Discussion on the Spike Train Recognition Mechanisms in Neural Circuits

The functions of neural system, such as learning, recognition and memory, are the emergences from the elementary dynamic mechanisms. To discuss how the dynamic mechanisms in the neurons and synapses work in the function of recognition, a dynamic neural circuit is designed. In the neural circuit, the information is expressed as the inter-spike intervals of the spike trains. The neural circuit with 5 neurons can recognize the inter-spike intervals in 5-15ms. A group of the neural circuits with 6 neurons recognize a spike train composed of three spikes. The dynamic neural mechanisms in the recognition processes are analyzed. The dynamic properties of the Hodgkin-Huxley neurons are the mechanism of the spike trains decomposition. Based on the dynamic synaptic transmission mechanisms, the synaptic delay times are diverse, which is the key mechanism in the inter-spike intervals recognition. The neural circuits in the group connect variously that every neuron can join in different circuits to recognize different inputs, which increases the information capacity of the neural circuit group.

[1]  Edward W. Large,et al.  Auditory Temporal Computation: Interval Selectivity Based on Post-Inhibitory Rebound , 2002, Journal of Computational Neuroscience.

[2]  L. Abbott,et al.  Synaptic computation , 2004, Nature.

[3]  T. Bliss,et al.  A synaptic model of memory: long-term potentiation in the hippocampus , 1993, Nature.

[4]  M M Merzenich,et al.  Temporal information transformed into a spatial code by a neural network with realistic properties , 1995, Science.

[5]  D. O. Hebb,et al.  The organization of behavior , 1988 .

[6]  Eugene M. Izhikevich,et al.  Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting , 2006 .

[7]  M. Paradiso,et al.  Neuroscience: Exploring the Brain , 1996 .

[8]  Barry W. Connors,et al.  Neuroscience: Exploring the brain, 3rd ed. , 2007 .

[9]  A. Hodgkin,et al.  A quantitative description of membrane current and its application to conduction and excitation in nerve , 1952, The Journal of physiology.

[10]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[11]  Dezhe Z Jin,et al.  Spiking neural network for recognizing spatiotemporal sequences of spikes. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Henry D I Abarbanel,et al.  Neural circuitry for recognizing interspike interval sequences. , 2006, Physical review letters.

[13]  Eugene M. Izhikevich,et al.  Polychronization: Computation with Spikes , 2006, Neural Computation.

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

[15]  A. Reyes,et al.  Synaptic mechanisms underlying auditory processing , 2006, Current Opinion in Neurobiology.

[16]  S. Strogatz Exploring complex networks , 2001, Nature.

[17]  J. Lisman Bursts as a unit of neural information: making unreliable synapses reliable , 1997, Trends in Neurosciences.

[18]  D V Buonomano,et al.  Decoding Temporal Information: A Model Based on Short-Term Synaptic Plasticity , 2000, The Journal of Neuroscience.