Population models of temporal differentiation

Neural Computation

Volumn 22, Issue 3, 2010, Pages 621-659

  Tripp, Bryan P ^a   Eliasmith, Chris ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CELL MEMBRANE POTENTIAL; COMPUTER SIMULATION; HUMAN; NERVE CELL; PERCEPTIVE DISCRIMINATION; PHYSIOLOGY; SYNAPSE; TIME; TIME PERCEPTION;

ACTION POTENTIALS; ALGORITHMS; COMPUTER SIMULATION; DISCRIMINATION (PSYCHOLOGY); HUMANS; MEMBRANE POTENTIALS; NEURAL NETWORKS (COMPUTER); NEURONS; SYNAPSES; TIME FACTORS; TIME PERCEPTION;

EID: 77953005821     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/neco.2009.02-09-970     Document Type: Article

References (44)

1. Abbott, L. F., & Regehr,W. G. (2004). Synaptic computation. Nature, 431, 796-803.
2. Anastasio, T. J. (1994). The fractional-order dynamics of brainstem vestibulooculomotor neurons. Biol. Cybern., 72, 69-79.
3. Benda, J., & Herz, A. (2003). A universal model for spike-frequency adaptation. Neural Computation, 15, 2523-2564.
4. Drew, P. J., & Abbott, L. F. (2006). Models and properties of power-law adaptation in neural systems. J. Neurophysiol., 96, 826-833.
5. Dunn, N. A., Lockery, S. R., Pierce-Shimomura, J. T., & Conery, J. S. (2004). A neural network model of chemotaxis predicts functions of synaptic connections in the nematode Caenorhabditis elegans. J. Comp. Neuro., 17, 137-147.
6. Eliasmith, C. (2004).Aunified approach to building and controlling spiking attractor networks. Neural Comput., 17, 1276-1314.
7. Eliasmith, C.,&Anderson, C.H. 2003. Neural engineering: Computation, representation, and dynamics in neurobiological systems. Cambridge, MA: MIT Press.
8. Fairhall, A. L., Lewen, G. D., Bialek, W., & de Ruyter Van Steveninck, R. R. (2001). Efficiency and ambiguity in an adaptive neural code. Nature, 412, 787- 792.
9. Fourcaud-Trocmé, N., Hansel, D., van Vreeswijk, C., & Brunel, N. (2003). How spike generation mechanisms determine the neuronal response to fluctuating inputs. J. Neurosci., 23(37), 11628-11640.
10. Geiger, J. R. P., L̈ubke, J., Roth, A., Frotscher, M., & Jonas, P. (1997). Submillisecond AMPA receptor-mediated signaling at a principal neuron-interneuron synapse. Neuron, 18, 1009-1023.
11. Goldman, M. S., Levine, J. H., Major, G., Tank, D. W., & Seung, H. S. (2003). Robust persistent neural activity in a model integrator with multiple hysteretic dendrites per neuron. Cereb. Cortex., 13(11), 1185-1195.
12. Goldman, M. S., Maldonado, P., & Abbott, L. F. (2002). Redundancy reduction and sustained firing with stochastic depressing synapses. J. Neurosci., 22(2), 584-591.
13. Holstein, G. R., Rabbitt, R. D., Martinelli, G. P., Friedrich, V. L., Boyle, R. D., & Highstein, S. M. (2004). Convergence of excitatory and inhibitory hair cell transmitters shapes vestibular afferent responses. Proc. Nat. Acad. Sci., 101(44), 15766- 15771.
14. Jenison, R. L. (2007). Neural dynamics in human auditory cortex. In CNC Conference: Direct Recordings from the Human Brain. N.p.
15. Joel, D., Niv, Y., & Ruppin, E. (2002). Actor-critic models of the basal ganglia: New anatomical and computational perspectives. Neural Networks, 15, 535-547.
16. Kawada, T., Uemura, K., Kashihara, K., Kamiya, A., Sugimachi, M., & Sunagawa, K. (2004). A derivative-sigmoidal model reproduces operating point-dependent baroreflex neural arc transfer characteristics. Am. J. Physiol. Heart Circ. Physiol., 286, H2272-H2279.
17. Kleinz, M., & Osler, T. J. (2000). A child's garden of fractional derivatives. College Mathematics Journal, 31, 82-88.
18. Koch, C. (1999). Biophysics of computation: Information processing in single neurons. New York: Oxford University Press.
19. Koulakov, A., Raghavachari, S., Kepecs, A., & Lisman, J. (2002). Model for a robust neural integrator. Nature Neuroscience, 5(8), 775-782.
20. La Camera, G., Rauch, A., L̈uscher,H. R., Senn,W.,&Fusi, S. (2004).Minimalmodels of adapted neuronal response in in vivo-like input currents. Neural Computation, 16, 2101-2124.
21. Lass, Y., & Abeles, M. (1975). Transmission of information by the axon: I. Noise and memory in the myelinated nerve fiber of the frog. Biological Cybernetics, 19(2), 61-67.
22. Liu, Y. H., & Wang, X. J. (2001). Spike-frequency adaptation of a generalized leaky integrate-and-fire model neuron. J. Computational. Neuroscience, 10, 25-45.
23. Lundstrom, B. N., Higgs, M. H., Spain, W. J., & Fairhall, A. L. (2008). Fractional differentiation by neocortical pyramidal neurons. Nature Neuroscience, 11, 1335- 42.
24. Miller, P., Brody, C. D., Romo, R., & Wang, X. J. (2003). A recurrent network model of somatosensory parametric working memory in the prefrontal cortex. Cerebral Cortex, 13, 1208-1218.
25. Naud, R., Berger, T., Badel, L., Roth, A., & Gerstner, W. (2008). Quantitative singleneuron modeling: Competition 2008. In Frontiers in Neuroinformatics. N.p.
26. Parisien, C. M., Anderson, C. H., & Eliasmith, C. (2008). Solving the problem of negative synaptic weights in cortical models. Neural Computation, 20(6), 1473- 1494.
27. Poon, C. S., Young, D. L., & Siniaia, M. S. (2000). High-pass filtering of carotidvagal influences on expiration in the rat: Role of n-methyl-d-aspartate receptors. Neuroscience Letters, 284, 5-8.
28. Puccini, G. D., Sanchez-Vives, M. V., & Compte, A. (2007). Integrated mechanisms of anticipation and rate-of-change computations in cortical circuits. PLoS Computational Biology, 3, 813-825.
29. Robinson, D. A. (1968). A note on the oculomotor pathway. Experimental Neurology, 22, 130-132.
30. Robinson, D. A. (1989). Integrating with neurons. Annual Review of Neuroscience, 12, 33-45.
31. Sanchez-Vives, M. V., Nowak, L. G., & McCormick, D. A. (2000a). Cellular mechanisms of long-lasting adaptation in visual cortical neurons in vitro. Journal of Neuroscience, 20(11), 4286-4299.
32. Sanchez-Vives, M. V.,Nowak, L. G., & McCormick, D. A. (2000b). Membrane mechanisms underlying contrast adaptation in cat area 17 in vivo. Journal of Neuroscience, 20(11), 4267-4285.
33. Sedra, A. S., & Smith, K. C. (1991). Microelectronic circuits (3rd ed.). Philadelphia: Saunders.
34. Seung, H. S. (1996). How the brain keeps the eyes still. Proc. Nat. Acad. Sci., 93, 13339-13344.
35. Stevens, C. F., & Wang, Y. (1994). Changes in reliability of synaptic function as a mechanism for plasticity. Nature, 371, 704-707.
36. Tamosiunaite, M., Porr, B., &Ẅorg̈otter, F. (2007). Developing velocity sensitivity in a model neuron by local synaptic plasticity. Biological Cybernetics, 96, 507-518.
37. Topka, H., Mescheriakov, S., Boose, A., Kuntz, R., Hertrich, I., Seydel, L., et al. (1999). A cerebellar-like terminal and postural tremor induced in normal man by transcranial magnetic stimulation. Brain, 122, 1551-1562.
38. Tripp, B. P. (2008). A search for principles of basal ganglia function. Ph.D. Dissertation, University ofWaterloo.
39. Van de Vegte, J. (1994). Feedback control systems. Englewood Cliffs, NJ: Prentice Hall.
40. Walker,H. C., Lawrence, J. J., &McBain, C. J. (2002). Activation of kinetically distinct synaptic conductances on inhibitory interneurons by electrotonically overlapping afferents. Neuron, 35, 161-171.
41. Wark, B., Lundstrom, B. N., & Fairhall, A. (2007). Sensory adaptation. Curr. Opin. Neurobiol., 17(4), 423-429.
42. Yoshida, K., Watanabe, D., Ishikane, H., Tachibana, M., Pastan, I., & Nakanishi, S. (2001). A key role of starburst amacrine cells in originating retinal direction selectivity and optokinetic eye movement. Neuron, 30, 771-780.
43. Young, D. L., Eldridge, F. L., & Poon, C. S. (2003). Integration-differentiation and gating of carotid afferent traffic that shapes the respiratory pattern. J. Appl. Physiol., 94, 1213-1229.
44. Zucker, R. S., & Regehr, W. G. (2002). Short-term synaptic plasticity. Annu. Rev. Physiol., 64, 355-405.