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1. Facilitation of motor adaptation using multiple gait rehabilitation interventions

   https://doi.org/10.3389/fresc.2024.1238139  

   Hoque, Adila; Kim, Seok Hun; Reed, Kyle B (October 2024, Frontiers in Rehabilitation Sciences)

   Escorpizo, Reuben (Ed.)

   The rate of adjustment in a movement, driven by feedback error, is referred to as the adaptation rate, and the rate of recovery of a newly adapted movement to its unperturbed condition is called the de-adaptation rate. The rates of adaptation and de-adaptation are dependent on the training mechanism and intrinsic factors such as the participant's sensorimotor abilities. This study investigated the facilitation of the motor adaptation and de-adaptation processes for spatiotemporal features of an asymmetric gait pattern by sequentially applying split-belt treadmill (SBT) and asymmetric rhythmic auditory cueing (ARAC). Methods: Two sessions tested the individual gait characteristics of SBT and ARAC, and the remaining four sessions consisted of applying the two interventions sequentially during training. The adjustment process to the second intervention is referred to as “re-adaptation” and is driven by feedback error associated with the second intervention. Results: Ten healthy individuals participated in the randomized six-session trial. Spatiotemporal asymmetries during the adaptation and post-adaptation (when intervention is removed) stages were fitted into a two-component exponential model that reflects the explicit and implicit adaptation processes. A double component was shown to fit better than a single-component model. The decay constants of the model were indicative of the corresponding timescales and compared between trials. Results revealed that the explicit (fast) component of adaptation to ARAC was reduced for step length and step time when applied after SBT. Contrarily, the explicit component of adaptation to SBT was increased when it was applied after ARAC for step length. Additionally, the implicit (slow) component of adaptation to SBT was inhibited when applied incongruently after ARAC for step time. These outcomes show that the role of working motor memory as a translational tool between different gait interventions is dependent on (i) the adaptation mechanisms associated with the interventions, (ii) the targeted motor outcome of the interventions; the effects of factors (i) and (ii) are specific to the explicit and implicit components of the adaptation processes; these effects are unique to spatial and temporal gait characteristics. 

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2. Two ways to learn in visuomotor adaptation

   https://doi.org/10.1101/2024.11.02.621678  

   Zhang, Yifan; Jayaswal, Sana; Schweighofer, Nicolas (November 2024, bioRxiv)

   Abstract Previous research has demonstrated significant inter-individual variability in the recruitment of the fast-explicit and slow-implicit processes during motor adaptation. In addition, we previously identified qualitative individual differences in adaptation linked to the formation and updating of new memory processes. Here, we investigated quantitative and qualitative differences in visuomotor adaptation with a design incorporating repeated learning and forgetting blocks, allowing for precise estimation of individual learning and forgetting rates in fast-slow adaptation models. Participants engaged in a two-day online visuomotor adaptation task. They first adapted to a 30-degree perturbation to eight targets in three blocks separated by short blocks of no feedback trials. Approximately 24 hours later, they performed a no-feedback retention block and a relearning block. We clustered the participants into strong and weak learners based on adaptation levels at the end of day one and fitted a fast-slow system to the adaptation data. Strong learners exhibited a strong negative correlation between the estimated slow and fast processes, which predicted 24-hour retention and savings, respectively, supporting the engagement of a fast-slow system. The pronounced individual differences in the recruitment of the two processes were attributed to wide ranges of estimated learning rates. Conversely, weak learners exhibited a positive correlation between the two estimated processes, as well as retention but no savings, supporting the engagement of a single slow system. Finally, both during baseline and adaptation, reaction times were shorter for weak learners. Our findings thus revealed two distinct ways to learn in visuomotor adaptation and highlight the necessity of considering both quantitative and qualitative individual differences in studies of motor learning. 

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3. A deep explainable artificial intelligent framework for neurological disorders discrimination

   https://doi.org/10.1038/s41598-021-88919-9  

   Shahtalebi, Soroosh; Atashzar, S. Farokh; Patel, Rajni V.; Jog, Mandar S.; Mohammadi, Arash (December 2021, Scientific Reports)

   null (Ed.)

   Abstract Pathological hand tremor (PHT) is a common symptom of Parkinson’s disease (PD) and essential tremor (ET), which affects manual targeting, motor coordination, and movement kinetics. Effective treatment and management of the symptoms relies on the correct and in-time diagnosis of the affected individuals, where the characteristics of PHT serve as an imperative metric for this purpose. Due to the overlapping features of the corresponding symptoms, however, a high level of expertise and specialized diagnostic methodologies are required to correctly distinguish PD from ET. In this work, we propose the data-driven $$\text {NeurDNet}$$ NeurDNet model, which processes the kinematics of the hand in the affected individuals and classifies the patients into PD or ET. $$\text {NeurDNet}$$ NeurDNet is trained over 90 hours of hand motion signals consisting of 250 tremor assessments from 81 patients, recorded at the London Movement Disorders Centre, ON, Canada. The $$\text {NeurDNet}$$ NeurDNet outperforms its state-of-the-art counterparts achieving exceptional differential diagnosis accuracy of $$95.55\%$$ 95.55 % . In addition, using the explainability and interpretability measures for machine learning models, clinically viable and statistically significant insights on how the data-driven model discriminates between the two groups of patients are achieved. 

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4. Somatosensory changes associated with motor skill learning

   https://doi.org/10.1152/jn.00497.2019  

   Mirdamadi, Jasmine Lauren; Block, Hannah J (January 2020, Journal of Neurophysiology)

   Trial-and-error motor adaptation has been linked to somatosensory plasticity and shifts in proprioception (limb position sense). The role of sensory processing in motor skill learning is less understood. Unlike adaptation, skill learning involves the acquisition of new movement patterns in the absence of perturbation, with performance limited by the speed-accuracy tradeoff. We investigated somatosensory changes during motor skill learning at the behavioral and neurophysiological level. Twenty-eight healthy young adults practiced a maze-tracing task, guiding a robotic manipulandum through an irregular 2D track featuring several abrupt turns. Practice occurred on days 1 and 2. Skill was assessed before practice on day 1 and again on day 3, with learning indicated by a shift in the speed-accuracy function between these assessments. Proprioceptive function was quantified with a passive two-alternative forced choice task. In a subset of 15 participants, we measured short latency afferent inhibition (SAI) to index somatosensory projections to motor cortex. We found that motor practice enhanced the speed-accuracy skill function (F 4,108 = 32.15, p < 0.001) and was associated with improved proprioceptive sensitivity at retention (t 22 = 24.75, p = 0.0031). Further, SAI increased after training (F 1,14 = 5.41, p = 0.036). Interestingly, individuals with larger increases in SAI, reflecting enhanced somatosensory afference to motor cortex, demonstrated larger improvements in motor skill learning. These findings suggest that SAI may be an important functional mechanism for some aspect of motor skill learning. Further research is needed to test what parameters (task complexity, practice time, etc) are specifically linked to somatosensory function. 

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5. Changes in Resting State Functional Connectivity Associated with Dynamic Adaptation of Wrist Movements

   https://doi.org/10.1523/JNEUROSCI.1916-22.2023  

   Farrens, Andria J.; Vahdat, Shahabeddin; Sergi, Fabrizio (March 2023, The Journal of Neuroscience)

   Dynamic adaptation is an error-driven process of adjusting planned motor actions to changes in task dynamics (Shadmehr, 2017). Adapted motor plans are consolidated into memories that contribute to better performance on re-exposure. Consolidation begins within 15 min following training (Criscimagna-Hemminger and Shadmehr, 2008), and can be measured via changes in resting state functional connectivity (rsFC). For dynamic adaptation, rsFC has not been quantified on this timescale, nor has its relationship to adaptative behavior been established. We used a functional magnetic resonance imaging (fMRI)-compatible robot, the MR-SoftWrist (Erwin et al., 2017), to quantify rsFC specific to dynamic adaptation of wrist movements and subsequent memory formation in a mixed-sex cohort of human participants. We acquired fMRI during a motor execution and a dynamic adaptation task to localize brain networks of interest, and quantified rsFC within these networks in three 10-min windows occurring immediately before and after each task. The next day, we assessed behavioral retention. We used a mixed model of rsFC measured in each time window to identify changes in rsFC with task performance, and linear regression to identify the relationship between rsFC and behavior. Following the dynamic adaptation task, rsFC increased within the cortico-cerebellar network and decreased interhemispherically within the cortical sensorimotor network. Increases within the cortico-cerebellar network were specific to dynamic adaptation, as they were associated with behavioral measures of adaptation and retention, indicating that this network has a functional role in consolidation. Instead, decreases in rsFC within the cortical sensorimotor network were associated with motor control processes independent from adaptation and retention. SIGNIFICANCE STATEMENTMotor memory consolidation processes have been studied via functional magnetic resonance imaging (fMRI) by analyzing changes in resting state functional connectivity (rsFC) occurring more than 30 min after adaptation. However, it is unknown whether consolidation processes are detectable immediately (<15 min) following dynamic adaptation. We used an fMRI-compatible wrist robot to localize brain regions involved in dynamic adaptation in the cortico-thalamic-cerebellar (CTC) and cortical sensorimotor networks and quantified changes in rsFC within each network immediately after adaptation. Different patterns of change in rsFC were observed compared with studies conducted at longer latencies. Increases in rsFC in the cortico-cerebellar network were specific to adaptation and retention, while interhemispheric decreases in the cortical sensorimotor network were associated with alternate motor control processes but not with memory formation. 

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