A unified framework and method for automatic neural spike identification

Journal of Neuroscience Methods

Volumn 222, Issue , 2014, Pages 47-55

  Ekanadham, Chaitanya ^a   Tranchina, Daniel ^a,b   Simoncelli, Eero P ^a,b,c  

^a NEW YORK UNIVERSITY   (United States)

^b NEW YORK UNIVERSITY   (United States)

^c HOWARD HUGHES MEDICAL INSTITUTE   (United States)

Author keywords

Action potential; Clustering; Multi electrode; Neural spike identification; Spike detection; Spike sorting

Indexed keywords

ALGORITHM; ANALYTIC METHOD; ARTICLE; BEST ELLIPSOIDAL ERROR RATE; CLUSTER ANALYSIS; CONTINUOUS BASIS PURSUIT; ELECTRIC POTENTIAL; ELECTRODE; HIPPOCAMPUS; HUMAN; MEASUREMENT ERROR; NERVE POTENTIAL; NOISE; PRIORITY JOURNAL; PROBABILITY; SPIKE; SPIKE SORTING METHOD; SPIKE WAVE; WAVEFORM;

ACTION POTENTIAL; CLUSTERING; MULTI-ELECTRODE; NEURAL SPIKE IDENTIFICATION; SPIKE DETECTION; SPIKE SORTING;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; ARTIFACTS; CA1 REGION, HIPPOCAMPAL; CLUSTER ANALYSIS; COMPUTER SIMULATION; ELECTROPHYSIOLOGY; GRASSHOPPERS; LINEAR MODELS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NEURONS; RATS; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME;

EID: 84888079100     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2013.10.001     Document Type: Article

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