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• We used simultaneous EEG and fNIRS to examine task-specific changes during finger-tapping and handwriting tasks in dystonia. • Patients with dystonia show altered connectivity between the supplementary motor area and left sensorimotor cortex during writing. • Differences in cortical blood flow and EEG spectral power between controls and patients with dystonia are task dependent. The aim of this study was to explore differences in brain activity and connectivity using simultaneous electroencephalography and near-infrared spectroscopy in patients with focal dystonia during handwriting and finger-tapping tasks. Patients with idiopathic right upper limb focal dystonia and controls were assessed by simultaneous near-infrared spectroscopy and electroencephalography during the writing and finger-tapping tasks in terms of the mu-alpha, mu-beta, beta and low gamma power and effective connectivity, as well as relative changes in oxyhemoglobin (oxy-Hb) and deoxyhemoglobin using a channel-wise approach with a mixed-effect model. Patients exhibited higher oxy-Hb levels in the right and left motor cortex and supplementary motor area during writing, but lower oxy-Hb levels in the left sensorimotor and bilateral somatosensory area during finger-tapping compared to controls. During writing, patients showed increased low gamma power in the bilateral sensorimotor cortex and less mu-beta and beta attenuation compared to controls. Additionally, patients had reduced connectivity between the supplementary motor area and the left sensorimotor cortex during writing. No differences were observed in terms of effective connectivity in either task. Finally, patients failed to attenuate the mu-alpha, mu-beta, and beta rhythms during the finger-tapping task. Cortical blood flow and EEG spectral power differ between controls and dystonia patients, depending on the task. Writing increased blood flow and altered connectivity in dystonia patients, and it also decreased slow-band attenuation. Finger-tapping decreased blood flow and slow-band attenuation. Simultaneous fNIRS and EEG may show relevant information regarding brain dynamics in movement disorders patients in unconstrained environments. [ABSTRACT FROM AUTHOR]

It is well-established that expertise developed through continuous and deliberate practice has the potential to delay age-related decline in fine motor skills. However, less is known about the underlying mechanisms, that is, whether expertise leads to a higher performance level changing the initial status from which age-related decline starts or if expertise-related changes result in qualitatively different motor output and neural processing providing a resource of compensation for age-related changes. Thus, as a first step, this study aims at a better understanding of expertise-related changes in fine motor control with respect to force output and respective electrophysiological correlates. Here, using a multidimensional approach, we investigated fine motor control of experts and novices in precision mechanics during the execution of a dynamic force control task. On the level of force output, we analyzed precision, variability, and complexity. We further used dynamic mode decomposition (DMD) to analyze the electrophysiological correlates of force control to deduce brain network dynamics. Experts’ force output was more precise, less variable, and more complex. Task-related DMD mean mode magnitudes within the α-band at electrodes over sensorimotor relevant areas were reduced in experts, and lower DMD mean mode magnitudes related to the force output in novices. Our results provide evidence for expertise dependent central adaptions with distinct and more complex organization and decentralization of sensorimotor subsystems. Results from our multidimensional approach can be seen as a step forward in understanding expertise-related changes and exploiting their potential as resources for healthy aging.

It is well-established that expertise developed through continuous and deliberate practice has the potential to delay age-related decline in fine motor skills. However, less is known about the underlying mechanisms, that is, whether expertise leads to a higher performance level changing the initial status from which age-related decline starts or if expertise-related changes result in qualitatively different motor output and neural processing providing a resource of compensation for age-related changes. Thus, as a first step, this study aims at a better understanding of expertise-related changes in fine motor control with respect to force output and respective electrophysiological correlates. Here, using a multidimensional approach, we investigated fine motor control of experts and novices in precision mechanics during the execution of a dynamic force control task. On the level of force output, we analyzed precision, variability, and complexity. We further used dynamic mode decomposition (DMD) to analyze the electrophysiological correlates of force control to deduce brain network dynamics. Experts' force output was more precise, less variable, and more complex. Task-related DMD mean mode magnitudes within the α-band at electrodes over sensorimotor relevant areas were reduced in experts, and lower DMD mean mode magnitudes related to the force output in novices. Our results provide evidence for expertise dependent central adaptions with distinct and more complex organization and decentralization of sensorimotor subsystems. Results from our multidimensional approach can be seen as a step forward in understanding expertise-related changes and exploiting their potential as resources for healthy aging. [ABSTRACT FROM AUTHOR]