FIRST

Functional Imaging and Robotics for Sensorimotor Transformation

 Coordinatore EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZURICH 

 Organization address address: Raemistrasse 101
city: ZUERICH
postcode: 8092

contact info
Titolo: Prof.
Nome: Roger
Cognome: Gassert
Email: send email
Telefono: +41 44 6323266

 Nazionalità Coordinatore Switzerland [CH]
 Totale costo 277˙296 €
 EC contributo 277˙296 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2013-IIF
 Funding Scheme MC-IIF
 Anno di inizio 2014
 Periodo (anno-mese-giorno) 2014-04-03   -   2016-04-02

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZURICH

 Organization address address: Raemistrasse 101
city: ZUERICH
postcode: 8092

contact info
Titolo: Prof.
Nome: Roger
Cognome: Gassert
Email: send email
Telefono: +41 44 6323266

CH (ZUERICH) coordinator 277˙296.80

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

connectivity    motor    haptic    individuals    functional    learning    commands    brain    sensorimotor    movements    learned    dexterous    networks    stroke    transformations    normal    computational    model    differences    performance    somatosensory    neurologically   

 Obiettivo del progetto (Objective)

'This proposed research addresses the question of how the brain transforms somatosensory information from the hand into motor commands to control the hand during tasks such as object manipulation and dexterous finger movements. Understanding the sensorimotor transformations performed by the brain to control upper limb movement is fundamental for a variety of fields, including motor development, athletic and artistic performance, sensorimotor rehabilitation, assistive technology and humanoid robotics. This project will investigate and model the computational processes underlying the sensorimotor transformations taking place in the brain during dexterous movements of the hand in neurologically normal individuals and individuals with impaired hand function following a stroke. This will be achieved by creating a set of novel haptic tasks implemented on state-of-the-art high fidelity haptic devices and quantifying the changes in performance and brain activity that occur as the tasks are learned. The changes in functional connectivity within brain networks as the tasks are learned will be used to determine how sensorimotor transformations are carried out in the brain. The performance measures and the way in which haptic features such as texture, compliance and shape are related to changes in motion and force during learning of the haptic tasks will be used to develop a computational model of how somatosensory information is transformed into commands to muscles that control the hand. Differences in changes in functional connectivity in brain networks between neurologically normal individual and post-stroke subjects during learning of haptic tasks will be used to advance our understanding of changes to the sensorimotor network of the brain following stroke. The computational model will be used to investigate the mechanisms responsible for differences in performance.'

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