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Regular version of the site

Motor Control Group

Matteo Feurra

Group Leader, Leading Research Fellow

Evgeny Blagoveshchensky

Senior Research Fellow

Carlos Muriel Nieto Doval

PhD student, Research Assistant

Alexandr Viazmin

PhD student

Перевознюк Глеб Сергеевич

PhD student

Artyom Batov

Research assistant

Aleksandra Pleskovskaya

Research Assistant

Саламатин Михаил Игоревич

Research Assistant

Пономарева Дарья Сергеевна

Research assistant

Anthony Mensah

Master student

Motor Control group (MMC) uses Non Invasive Brain Stimulation (NIBS) to modulate human cortical brain processing and functions. Our group uses NIBS to increase cortical excitability which may have a huge impact in rehabilitation of patients with motor deficits. It is possible to apply transcranial electrical current (tDCS, tACS) to target specific brain regions or networks of regions in order to increase behavioural performance in healthy humans. This principle has been shown to be valid also in clinical populations of patients. Motion tracking research, NIBS, motor imagery, mirror neurons, motor plasticity, gender excitability indexes are the main topics of our group.

 

International colleagues 

 

David Bartrés-Faz, professor BBSLab, Department of Psychiatry and Clinical Psychobiology, Faculty of Medicine, University of Barcelona, Spain.
Giulia Galli, PhD Department of Psychology, Kingston University, Penrhyn Road, Kingston Upon Thames, Surrey, KT1 2EE, London, UK.
Simone Rossi, professor Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Brain Investigation and NeuromodulationLab. (Si-BIN Lab), Siena, Italy.

Current projects

Project 1: Motor Imagery: Kinesthetic vs. Visual Representations.

A project that investigates the differential impact of motor imagery types on the sensory-motor system using TMS.

Project 2: Motion Tracking and Motor Planning Investigations.

A project that uses advanced motion capture techniques to study movement execution and planning.

Project 3: Machine Learning & AI in Brain Stimulation. 
The development of predictive models for motor responses based on neurostimulation data.


 

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