[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100353218":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":25,"centralContacts":30,"locations":36,"responsibleParty":56,"collaborators":59,"id":65,"slug":66,"hasResults":67,"nctId":68,"briefTitle":69,"officialTitle":69,"acronym":24,"eligibilityCriteria":70,"healthyVolunteers":67,"sex":71,"minAge":72,"maxAge":73,"enrollmentInfo":74,"targetDuration":24,"studyType":77,"phases":78,"briefSummary":80,"conditions":81,"keywords":83,"overallStatus":39,"whyStopped":24,"lastUpdateSubmitDate":84,"lastUpdatePostDateStruct":85,"startDateStruct":88,"completionDateStruct":90,"leadSponsor":92,"locationsCount":93},{"fullName":5,"class":6},"Hugo W. Moser Research Institute at Kennedy Krieger, Inc.","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Reinforcement Training","EXPERIMENTAL","Reach training with visual feedback. During each training session, participants will first be familiarized with the task and then will reach from a home position to 4 virtual targets that are presented in the front of the participant and within the workspace where most natural arm movements are performed. During training the participant will reach a total of 400 times. For reinforcement training, participants will not see their hand or a cursor, but instead participants will receive target-specific binary feedback after each reach (i.e. based on running average of last 10 reaches to that target). Binary feedback indicates only whether the reach was successful or unsuccessful and provides no specific information about the location of the hand.",[13],"Behavioral: Reach training with visual feedback",{"label":15,"type":10,"description":16,"interventionNames":17},"Standard Practice Training","Reach training with visual feedback. During each training session, participants will first be familiarized with the task and then will reach from a home position to 4 virtual targets that are presented in the front of the participant and within the workspace where most natural arm movements are performed. During training the participant will reach a total of 400 times. For standard practice, participants will be able to see a cursor that represents the position of the hand at all times and try to make straight reaches to the targets. This type of feedback provided specific information about the location of the hand.",[13],[19],{"type":20,"name":21,"description":22,"armGroupLabels":23,"otherNames":24},"BEHAVIORAL","Reach training with visual feedback","Reach training will be accomplished using an Oculus Rift and Touch 3D headset. Active markers will be placed on the shoulder, elbow, wrist, and finger in order to capture limb movement in real time. During each training session, participants will first be familiarized with the task and then will reach from a home position to 4 virtual targets that are presented in the front of the participant and within the workspace where most natural arm movements are performed.Targets will be presented in a pseudorandom order and participants will reach a total of 400 times",[9,15],null,[26],{"name":27,"affiliation":28,"role":29},"Amy J Bastian, PhD, PT","Kennedy Krieger Institute and Johns Hopkins School of Medicine","PRINCIPAL_INVESTIGATOR",[31],{"name":32,"role":33,"phone":34,"phoneExt":24,"email":35},"Anthony J Gonzalez, BS","CONTACT","4439232716","agonza30@jhmi.edu",[37],{"facility":38,"status":39,"city":40,"state":41,"zip":42,"country":43,"countryCode":44,"cosmosGeoPoint":45,"geoPoint":50,"contacts":51},"Motion Analysis Lab in the Kennedy Krieger Institute","RECRUITING","Baltimore","Maryland","21205","United States","US",{"type":46,"coordinates":47},"Point",[48,49],-76.61219,39.29038,{"lat":49,"lon":48},[52,55],{"name":32,"role":33,"phone":53,"phoneExt":24,"email":54},"443-923-2716","gonzalezan@kennedykrieger.org",{"name":27,"role":29,"phone":24,"phoneExt":24,"email":24},{"type":29,"investigatorFullName":57,"investigatorTitle":58,"investigatorAffiliation":5,"oldNameTitle":24,"oldOrganization":24},"Amy J. Bastian, Ph.D.","Professor of Neuroscience",[60,63],{"name":61,"class":62},"National Institutes of Health (NIH)","NIH",{"name":64,"class":62},"Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)","100353218","retraining-reaching-in-cerebellar-ataxia-100353218",false,"NCT03879018","Retraining Reaching in Cerebellar Ataxia","Inclusion Criteria:\n\n* Cerebellar damage from stroke, tumor or degeneration\n* Age 22-80\n\nExclusion Criteria:\n\n* Clinical or MRI evidence of damage to extracerebellar brain (e.g. multiple system atrophy)\n* Extrapyramidal symptoms, peripheral vestibular loss, or sensory neuropathy\n* Dementia ( Mini-Mental State exam \\> 22)\n* Pain that interferes with the tasks\n* Vision loss that interferes with the tasks","ALL","22 Years","80 Years",{"count":75,"type":76},18,"ESTIMATED","INTERVENTIONAL",[79],"NA","The purpose of this study is to test for benefits of reinforcement based training paradigm versus standard practice over weeks for improving reaching movements in people with ataxia.",[82],"Cerebellar Ataxia",[82],"2026-06-29",{"date":86,"type":87},"2026-07-01","ACTUAL",{"date":89,"type":87},"2019-08-01",{"date":91,"type":76},"2027-01-01",{"name":5,"class":6},1]