Title
Principal component analysis of ensemble recordings reveals cell assemblies at high temporal resolution.
Abstract
Simultaneous recordings of many single neurons reveals unique insights into network processing spanning the timescale from single spikes to global oscillations. Neurons dynamically self-organize in subgroups of coactivated elements referred to as cell assemblies. Furthermore, these cell assemblies are reactivated, or replayed, preferentially during subsequent rest or sleep episodes, a proposed mechanism for memory trace consolidation. Here we employ Principal Component Analysis to isolate such patterns of neural activity. In addition, a measure is developed to quantify the similarity of instantaneous activity with a template pattern, and we derive theoretical distributions for the null hypothesis of no correlation between spike trains, allowing one to evaluate the statistical significance of instantaneous coactivations. Hence, when applied in an epoch different from the one where the patterns were identified, (e.g. subsequent sleep) this measure allows to identify times and intensities of reactivation. The distribution of this measure provides information on the dynamics of reactivation events: in sleep these occur as transients rather than as a continuous process.
Year
DOI
Venue
2010
10.1007/s10827-009-0154-6
Journal of Computational Neuroscience
Keywords
Field
DocType
pca · reactivation · sleep · memory consolidation,reactivation event,subsequent sleep,high temporal resolution,neural activity,instantaneous coactivations,single spike,cell assembly,ensemble recording,single neuron,neurons dynamically self-organize,subsequent rest,instantaneous activity,principal component analysis,statistical significance,self organization,oscillations,pca,probability,action potentials,memory consolidation,temporal resolution,sleep
Oscillation,Engram,Neural activity,Memory consolidation,Artificial intelligence,Network processing,Temporal resolution,Mathematics,Machine learning,Principal component analysis
Journal
Volume
Issue
ISSN
29
1-2
1573-6873
Citations 
PageRank 
References 
14
1.02
1
Authors
5
Name
Order
Citations
PageRank
Adrien Peyrache1141.02
Karim Benchenane2141.02
Khamassi Mehdi311216.51
Sidney I. Wiener4171.52
Francesco P. Battaglia5295.43