STOCHASTIC SYSTEMS SEMINAR

SOME SAMPLE PAPERS: NEUROSCIENCE

  • Generalized Integrate-and-Fire Models of Neuronal Activity Approximate Spike Trains of a Detailed Model to a High Degree of Accuracy, Renaud Jolivet, Timothy J. Lewis, and Wulfram Gerstner, 2004.
  • Simple model of spiking neurons, E. M. Izhikevich, 2003.
  • Which model to use for spiking neurons?, E. M. Izhikevich, 2004.
  • B. A. J. Reddi and R. H. S. Carpenter, The influence of urgency on decision time, Nature America Inc., 2000, 827-830.
  • Mazurek, M. E., Roitman, J. D., Ditterich, J. and Shadlen, M. N., A role for neural integrators in perceptual decision making, Cerebral Cortex, Nov. 2003, Vol. 13, 1257-1269.
  • Kohn, A. and Movshon, J. A., Adaptation changes the direction tuning of macaque MT neurons, Nature Neuroscience, Vol. 7, July 2004, 764-772.
  • Likelihood methods for neural spike train analysis, Emery N. Brown, Ricardo Barbieri, Uri Eden, Loren Frank, in Computational Neuroscience: A comprehensive approach.
  • Theory of Point Processes for Neural Systems, Emery N. Brown, 2003.
  • A Point Process Framework for Relating Neural Spiking Activity to Spiking History, Neural Ensemble, and Extrinsic Covariate Effects, Wilson Truccolo, Uri T. Eden, Matthew R. Fellows, John P. Donoghue, and Emery N. Brown, Neuroscience Department, J. Neurophys. 93 (2005), 1074-1089.
  • Background reference on Dynamical Systems in Neuroscience, by Eugene Izhikevich, Neurosciences Institute.