Neural circuitry for recognizing interspike interval sequences.

Sensory systems present environmental information to central nervous system as sequences of action potentials or spikes. How do animals recognize these sequences carrying information about their world? We present a biologically inspired neural circuit designed to enable spike pattern recognition. This circuit is capable of training itself on a given interspike interval (ISI) sequence and is then able to respond to presentations of the same sequence. The essential ingredients of the recognition circuit are (a) a tunable time delay circuit, (b) a spike selection unit, and (c) a tuning mechanism using spike timing dependent plasticity of inhibitory synapses. We have investigated this circuit using Hodgkin-Huxley neuron models connected by realistic excitatory and inhibitory synapses. It is robust in the presence of noise represented as jitter in the spike times of the ISI sequence.

[1]  R. Mooney,et al.  Synaptic Transformations Underlying Highly Selective Auditory Representations of Learned Birdsong , 2004, The Journal of Neuroscience.

[2]  Bard Ermentrout,et al.  Type I Membranes, Phase Resetting Curves, and Synchrony , 1996, Neural Computation.

[3]  Allison J Doupe,et al.  Propagation of Correlated Activity through Multiple Stages of a Neural Circuit , 2003, The Journal of Neuroscience.

[4]  Kenji Kawano,et al.  Global and fine information coded by single neurons in the temporal visual cortex , 1999, Nature.

[5]  T. Albright,et al.  Efficient Discrimination of Temporal Patterns by Motion-Sensitive Neurons in Primate Visual Cortex , 1998, Neuron.

[6]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[7]  D. Buonomano,et al.  The neural basis of temporal processing. , 2004, Annual review of neuroscience.

[8]  D Margoliash,et al.  Preference for autogenous song by auditory neurons in a song system nucleus of the white-crowned sparrow , 1986, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[9]  宁北芳,et al.  疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A , 2005 .

[10]  Daniel B. Forger,et al.  A detailed predictive model of the mammalian circadian clock , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[11]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[12]  R. Morris.  Foundations of cellular neurophysiology , 1996 .

[13]  Y. Dan,et al.  Spike-timing-dependent synaptic modification induced by natural spike trains , 2002, Nature.

[14]  R. Ivry.  The representation of temporal information in perception and motor control , 1996, Current Opinion in Neurobiology.

[15]  R. Kempter,et al.  Hebbian learning and spiking neurons , 1999 .

[16]  Patrick D. Roberts,et al.  Computational Consequences of Temporally Asymmetric Learning Rules: I. Differential Hebbian Learning , 1999, Journal of Computational Neuroscience.

[17]  Sachin S Talathi,et al.  Dynamical model of birdsong maintenance and control. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  K. Abbink,et al.  24 , 1871, You Can Cross the Massacre on Foot.