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      Brain stimulation and brain lesions converge on common causal circuits in neuropsychiatric disease

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          Abstract

          Damage to specific brain circuits can cause specific neuropsychiatric symptoms. Therapeutic stimulation to these same circuits may modulate these symptoms. To determine if these circuits converge, we studied depression severity after brain lesions (n=461, five datasets), transcranial magnetic stimulation (TMS) (n=151, four datasets), and deep brain stimulation (DBS) (n=101, five datasets). Lesions and stimulation sites most associated with depression severity were connected to a similar brain circuit across all 14 datasets (p<0.001). Circuits derived from lesions, DBS, and TMS were similar (p<0.0005), as were circuits derived from patients with major depression versus other diagnoses (p<0.001). Connectivity to this circuit predicted out-of-sample antidepressant efficacy of TMS and DBS sites (p<0.0001). In an independent analysis, 29 lesions and 95 stimulation sites converged on a distinct circuit for motor symptoms of Parkinson’s disease (p<0.05). We conclude that lesions, TMS, and DBS converge on common brain circuitry that may represent improved neurostimulation targets for depression and other disorders.

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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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            Animal models of neuropsychiatric disorders.

            Modeling of human neuropsychiatric disorders in animals is extremely challenging given the subjective nature of many symptoms, the lack of biomarkers and objective diagnostic tests, and the early state of the relevant neurobiology and genetics. Nonetheless, progress in understanding pathophysiology and in treatment development would benefit greatly from improved animal models. Here we review the current state of animal models of mental illness, with a focus on schizophrenia, depression and bipolar disorder. We argue for areas of focus that might increase the likelihood of creating more useful models, at least for some disorders, and for explicit guidelines when animal models are reported.
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              Resting-state connectivity biomarkers define neurophysiological subtypes of depression

              Using functional MRI in a large multisite sample of more that 1,000 patients, four distinct neurophysiological biotypes of depression are defined. These biotypes are used to develop diagnostic classifiers that distinguish patients with depression from controls in separate multisite validation and replication cohorts, and can predict patient responsiveness to therapy.
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                Author and article information

                Journal
                101697750
                46015
                Nat Hum Behav
                Nat Hum Behav
                Nature human behaviour
                2397-3374
                17 June 2021
                08 July 2021
                December 2021
                08 January 2022
                : 5
                : 12
                : 1707-1716
                Affiliations
                [1. ]Center for Brain Circuit Therapeutics, Brigham & Women’s Hospital, Boston, MA, USA
                [2. ]Department of Psychiatry, Harvard Medical School, Boston, MA, USA
                [3. ]Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité University Medicine Berlin, Germany
                [4. ]University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
                [5. ]Melbourne Neuropsychiatry Centre, The University of Melbourne, Victoria, Australia
                [6. ]Department of Biomedical Engineering, The University of Melbourne, Victoria, Australia
                [7. ]Department of Neuroscience, Padova Neuroscience Center (PNC), Venetian Institute of Molecular Medicine (VIMM), University of Padova, Italy
                [8. ]Departments of Neurology, Radiology, Bioengineering, and Neuroscience, Washington University, St. Louis, MO, USA
                [9. ]Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
                [10. ]Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
                [11. ]Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia.
                [12. ]The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
                [13. ]Epworth Centre for Innovation in Mental Health, Epworth Healthcare and Monash University Department of Psychiatry, Camberwell, Victoria, Australia
                [14. ]Brain Stimulation Laboratory, Psychiatry Department, Medical University of South Carolina, Charleston, SC, USA
                [15. ]Ralph H. Johnson VA Medical Center, Charleston, SC, USA
                [16. ]Department of Neurology, Monash Health and Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Victoria, Australia
                [17. ]Department of Neurology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany
                [18. ]School of Medicine, Florida State University, Tallahassee, FL, USA
                [19. ]Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
                [20. ]Hinda and Arthur Marcus Institute for Aging Research and Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
                [21. ]Guttmann Brain Health Institut, Guttmann Institut, Universitat Autonoma, Barcelona, Spain
                [22. ]Department of Neurology, Harvard Medical School, Boston, MA, USA
                [23. ]Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
                [24. ]School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
                [25. ]Academic Center for Epileptology Kempenhaeghe/Maastricht University Medical Center, the Netherlands
                [26. ]Department of Psychiatry, University of Michigan School of Medicine, Ann Arbor, MI, USA
                [27. ]Shirley Ryan AbilityLab, Chicago, IL, USA
                Author notes

                Author contributions:

                Conception and design of study: SHS, AH, MDF

                Design of analytical procedures: SHS, MDF

                Neuroimaging analyses and statistical analyses: SHS

                Preprocessing and preparation of data for analysis: SHS, AH, JH, JLP, FS

                Contribution of data: AH, FS, RFHC, AB, KAJ, NE, AMN, SG, TGP, KSC, FI, AK, PBF, MSG, RPWR, SFT, AZ, JLV, MC, DDD, APL, JHG, HSM, MDF

                Writing of manuscript: SHS and MDF, with input from all authors

                Corresponding author: Shan H. Siddiqi, MD, BWH Center for Brain Circuit Therapeutics, 75 Francis St, Boston, MA 02115, Shsiddiqi@ 123456bwh.harvard.edu
                Article
                NIHMS1714592
                10.1038/s41562-021-01161-1
                8688172
                34239076
                bd7f54cf-de9f-4993-b583-9d71bf8e27a2

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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