Information Processing by Dynamical Interaction of Oscillatory Modes in Coupled Cortical Networks

We show how hierarchical networks may be constructed of interconnected oscillatory network modules developed previously as models of olfactory cortex, or caricatures of “patches”of neocortex. The architecture is such that the larger system is itself a special case of the type of network of the submodules, and can be analysed with the same tools used to design the subnetwork modules. A particular subnetwork is formed by a set of neural populations whose interconnections also contain higher order synapses. These synapses determine attractors for that subnetwork independent of other subnetworks. Each subnetwork module assumes only minimal coupling justified by known anatomy. An N node network can be shown to function as an associative memory for up to N/2 oscillatory and N/3 chaotic memory attractors.

[1]  J. Jack,et al.  Electric current flow in excitable cells , 1975 .

[2]  Donald O. Walter,et al.  Mass action in the nervous system , 1975 .

[3]  James L. McClelland,et al.  An interactive activation model of context effects in letter perception: I. An account of basic findings. , 1981 .

[4]  Arnold J. Mandell,et al.  Synergetics of the Brain , 1983 .

[5]  Ch. von der Malsburg,et al.  How are Nervous Structures Organized , 1983 .

[6]  P. Holmes,et al.  Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields , 1983, Applied Mathematical Sciences.

[7]  W. Freeman,et al.  Spatial patterns of visual cortical fast EEG during conditioned reflex in a rhesus monkey , 1987, Brain Research.

[8]  B. Baird,et al.  Relation of Olfactory EEG to Behavior: Spatial Analysis , 1987 .

[9]  Yong Yao,et al.  Central pattern generating and recognizing in olfactory bulb: A correlation learning rule , 1988, Neural Networks.

[10]  James L. McClelland,et al.  An interactive activation model of context effects in letter perception: part 1.: an account of basic findings , 1988 .

[11]  J. Bower,et al.  Olfactory cortex: model circuit for study of associative memory? , 1989, Trends in Neurosciences.

[12]  Jürgen Schmidhuber,et al.  A Local Learning Algorithm for Dynamic Feedforward and Recurrent Networks , 1989 .

[13]  B. Baird A bifurcation theory approach to vector field programming for periodic attractors , 1989, International 1989 Joint Conference on Neural Networks.

[14]  W. Singer,et al.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties , 1989, Nature.

[15]  Joachim M. Buhmann,et al.  Pattern Segmentation in Associative Memory , 1990, Neural Computation.

[16]  B. Baird A learning rule for CAM storage of continuous periodic sequences , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[17]  G. Hartmann,et al.  Parallel Processing in Neural Systems and Computers , 1990 .

[18]  Emergent computation , 1991 .

[19]  M. Usher,et al.  Parallel Activation of Memories in an Oscillatory Neural Network , 1991, Neural Computation.

[20]  Yong Yao,et al.  Applications of chaotic neurodynamics in pattern recognition , 1991 .

[21]  Michael I. Jordan Motor Learning and the Degrees of Freedom Problem , 2018, Attention and Performance XIII.