Transcranial direct current stimulation (tDCS) is a promising tool to improve and speed up motor rehabilitation after stroke, but inconsistent clinical effects refrain tDCS from clinical implementation. Therefore, this study aimed to assess the need for individualized tDCS configurations in stroke, considering interindividual variability in brain anatomy and motor function representation. We simulated tDCS in individualized MRI-based finite element head models of 21 chronic stroke subjects and 10 healthy age-matched controls. An anatomy-based stimulation target, i.e. the motor hand knob, was identified with MRI, whereas a motor function-based stimulation target was identified with EEG. For each subject, we simulated conventional anodal tDCS electrode configurations and optimized electrode configurations to maximize stimulation strength within the anatomical and functional target. The normal component of the electric field was extracted and compared between subjects with stroke and healthy, age-matched controls, for both targets, during conventional and optimized tDCS. Electrical field strength was significantly lower, more variable and more frequently in opposite polarity for subjects with stroke compared to healthy age-matched subjects, both for the anatomical and functional target with conventional, i.e. non-individualized, electrode configurations. Optimized, i.e. individualized, electrode configurations increased the electrical field strength in the anatomical and functional target for subjects with stroke but did not reach the same levels as in healthy subjects. Considering individual brain structure and motor function is crucial for applying tDCS in subjects with stroke. Lack of individualized tDCS configurations in subjects with stroke results in lower electric fields in stimulation targets, which may partially explain the inconsistent clinical effects of tDCS in stroke trials.

Transcranial direct current stimulation (tDCS) over the contralateral primary motor cortex of the target muscle (conventional tDCS) has been described to enhance corticospinal excitability, as measured with transcranial magnetic stimulation. Recently, tDCS targeting the brain regions functionally connected to the contralateral primary motor cortex (motor network tDCS) was reported to enhance corticospinal excitability more than conventional tDCS. We compared the effects of motor network tDCS, 2 mA conventional tDCS, and sham tDCS on corticospinal excitability in 21 healthy participants in a randomized, single-blind within-subject study design. We applied tDCS for 12 min and measured corticospinal excitability with TMS before tDCS and at 0, 15, 30, 45, and 60 min after tDCS. Statistical analysis showed that neither motor network tDCS nor conventional tDCS significantly increased corticospinal excitability relative to sham stimulation. Furthermore, the results did not provide evidence for superiority of motor network tDCS over conventional tDCS. Motor network tDCS seems equally susceptible to the sources of intersubject and intrasubject variability previously observed in response to conventional tDCS.

Neurophysiologic correlates of motor learning that can be monitored during neurorehabilitation interventions can facilitate the development of more effective learning methods. Previous studies have focused on the role of the beta band (14–30 Hz) because of its clear response during motor activity. However, it is difficult to discriminate between beta activity related to learning a movement and performing the movement. In this study, we analysed differences in the electroencephalography (EEG) power spectra of complex and simple explicit sequential motor tasks in healthy young subjects. The complex motor task (CMT) allowed EEG measurement related to motor learning. In contrast, the simple motor task (SMT) made it possible to control for EEG activity associated with performing the movement without significant motor learning. Source reconstruction of the EEG revealed task-related activity from 5 clusters covering both primary motor cortices (M1) and 3 clusters localised to different parts of the cingulate cortex (CC). We found no association between M1 beta power and learning, but the CMT produced stronger bilateral beta suppression compared to the SMT. However, there was a positive association between contralateral M1 theta (5–8 Hz) and alpha (8–12 Hz) power and motor learning, and theta and alpha power in the posterior mid-CC and posterior CC were positively associated with greater motor learning. These findings suggest that the theta and alpha bands are more related to motor learning than the beta band, which might merely relate to the level of perceived difficulty during learning.

Vestibular signals, which encode head movement in space as well as orientation relative to gravity, contribute to the ongoing muscle activity required to stand. The strength of this vestibular contribution changes with the presence and quality of sensory cues of balance. Here we investigate whether the vestibular drive for standing balance also depends on different sensory cues of gravity by examining vestibular-evoked muscle responses when independently varying load and gravity conditions. Standing subjects were braced by a backboard structure that limited whole-body sway to the sagittal plane while load and vestibular cues of gravity were manipulated by: (a) loading the body downward at 1.5 and 2 times body weight (i.e., load cues), and/or (b) exposing subjects to brief periods (20 s) of micro- (<0.05 g) and hyper-gravity (∼1.8 g) during parabolic flights (i.e., vestibular cues). A stochastic electrical vestibular stimulus (0-25 Hz) delivered during these tasks evoked a vestibular-error signal and corrective muscles responses that were used to assess the vestibular drive to standing balance. With additional load, the magnitude of the vestibular-evoked muscle responses progressively increased, however, when these responses were normalized by the ongoing muscle activity, they decreased and plateaued at 1.5 times body weight. This demonstrates that the increased muscle activity necessary to stand with additional load is accompanied a proportionally smaller increase in vestibular input. This reduction in the relative vestibular contribution to balance was also observed when we varied the vestibular cues of gravity, but only during an absence (<0.05 g) and not an excess (∼1.8 g) of gravity when compared to conditions with normal 1 g gravity signals and equivalent load signals. Despite these changes, vestibular-evoked responses were observed in all conditions, indicating that vestibular cues of balance contribute to upright standing even in the near absence of a vestibular signal of gravity (i.e., micro-gravity). Overall, these experiments provide evidence that both load and vestibular cues of gravity influence the vestibular signal processing for the control of standing balance.