Incremental mutual information: A new method for characterizing the strength and dynamics of connections in neuronal circuits

PLoS Computational Biology

Volumn 6, Issue 12, 2010, Pages

  Singh, Abhinav ^a   Lesica, Nicholas A ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION THEORY; TIMING CIRCUITS;

CELLULAR MECHANISMS; MUTUAL INFORMATIONS; NETWORK MECHANISM; NEURONAL CIRCUITS; OR-NETWORKS; SENSORY SYSTEM; STATISTICAL DEPENDENCIES; TIME-SCALES; VISUAL SYSTEMS;

NEURONS;

ANALYTIC METHOD; ANIMAL CELL; ARTICLE; CONTROLLED STUDY; ENTROPY; INCREMENTAL MUTUAL INFORMATION; LATERAL GENICULATE NUCLEUS; MATHEMATICAL COMPUTING; MOLECULAR DYNAMICS; NERVE CELL NETWORK; NERVE CONDUCTION; NERVE STIMULATION; NONHUMAN; POSTSYNAPTIC POTENTIAL; PROCESS DEVELOPMENT; RETINA GANGLION CELL; SIGNAL NOISE RATIO; STATISTICAL ANALYSIS; STIMULUS RESPONSE; STRENGTH; VISUAL STIMULATION; ACTION POTENTIAL; ALGORITHM; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; CYTOLOGY; HAPLORHINI; METHODOLOGY; NERVE CELL; NORMAL DISTRIBUTION; PHYSIOLOGY; THALAMUS;

PRIMATES;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; HAPLORHINI; MODELS, NEUROLOGICAL; NEURONS; NORMAL DISTRIBUTION; RETINAL GANGLION CELLS; THALAMUS;

EID: 78651231390     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1001035     Document Type: Article

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