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107 results for “motor tasks”
A multi-modal human neuroimaging dataset for data integration: simultaneous EEG and fMRI acquisition during a motor imagery neurofeedback task: XP1
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Experimental data for the motor learning study performed: "Promoting Motor Variability During Robotic Assistance Enhances Motor Learning of Dynamic Tasks"
<p>The dataset contains the kinematic data and the questionnaire responses for a robot-assisted motor learning study performed in the Motor Learning and Neurorehabilitation Laboratory at University of Bern. The details of the study are described in [doi: 10.3389/fnins.2020.600059]. The kinematic data for each participant is stored as a data frame inside a “pickle” (serialized python object) file. The questionnaire responses are stored as a “csv” file. The variables inside the files are explained in “DataframeVariableDescription.rtf”. For questions, please contact oezhan.oezen@artorg.unibe.ch or L.MarchalCrespo@tudelft.nl.</p>
Experimental data for the motor learning study performed: "Towards functional robotic training: Motor learning of dynamic tasks is enhanced by haptic rendering but hampered by robotic assistance"
<p>The dataset contains the kinematic data and the questionnaire responses for a robot-assisted motor learning study performed in the Motor Learning and Neurorehabilitation Laboratory at the University of Bern. The details of the study are described in [doi: ]. The kinematic data for each participant is stored as a data frame inside a “pickle” (serialized python object) file. The questionnaire responses and population metrics are stored as “CSV” files. The variables inside the files are explained in “DataframeVariableDescription.rtf”. For questions, please contact oezhan.oezen@artorg.unibe.ch or L.MarchalCrespo@tudelft.nl.</p>
Dataset: Neural correlates of error prediction in a complex motor task
<p>There are two files for each subject:</p> <p>1. errorsegments_sub##.mat -> Contains EEG Segments, that were recorded while the subject executed a clear target miss (minimal distance between the center of the ball and target > 12 cm) in the task (segment and electrode information can be found below).</p> <p>2. hitsegments_sub##.mat -> Contains EEG Segments, that were recorded while the subject executed a clear target hit (minimal distance between the center of the ball and the target < 5 cm) in the task (segment and electrode information can be found below).</p> <p>The data in the *.mat-files are stored in a three dimensional matrix: 1300 datapoints x n segments x 14 electrodes</p> <p>datapoints: The first dimension contains 1300 data points for each segment which translates to 2600 ms (500 Hz sampling frequency). The time of the ball´s release set at the 301st data point in each segment.</p> <p>segments: The second dimension stands for the number of segments. Since the number of trials which satisfy the above described distance criterion for hit and error trials differ for participants size, n is variable. </p> <p>electrodes: The third dimension consists of the 14 different electrodes that were used during data recording in this exact order: [F3 Fz F4 C4 Cz C3 P3 Pz P4 VEOGu VEOGo HEOGre HEOGli FCz]</p> <p> </p> <p> </p>
Dataset of behavioral and neurophysiological data of a virtual sailing task published in: "Providing task instructions during motor training enhances performance and modulates attentional brain networks"
<p>Dataset belonging to the behavioral and neurophysiological data of the publication: "Providing task instructions during motor training enhances performance and modulates attentional brain networks". The two uploaded Zip files contain kinematic and electroencephalographic data of 36 participants for the Obstacle and HorizonTask.</p>
Functional Near-Infrared Spectroscopy Reveals Delayed Hemodynamic Changes in the Primary Motor Cortex During Fine Motor Tasks and Decreased Interhemispheric Connectivity in Parkinson's Disease Patients
<p>This dataset contains functional near-infrared spectroscopy (fNIRS) data from 20 patients with Parkinson’s disease and 20 age- and sex-matched healthy subjects without movement disorders. There are 3 folders, each corresponding to a different task: a 10-second finger-tapping task, a 2-minute walking task, and a 6-minute resting-state. When using this dataset, please cite our work:</p> <div> <div>Guevara, E., Rivas-Ruvalcaba, F. J., Kolosovas-Machuca, E. S., Ramírez-Elías, M., Zapata, R. D. de L., Ramirez-GarciaLuna, J. L., & Rodríguez-Leyva, I. (2024). Parkinson’s disease patients show delayed hemodynamic changes in primary motor cortex in fine motor tasks and decreased resting-state interhemispheric functional connectivity: A functional near-infrared spectroscopy study. <em>Neurophotonics</em>, <em>11</em>(2), 025004. <a href="https://doi.org/10.1117/1.NPh.11.2.025004">https://doi.org/10.1117/1.NPh.11.2.025004</a></div> <div> <div> <div>Guevara, E., Solana-Lavalle, G., & Rosas-Romero, R. (2024). Integrating fNIRS and machine learning: Shedding light on Parkinson’s disease detection. <em>EXCLI Journal</em>, <em>23</em>, 763–771. <a href="https://doi.org/10.17179/excli2024-7151">https://doi.org/10.17179/excli2024-7151</a></div> <div> <div> <div> <div> <div>Guevara, E., Kolosovas-Machuca, E. S., & Rodríguez-Leyva, I. (2024). Exploring motor cortex functional connectivity in Parkinson’s disease using fNIRS. <em>Brain Organoid and Systems Neuroscience Journal</em>, <em>2</em>, 23–30. <a href="https://doi.org/10.1016/j.bosn.2024.04.001">https://doi.org/10.1016/j.bosn.2024.04.001</a></div> </div> </div> </div> </div> </div> </div> </div>
fMRI study of a VR-based motor imagery and observation task, a conventional motor imagery task, and a motor execution task
<p>We used functional magnetic resonance imaging (fMRI) to map brain activation during: i) a VR-based motor imagery and observation task called NeuRow; ii) a conventional non-VR, motor imagery task based on the Graz paradigm; and iii) a motor execution task. Data were collected from two groups of healthy right-handed participants: 11 young adults (mean 58 age 27 ± 4 years) and 10 older adults (mean age 51 ± 6 years). The experimental protocol was designed in collaboration with the local healthcare system of Madeira, Portugal (SESARAM), in accordance with the 1964 Declaration of Helsinki, and approved by the scientific and ethic committees of the Central Hospital of Funchal with approval reference number: 21/2019. A written informed consent was obtained from each participant upon recruitment.</p> <p>Imaging was carried out on a 3T GE Signa HDxt MRI scanner (General Electrics Healthcare, Little Chalfont, United Kingdom) using a 12-channel head coil. fMRI data were acquired using a multi-slice 2D gradient-echo EPI sequence (TR/TE = 2500/30 ms, voxel size = 3.75x3.75x3.00 mm3, flip angle = 90, and FoV = 240x240 mm2). For co-registration purposes, whole-brain structural images were also acquired using a T1-weighted 3D Fast Spoiled Gradient-Echo (FSPGR) sequence (TR/TE = 7.8/3.0 ms, voxel size = 1.00x1.00x0.60 mm3).</p> <p>The following three tasks were performed for left and right arm movement separately, yielding a total of six fMRI runs (pseudo-randomized order): (a) NeuRow task: motor imagery and observation task through VR scenario (NeuRow); (b) Graz task: motor imagery only with abstract instructions (Graz), (c) and motor execution (ME): finger-tapping. Each fMRI run consisted of 8 trials, each with 20 s of baseline followed by 20 s of task (total run duration 5.33 min).</p>
Prescheduled Interleaving of Processing Reduces Interference in Motor-Cognitive Dual Tasks
<p>All performance-data sets are provided in three seperate .txt-files for each subject.</p> <p>Subject_##_CognitiveTask.txt consists of a chronology table of 8 columns and subject depent number of rows for the 2-back task.</p> <p>col. 1: "Stimulus number" = running number of n stimuli ("0001,0002, ..., n").<br> col. 2: "Day" = Number of the testing day, which is:<br> "1" for day 1, <br> "2" for day 2, or<br> "3" for day 3.<br> col. 3: "Walking Speed [km/h]" = Speed condition of the testing day, which is:<br> "3" for 3 km/h,<br> "4" for 4 km/h, or<br> "5" for 5 km/h.<br> col. 4: "Test block" = Each day includes seven test blocks, where:<br> "1" is the Sitting condition conducted twice, in the beginning and the end of each testing day.<br> "2" is the 0% condition,<br> "3" is the 50% condition,<br> "4" is the 75% condition,<br> "5" is the Earlier condition, and<br> "6" is the Later condition.<br> col. 5: "Trial" = "1" is the first trial,<br> "2" is the second trial, and<br> "3" is the third trial.<br> col. 6: "Reaction time [ms]" = Reaction time data in milliseconds as floating-point numbers. Missing values are substituted by a "NaN" signature.<br> col. 7: "Required decision" = This column shows, whether there was a matching ("1") or a non-matching ("0") required in the 2-back task. Missing values are substituted by a "NaN" signature.<br> col. 8: "Performed decision" = The column shows, whether the subject responded indicating a matching ("1") or a non-matching ("0") in the 2-back task. Missing values are substituted by a "NaN" signature.</p> <p><br> Subject_##_MotorTask_StrideDuration.txt consists of a chronology table of 7 columns and subject depent number of rows for walking strides under single-task and dual-task condition.</p> <p>col. 1: Stride number" = running number of n strides ("0001,0002, ..., n").<br> col. 2: "Day" = Number of the testing day, which is:<br> "1" for day 1, <br> "2" for day 2, or<br> "3" for day 3.<br> col. 3: "Walking Speed [km/h]" = Speed condition of the testing day, which is:<br> "3" for 3 km/h,<br> "4" for 4 km/h, or<br> "5" for 5 km/h.<br> col. 4: "Test block" = Each day includes seven test blocks, where:<br> "2" is the 0% condition,<br> "3" is the 50% condition,<br> "4" is the 75% condition,<br> "5" is the Earlier condition, and<br> "6" is the Later condition.<br> col. 5: "Trial" = Each block consisted of six trials ("1, 2,..., or 6").<br> col. 6: "Task condition" = shows whether the trial was instructed as a single-task ("1") or as a motor-cognitive dualtask ("2").<br> col. 7: "Stride duration [s]" = The duration of each detected stride is written in seconds. Missing values are substituted by a "NaN" signature.</p> <p><br> Subject_##_MotorTask_StrideLength.txt consists of a chronology table of 7 columns and subject depent number of rows for walking strides under single-task and dual-task condition.</p> <p>col. 1: Stride number" = running number of n strides ("0001,0002, ..., n").<br> col. 2: "Day" = Number of the testing day, which is:<br> "1" for day 1, <br> "2" for day 2, or<br> "3" for day 3.<br> col. 3: "Walking Speed [km/h]" = Speed condition of the testing day, which is:<br> "3" for 3 km/h,<br> "4" for 4 km/h, or<br> "5" for 5 km/h.<br> col. 4: "Test block" = Each day includes seven test blocks, where:<br> "2" is the 0% condition,<br> "3" is the 50% condition,<br> "4" is the 75% condition,<br> "5" is the Earlier condition, and<br> "6" is the Later condition.<br> col. 5: "Trial" = Each block consisted of six trials ("1, 2,..., or 6").<br> col. 6: "Task condition" = shows whether the trial was instructed as a single-task ("1") or as a motor-cognitive dual task ("2").<br> col. 7: "Stride duration [mm]" = The length of each detected stride is written in millimeter. Missing values are substituted by a "NaN" signature.</p>
Multiple motor tasks while walking in patients with chronic bilateral and unilateral vestibulopathy
<p><em><span>This dataset contains whole body movements (i.e. 3D trajectories) and 3D kinematics from 30 subjects (10 with bilateral vestibulopathy, 10 with unilateral vestibulopathy, and 10 healthy subjects) during multiple motor tasks while walking: change of speed, double task, gait with eyes closed, gait with head horizontal turns, gait with head vertical turn, step over an obstacle, gait and U-turn. Participants were instrumented with 35 reflective placed on the whole body according to the Convention Gait Model 1.0. </span></em><em><span>A 12-camera motion capture system (Oqus 7+, Qualisys, Göteborg, Sweden), set at a 100 Hz sampling frequency, was used to track cutaneous reflective markers. The marker trajectories were labeled using Qualisys Tracking Manager software (QTM 2019.3, Qualisys, Göteborg, Sweden) and exported in the C3D file format. Joint kinematics were calculated from the raw data of the marker trajectories and stored in C3D files.</span></em></p>
Reconfiguring motor circuits for a joint manual and BCI task
<p>SQL database containing all models and analysis results for listed publication. Results and figures from paper can be reproduced by using the code at https://github.com/benlansdell/dualbci</p>
Influence of motor and cognitive tasks on time estimation
<p>The folder<strong> "DataTapisTime" </strong>contains <strong>thirty-two .MAT files.</strong> The .mat files’ name includes the number of subject (“SXX”, from S01 to S16) and the condition (Sitting or Walking). Each matrix contains 7 columns:</p> <ul> <li><strong>Column 1:</strong> Trial number</li> <li><strong>Column 2:</strong> Cognitive task code – 1) Look; 2) Read; 3) Solve Simple; 4) Solve Hard</li> <li><strong>Column 3:</strong> Time interval code – 1) 15 sec; 2) 30 sec; 3) 60 sec; 4) 90 sec; 5) 120 sec</li> <li><strong>Column 4:</strong> Tested duration (in seconds)</li> <li><strong>Column 5:</strong> Exact duration measured online (as a control)</li> <li><strong>Column 6:</strong> If the trial was “look” or “read” task the structure is composed only by “NaN”. In the two solve tasks the structure contains information about the operations to be solved. It contains 6 columns: 1) number1; 2) number2; 3) Participant solution; 4) Reaction time; 5) Correct solution; 6) Response correction (0: Wrong; 1: correct: NaN=not given).</li> <li><strong>Column 7:</strong> Temporal estimation (in seconds)</li> </ul>
Effects of Attentional Focus on Motor Performance and Physiology in a Slow-Motion Violin Bow-Control Task: Evidence for the Constrained Action Hypothesis in Bowed String Technique
<p>The constrained action hypothesis states that focusing attention on action outcomes rather than body movement improves motor performance. Dexterity of motor control is key to successful music performance, making this a highly relevant topic to music education. We investigated effects of focus of attention (FOA) on motor skill performance and EMG muscle activity in a violin bowing task among experienced and novice upper strings players. Following a pedagogically informed exercise, participants attempted to produce single oscillations of the string at a time under three FOA: internal (on arm movement), external (on sound produced), and somatic (on string resistance). Experienced players’ number of bow slips was significantly reduced under somatic focus relative to internal, although number of successful oscillations was not affected. Triceps electromyographic activity was also significantly lower in somatic compared to internal foci for both expertise groups, consistent with physiological understandings of FOA effects. Participants’ reported thoughts during the experiment provided insight into whether aspects of constrained action may be evident in performers’ conscious thinking. These results provide novel support for the constrained action hypothesis in violin bow control, suggesting a somatic FOA as a promising performance-enhancing strategy for bowed string technique.</p>
Embodiment of virtual feet correlates with motor performance in a target-stepping task
<p>Dataset for the human factors experiment of "Embodiment of virtual feet correlates with motor performance in a target-stepping task".</p>
Embodiment of virtual feet correlates with motor performance in a target-stepping task: A pilot study
<p>Dataset for the human factors pilot experiment of "Embodiment of virtual feet correlates with motor performance in a target-stepping task: A pilot study"</p>
Motor sources of dual-task interference: Evidence for effector-based prioritization in dual-task control
<p>Data of "Motor sources of dual-task interference: Evidence for effector-based prioritization in dual-task control", Hoffmann, Pieczykolan, Koch, & Huestegge.</p> <p>Dual-task costs in error rates and reaction times in six pairwise combination groups of effector systems.</p>
Effect of Structured Progressive Task-Oriented Circuit Class Training With Motor Imagery on Gait in Stroke
ClinicalTrials.gov study NCT03436810. IPD Sharing: NO. Countries: 1. Publications: 18.
A Comparison of Cognitive-Motor Dual-Task Exercise and Exergaming on Balance, Functional Mobility, and Executive Function in Down Syndrome Children
ClinicalTrials.gov study NCT06146907. IPD Sharing: YES. Countries: 1. Publications: 1.
Individualized rTMS Synchronized Task Training for Closed-loop Neuromodulation of Post-stroke Motor Dysfunction
ClinicalTrials.gov study NCT07049211. IPD Sharing: YES. Countries: 1. Publications: 26.
Effect of Adherence to a Gluten-Free Diet on Cognitive and Motor Dual-Task Performance in Adolescents Diagnosed With Celiac Disease
ClinicalTrials.gov study NCT07382999. IPD Sharing: NO. Countries: 1. Publications: 0.
Differences in polyrhythmic movement production between artistic swimmers and water polo players during the complex motor task of eggbeater kicking
<p>TableⅠ. Eggbeater kick frequency over three trials of artistic swimmers and water polo players in task1</p> <p>TableⅡ. Eggbeater kick and circular arm movement frequency in task2: Normal-slow-fast task</p> <p>TableⅢ. Eggbeater kick and circular arm movement frequency in task2: Normal-fast-slow task</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
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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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