< Back to previous page

Project

Brain-machine interfacing with micro-electrode arrays in the visual cortex.

Brain-Machine interfaces (BMIs, also called Neuromotor prostheses) provide an outlook for immediately improving the quality of life of neurologically impaired persons. Nowadays, in these BMIs, a micro-electrode array, consisting of tens of electrodes, is implanted in the brain in the (pre)motor frontal areas and in the parietal cortex, region involved in motor intention, motor planning and motor execution. There it captures brain signals from which the information is extracted by further processing, but the human operator is still needed to run the systems. The aim of this project is to develop a fully autonomous BMI, the system that should be able to work without human assistance. The system will provide: 1) automatic on-line spike detection; 2) automatic spike sorting (spike discrimination) and 3) array decoding (spike decoding). In stead or recording in the (pre)motor regions, we will measure the responses in the visual cortical area V4 neurons to a set of visual stimuli that the monkey learned to discriminate. Since recording in this area is much harder than in the (pre)motor cortex, due to the lesser amount of pyramidal neurons, the spike detection and spike discrimination problem becomes much tougher and success in this matter will ensure success in most other cortical areas. Recording in the visual area instead of a motor region is necessary for the development of a functional autonomous prosthetic device that will produce the same output as the stimulus-driven behavioural response of the animal.
Date:1 Jan 2009 →  31 Dec 2012
Keywords:Neuroscience, Neuromotor prostheses, Spike detection, Array decoding, Spike sorting
Disciplines:Scientific computing, Bioinformatics and computational biology, Public health care, Public health services, Neurosciences, Biological and physiological psychology, Cognitive science and intelligent systems, Developmental psychology and ageing, Modelling, Biological system engineering, Signal processing