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Neuroscience of Motivation and Cognition in Rehabilitation

Projects

EEG and Motivation (Eemotive)

Project leader: L. Legrand

In this project we aim to elucidate the neuronal underpinnings of motivational processes. Reward is a strong motivational driver. Thus, high density EEG measurements of rewarded compared to unrewarded task performance is recorded in healthy participants. Ongoing projects are to record stroke patients with different lesion locations to elucidate the differential impact on reward processing.

Neuropsychological Minimal Dataset after Stroke (NMDS)

Project leaders: L. Legrand, S. Giovanoli

The aim is to reach a first harmonization agreement of diagnostic post-stroke cognitive assessments within the European Economic Area (EEA). An expert consortium representing 26 EEA countries determined a consensus-based, multilingual neuropsychological minimal dataset after stroke (NMDS). Current projects relate to the clinical implementation of the NMDS. We are working on an NMDS online platform rendering normed patient profiles to facilitate the neuropsychologists’ assessment procedures. 

COgnition MOtor Interaction (COMO)

Project leader: L. Legrand

We are interested in the interaction of cognitive and motor deficits in stroke patients. In this project we retrospectively analyse stroke assessments and rehabilitation data with the aim to elucidate cognitive-motor patient and rehabilitation profiles.

PERfusion augmentation through EXercise (PERFEX)

Project leader: L. legrand, Y. Rottenberger

This study aims to investigate the effect of aerobic exercise against control therapy on brain perfusion as well as motor and cognitive functioning in stroke patients with perfusion compromise due to large vessel occlusion or stenosis. Even with upgrowth of surgical or endovascular interventions, many subjects do not qualify for mechanical recanalization of the occluded vessel. Alternative treatment opportunities are limited. Aerobic exercise is a conservative approach, which has been shown to increase cerebral blood flow. However, it is remains unknown, how physiological adaptation to physical activity expresses in subjects after stroke. Over a period of three months, the study participants will perform guided aerobic exercise sessions or control intervention (stretching exercise) at a frequency of 3x per week.

We are looking for participants that match the following criteria:

  • Ischemic stroke due to large vessel occlusion or stenosis (≥ 3 months ago)
  • Able to walk with or without supervision
  • No recanalization or revascularization planned
  • No severe cardiac disease
  • No intermittent claudication at <1000m walking distance
  • No MRI contraindications such as pacemaker, deep brain stimulator or metal in the head

If you are interested in participating or would like more information about the study, please contact Yannik Rottenberger 

Cerebral hemodynamics during early verticalization after (successful) thrombectomy poststroke (CHEST)

Project leader: C. Globas, T.Pipping

This project aims to study how the blood flow in the brain responds to the uprighting of the body in stroke patients who have recently undergone thrombectomy. Although removing a blood clot can be very successful in improving the outcome after a stroke, it also carries the risk of excessive blood flow to the brain, which can lead to problems. An early verticalization of the body after such an intervention can possibly have a positive effect on the blood flow situation in the brain. We hope to use this information to develop new and/or improve existing post-stroke treatment approaches.

Enhancement of Stroke Rehabilitation with Levodopa (ESTREL)

Project leader: Y. Rottenberger

ESTREL is a placebo controlled drug study  conducted at several Swiss hospitals and rehabilitation centers, organized by Professor Stefan Engelter (Felix Platter Hospital Basel). The aim is to investigate whether the active substance levodopa improves the effect of rehabilitation in stroke patients with paresis, i.e. how effective it is and whether it is safe to use. Levodopa is approved for the treatment of Parkinson's disease. In stroke patients, there is evidence that levodopa combined with rehabilitative therapies can lead to a patient-relevant enhancement of functional recovery in acute stroke patients.

iARAT

Project leader: J. Schönhammer

The iARAT project aims to transform upper limb function assessment and rehabilitation. It introduces a sensor-driven enhancement to the Action Research Arm Test (ARAT), increasing its accuracy and clinical relevance. The core technology is a tablet application facilitating the ARAT, featuring task instructions, a digital stopwatch, and scoring, and date transfer to the clinical information system. Five movement sensors attached to the patient provide detailed kinematic data, enabling finer detection of limb function improvements. These sensors allow for precise movement analysis, aiding therapists in designing personalized rehabilitation plans. The project is expanding to other rehabilitation centers, promising broader data insights into patients’ motor recovery.

DELTA

Project leader: J. Schönhammer

The project aims to develop a low-cost, simple sensor setup for accurately measuring upper body kinematics in stroke patients, accessible for use outside a lab. It involves replicating typical neurorehabilitation clinical tests (like the drinking task and box and block) in approximately 30 stroke patients. Data on movement (using IMUs, webcams, depth cameras, and 3D optical motion capture), and clinical information are collected. The goal is to determine the minimal sensor configuration needed for precise kinematics and clinical score reproduction. The project will enhance understanding of stroke kinematics and compensatory movements.

Cognitive Load fNIRS

Project leader: J. Schönhammer

The project aims to develop biomarkers of cognitive processes using functional near-infrared spectroscopy (fNIRS), focusing on estimating mental workload, including subcategories like working memory, attentional, and perceptual load. We conduct lab experiments to identify specific biomarkers of each load type, integrating them into a mental workload classifier using machine learning. In neurorehabilitation, this classifier will adapt workload in gamified training, preventing mental overload. This approach aims to make gamified training more tailored to individual needs and to reduce the likelihood of patients abandoning training.