A mathematical framework for inferring connectivity in probabilistic neuronal networks

Mathematical Biosciences

Volumn 205, Issue 2, 2007, Pages 204-251

  Nykamp, Duane Q ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Causality; Correlations; Maximum likelihood; Neural networks; Point process

Indexed keywords

MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILISTIC LOGICS; ROBUSTNESS (CONTROL SYSTEMS);

CAUSALITY; CORRELATIONS; NEUROSCIENCE; POINT PROCESS;

NEURAL NETWORKS;

CORRELATION; NERVOUS SYSTEM; NUMERICAL METHOD; PROBABILITY;

ARTICLE; BAYES THEOREM; CALCULATION; CAUSAL MODELING; CELL SUBPOPULATION; CORRELATION ANALYSIS; CORRELATION COEFFICIENT; COVARIANCE; MATHEMATICAL ANALYSIS; MAXIMUM LIKELIHOOD METHOD; MEASUREMENT; NERVE CELL NETWORK; NEUROSCIENCE; POISSON DISTRIBUTION; PROBABILITY; SPIKE; TIME; VALIDATION PROCESS; VARIANCE;

ALGORITHMS; ANIMALS; COMPUTER SIMULATION; HUMANS; LIKELIHOOD FUNCTIONS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NERVE NET; NEURONS;

EID: 33845459534     PISSN: 00255564     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mbs.2006.08.020     Document Type: Article

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