Maximising sensitivity in a spiking network

Advances in Neural Information Processing Systems

Volumn , Issue , 2005, Pages

  Bell, Anthony J ^a   Parra, Lucas C ^b  

^a Redwood Neuroscience Institute   (United States)

^b Robotics and Intelligent Systems Lab   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

NETWORK LAYERS;

BIOPHYSICAL PROCESS; INPUT SPIKE TRAIN; MUTUAL INFORMATIONS; NETWORK SENSITIVITY; PROBABILISTIC MACHINES; SELF-ORGANISATION; SPIKING NETWORKS; VISUAL RECEPTIVE FIELDS;

NETWORK CODING;

EID: 84898957456     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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3. Barber D. & Agakov F. 2003. The IM Algorithm: A Variational Approach to Information Maximization. Advances in Neural Information Processing Systems 16, MIT Press.
4. Bell A.J. & Sejnowski T.J. 1995. An information maximization approach to blind separation and blind deconvolution, Neural Computation, 7, 1129-1159.
5. Dan Y. & Poo M-m. 2004. Spike timing-dependent plasticity of neural circuits, Neuron, 44, 23-30.
6. Froemke R.C. & Dan Y. 2002. Spike-timing-dependent synaptic modification induced by natural spike trains. Nature, 28, 416: 433-8.
7. Gerstner W. & Kistner W.M. 2002. Spiking neuron models, Camb. Univ. Press.
8. Zador A.M., Agmon-Snir H. & Segev I. 1995. The morphoelectrotonic transform: A graphical approach to dendritic function, J. Neurosci., 15(3): 1669-1682.