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Grasp-Related Neuronal Activity in Monkey and Human and Its Applicability in BMI (Grasp Control & BMI)
Start date: Jun 1, 2012, End date: May 31, 2014 PROJECT  FINISHED 

The complexity and precision of human hand control is staggering and unravelled, yet, its neuronal control is not well understood. Loss of this ability has devastating consequences for a human’s daily life. Restoring this ability and, thus, bringing relief to the patient’s condition should be an important aim of science.We propose an interdisciplinary investigation of both the neuronal activity controlling skilled hand movements and how this activity can be used in a Brain-Machine Interface (BMI) to control hand postures suitable for grasp of different everyday objects. For example, relevant patients rank the loss of skilled grasp as one of the most debilitating features of their injury (Anderson, 2004). Thus, grasp BMIs are of great importance, but not yet available.We will investigate grasp-related neuronal activity in monkeys and human volunteers based on recordings of (i) intracortical single-unit activity (SUA) and local field potentials (LFP) through multiple electrodes in monkey primary motor cortex (M1), ventral pre-motor cortex (PMv) and boundary areas between M1 and PMv, and (ii) non-invasive human magnetoencephalograms (MEG).Recent studies have shown grasp-specific neuronal activity in SUA and LFP recorded in monkey. We will record grasp-related activity simultaneously at various sites ranging from PMv to M1. Central points are the investigation of the spatial distribution of this activity across motor areas and different cortical laminae, the long-term stability and how this activity is modulated by novel motor tasks. We will also assess how these points affect the decoding of different grasps in a potential BMI and whether human MEG shows similar grasp specificity during execution and imagination of grasp, which is significant for patients controlling a BMI by imagining performance of different actions.The ultimate goal is precise, dexterous, real-time BMI grasp control of hand prostheses; our project represents a first step in this direction.
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