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      Regular cannabis use alters the neural dynamics serving complex motor control

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          Abstract

          Cannabis is the most widely used recreational drug in the United States and regular use has been linked to deficits in attention and memory. However, the effects of regular use on motor control are less understood, with some studies showing deficits and others indicating normal performance. Eighteen users and 23 nonusers performed a motor sequencing task during high‐density magnetoencephalography (MEG). The MEG data was transformed into the time‐frequency domain and beta responses (16–24 Hz) during motor planning and execution phases were imaged separately using a beamformer approach. Whole‐brain maps were examined for group (cannabis user/nonuser) and time window (planning/execution) effects. As expected, there were no group differences in task performance (e.g., reaction time, accuracy, etc.). Regular cannabis users exhibited stronger beta oscillations in the contralateral primary motor cortex compared to nonusers during the execution phase of the motor sequences, but not during the motor planning phase. Similar group‐by‐time window interactions were observed in the left superior parietal, right inferior frontal cortices, right posterior insular cortex, and the bilateral motor cortex. We observed differences in the neural dynamics serving motor control in regular cannabis users compared to nonusers, suggesting regular users may employ compensatory processing in both primary motor and higher‐order motor cortices to maintain adequate task performance. Future studies will need to examine more complex motor control tasks to ascertain whether this putative compensatory activity eventually becomes exhausted and behavioral differences emerge.

          Abstract

          Recreational cannabis use is becoming increasingly more common, but the long‐term impact of regular use on the brain is poorly understood. Herein, we investigated how regular cannabis use affects the brain circuitry and dynamics serving motor control in adults. We found that regular cannabis use alters the dynamics serving motor control in primary and higher‐order motor cortices.

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          Most cited references97

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          Nonparametric statistical testing of EEG- and MEG-data.

          In this paper, we show how ElectroEncephaloGraphic (EEG) and MagnetoEncephaloGraphic (MEG) data can be analyzed statistically using nonparametric techniques. Nonparametric statistical tests offer complete freedom to the user with respect to the test statistic by means of which the experimental conditions are compared. This freedom provides a straightforward way to solve the multiple comparisons problem (MCP) and it allows to incorporate biophysically motivated constraints in the test statistic, which may drastically increase the sensitivity of the statistical test. The paper is written for two audiences: (1) empirical neuroscientists looking for the most appropriate data analysis method, and (2) methodologists interested in the theoretical concepts behind nonparametric statistical tests. For the empirical neuroscientist, a large part of the paper is written in a tutorial-like fashion, enabling neuroscientists to construct their own statistical test, maximizing the sensitivity to the expected effect. And for the methodologist, it is explained why the nonparametric test is formally correct. This means that we formulate a null hypothesis (identical probability distribution in the different experimental conditions) and show that the nonparametric test controls the false alarm rate under this null hypothesis.
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            Event-related EEG/MEG synchronization and desynchronization: basic principles.

            An internally or externally paced event results not only in the generation of an event-related potential (ERP) but also in a change in the ongoing EEG/MEG in form of an event-related desynchronization (ERD) or event-related synchronization (ERS). The ERP on the one side and the ERD/ERS on the other side are different responses of neuronal structures in the brain. While the former is phase-locked, the latter is not phase-locked to the event. The most important difference between both phenomena is that the ERD/ERS is highly frequency band-specific, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously. Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments.
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              Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements.

              Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.
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                Author and article information

                Contributors
                tony.wilson@boystown.org
                Journal
                Hum Brain Mapp
                Hum Brain Mapp
                10.1002/(ISSN)1097-0193
                HBM
                Human Brain Mapping
                John Wiley & Sons, Inc. (Hoboken, USA )
                1065-9471
                1097-0193
                13 November 2023
                15 December 2023
                : 44
                : 18 ( doiID: 10.1002/hbm.v44.18 )
                : 6511-6522
                Affiliations
                [ 1 ] Institute for Human Neuroscience Boys Town National Research Hospital Boys Town Nebraska USA
                [ 2 ] Department of Pharmacology & Neuroscience Creighton University Omaha Nebraska USA
                [ 3 ] College of Medicine University of Nebraska Medical Center Omaha Nebraska USA
                Author notes
                [*] [* ] Correspondence

                Tony W. Wilson, Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA.

                Email: tony.wilson@ 123456boystown.org

                Author information
                https://orcid.org/0000-0002-5053-8306
                Article
                HBM26527
                10.1002/hbm.26527
                10681654
                37955378
                be7aef20-68b4-4786-a685-248df2eb598e
                © 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 01 September 2023
                : 18 May 2023
                : 08 October 2023
                Page count
                Figures: 5, Tables: 1, Pages: 12, Words: 11028
                Funding
                Funded by: National Institute of General Medical Sciences , doi 10.13039/100000057;
                Funded by: National Institute of Mental Health , doi 10.13039/100000025;
                Funded by: National Institute on Aging , doi 10.13039/100000049;
                Funded by: National Institute on Drug Abuse , doi 10.13039/100000026;
                Funded by: National Institutes of Health , doi 10.13039/100000002;
                Award ID: R01‐DA047828
                Award ID: R03‐DA041917
                Award ID: R01‐DA056223
                Award ID: R01‐MH103220
                Award ID: R01‐MH116782
                Award ID: R01‐MH118013
                Award ID: P20‐GM144641
                Award ID: F31‐DA056296
                Award ID: R36‐DA059323
                Award ID: F30‐AG076259
                Award ID: F30‐MH130150
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                15 December, 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.5 mode:remove_FC converted:27.11.2023

                Neurology
                beta,gamma,marijuana,movement,motor sequencing,oscillations
                Neurology
                beta, gamma, marijuana, movement, motor sequencing, oscillations

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