Assessing functional connectivity of neural ensembles using directed information

Journal of Neural Engineering

Volumn 9, Issue 2, 2012, Pages

  So, Kelvin ^a   Koralek, Aaron C ^b   Ganguly, Karunesh ^a,b,c,d   Gastpar, Michael C ^a,e   Carmena, Jose M ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d VETERANS AFFAIRS MEDICAL CENTER   (United States)

^e EPFL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN STRUCTURE; COMPLEX NETWORKS; CONNECTIVITY STRUCTURES; CORRELATION ANALYSIS; DATA SETS; DIRECTED INFORMATION; EXPERIMENTAL DATA; FUNCTIONAL CONNECTIVITY; INFORMATION-THEORETIC APPROACH; NEURAL ENSEMBLES; NEURAL SPIKE TRAINS; REALISTIC SIMULATION; SYNAPTIC CONNECTIONS;

ANIMALS; INFORMATION THEORY; NEURAL NETWORKS;

CORRELATION METHODS;

ACTION POTENTIAL; ANIMAL EXPERIMENT; ARTICLE; BRAIN FUNCTION; BRAIN MAPPING; CONTROLLED STUDY; CORPUS STRIATUM; CORRELATION ANALYSIS; EVOKED CORTICAL RESPONSE; FEEDBACK SYSTEM; FUNCTIONAL ASSESSMENT; INFORMATION PROCESSING; LATENT PERIOD; LEARNING; MALE; MEMORY CONSOLIDATION; MENTAL TASK; MICROELECTRODE; NERVE CELL; NERVE CELL NETWORK; NERVE CELL STIMULATION; NEUROPHYSIOLOGY; NEUROTRANSMISSION; NONHUMAN; PRIORITY JOURNAL; RHESUS MONKEY; SPIKE; ALGORITHM; ANIMAL; ARTIFICIAL NEURAL NETWORK; BRAIN; COMPUTER INTERFACE; COMPUTER SIMULATION; CONFIDENCE INTERVAL; ELECTRODE; INFORMATION SCIENCE; LONG EVANS RAT; MACACA MULATTA; NERVE CONDUCTION; NERVE TRACT; NEUROPROSTHESIS; PHYSIOLOGY; PROSTHESIS; PSYCHOMOTOR PERFORMANCE; RAT; STATISTICAL MODEL;

ANIMALIA; PRIMATES; RODENTIA;

ALGORITHMS; ANIMALS; BRAIN; COMPUTER SIMULATION; CONFIDENCE INTERVALS; ELECTRODES, IMPLANTED; INFORMATION THEORY; LINEAR MODELS; MACACA MULATTA; MALE; NEURAL CONDUCTION; NEURAL NETWORKS (COMPUTER); NEURAL PATHWAYS; NEURAL PROSTHESES; NEURONS; PROSTHESIS DESIGN; PSYCHOMOTOR PERFORMANCE; RATS; RATS, LONG-EVANS; USER-COMPUTER INTERFACE;

EID: 84857863324     PISSN: 17412560     EISSN: 17412552     Source Type: Journal    
DOI: 10.1088/1741-2560/9/2/026004     Document Type: Article

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