Local excitation solutions in one-dimensional neural fields by external input stimuli

Cortical neurons are massively connected with other cortical and subcortical cells, and they receive synaptic inputs from multiple sources. To explore the basis of how interconnected cortical cells are locally activated by such inputs, we theoretically analyze the local excitation patterns elicited by external input stimuli by using a one-dimensional neural field model. We examine the conditions for the existence and stability of the local excitation solutions under arbitrary time-invariant inputs and establish a graphic analysis method that can detect all steady local excitation solutions and examine their stability. We apply this method to a case where a pair of supra- and subthreshold stimuli are applied to nearby positions in the field. The results demonstrate that there can exist bistable local excitation solutions with different lengths and that the local excitation exhibits hysteretic behavior when the relative distance between the two stimuli is altered.

[1]  B. Ermentrout Neural networks as spatio-temporal pattern-forming systems , 1998 .

[2]  Boris S. Gutkin,et al.  Multiple Bumps in a Neuronal Model of Working Memory , 2002, SIAM J. Appl. Math..

[3]  Stephen Coombes,et al.  Waves, bumps, and patterns in neural field theories , 2005, Biological Cybernetics.

[4]  H. Sompolinsky,et al.  Theory of orientation tuning in visual cortex. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[5]  M. Giese Dynamic neural field theory for motion perception , 1998 .

[6]  S. Coombes,et al.  Bumps and rings in a two-dimensional neural field: splitting and rotational instabilities , 2007 .

[7]  Y. Yamane,et al.  Complex objects are represented in macaque inferotemporal cortex by the combination of feature columns , 2001, Nature Neuroscience.

[8]  S. Amari Dynamics of pattern formation in lateral-inhibition type neural fields , 1977, Biological Cybernetics.

[9]  J. Cowan,et al.  A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue , 1973, Kybernetik.

[10]  Bard Ermentrout,et al.  Spatially Structured Activity in Synaptically Coupled Neuronal Networks: I. Traveling Fronts and Pulses , 2001, SIAM J. Appl. Math..

[11]  Herrad Werner,et al.  Circular stationary solutions in two-dimensional neural fields , 2001, Biological Cybernetics.

[12]  Kazuyuki Aihara,et al.  Analyzing Global Dynamics of a Neural Field Model , 2004, Neural Processing Letters.

[13]  Michael Bestehorn,et al.  Activity dynamics in nonlocal interacting neural fields. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  B. Julesz,et al.  Extension of Panum's fusional area in binocularly stabilized vision. , 1967, Journal of the Optical Society of America.

[15]  Manabu Tanifuji,et al.  Representation of the spatial relationship among object parts by neurons in macaque inferotemporal cortex. , 2006, Journal of neurophysiology.

[16]  Thomas Wennekers,et al.  Pattern formation in intracortical neuronal fields , 2003, Network.

[17]  T. Sejnowski,et al.  Neurocomputational models of working memory , 2000, Nature Neuroscience.

[18]  S. Amari Dynamical stability of formation of cortical maps , 1988 .

[19]  P. Bressloff Traveling fronts and wave propagation failure in an inhomogeneous neural network , 2001 .

[20]  Haim Sompolinsky,et al.  Traveling Waves and the Processing of Weakly Tuned Inputs in a Cortical Network Module , 2004, Journal of Computational Neuroscience.

[21]  Xiao-Jing Wang Synaptic reverberation underlying mnemonic persistent activity , 2001, Trends in Neurosciences.

[22]  S. Amari,et al.  Dynamic Interactions in Neural Networks: Models and Data , 1988, Research Notes in Neural Computing.

[23]  C. Laing,et al.  Two-bump solutions of Amari-type models of neuronal pattern formation , 2003 .

[24]  Bard Ermentrout,et al.  Spatially Structured Activity in Synaptically Coupled Neuronal Networks: II. Lateral Inhibition and Standing Pulses , 2001, SIAM J. Appl. Math..

[25]  S. Tsujimoto,et al.  Properties of delay‐period neuronal activity in the primate prefrontal cortex during memory‐ and sensory‐guided saccade tasks , 2004, The European journal of neuroscience.

[26]  S. Funahashi,et al.  Activity of primate orbitofrontal and dorsolateral prefrontal neurons: task-related activity during an oculomotor delayed-response task , 2007, Experimental Brain Research.

[27]  Matthew L. Tullman,et al.  Lesions of the Tegmentomammillary Circuit in the Head Direction System Disrupt the Head Direction Signal in the Anterior Thalamus , 2007, The Journal of Neuroscience.

[28]  Xiao-Jing Wang,et al.  The dynamical stability of reverberatory neural circuits , 2002, Biological Cybernetics.

[29]  K. Zhang,et al.  Representation of spatial orientation by the intrinsic dynamics of the head-direction cell ensemble: a theory , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.