Dynamical estimation of neuron and network properties I: Variational methods

Biological Cybernetics

Volumn 105, Issue 3-4, 2011, Pages 217-237

  Toth, Bryan A ^a   Kostuk, Mark ^a   Meliza, C Daniel ^b   Margoliash, Daniel ^b   Abarbanel, Henry D I ^a,c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

^c UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

Data assimilation; Ion channel properties; Neuronal dynamics

Indexed keywords

COMPUTATIONALLY EFFICIENT; DATA ASSIMILATION; DIVERSE RANGE; HIGH-DIMENSIONAL INTEGRALS; INCOMPLETE INFORMATION; ION CHANNEL PROPERTIES; MEMBRANE VOLTAGE; MODEL CONSISTENCY; MODEL PARAMETERS; MODEL STATE; NETWORK PROBLEMS; NETWORK PROPERTIES; NEURONAL DYNAMICS; NEURONAL MODEL; NOISY DATA; NONLINEAR DATA; NUMERICAL EXPERIMENTS; OBSERVATION WINDOW; PARALLELIZATIONS; PATH APPROXIMATION; SPARSE SET; STATE VARIABLES; TIME VARYING; VARIATIONAL METHODS; VOLTAGE GATED ION CHANNELS;

DATA PROCESSING; DYNAMICS; ELECTRIC ARC WELDING; ESTIMATION;

NEURAL NETWORKS;

ION CHANNEL;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; CELL MEMBRANE POTENTIAL; NERVE CELL; PHYSIOLOGY; THEORETICAL MODEL;

ALGORITHMS; ION CHANNELS; MEMBRANE POTENTIALS; MODELS, NEUROLOGICAL; MODELS, THEORETICAL; NEURONS;

EID: 84856597126     PISSN: 03401200     EISSN: 14320770     Source Type: Journal    
DOI: 10.1007/s00422-011-0459-1     Document Type: Article

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