期刊
JOURNAL OF NEUROSCIENCE METHODS
卷 220, 期 2, 页码 149-166出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2013.04.010
关键词
Cell assemblies; Principal component analysis; Independent component analysis; Assembly vectors
资金
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)
- Fundacao de Apoio a Pesquisa do Estado do Rio Grande do Norte (FAPERN)
- National Science Foundation
Recent progress in the technology for single unit recordings has given the neuroscientific community the opportunity to record the spiking activity of large neuronal populations. At the same pace, statistical and mathematical tools were developed to deal with high-dimensional datasets typical of such recordings. A major line of research investigates the functional role of subsets of neurons with significant co-firing behavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cell assemblies in large neuronal populations that rely on principal and independent component analysis. Based on their performance in spike train simulations, we propose a modified framework that incorporates multiple features of these previous methods. We apply the new framework to actual single unit recordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate at theta frequencies and couple to different phases of the underlying field rhythm. (C) 2013 Elsevier B.V. All rights reserved.
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