Objective Cognition is achieved through communication between brain regions. Consequently, there is considerable interest in measuring effective connectivity. A promising effective connectivity metric is transcranial magnetic stimulation (TMS) evoked potentials (TEPs), an inflection in amplitude of the electroencephalogram (EEG) recorded from one brain region as a result of TMS applied to another region. However, the TEP is confounded by multiple factors and there is a need for further investigation of the TEP as a measure of effective connectivity and to compare it to existing statistical measures of effective connectivity. Approach To this end, we used a pre-existing experimental dataset to compare TEPs between a motor control task with and without visual feedback. We then used the results to compare our TEP-based measures of effective connectivity to established statistical measures of effective connectivity provided by Multivariate Auto-Regressive (MVAR) modelling. Main results Our results reveal significantly more negative TEPs when feedback is not presented from 40ms to 100\,ms post-TMS over frontal and central channels. We also see significantly more positive later TEPs from 280-400\,ms on the contra-lateral hemisphere motor and parietal channels when no feedback is presented. These results suggest differences in effective connectivity are induced by visual feedback of movement. We further find that the variation in one of these early TEPs (the N40) is reliably related to directed coherence. Significance Taken together, these results indicate components of the TEPs serve as a measure of effective connectivity. Furthermore, our results also support the idea that effective connectivity is a dynamic process and, importantly, support the further use of TEPs in delineating region-to-region maps of changes in effective connectivity as a result of motor control feedback.
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http://dx.doi.org/10.1088/1741-2552/ad9ee0 | DOI Listing |
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The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China; State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital, Beijing 100853, China. Electronic address:
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School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, PR China.
Point-of-care testing methods are essential for the large-scale diagnosis and monitoring of bacterial infections. This study introduces an integrated platform designed for the simultaneous detection of pathogenic bacteria. Users can simply inject samples into the system, which then conducts the entire procedure in a fully automated manner, eliminating the need for external power sources, all within 60 min or less.
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