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Dynamic balance control is associated with the function of multiple brain networks and is impaired following Acquired Brain Injury (ABI). This study aims to characterize the functional and structural correlates of ABI-induced dynamic balance impairments and recovery following a rehabilitation treatment. Thirty-one chronic participants with ABI participated in a novel rehabilitation treatment composed of 22 sessions of a perturbation-based rehabilitation training. Dynamic balance was assessed using the Community Balance and Mobility scale (CB&M) and the 10-Meter Walking Test (10MWT). Brain function was estimated using resting-state fMRI imaging that was analysed using independent component analysis (ICA), and regions-of-interest analyses. Brain morphology was also assessed using structural MRI. ICA revealed a reduction in component-related activation within the sensorimotor and cerebellar networks post-intervention. Improvement in CB&M scale was associated with a reduction in FC within the cerebellar network and with baseline FC within the cerebellar-putamen and cerebellar-thalamic networks. Improvement in 10MWT was associated with baseline FC within the cerebellar-putamen and cerebellar-cortical networks. Brain volume analysis did not reveal structural correlates of dynamic balance, but dynamic balance was correlated with time since injury. Our results show that dynamic balance recovery is associated with FC reduction within and between the cerebellar and sensorimotor networks. The lack of global structural correlates of dynamic balance may point to the involvement of specific networks in balance control.

Motor imagery (MI) based brain computer interfaces (BCI) detect changes in brain activity associated with imaginary limb movements, and translate them into device commands. MI based BCIs require training, during which the user gradually learns how to control his or her brain activity with the help of feedback. Additionally, machine learning techniques are frequently used to boost BCI performance and to adapt the decoding algorithm to the user's brain. Thus, both the brain and the machine need to adapt in order to improve performance. To study the utility of co-adaptive training in the BCI paradigm and the time scales involved, we investigated the performance of 18 subjects in two groups, in a 4-day MI experiment using EEG recordings. One group (control, n=9 subjects) performed the BCI task using a fixed classifier based on MI data from day 1. In the second group (experimental, n=9 subjects), the classifier was regularly adapted based on brain activity patterns during the experiment days. We found that the experimental group showed a significantly larger change in performance following training compared to the control group. Specifically, although the experimental group exhibited a decrease in performance between days, it showed an increase in performance within each day, which compensated for the decrease. The control group showed decreases both within and between days. A correlation analysis in subjects who had a notable improvement in performance following training showed that performance was mainly associated with modulation of power in the $\\alpha$ frequency band. To conclude, continuous updating of the classification algorithm improves the performance of subjects in longitudinal BCI training.

In sensorimotor adaptation paradigms, participants learn to adjust their behavior in response to an external perturbation. Locomotor adaptation and reaching adaptation depend on the cerebellum and are accompanied by changes in functional connectivity in cortico-cerebellar circuits. In order to gain a better understanding of the particular cerebellar projections involved in locomotor adaptation, we assessed the contribution of specific white matter pathways to the magnitude of locomotor adaptation and to long-term motor adaptation effects (recall and relearning). Diffusion magnetic resonance imaging with deterministic tractography was used to delineate the inferior and superior cerebellar peduncles (ICP, SCP) and the corticospinal tract (CST). Correlations were calculated to assess the association between the diffusivity values along the tracts and behavioral measures of locomotor adaptation. The results point to a significant correlation between the magnitude of adaptation and diffusivity values in the left ICP. Specifically, a higher magnitude of adaptation was associated with higher mean diffusivity and with lower anisotropy values in the left ICP, but not in other pathways. Post hoc analysis revealed that the effect stems from radial, not axial, diffusivity. The magnitude of adaptation was further associated with the degree of ICP lateralization, such that greater adaptation magnitude was correlated with increased rightward asymmetry of the ICP. Our findings suggest that the magnitude of locomotor adaptation depends on afferent signals to the cerebellum, transmitted via the ICP, and point to the contribution of error detection to locomotor adaptation rate.

Shmuelof and Zohary report that actions seen from an allocentric point of view evoke more activation in the ipsilateral anterior parietal cortex than those seen from an egocentric point of view, even in the absence of active imitation, supporting the idea that there is a mirror-image representation of action in this brain region. Mimicking hand actions made by someone facing us (that is, allocentric viewpoint) is typically performed with the opposite hand. Using functional magnetic resonance imaging (fMRI), we found a similar mirror-image representation of others' actions in the human anterior parietal cortex. Viewing egocentric-based actions elicited greater fMRI activation in the contralteral hemisphere (as in, self action), whereas observation of action seen from an allocentric viewpoint generated greater activation in the ipsilateral hemisphere. This mirror-like mapping occurs without active imitation, providing further evidence for an automatic action-simulation system in the parietal cortex.

Background The lower-extremity motor coordination test (LEMOCOT) is a performance-based measure used to assess motor coordination deficits after stroke. We aimed to automatically quantify performance on the LEMOCOT and to extract additional performance parameters based on error analysis in persons with stroke (PwS) and healthy controls. We also aimed to explore whether these parameters provide additional information regarding motor control deficit that is not captured by the traditional LEMOCOT score. In addition, the associations between the LEMOCOT score, parameters of error and performance-based measures of lower-extremity impairment and gait were tested. Methods Twenty PwS (age: 62 ± 11.8 years, time after stroke onset: 84 ± 83 days; lower extremity Fugl-Meyer: 30.2 ± 3.7) and 20 healthy controls (age: 42 ± 15.8 years) participated in this cross-sectional exploratory study. Participants were instructed to move their big toe as fast and accurately as possible between targets marked on an electronic mat equipped with force sensors (Zebris FDM-T, 60 Hz). We extracted the contact surface area of each touch, from which the endpoint location, the center of pressure (COP), and the distance between them were computed. In addition, the absolute and variable error were calculated. Results PwS touched the targets with greater foot surface and demonstrated a greater distance between the endpoint location and the location of the COP. After controlling for the number of in-target touches, greater absolute and variable errors of the endpoint were observed in the paretic leg than in the non-paretic leg and the legs of controls. Also, the COP variable error differentiated between the paretic, non-paretic, and control legs and this parameter was independent of in-target counts. Negative correlations with moderate effect size were found between the Fugl Meyer assessment and the error parameters. Conclusions PwS demonstrated lower performance in all outcome measures than did controls. Several parameters of error indicated differences between legs (paretic leg, non-paretic leg and controls) and were independent of in-target touch counts, suggesting they may reflect motor deficits that are not identified by the traditional LEMOCOT score.

When subjects are intentionally preparing a curved trajectory, they are engaged in a time-consuming trajectory planning process that is separate from target selection. To investigate the construction of such a plan, we examined the effect of artificially shortening preparation time on the performance of intentionally curved trajectories using the Timed Response task that enforces initiation of movements prematurely. Fifteen subjects performed obstacle avoidance movements toward one of four targets that were presented 25 or 350 ms before the \"go\" signal, imposing short and long preparation time conditions with mean values of 170 ms and 493 ms, respectively. While trajectories with short preparation times showed target specificity at their onset, they were significantly more variable and showed larger angular deviations from the lines connecting their initial position and the target, compared to the trajectories with long preparation times. Importantly, the trajectories of the short preparation time movements still reached their end-point targets accurately, with comparable movement durations. We hypothesize that success in the short preparation time condition is a result of an online control mechanism that allows further refinement of the plan during its execution and study this control mechanism with a novel trajectory analysis approach using minimum jerk optimization and geometrical modeling approaches. Results show a later agreement of the short preparation time trajectories with the optimal minimum jerk trajectory, accompanied by a later initiation of a parabolic segment. Both observations are consistent with the existence of an online trajectory planning process.Our results suggest that when preparation time is not sufficiently long, subjects execute a more variable and less optimally prepared initial trajectory and exploit online control mechanisms to refine their actions on the fly.

Upper-extremity hemiparesis is a common and debilitating impairment after stroke, severely restricting stroke survivors' ability to participate in daily activities and function independently. Alarmingly, only a small percentage of stroke patients fully recover upper extremity function. Animal models indicate that high-dose upper extremity training during the early poststroke phase can significantly enhance motor recovery. However, translating such programs for human patients remains challenging due to resource limitations, patient compliance issues, and administrative constraints. This study aimed to assess the feasibility and potential efficacy of an intensive, video game-based upper-extremity training protocol designed to improve movement quality during inpatient stroke rehabilitation. Additionally, it evaluated the resources required for this intervention. Specifically, the protocol provides high-intensity, high-dose training to facilitate motor recovery by engaging patients in targeted interactive exercises. Twelve patients with upper-extremity hemiparesis completed a 4-week intensive training program comprising 40 sessions of 60 minutes; the training was conducted for 2 hours per day, 5 days per week. This was delivered in addition to standard care, which included 3 therapeutic sessions daily. Two video game-based platforms were used: one platform (tech 1) targeted proximal movements involving the shoulder and elbow, while the second platform (tech 2) emphasized distal movements of the wrist and fingers. Feasibility was assessed using the measure of time on task and measures of patients' motivation and engagement. Potential effectiveness was assessed using the Fugl-Meyer Assessment of the upper extremity (FMA-UE) scale, Action Research Arm Test (ARAT), and Stroke Impact Scale (SIS). Of the 12 patients, 8 completed the full protocol, 3 completed 34-38 sessions, and 1 completed 27 sessions. On average, patients actively engaged in exercises for 35 (SD 4) minutes per hour on the proximal platform (tech 1) and 37 (SD 2) minutes on the distal platform (tech 2). Patients reported high motivation and enjoyment throughout the sessions, with an Intrinsic Motivation Inventory enjoyment score of 6.49 (SD 0.66) out of 7. Pain levels were minimal, with a visual analogue scale (VAS) mean score of 2.00 (SD 2.32). Significant improvements were observed in motor function assessments: the mean improvement in FMA-UE score was 16.5 (SD 10.2) points, ARAT scores increased by 22.9 (SD 13.1) points, and the SIS Hand Function and Recovery score showed a mean delta of 1.23 (SD 0.80) points and a 23.33% (SD 21.5%) improvement, respectively. These findings demonstrate that a high-dose, high-intensity, video game-based training protocol is feasible and can be successfully integrated into subacute stroke rehabilitation. Additionally, preliminary evidence suggests that this supplementary intervention may be effective in enhancing motor recovery. This approach holds promise for future stroke rehabilitation protocols by offering an engaging, high-dose, and high-intensity program during early recovery.

Automaticity is still ill-understood, and its relation to habit formation and skill acquisition is highly debated. Recently, the principle of caching has been advanced as a potentially promising avenue for studying automaticity. It is roughly understood as a means of storing direct input-output associations in a manner that supports instant lookup. We raise various concerns that should be addressed before the theoretical progress afforded by this principle can be evaluated. Is caching merely a metaphor for computer caching or is it a computational model that can be used to derive testable predictions? How do the short-term and long-term effects of automaticity relate to the distinction between working memory and long-term memory? Does caching apply to stimulus-response associations – as already suggested by Logan’s instance theory – or to algorithms, too? How much practice is required for caching and how does caching depend on the task’s type? What is the relation between control processes and caching as these pertain to the possible suppression of automatic processes? Dealing with these questions will arguably also advance our understanding of automaticity.

The lower-extremity motor coordination test (LEMOCOT) is a performance-based measure used to assess motor coordination deficits after stroke. We aimed to automatically quantify performance on the LEMOCOT and to extract additional performance parameters based on error analysis in persons with stroke (PwS) and healthy controls. We also aimed to explore whether these parameters provide additional information regarding motor control deficit that is not captured by the traditional LEMOCOT score. In addition, the associations between the LEMOCOT score, parameters of error and performance-based measures of lower-extremity impairment and gait were tested. Twenty PwS (age: 62 [+ or -] 11.8 years, time after stroke onset: 84 [+ or -] 83 days; lower extremity Fugl-Meyer: 30.2 [+ or -] 3.7) and 20 healthy controls (age: 42 [+ or -] 15.8 years) participated in this cross-sectional exploratory study. Participants were instructed to move their big toe as fast and accurately as possible between targets marked on an electronic mat equipped with force sensors (Zebris FDM-T, 60 Hz). We extracted the contact surface area of each touch, from which the endpoint location, the center of pressure (COP), and the distance between them were computed. In addition, the absolute and variable error were calculated. PwS touched the targets with greater foot surface and demonstrated a greater distance between the endpoint location and the location of the COP. After controlling for the number of in-target touches, greater absolute and variable errors of the endpoint were observed in the paretic leg than in the non-paretic leg and the legs of controls. Also, the COP variable error differentiated between the paretic, non-paretic, and control legs and this parameter was independent of in-target counts. Negative correlations with moderate effect size were found between the Fugl Meyer assessment and the error parameters. PwS demonstrated lower performance in all outcome measures than did controls. Several parameters of error indicated differences between legs (paretic leg, non-paretic leg and controls) and were independent of in-target touch counts, suggesting they may reflect motor deficits that are not identified by the traditional LEMOCOT score.

Cerebral Palsy (CP) results from an insult to the developing brain and is associated with deficits in locomotor and manual skills and in sensorimotor adaptation. We hypothesized that the poor sensorimotor adaptation in persons with CP is related to their high execution variability and does not reflect a general impairment in adaptation learning. We studied the interaction between performance variability and adaptation deficits using a multi-session locomotor adaptation design in persons with CP. Six adolescents with diplegic CP were exposed, during a period of 15 weeks, to a repeated split-belt treadmill perturbation spread over 30 sessions and were tested again 6 months after the end of training. Compared to age-matched healthy controls, subjects with CP showed poor adaptation and high execution variability in the first exposure to the perturbation. Following training they showed marked reduction in execution variability and an increase in learning rates. The reduction in variability and the improvement in adaptation were highly correlated in the CP group and were retained 6 months after training. Interestingly, despite reducing their variability in the washout phase, subjects with CP did not improve learning rates during washout phases that were introduced only four times during the experiment. Our results suggest that locomotor adaptation in subjects with CP is related to their execution variability. Nevertheless, while variability reduction is generalized to other locomotor contexts, the development of savings requires both reduction in execution variability and multiple exposures to the perturbation.