Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks

Frontiers in Neural Circuits

Volumn 8, Issue MAR, 2014, Pages

  Cavallari, Stefano ^a   Panzeri, Stefano ^a,b   Mazzoni, Alberto ^a,c  

^a ISTITUTO ITALIANO DI TECNOLOGIA   (Italy)

^b MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

^c SCUOLA SUPERIORE SANT ANNA   (Italy)

Author keywords

Conductance based neuron models; Correlation analysis; Current based neuron models; Information encoding; Integrate and fire neurons; Local field potentials; Recurrent neural network; Spike correlation

Indexed keywords

ARTICLE; CELL INTERACTION; CELL POPULATION; CONDUCTANCE BASED NETWORK; CONTROLLED STUDY; CURRENT BASED NETWORK; EXCITATORY JUNCTION POTENTIAL; MATHEMATICAL COMPUTING; MOLECULAR DYNAMICS; NERVE CELL INHIBITION; NERVE CELL NETWORK; NERVOUS SYSTEM CONDUCTANCE; STATISTICAL MODEL; STIMULUS RESPONSE; SYNAPTIC POTENTIAL; ACTION POTENTIAL; BIOLOGICAL MODEL; COMPUTER SIMULATION; CONDUCTANCE BASED NEURON MODELS; CORRELATION ANALYSIS; CURRENT BASED NEURON MODELS; INFORMATION ENCODING; INTEGRATE-AND-FIRE NEURONS; LOCAL FIELD POTENTIALS; NERVE CELL; PHYSIOLOGY; RECURRENT NEURAL NETWORK; SPIKE CORRELATION; SYNAPTIC TRANSMISSION;

CONDUCTANCE BASED NEURON MODELS; CORRELATION ANALYSIS; CURRENT BASED NEURON MODELS; INFORMATION ENCODING; INTEGRATE-AND-FIRE NEURONS; LOCAL FIELD POTENTIALS; RECURRENT NEURAL NETWORK; SPIKE CORRELATION;

ACTION POTENTIALS; COMPUTER SIMULATION; MODELS, NEUROLOGICAL; NERVE NET; NEURAL INHIBITION; NEURONS; SYNAPTIC TRANSMISSION;

EID: 84896928546     PISSN: 16625110     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncir.2014.00012     Document Type: Article

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