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      Effect of concurrent action observation, peripheral nerve stimulation and motor imagery on dexterity in patients after stroke: a pilot study

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          Abstract

          Research to improve and expand treatment options for motor impairment after stroke remains an important issue in rehabilitation as the reduced ability to move affected limbs is still a limiting factor in the selection of training content for stroke patients. The combination of action observation and peripheral nerve stimulation is a promising method for inducing increased excitability and plasticity in the primary motor cortex of healthy subjects. In addition, as reported in the literature, the use of action observation and motor imagery in conjunction has an advantage over the use of one or the other alone in terms of the activation of motor-related brain regions. The aim of the pilot study was thus to combine these findings into a multimodal approach and to evaluate the potential impact of the concurrent application of the three methods on dexterity in stroke patients. The paradigm developed accordingly was tested with 10 subacute patients, in whom hand dexterity, thumb-index pinch force and thumb tapping speed were measured for a baseline assessment and directly before and after the single intervention. During the 10-min session, patients were instructed to watch a repetitive thumb-index finger tapping movement displayed on a monitor and to imagine the sensations that would arise from physically performing the same motion. They were also repeatedly electrically stimulated at the wrist on the motorically more affected body side and asked to place their hand behind the monitor for the duration of the session to support integration of the displayed hand into their own body schema. The data provide a first indication of a possible immediate effect of a single application of this procedure on the dexterity in patients after stroke.

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          The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment.

          To develop a 10-minute cognitive screening tool (Montreal Cognitive Assessment, MoCA) to assist first-line physicians in detection of mild cognitive impairment (MCI), a clinical state that often progresses to dementia. Validation study. A community clinic and an academic center. Ninety-four patients meeting MCI clinical criteria supported by psychometric measures, 93 patients with mild Alzheimer's disease (AD) (Mini-Mental State Examination (MMSE) score > or =17), and 90 healthy elderly controls (NC). The MoCA and MMSE were administered to all participants, and sensitivity and specificity of both measures were assessed for detection of MCI and mild AD. Using a cutoff score 26, the MMSE had a sensitivity of 18% to detect MCI, whereas the MoCA detected 90% of MCI subjects. In the mild AD group, the MMSE had a sensitivity of 78%, whereas the MoCA detected 100%. Specificity was excellent for both MMSE and MoCA (100% and 87%, respectively). MCI as an entity is evolving and somewhat controversial. The MoCA is a brief cognitive screening tool with high sensitivity and specificity for detecting MCI as currently conceptualized in patients performing in the normal range on the MMSE.
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            Global, regional, and national age–sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

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              PsychoPy2: Experiments in behavior made easy

              PsychoPy is an application for the creation of experiments in behavioral science (psychology, neuroscience, linguistics, etc.) with precise spatial control and timing of stimuli. It now provides a choice of interface; users can write scripts in Python if they choose, while those who prefer to construct experiments graphically can use the new Builder interface. Here we describe the features that have been added over the last 10 years of its development. The most notable addition has been that Builder interface, allowing users to create studies with minimal or no programming, while also allowing the insertion of Python code for maximal flexibility. We also present some of the other new features, including further stimulus options, asynchronous time-stamped hardware polling, and better support for open science and reproducibility. Tens of thousands of users now launch PsychoPy every month, and more than 90 people have contributed to the code. We discuss the current state of the project, as well as plans for the future.
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                Author and article information

                Contributors
                frank.behrendt@unibas.ch
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 June 2024
                27 June 2024
                2024
                : 14
                : 14858
                Affiliations
                [1 ]Research Department, Reha Rheinfelden, ( https://ror.org/051h7x990) Rheinfelden, Switzerland
                [2 ]Institute of Physiotherapy, Zurich University of Applied Sciences, ( https://ror.org/05pmsvm27) Winterthur, Switzerland
                [3 ]Department of Sport, Exercise and Health, University of Basel, ( https://ror.org/02s6k3f65) Basel, Switzerland
                [4 ]School of Engineering and Computer Science, Bern University of Applied Sciences, ( https://ror.org/02bnkt322) Biel, Switzerland
                [5 ]Institute for Optimization and Data Analysis, Bern University of Applied Sciences, ( https://ror.org/02bnkt322) Biel, Switzerland
                [6 ]GRID grid.410567.1, ISNI 0000 0001 1882 505X, Department of Neurology, , University Hospital Basel, ; Basel, Switzerland
                [7 ]Department of Clinical Research, University of Basel, ( https://ror.org/02s6k3f65) Basel, Switzerland
                [8 ]Department of Medicine, University Hospital Münster, ( https://ror.org/01856cw59) Münster, Germany
                Article
                65911
                10.1038/s41598-024-65911-7
                11211322
                38937566
                40a1b332-5216-4a49-99c7-a8705ad7d93d
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 February 2024
                : 25 June 2024
                Categories
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                © Springer Nature Limited 2024

                Uncategorized
                medical research,motor control
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                medical research, motor control

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