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J Neurophysiol 92: 600-608, 2004. First published March 31, 2004; doi:10.1152/jn.01170.2003
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INNOVATIVE METHODOLOGY

Characterization of Neocortical Principal Cells and Interneurons by Network Interactions and Extracellular Features

Peter Barthó, Hajime Hirase, Lenaïc Monconduit, Michael Zugaro, Kenneth D. Harris and György Buzsáki

Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark, New Jersey 07102

Submitted 8 December 2003; accepted in final form 6 February 2004

Most neuronal interactions in the cortex occur within local circuits. Because principal cells and GABAergic interneurons contribute differently to cortical operations, their experimental identification and separation is of utmost important. We used 64-site two-dimensional silicon probes for high-density recording of local neurons in layer 5 of the somatosensory and prefrontal cortices of the rat. Multiple-site monitoring of units allowed for the determination of their two-dimensional spatial position in the brain. Of the ~60,000 cell pairs recorded, 0.2% showed robust short-term interactions. Units with significant, short-latency (<3 ms) peaks following their action potentials in their cross-correlograms were characterized as putative excitatory (pyramidal) cells. Units with significant suppression of spiking of their partners were regarded as putative GABAergic interneurons. A portion of the putative interneurons was reciprocally connected with pyramidal cells. Neurons physiologically identified as inhibitory and excitatory cells were used as templates for classification of all recorded neurons. Of the several parameters tested, the duration of the unfiltered (1 Hz to 5 kHz) spike provided the most reliable clustering of the population. High-density parallel recordings of neuronal activity, determination of their physical location and their classification into pyramidal and interneuron classes provide the necessary tools for local circuit analysis.


Address for reprint requests and other correspondence: G. Buzsáki, Center for Molecular and Behavioral Neuroscience, Rutgers University, 197 University Ave., Newark, NJ 07102 (E-mail: buzsaki{at}axon.rutgers.edu).




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