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47 results for “motor adaptation”

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zenodo40/100

Motor adaptation distorts visual space

<p>The folder Visual Adaptation contains the data for the visual adaptation experiment</p> <p>Each file contains a matrix called &ldquo;MatriceRisultati&rdquo;. Each row of the matrix &ldquo;MatriceRisultati&rdquo; is a trial.&nbsp;</p> <p>The columns contain the following information:</p> <ul> <li>1<sup>st</sup>: Number of trial</li> <li>2<sup>nd</sup>: Test size</li> <li>3<sup>rd</sup>: Subject response on test</li> <li>4<sup>th</sup>: Condition&nbsp;</li> <li>5<sup>th</sup>: Test side</li> </ul> <p>The folder Motor Adaptation contains the data for the visual adaptation experiment</p> <p>Each file contains a matrix called &ldquo;MatriceRisultati&rdquo;. Each row of the matrix &ldquo;MatriceRisultati&rdquo; is a trial.&nbsp;</p> <p>The columns contain the following information:</p> <ul> <li>1<sup>st</sup>: Number of trial</li> <li>2<sup>nd</sup>: Test size</li> <li>3<sup>rd</sup>: Subject response on test</li> </ul> <p>The structure &ldquo;Resp&rdquo; contains one matrix for each trial with the hand coordinates for the motor adaptation</p>

opencc-by-4.0Nov 2020View details →
zenodo36/100

Supplementary Figures 1 and 2, research article "Can Moving in a Redundant Workspace Accelerate Motor Adaptation?"

<p><strong>Supplementary Figures 1 and 2. Movement endpoints during the priming phase (figure 1) and test phase (figure 2), shown separately for each target location (colors) and target shape (background shading). </strong>Each panel shows movement endpoints for a different subjects (the order of subjects is identical in figure 1 and 2). The home position is at (0,0). Movements to different target locations are indicated by different colors (purple = left target, green = center targer, red = right target). Thick outlines around movement endpoints indicate outliers excluded from all analyses.</p>

opencc-by-4.0Aug 2022View details →
dryad36/100

Separability of human motor memories during reaching adaptation with force cues

<p><span>Judging by the breadth of our motor repertoire during daily activities, it is clear that learning different tasks is a hallmark of the human motor system. However, for reaching adaptation to different force fields, the conditions under which this is possible in laboratory settings have remained a challenging question. Previous work has shown that independent movement representations or goals enabled dual adaptation. Considering the importance of force feedback during limb control, here we hypothesised that independent cues delivered by means of background loads could support simultaneous adaptation to various velocity-dependent force fields, for identical kinematic plan and movement goal. We demonstrate in a series of experiments that indeed healthy adults can adapt to opposite force fields, independently of the direction of the background force cue. However, when the cue and force field were in the same direction but differed by their magnitude, the formation of different motor representations was still observed but the associated mechanism was subject to increased interference. Finally, we highlight that this paradigm allows dissociating trial-by-trial adaptation from online feedback adaptation, as these two mechanisms are associated with different time scales that can be identified reliably and reproduced in a computational model. </span></p>

opencc-zeroOct 2022View details →
zenodo36/100

Real-Time Motor Unit Tracking from sEMG Signals with Adaptive ICA on a Parallel Ultra-Low Power Processor

<p>Dataset and code to replicate the paper:</p> <p>Orlandi et al., "Real-Time Motor Unit Tracking from sEMG Signals with Adaptive ICA on a Parallel Ultra-Low Power Processor"</p>

openapache2.0Apr 2024View details →
dryad36/100

Data for: Hierarchial motor adaptations negotiate failures during force field learning

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publicApr 2021View details →
dryad36/100

Separability of human motor memories during reaching adaptation with force cues

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publicOct 2022View details →
dryad36/100

Sensory-motor tuning allows generic features of conspecific acoustic scenes to guide rapid, adaptive, call-timing responses in Túngara frogs

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publicAug 2024View details →
dryad36/100

Miniature linear and split-belt treadmills reveal mechanisms of adaptive motor control in walking Drosophila

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publicAug 2024View details →
dryad32/100

Data from: Control of adaptive action selection by secondary motor cortex during flexible visual categorization

<p>Adaptive action selection during stimulus categorization is an important feature of flexible behavior. To examine neural mechanism underlying this process, we trained mice to categorize the spatial frequencies of visual stimuli according to a boundary that changed between blocks of trials in a session. Using a model with a dynamic decision criterion, we found that sensory history was important for adaptive action selection after the switch of boundary. Bilateral inactivation of the secondary motor cortex (M2) impaired adaptive action selection by reducing the behavioral influence of sensory history. Electrophysiological recordings showed that M2 neurons carried more information about upcoming choice and previous sensory stimuli when sensorimotor association was being remapped than when it was stable. Thus, M2 causally contributes to flexible action selection during stimulus categorization, with the representations of upcoming choice and sensory history regulated by the demand to remap stimulus-action association.</p>

opencc-zeroJul 2020View details →
zenodo32/100

Distortions of Visual Time Induced by Motor Adaptation

<p>For details please read the file readme.txt.</p> <p>For more details contact the authors.</p>

opencc-by-4.0Jan 2021View details →
zenodo32/100

The P3 event-related potential increases when humans learn a strategy for motor adaptation

<p>This publication contains the raw EEG and kinematics datasets along with the PCA solutions for experiments 1 and 2 presented in the manuscript entitled The <em>P3 event-related potential increases when humans learn a strategy for motor adaptation</em> by Betina Korka and Max-Philipp Stenner.</p>

opencc-by-4.0Jun 2024View details →
zenodo32/100

Plantar Somatosensory Restoration Enhances Gait, Speed Perception, and Motor Adaptation

<p>These are the data/code needed to reproduce our results.</p> <p>Below is a description of the data stored inside &#39;DATA.mat&#39;.</p> <p>- Baseline: Walking at 0.5 m/s (tied-belt)</p> <ul> <li>Controls: 6 able-bodied participants</li> <li>LLA01, LLA02, &amp; LLA03: 3 participants used sensory neuroprosthesis</li> <li>SL_DominantLimb: Dominant leg&#39;s step length (SL)</li> <li>SL_NonDominantLimb: Non-dominant leg&#39;s step length</li> <li>SL_Symmetry: Step length symmetry between dominant and non-dominant legs</li> <li>ST_DominantLimb: Dominant leg&#39;s stance time (ST)</li> <li>ST_NonDominantLimb: Non-dominant leg&#39;s stance time</li> <li>ST_Symmetry: Stance time symmetry between dominant and non-dominant legs</li> <li>GRFx_DominantLimb: Mediolateral ground reaction force (GRF) generated from dominant leg</li> <li>GRFy_DominantLimb: Anteroposterior GRF generated from dominant leg</li> <li>GRFz_DominantLimb: Vertical GRF generated from dominant leg</li> <li>GRFx_NonDominantLimb: Mediolateral GRF generated from non-dominant leg</li> <li>GRFy_NonDominantLimb: Anteroposterior GRF generated from non-dominant leg</li> <li>GRFz_NonDominantLimb: Vertical GRF generated from non-dominant leg</li> <li>COP_COM_x: Mediolateral distance between center of pressure (COP) and center of mass (COM) trajectories</li> <li>COP_COM_y: Anteroposterior distance between center of pressure and center of mass trajectories</li> <li>AMx: Whole-body angular momentum (AM) in the sagittal plane</li> <li>AMy: Whole-body AM in the frontal plane</li> </ul> <p>- StimOff/On: Condition under which sensory neuroprosthesis turned off/on</p> <ul> <li>SL_ProstheticLimb: Prosthetic leg&#39;s step length</li> <li>SL_IntactLimb: Intact leg&#39;s step length</li> <li>SL_Symmetry: Step length symmetry between Prosthetic and Intact legs</li> <li>ST_ProstheticLimb: Prosthetic leg&#39;s stance time</li> <li>ST_IntactLimb: Intact leg&#39;s stance time</li> <li>ST_Symmetry: Stance time symmetry between Prosthetic and Intact legs</li> <li>GRFx_ProstheticLimb: Mediolateral GRF generated from Prosthetic leg</li> <li>GRFy_ProstheticLimb: Anteroposterior GRF generated from Prosthetic leg</li> <li>GRFz_ProstheticLimb: Vertical GRF generated from Prosthetic leg</li> <li>GRFx_IntactLimb: Mediolateral GRF generated from Intact leg</li> <li>GRFy_IntactLimb: Anteroposterior GRF generated from Intact leg</li> <li>GRFz_IntactLimb: Vertical GRF generated from Intact leg</li> <li>COP_COM_x: Mediolateral distance between center of pressure and center of mass trajectories</li> <li>COP_COM_y: Anteroposterior distance between center of pressure and center of mass trajectories</li> <li>AMx: Whole-body angular momentum in the sagittal plane</li> <li>Amy: Whole-body angular momentum in the frontal plane</li> </ul> <p>- MAT: Motor adaptation task (a 2:1, 1.0 m/s:0.5 m/s,&nbsp;belt speed perturbation for 10 minutes)</p> <ul> <li>COMVy: Forward velocity of the body&#39;s center of mass&nbsp;</li> </ul> <p>- SJTpre/post: Symmetry judgment task (verbally announcing whether they perceived both limbs at the same speed) before/after performing the MAT</p> <ul> <li>SymmetryResponse_Early/Late: Verbal response from the participant on whether the treadmill belts were at the same speed (at early/late SJT)</li> <li>ResponseDealy_Early/Late: Time delay to the verbal response (at early/late SJT)</li> </ul>

opencc-by-4.0Sep 2023View details →
ClinicalTrials.gov32/100

Motor Adaptation to Split-Belt Treadmill in Parkinson's Disease

ClinicalTrials.gov study NCT03725215. IPD Sharing: NO. Countries: 2. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Adaptive Deep Brain Stimulation to Improve Motor and Gait Functions in Parkinson's Disease

ClinicalTrials.gov study NCT04675398. IPD Sharing: NO. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Self-Adaptive Immersive Virtual Reality Serious Game to Enhance Motor Skill Learning and Attention in Older Adults

ClinicalTrials.gov study NCT06141642. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Motor Neurone Disease - Systematic Multi-Arm Adaptive Randomised Trial

ClinicalTrials.gov study NCT04302870. IPD Sharing: YES. Countries: 1. Publications: 4.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov32/100

Effects of Protective Step Training on Proactive and Reactive Motor Adaptations in Parkinson's Disease Patients

ClinicalTrials.gov study NCT07399613. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Adaptation of the Motor System to Experimental Pain

ClinicalTrials.gov study NCT05396820. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Effects of Adapted Physical Activities on Visual Motor Integration in Children With Developmental Delay

ClinicalTrials.gov study NCT05969808. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Assessment of Motor Adaptation in Precision Grip Performance of Children

ClinicalTrials.gov study NCT05574075. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →

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International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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OpenNeuro

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