Competition in the temporal domain among neural activities phase-locked to subthreshold oscillations

Abstract. In the presence of a subthreshold membrane oscillation, analog information may be encoded in the timing of spike generation phase-locked to the oscillation. With this spike timing neural code, a competitive network of inhibitory spiking neurons was shown to achieve a novel timing mechanism of neural activity selection: the neurons had higher probabilities of becoming winners if they were stimulated earlier in each oscillatory cycle. Here the timing mechanism and its robustness are studied both numerically and analytically, and the conditions to yield a given number of winners (the inhibitory neurons that remain active after the competition) are investigated. The analysis revealed that activity selection with a small number of winners is ensured for broad ranges of values of the parameters such as the strength and time constant of inhibition. In particular, the number of winners is almost unchanged for various timing differences between stimuli to different neurons. This implies that the timing mechanism is useful for such biological information processing as requires perception of a relatively small number of significant stimulus components.

[1]  F. Crick.  Function of the thalamic reticular complex: the searchlight hypothesis. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[2]  T. Bullock.  Integrative systems research on the brain: resurgence and new opportunities. , 1993, Annual review of neuroscience.

[3]  Simon J. Thorpe,et al.  Spike arrival times: A highly efficient coding scheme for neural networks , 1990 .

[4]  E. Adrian.  Olfactory reactions in the brain of the hedgehog , 1942, The Journal of physiology.

[5]  J E Lisman,et al.  Storage of 7 +/- 2 short-term memories in oscillatory subcycles , 1995, Science.

[6]  R. Cubelli.  A selective deficit for writing vowels in acquired dysgraphia , 1991, Nature.

[7]  Richard Granger,et al.  A cortical model of winner-take-all competition via lateral inhibition , 1992, Neural Networks.

[8]  Denis A. Baylor,et al.  Synaptic circuitry of the retina and olfactory bulb , 1993, Cell.

[9]  J. O’Keefe,et al.  Phase relationship between hippocampal place units and the EEG theta rhythm , 1993, Hippocampus.

[10]  O. Hikosaka.  Basal ganglia — possible role in motor coordination and learning , 1991, Current Opinion in Neurobiology.

[11]  Samuel Kaski,et al.  Winner-take-all networks for physiological models of competitive learning , 1994, Neural Networks.

[13]  Alan L. Yuille,et al.  A Winner-Take-All Mechanism Based on Presynaptic Inhibition Feedback , 1989, Neural Computation.

[14]  Lance M. Optican,et al.  Superior colliculus cell types and models of saccade generation , 1994, Current Opinion in Neurobiology.

[15]  Shigeru Tanaka,et al.  Theory of self-organization of cortical maps: Mathematical framework , 1990, Neural Networks.

[16]  B. McNaughton,et al.  Theta phase precession in hippocampal neuronal populations and the compression of temporal sequences , 1996, Hippocampus.

[17]  J. J. Hopfield,et al.  Pattern recognition computation using action potential timing for stimulus representation , 1995, Nature.

[18]  G. Buzsáki,et al.  Temporal structure in spatially organized neuronal ensembles: a role for interneuronal networks , 1995, Current Opinion in Neurobiology.

[19]  W. Freeman.  Spatial properties of an EEG event in the olfactory bulb and cortex. , 1978, Electroencephalography and clinical neurophysiology.

[20]  C. Koch,et al.  A brief history of time (constants). , 1996, Cerebral cortex.

[21]  Tomoki Fukai,et al.  A Simple Neural Network Exhibiting Selective Activation of Neuronal Ensembles: From Winner-Take-All to Winners-Share-All , 1997, Neural Computation.

[22]  J. E. Hind,et al.  Some discharge characteristics of single neurons in the inferior colliculus of the cat. II. Timing of the discharges and observations on binaural stimulation. , 1963, Journal of neurophysiology.

[23]  W. Gerstner,et al.  Time structure of the activity in neural network models. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[24]  Klaus Schulten,et al.  Models of Orientation and Ocular Dominance Columns in the Visual Cortex: A Critical Comparison , 1995, Neural Computation.

[25]  W Singer,et al.  Visual feature integration and the temporal correlation hypothesis. , 1995, Annual review of neuroscience.

[26]  Yaser S. Abu-Mostafa,et al.  On the K-Winners-Take-All Network , 1988, NIPS.

[27]  T Fukai.  Oscillations for rapid selection of neural activities based on spike timing , 1995, Neuroreport.

[28]  D. Sparks,et al.  Population coding of saccadic eye movements by neurons in the superior colliculus , 1988, Nature.