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A1: Connecting brain activity across levels of resolution

Clemens BoucseinA and Ad AertsenA


A
= Neurobiology and Biophysics;

Scientific background

A much debated question in brain-machine interfacing (BMI) research is which neuronal signal (or combination of signals) is optimal for controlling neuronal motor prostheses. It has been shown that signals on different scales (spikes, LFP, ECoG, EEG, MEG, fMRI) carry partially overlapping, partially complementary information about motor plans. Moreover, even within a single signal type, information about an upcoming movement is manifested differentially in different features of the signal (e.g. different frequency bands in the LFP). However, it is still unclear how these different signals and features of signals, which all reflect activity of the same neuronal network, relate to each other, and to which extent they provide information on the underlying network dynamics and the motor plans carried by them. Clarifying these basic questions is of key importance for identifying which brain signals (or combinations thereof) provide optimal control signals for brain-machine interfaces and for determining which electrode designs and recording technologies should, accordingly, be pursued.

Objectives

The aim of this project is to improve our understanding of brain activity signals at multiple different scales of resolution in space and time, to clarify how they are linked across scales, and to determine how their dynamics relates to the underlying mechanisms of brain function.

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