Interspike interval attractors from chaotically driven neuron models
暂无分享,去创建一个
[1] Robert Shaw,et al. The Dripping Faucet As A Model Chaotic System , 1984 .
[2] J. Rinzel. Discussion: Electrical excitability of cells, theory and experiment: Review of the Hodgkin-Huxley foundation and an update , 1990 .
[3] Sauer,et al. Reconstruction of dynamical systems from interspike intervals. , 1994, Physical review letters.
[4] S. Yoshizawa,et al. An Active Pulse Transmission Line Simulating Nerve Axon , 1962, Proceedings of the IRE.
[5] G Palm,et al. Are Fractal Dimensions a Good Measure for Neuronal Activity , 1990 .
[6] S. Levin. Lectu re Notes in Biomathematics , 1983 .
[7] J. Rinzel,et al. INTEGRATE-AND-FIRE MODELS OF NERVE MEMBRANE RESPONSE TO OSCILLATORY INPUT. , 1981 .
[8] William Bialek,et al. Reading a Neural Code , 1991, NIPS.
[9] J. Segundo,et al. The spike trains of inhibited pacemaker neurons seen through the magnifying glass of nonlinear analyses. , 1998, Neuroscience.
[10] K. Aihara,et al. Structures of attractors in periodically forced neural oscillators , 1986 .
[11] P. Rapp,et al. Dynamics of spontaneous neural activity in the simian motor cortex: The dimension of chaotic neurons , 1985 .
[12] L. Glass,et al. A simple model for phase locking of biological oscillators , 1979, Journal of mathematical biology.
[13] L F Abbott,et al. Decoding neuronal firing and modelling neural networks , 1994, Quarterly Reviews of Biophysics.
[14] S J Schiff,et al. Stochastic versus deterministic variability in simple neuronal circuits: II. Hippocampal slice. , 1994, Biophysical journal.
[15] J. Elsner,et al. Nonlinear prediction as a way of distinguishing chaos from random fractal sequences , 1992, Nature.
[16] Farmer,et al. Predicting chaotic time series. , 1987, Physical review letters.
[17] James Theiler,et al. Testing for nonlinearity in time series: the method of surrogate data , 1992 .
[18] Michael C. Mackey,et al. The statistical dynamics of recurrent biological events , 1992 .
[19] André Longtin,et al. NONLINEAR FORECASTING OF SPIKE TRAINS FROM SENSORY NEURONS , 1993 .
[20] David J. Wales,et al. Calculating the rate of loss of information from chaotic time series by forecasting , 1991, Nature.
[21] P. Alstrøm,et al. Phase-locking structure of “integrate-and-fire” models with threshold modulation , 1988 .
[22] P. N. Bhat,et al. Evidence for sub-millisecond structure in a γ-ray burst , 1992, Nature.
[23] Manfred Clynes,et al. Biomedical engineering systems , 1970 .
[24] A. Holden. Models of the stochastic activity of neurones , 1976 .
[25] F. Takens. Detecting strange attractors in turbulence , 1981 .
[26] Christof Koch,et al. Coding of Time-Varying Signals in Spike Trains of Integrate-and-Fire Neurons with Random Threshold , 1999, Neural Computation.
[27] Alfonso M Albano,et al. Phase-randomized surrogates can produce spurious identifications of non-random structure , 1994 .
[28] T. Musha,et al. Global Bifurcation Structure in Periodically Stimulated Giant Axons of Squid(Mathematical Topics in Biology) , 1989 .
[29] André Longtin,et al. Reconstructing dynamics from neural spike trains , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.
[30] Michael C. Mackey,et al. The dynamics of production and destruction: Analytic insight into complex behavior , 1982 .
[31] H. Schwan,et al. Biological Engineering , 1970 .
[32] D. Chialvo,et al. Non-linear dynamics of cardiac excitation and impulse propagation , 1987, Nature.
[33] G. Hartmann,et al. Parallel Processing in Neural Systems and Computers , 1990 .
[34] Henry C. Tuckwell,et al. Stochastic processes in the neurosciences , 1989 .
[35] Moss,et al. Detecting periodic unstable points in noisy chaotic and limit cycle attractors with applications to biology. , 1995, Physical review letters.