Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models

PLoS Computational Biology

Volumn 11, Issue 6, 2015, Pages

  Pozzorini, Christian ^a   Mensi, Skander ^a   Hagens, Olivier ^a   Naud, Richard ^b   Koch, Christof ^c   Gerstner, Wulfram ^a  

^a EPFL   (Switzerland)

^b UNIVERSITY OF OTTAWA   (Canada)

^c ALLEN INSTITUTE FOR BRAIN SCIENCE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTROPHYSIOLOGY; NEURONS; THROUGHPUT;

CONVEX OPTIMISATION; ELECTROPHYSIOLOGICAL RECORDINGS; EMERGENT PROPERTY; HIGH THROUGH-PUT CHARACTERIZATION; LARGE SCALE SIMULATIONS; NEURAL CIRCUITS; OPTIMIZATION PROCEDURES; SINGLE NEURON; SINGLE-NEURON MODELS; SPIKING MODEL;

CONVEX OPTIMIZATION;

AUTOMATED PATCH CLAMP; HUMAN; HUMAN CELL; IN VITRO STUDY; MODEL; NERVE CELL; ACTION POTENTIAL; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; BRAIN; C57BL MOUSE; COMPUTER SIMULATION; CYTOLOGY; ELECTROPHYSIOLOGY; HIGH THROUGHPUT SCREENING; MALE; MOUSE; PHYSIOLOGY; PROCEDURES;

ACTION POTENTIALS; ANIMALS; BRAIN; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; ELECTROPHYSIOLOGY; HIGH-THROUGHPUT SCREENING ASSAYS; MALE; MICE; MICE, INBRED C57BL; MODELS, NEUROLOGICAL; NEURONS;

EID: 84953224905     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1004275     Document Type: Article

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