Intrinsic Oscillations in Neural Networks

A Linear Model for the [n]th-Order Loop

by Ronald J. MacGregor


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A preliminary study of the inherent dynamic properties of feedback pathways composed of millions of brain cells. The ultimate aim is to predict feelings and behavior from the anatomical arrangement of nerve cells. This report maps the characteristic modes of oscillation for cells in a single closed loop — a linearized generalization of the interconnection pattern found in the hippocampus of the mammalian brain. Any or all cells may be externally stimulated, may activate or be activated by any other, and may contribute output individually or jointly, all with time lags. The analysis suggests that to possess many different persisting modes, a loop should have many cells with high average interunit conduction time and a large mean connective coefficient. This may be expected in cell networks with long, thin, unmyelinated axons and strong interconnections, such as the "open system" networks of the lateral hypothalamus and the brain stem reticular formation.

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