. Motor learning and memory consolidation require the contribution of different cortices. For motor sequence learning, the primary motor cortex is involved primarily in its acquisition. Premotor areas might be important for consolidation. In accordance, modulation of cortical excitability via transcranial DC stimulation (tDCS) during learning affects performance when applied to the primary motor cortex, but not premotor cortex. We aimed to explore whether premotor tDCS influences task performance during motor memory consolidation. The impact of excitability-enhancing, -diminishing, or placebo premotor tDCS during rapid eye movement (REM) sleep on recall in the serial reaction time task (SRTT) was explored in healthy humans. The motor task was learned in the evening. Recall was performed immediately after tDCS or the following morning. In two separate control experiments, excitability-enhancing premotor tDCS was performed 4 h after task learning during daytime or immediately before conduction of a simple reaction time task. Excitability-enhancing tDCS performed during REM sleep increased recall of the learned movement sequences, when tested immediately after stimulation. REM density was enhanced by excitability-increasing tDCS and reduced by inhibitory tDCS, but did not correlate with task performance. In the control experiments, tDCS did not improve performance. We conclude that the premotor cortex is involved in motor memory consolidation during REM sleep.
With the ACS we can exploit the untapped potential of the PAMs by assigning them a new, complex function. The inherent advantages of the ACS, such as not interfering with oral communication, robustness, stability over time and proportional and continuous signal generation, meet the specific needs of wheelchair users and render it a realistic alternative to currently available assistive technologies.
The hACS therefore offers an alternative solution for simultaneous and proportional myoelectric control of two degrees of freedom that avoids several robustness issues related to machine learning based approaches.
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