new software packages for brain image analysis. Copyright © 2011 Elsevier Inc. All rights reserved.
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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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              Cortical surface-based analysis. I. Segmentation and surface reconstruction.

              Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SoftwareRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: SoftwareRole: Writing – review & editing
                Role: Formal analysisRole: SoftwareRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: SoftwareRole: Writing – review & editing
                Role: Data curationRole: Investigation
                Role: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                PLOS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                31 August 2023
                August 2023
                31 August 2023
                : 21
                : 8
                : e3002239
                Affiliations
                [1 ] Department of Anesthesiology, University of Wisconsin, Madison, Wisconsin, United States of America
                [2 ] Department of Neuroscience, University of Wisconsin, Madison, Wisconsin, United States of America
                [3 ] Department of Neurology, The University of Iowa, Iowa City, Iowa, United States of America
                [4 ] Department of Neurosurgery, The University of Iowa, Iowa City, Iowa, United States of America
                [5 ] Department of Neurology, Albert Einstein College of Medicine, New York, New York, United States of America
                [6 ] Department of Neuroscience, Albert Einstein College of Medicine, New York, New York, United States of America
                [7 ] Iowa Neuroscience Institute, The University of Iowa, Iowa City, Iowa, United States of America
                Universidad de Salamanca, SPAIN
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-1936-7529
                Article
                PBIOLOGY-D-22-02638
                10.1371/journal.pbio.3002239
                10499207
                37651504
                24f417c2-fa70-4786-af70-04d3551c5beb
                © 2023 Banks et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 November 2022
                : 7 July 2023
                Page count
                Figures: 8, Tables: 0, Pages: 44
                Funding
                Funded by: National Institutes of Health
                Award ID: R01-GM109086
                Award Recipient :
                Funded by: National Institutes of Health
                Award ID: R01-DC04290
                Award Recipient :
                This work was supported by the National Institutes of Health (grant numbers R01-GM109086 to MIB and to KVN and R01-DC04290 to KVN). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                2023-09-13
                Software and data used to generate figures are freely available at https://zenodo.org/record/8235227 or DOI 10.5281/zenodo.8235227. The IRB protocol under which these patients were consented specified that participants’ data would be shared with qualified individuals working on approved scientific projects following establishment of a data use agreement. Intracranial EEG data are collected during a medical procedure (inpatient monitoring for seizure) and, as such, contain information that could be used to draw inferences about the medical conditions of an individual. The neural data from iEEG and fMRI, along with demographic data reported in the manuscript, have the potential for use beyond scientific inquiry were it shared without restrictions. A data transfer and use agreement between the Authors’ institution and scientists with legitimate interest in the dataset reduces the risk of loss of privacy of the research participants who have contributed their neural data to this work. Thus, the complete data set is available upon request and establishment of a formal data sharing agreement. Please contact The University of Iowa Division of Sponsored Projects at dsp-contracts@ 123456uiowa.edu to request data access. Further information is available from Bryan Krause ( bmkrause@ 123456wisc.edu ) or the corresponding author.

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