A control algorithm for autonomous optimization of extracellular recordings.

Zoran Nenadic; Joel W Burdick

doi:10.1109/tbme.2005.863930

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A control algorithm for autonomous optimization of extracellular recordings.

Zoran Nenadic·Joel W Burdick

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Abstract

This paper develops a control algorithm that can autonomously position an electrode so as to find and then maintain an optimal extracellular recording position. The algorithm was developed and tested in a two-neuron computational model representative of the cells found in cerebral cortex. The algorithm is based on a stochastic optimization of a suitably defined signal quality metric and is shown capable of finding the optimal recording position along representative sampling directions, as well as maintaining the optimal signal quality in the face of modeled tissue movements. The application of the algorithm to acute neurophysiological recording experiments and its potential implications to chronic recording electrode arrays are discussed.

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Action Potentials Algorithms Animals Artifacts Artificial Intelligence Computer Simulation Diagnosis, Computer-Assisted Humans Models, Neurological Neurons Pattern Recognition, Automated Signal Processing, Computer-Assisted Evaluation Study Journal Article Research Support, U.S. Gov't, Non-P.H.S.

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Zoran Nenadic, Joel W Burdick. 2006. A control algorithm for autonomous optimization of extracellular recordings.. https://doi.org/10.1109/tbme.2005.863930

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