Noise Shaping in Neural Populations with Global Delayed Feedback

O. Ávila Åkerberg¹ ; M. J. Chacron^1, 2

¹ Department of Physics, McGill University, Montreal, H3G 1Y6, Canada
² Department of Physiology, McGill University, Montreal , H3G 1Y6, Canada

Mathematical modelling of natural phenomena, Tome 5 (2010) no. 2, pp. 100-124

Résumé

The interplay between intrinsic and network dynamics has been the focus of many investigations. Here we use a combination of theoretical and numerical approaches to study the effects of delayed global feedback on the information transmission properties of neural networks. Specifically, we compare networks of neurons that display intrinsic interspike interval correlations (nonrenewal) to networks that do not (renewal). We find that excitatory and inhibitory delays can tune information transmission by single neurons but not by the entire network. Most surprisingly, addition of a delay can change the dependence of the information on the coupling strength for renewal neurons and not for nonrenewal neurons. Our results show that intrinsic ISI correlations can have nontrivial interactions with network-induced phenomena.

Détail

DOI : 10.1051/mmnp/20105204

Bibliographie

[1] O. Ávila Åkerberg, M.J. Chacron Noise shaping in neural populations Phys. Rev. E 2009

[2] S. Bahar, J.W. Kantelhardt, A. Neiman, H.H.A. Rego, D.F. Russell, L. Wilkens, A. Bunde, F. Moss Long range temporal anti-correlations in paddlefish electroreceptors Europhys. Lett. 2001 454 460

[3] A. Borst, F. Theunissen Information theory and neural coding Nat. Neurosci. 1999 947 957

[4] V. Braitenberg, A. Schüz. Anatomy of the Cortex. Springer, Berlin, 1991.

[5] A. Bulsara, P. Hänggi, F. Marchesoni, F. Moss, M. Shlesinger Special Issue for Proceedings of The Nato Advanced Research WorkshopStochastic Resonance in Physics and Biology J. Stat. Phys. 1993 1 2

[6] R.S. Cajal. Histologie du système nerveux de l’Homme et des vertébrés. Paris, Maloine, 1909.

[7] M.J. Chacron, A. Longtin, M. St-Hilaire, L. Maler Suprathreshold stochastic firing dynamics with memory in P-type electroreceptors Phys. Rev. Lett. 2000 1576 1579

[8] M.J. Chacron, L. Maler, J. Bastian Electroreceptor neuron dynamics shape information transmission Nat. Neurosci. 2005 673 678

[9] M.J. Chacron, A. Longtin, L. Maler Negative interspike interval correlations increase the neuronal capacity for encoding time-dependent stimuli J. Neurosci. 2001 5328 5343

[10] M.J. Chacron, B. Lindner, A. Longtin Noise shaping by interval correlations increases information transfer Phys. Rev. Lett. 2004

[11] M.J. Chacron, B. Lindner, A. Longtin ISI Correlations and Information Transfer Fluct. Noise Lett. 2004 L195 L205

[12] M.J. Chacron, A. Longtin, L. Maler Delayed excitatory and inhibitory feedback shape neural information transmission Phys. Rev. E 2005

[13] M.J. Chacron, A. Longtin, L. Maler The effects of spontaneous activity, background noise, and the stimulus ensemble on information transfer in neurons Network 2003 803 824

[14] M.J. Chacron, B. Doiron, L. Maler, A. Longtin, J. Bastian Non-classical receptive field mediates switch in a sensory neuron’s frequency tuning Nature 2003 77 81

[15] M.J. Chacron, L. Maler, J. Bastian Feedback and feedforward control of frequency tuning to naturalistic stimuli J. Neurosci. 2005 5521 5532

[16] M.J. Chacron Nonlinear information processing in a model sensory system J. Neurophysiol. 2006 2933 2946

[17] M.J. Chacron, B. Lindner, A. Longtin Threshold fatigue and information transfer J. Comput. Neurosci. 2007 301 311

[18] M.J. Chacron, J. Bastian Population coding by electrosensory neurons J. Neurophysiol. 2008 1825 1835

[19] T. Cover, J. Thomas. Elements of Information Theory, Wiley, New-York, 1991.

[20] B. Doiron, M.J. Chacron, L. Maler, A. Longtin, J. Bastian Inhibitory feedback required for network oscillatory responses to communication but not prey stimuli Nature 2003 539 543

[21] B. Doiron, B. Lindner, A. Longtin, L. Maler, J. Bastian Oscillatory activity in electrosensory neurons increases with the spatial correlation of the stochastic input stimulus Phys. Rev. Lett. 2004

[22] L.D. Ellis, R. Krahe, C.M. Bourque, R.J. Dunn, M.J. Chacron Muscarinic receptors control frequency tuning through the downregulation of an A-type potassium current J. Neurophysiol. 2007 1526 1537

[23] T.A. Engel, B. Helbig, D.F. Russell, L. Schimansky-Geier, A.B. Neiman Coherent stochastic oscillations enhance signal detection in spiking neurons Phys. Rev. E 2009

[24] F. Farkhooi, M.F. Strube-Bloss, M.P. Nawrot Serial correlation in neural spike trains: Experimental evidence, stochastic modeling, and single neuron variability Phys. Rev. E 2009

[25] L. Gammaitoni, P. Hänggi, P. Jung, F. Marchesoni Stochastic resonance Rev. Mod. Phys. 1998 223 287

[26] L. Glass, M.C. Mackey. From Clocks to Chaos. Princeton Univ. Press, Princeton, 1988.

[27] J.B.M. Goense, R. Ratnam Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance J. Comp. Physiol. A 2003 741 759

[28] C. Gray, W. Singer Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex Proc. Natl Acad. Sci. USA 1989 1698 1702

[29] N.B. Janson, A.G. Balanov, E. Schöll Delayed Feedback as a Means of Control of Noise-Induced Motion Phys. Rev. Lett. 2004

[30] A. V. Holden. Models of the Stochastic Activity of Neurons. Springer, Berlin, 1976.

[31] H. Hollander The projection from the visual cortex to the lateral geniculate body (LGB). An experimental study with silver impregnation methods in the cat Exp. Brain Res. 1990 219 235

[32] B. Hutcheon, Y. Yarom Resonance, oscillation and the intrinsic frequency preferences of neurons Trends Neurosci. 2000 216 222

[33] E.M. Izhikevich Neural Excitability, Spiking, and Bursting Int. J. Bif. Chaos 2000 1171 1266

[34] H. Kashiwadani, Y.F. Sasaki, N. Uchida, K. Mori Synchronized oscillatory discharges of mitral/tufted cells with different molecular receptive ranges in the rabbit olfactory bulb J. Neurophysiol. 1999 1786 1792

[35] Z.F. Kisvárday, K.A. Martin, T.F. Freund, Z. Maglóczky, D. Whitteridge, P. Somogyi Synaptic targets of HRP-filled layer III pyramidal cells in the cat striate cortex Exp. Brain. Res. 1986 541 552

[36] W.R. Klemm, C.J. Sherry Entropy as an index of the informational state of neurons Int. J. Neurosci. 1981 171 178

[37] H. Korn, P. Faure Is there chaos in the brain? I. Concepts of nonlinear dynamics and methods of investigation C. R. Acad. Sci. III 2003 773 793

[38] R. Krahe, J. Bastian, M.J. Chacron Temporal processing across multiple topographic maps in the electrosensory system J. Neurophysiol. 2008 852 867

[39] M.A. Lebedev, R.J. Nelson High-frequency vibratory sensitive neurons in monkey primary somatosensory cortex: entrained and nonentrained responses to vibration during the performance of vibratory-cued hand movements Exp. Brain Res. 1996 313 325

[40] B. Lindner, M.J. Chacron, A. Longtin Integrate-and-fire neurons with threshold noise: a tractable model of how interspike interval correlations affect neuronal signal transmission Phys. Rev. E 2005

[41] B. Lindner, B. Doiron, A. Longtin Theory of oscillatory firing induced by spatially correlated noise and delayed inhibitory feedback Phys. Rev. E 2005

[42] B. Lindner, D. Gangloff, A. Longtin, J.E. Lewis Broadband Coding with Dynamic Synapses J. Neurosci. 2004 2076 2087

[43] S.B. Lowen, M.C. Teich Auditory-nerve action potentials form a nonrenewal point process over short as well as long time scales J. Accoust. Soc. Am. 1992 803 806

[44] N. Lüdtke, M.E. Nelson Short-term synaptic plasticity can enhance weak signal detectability in nonrenewal spike trains Neural Comput. 2006 2879 2916

[45] K. Macleod, G. Laurent Distinct mechanisms for synchronization and temporal patterning of odor-encoding neural assemblies Science 1996 976 979

[46] Z.F. Mainen, T. J. Sejnowski Reliability of spike timing in neocortical neurons Science 1995 1503 1506

[47] L. Maler, E. Mugnaini Organization and function of feedback to the electrosensory lateral line lobe of gymnotiform fish, with emphasis on a searchlight mechanism J. Comp. Physiol. A 1993 667 670

[48] L. Maler, E. Mugnaini Correlating gamma-aminobutyric circuits and sensory function in the electrosensory lateral line lobe of a gymnotiform fish J. Comp. Neurol. 1994 224 252

[49] D.J. Mar, C.C. Chow, W. Gerstner, R.W. Adams, J.J. Collins Noise shaping in populations of coupled model neurons Proc. Natl. Acad. Sci. 1999 10450 10455

[50] G. Marsat, G.S. Pollack Effect of the temporal pattern of contralateral inhibition on sound localization cues J. Neurosci. 2005 6137 6144

[51] M. Mattia, P. Del Giudice Finite-size dynamics of inhibitory and excitatory interacting spiking neurons Phys. Rev. E 2004

[52] J.W. Middleton, M.J. Chacron, B. Lindner, A. Longtin Firing statistics of a neuron model driven by long-range correlated noise Phys. Rev. E 2003

[53] B.A. Mcguire, J.P. Hornung, C.D. Gilbert, T.N. Wiesel Patterns of synaptic input to layer 4 of cat striate cortex J. Neurosci. 1984 3021 3033

[54] F. Moss, L. Ward, W. Sannita Stochastic resonance and sensory information processing: a tutorial and review of application Clin. Neurophysiol. 2004 267 281

[55] M.E. Nelson, M.A. Maciver Prey capture in the weakly electric fish Apteronotus albifrons: sensory acquisition strategies and electrosensory consequences J. Exp. Biol. 1999 1195 1203

[56] S.R. Norsworthy, R. Schreier, G. C. Temes. Delta-Sigma Data Converters. IEEE Press, Piscataway, 1997.

[57] E.M. Ostapoff, D.K. Morest, S.J. Potashner Uptake and retrograde transport of [ 3H]GABA from the cochlear nucleus to the superior olive in the guinea pig J. Chem. Neuroanat. 1990 285 295

[58] C.L. Passaglia, J.B. Troy Information transmission rates of cat retinal ganglion cells J. Neurophysiol. 2004 1217 1229

[59] A. Pototsky, N. Janson Excitable systems with noise and delay, with applications to control: Renewal theory approach Phys. Rev. E 2008

[60] T. Prager, H.P. Lerch, L. Schimansky-Geier, E. Schöll Increase of coherence in excitable systems by delayed feedback J. Phys. A 2007 11045 11055

[61] R. Ratnam, M.E. Nelson Nonrenewal statistics of electrosensory afferent spike trains: implications for the detection of weak sensory signals J. Neurosci. 2000 6672 6683

[62] F. Rieke, D. Warland, R.R. de Ruyter van Steveninck, W. Bialek. Spikes: Exploring the Neural Code. MIT press, Cambridge, MA, 1996.

[63] H. Risken. The Fokker-Planck Equation. Springer, Berlin, 1996.

[64] J.C. Roddey, B. Girish, J.P. Miller Assessing the performance of neural encoding models in the presence of noise J. Comput. Neurosci. 2000 95 112

[65] S. Sadeghi, M.J. Chacron, M.C. Taylor, K.E. Cullen Neural variability, detection thresholds, and information transmission in the vestibular system J. Neurosci. 2007 771 781

[66] A.M. Sillito, H.E. Jones, G.L. Gerstein, D.C. West Feature-linked synchronization of thalamic relay cell firing induced by feedback from the visual cortex Nature 1994 479 482

[67] R. Shannon The mathematical theory of communication Bell. Syst. Tech. J. 1948 379 423

[68] S.M. Sherman Tonic and burst firing: dual modes of thalamocortical relay TINS 2001 122 126

[69] S.M. Sherman, R.W. Guillery The role of the thalamus in the flow of information to the cortex Philos. Trans. R. Soc. Lond. B Biol. Sci. 2002 1695 1708

[70] J. Shin Adaptation in spiking neurons based on the noise shaping neural coding hypothesis Neural Networks 2001 907 919

[71] N.G. Stocks Suprathreshold stochastic resonance in multilevel threshold systems Phys. Rev. Lett. 2000 2310 2313

[72] M. Stopfer, S. Bhagavan, B.H. Smith, G. Laurent Impaired odour discrimination on desynchronization of odour-encoding neural assemblies Nature 1997 70 74

[73] A.M. Yacomotti, M.C. Eguia, J. Aliaga, O.E. Martinez, G.B. Mindlin Interspike Time Distribution in Noise Driven Excitable Systems Phys. Rev. Lett. 1999 292 295

[74] M.K.S. Yeung, S.H. Strogatz Time Delay in the Kuramoto Model of Coupled Oscillators Phys. Rev. Lett. 1999 648 651

[75] K. Wiesenfeld, I. Satija Noise tolerance of frequency-locked dynamics Phys. Rev. B 1987 2483 2492