Massively Parallel Recording of Unit and Local Field Potentials With Silicon-Based Electrodes

1 Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey 07102 2 Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, Michigan 48109-2122 Submitted 8 February 2003; accepted in final form 17 April...

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Veröffentlicht in:Journal of neurophysiology 2003-08, Vol.90 (2), p.1314-1323
Hauptverfasser: Csicsvari, Jozsef, Henze, Darrell A, Jamieson, Brian, Harris, Kenneth D, Sirota, Anton, Bartho, Peter, Wise, Kensall D, Buzsaki, Gyorgy
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Sprache:eng
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Zusammenfassung:1 Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey 07102 2 Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, Michigan 48109-2122 Submitted 8 February 2003; accepted in final form 17 April 2003 ABSTRACT Parallel recording of neuronal activity in the behaving animal is a prerequisite for our understanding of neuronal representation and storage of information. Here we describe the development of micro-machined silicon microelectrode arrays for unit and local field recordings. The two-dimensional probes with 96 or 64 recording sites provided high-density recording of unit and field activity with minimal tissue displacement or damage. The on-chip active circuit eliminated movement and other artifacts and greatly reduced the weight of the headgear. The precise geometry of the recording tips allowed for the estimation of the spatial location of the recorded neurons and for high-resolution estimation of extracellular current source density. Action potentials could be simultaneously recorded from the soma and dendrites of the same neurons. Silicon technology is a promising approach for high-density, high-resolution sampling of neuronal activity in both basic research and prosthetic devices. G. Buzsáki, Center for Molecular and Behavioral, Neuroscience, Rutgers University, 197 University Ave., Newark, NJ 07102 (E-mail: Buzsaki{at}axon.rutgers.edu ).
ISSN:0022-3077
1522-1598
DOI:10.1152/jn.00116.2003