Towards an implantable brain-machine interface based on epicortical field potentials
Year: 2004
Type: article
Abstract: Today, a major challenge in neuro-engineering is to develop a brain-machine interface (BMI) suitable to restore communication and motor control in paralyzed patients. One fundamental, unresolved question is which neuronal signal type should be recorded and decoded for such purposes. Here we review work on neuronal population activity, i.e. the ensemble activity of local groups of neurons, as a control signal for BMIs. Further, we propose a BMI approach based on population activity recorded directly from the human cortical surface. Using a finger movement task, we evaluate movement related changes in epicortical potentials across a broad frequency range and we show that the side of index finger flexions can be inferred from primary motor cortex population activity with up to 100 % accuracy from single trial data.
Institution: University of Freiburg
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W2139864007