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      Spatiotemporal integration of contextual and sensory information within the cortical hierarchy in human pain experience

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          Abstract

          Pain is not a mere reflection of noxious input. Rather, it is constructed through the dynamic integration of current predictions with incoming sensory input. However, the temporal dynamics of the behavioral and neural processes underpinning this integration remain elusive. In the current study involving 59 human participants, we identified a series of brain mediators that integrated cue-induced expectations with noxious inputs into ongoing pain predictions using a semicircular scale designed to capture rating trajectories. Temporal mediation analysis revealed that during the early-to-mid stages of integration, the frontoparietal and dorsal attention network regions, such as the lateral prefrontal, premotor, and parietal cortex, mediated the cue effects. Conversely, during the mid-to-late stages of integration, the somatomotor network regions mediated the effects of stimulus intensity, suggesting that the integration occurs along the cortical hierarchy from the association to sensorimotor brain systems. Our findings advance the understanding of how the brain integrates contextual and sensory information into pain experience over time.

          Abstract

          When we experience pain, the sensory input is modulated by contextual information. This neuroimaging study shows how expectation and sensory input are integrated in the human brain during pain perception, delineating the spatiotemporal architecture of this process in different brain regions.

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          Most cited references79

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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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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              An integrative theory of prefrontal cortex function.

              The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task. We review neurophysiological, neurobiological, neuroimaging, and computational studies that support this theory and discuss its implications as well as further issues to be addressed
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: 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
                13 November 2024
                November 2024
                13 November 2024
                : 22
                : 11
                : e3002910
                Affiliations
                [1 ] Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
                [2 ] Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
                [3 ] Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
                [4 ] Center for the Developing Brain, Child Mind Institute, New York, New York State, United States of America
                [5 ] Life-inspired Neural Network for Prediction and Optimization Research Group, Suwon, South Korea
                [6 ] Department of Psychology, University of Miami, Coral Gables, Florida, United States of America
                [7 ] Department of Biobehavioral Health, Pennsylvania State University, University Park, Pennsylvania, United States of America
                Technical University of Munich: Technische Universitat Munchen, GERMANY
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-6965-3315
                https://orcid.org/0000-0002-1847-578X
                https://orcid.org/0000-0002-6791-2130
                https://orcid.org/0000-0002-7423-5422
                Article
                PBIOLOGY-D-24-01392
                10.1371/journal.pbio.3002910
                11602096
                39536050
                089c8e5a-82af-4906-a18f-7340f2b485c7

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 9 May 2024
                : 22 October 2024
                Page count
                Figures: 6, Tables: 0, Pages: 31
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100010446, Institute for Basic Science;
                Award ID: IBS-R015-D1
                Award Recipient :
                Funded by: National Research Foundation of Korea
                Award ID: 2021M3E5D2A01022515
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003710, Korea Health Industry Development Institute;
                Award ID: HI19C1328
                Award Recipient :
                This work was supported by IBS-R015-D1 (Institute for Basic Science; https://www.ibs.re.kr/eng.do; to C.-W.W.), 2021M3E5D2A01022515 (National Research Foundation of Korea; https://www.nrf.re.kr/eng/main; to C.-W.W.), and HI19C1328 (Korea Health Technology R&D Project through the Korea Health Industry Development Institute; https://www.khidi.or.kr/eps, the Ministry of Health & Welfare, Republic of Korea; https://www.mohw.go.kr/eng/; to S.G.). The funders had no role in designing the study, collecting and analyzing the data, deciding to publish, or preparing the manuscript.
                Categories
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                2024-11-27
                All relevant data used to generate figures, as well as the scripts for analysis, are available in the Figshare repository at https://doi.org/10.6084/m9.figshare.25040951 and Supporting information ( S1 Data).

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