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      Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity

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          Abstract

          Background:

          Classic psychedelics, such as psilocybin and LSD, and other serotonin 2A receptor (5-HT 2AR) agonists evoke acute alterations in perception and cognition. Altered thalamocortical connectivity has been hypothesized to underlie these effects, which is supported by some functional MRI (fMRI) studies. These studies have treated the thalamus as a unitary structure, despite known differential 5-HT 2AR expression and functional specificity of different intrathalamic nuclei. Independent Component Analysis (ICA) has been previously used to identify reliable group-level functional subdivisions of the thalamus from resting-state fMRI (rsfMRI) data. We build on these efforts with a novel data-maximizing ICA-based approach to examine psilocybin-induced changes in intrathalamic functional organization and thalamocortical connectivity in individual participants.

          Methods:

          Baseline rsfMRI data (n=38) from healthy individuals with a long-term meditation practice was utilized to generate a statistical template of thalamic functional subdivisions. This template was then applied in a novel ICA-based analysis of the acute effects of psilocybin on intra- and extra-thalamic functional organization and connectivity in follow-up scans from a subset of the same individuals (n=18). We examined correlations with subjective reports of drug effect and compared with a previously reported analytic approach (treating the thalamus as a single functional unit).

          Results:

          Several intrathalamic components showed significant psilocybin-induced alterations in spatial organization, with effects of psilocybin largely localized to the mediodorsal and pulvinar nuclei. The magnitude of changes in individual participants correlated with reported subjective effects. These components demonstrated predominant decreases in thalamocortical connectivity, largely with visual and default mode networks. Analysis in which the thalamus is treated as a singular unitary structure showed an overall numerical increase in thalamocortical connectivity, consistent with previous literature using this approach, but this increase did not reach statistical significance.

          Conclusions:

          We utilized a novel analytic approach to discover psilocybin-induced changes in intra- and extra-thalamic functional organization and connectivity of intrathalamic nuclei and cortical networks known to express the 5-HT 2AR. These changes were not observed using whole-thalamus analyses, suggesting that psilocybin may cause widespread but modest increases in thalamocortical connectivity that are offset by strong focal decreases in functionally relevant intrathalamic nuclei.

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          Most cited references70

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

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            An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

            In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.
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              Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.

              Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                9215515
                20498
                Neuroimage
                Neuroimage
                NeuroImage
                1053-8119
                1095-9572
                23 October 2023
                15 October 2022
                02 July 2022
                25 December 2023
                : 260
                : 119434
                Affiliations
                [a ]Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
                [b ]Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD 21205, USA
                [c ]Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
                [d ]Center for Psychedelic and Consciousness Research, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA
                [e ]Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
                [f ]Department of Statistics, Indiana University Bloomington, Bloomington, IN 47408, USA
                [g ]Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA
                Author notes
                [1]

                These authors contributed equally to this manuscript.

                [* ]Corresponding authors. gaddis@ 123456jhmi.edu (A. Gaddis), fbarrett@ 123456jhmi.edu (F.S. Barrett).
                Article
                NIHMS1833498
                10.1016/j.neuroimage.2022.119434
                10749714
                35792293
                ba4c3ef9-c782-40f5-9632-86f267ce7672

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/)

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                Categories
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                Neurosciences
                functional mri,functional connectivity,independent component analysis,resting state,psilocybin,psychedelics,thalamus,thalamocortical connectivity

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