Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime

Journal of Computational Neuroscience

Volumn 32, Issue 2, 2012, Pages 347-366

  Huggins, Jonathan Hunter ^a   Paninski, Liam ^a  

^a Och Spine at New York Presbyterian Hospitals   (United States)

Author keywords

Markov random field; Optimal experimental design; State space model; Submodularity; Voltage sensitive imaging

Indexed keywords

DESIGN; KALMAN FILTERS; MARKOV PROCESSES; OPTIMIZATION; SAMPLING; STATE SPACE METHODS; STATISTICS; VOLTAGE MEASUREMENT;

DENDRITICS; EXPERIMENTAL DESIGN METHOD; GREEDY ALGORITHMS; MARKOV RANDOM FIELDS; OPTIMAL EXPERIMENTAL DESIGNS; STATE-SPACE MODELS; SUBMODULARITY; TIME INVARIANTS; VOLTAGE SIGNALS; VOLTAGE-SENSITIVE IMAGING;

APPROXIMATION ALGORITHMS;

ALGORITHM; ANIMAL CELL; COMPUTER MODEL; COMPUTER SIMULATION; COVARIANCE; DENDRITE; ELECTRIC POTENTIAL; ERROR; EXPERIMENTAL DESIGN; GEOMETRY; MATHEMATICAL ANALYSIS; NONHUMAN; PRIORITY JOURNAL; PROCESS OPTIMIZATION; QUALITY CONTROL; RAT; REVIEW; SIGNAL NOISE RATIO;

EID: 84863880612     PISSN: 09295313     EISSN: 15736873     Source Type: Journal    
DOI: 10.1007/s10827-011-0357-5     Document Type: Review

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