The spike response model: A framework to predict neuronal spike trains

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2714, Issue , 2003, Pages 846-853

  Jolivet, Renaud ^a   Lewis, Timothy J ^b   Gerstner, Wulfram ^a  

^a EPFL   (Switzerland)

^b NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FORECASTING; NEURONS;

ARTIFICIAL DATA; COEFFICIENT OF VARIATION; NEURON MODEL; NEURONAL ACTIVITIES; PRIORI INFORMATION; SIMPLE METHOD; SPIKE RESPONSE MODELS; THRESHOLD MODEL;

NEURAL NETWORKS;

EID: 35248819696     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44989-2_101     Document Type: Article

References (7)

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3. + channels in sustained high-frequency firing of fast-spiking neocortical interneurons, J. Neurophysiol. 82: 2476-2489 (1999)
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5. Wiener, N., Nonlinear problems in random theory, MIT Press, Cambridge (1958)
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7. Rauch, A., La Camera, G., Lüscher, H.-R., Senn, W. and Fusi, S., unpublished observations (2002)