Intrinsic Oscillations in Neural Networks: A Linear Model for Parallel, Single-Unit Pathways.
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Describes research which explores the characteristics of neuroelectric activity that reflect the intrinsic physical and configurational properties of neural systems. The report presents an analytical exploration of neuroelectric oscillation in configurations consisting of two parallel, single-unit pathways feeding back on a single primary cell. A linear model with time-lag is used to derive theoretical maps of the characteristic states of such systems. It is found that increasing the mean interconnection coefficient increases the endurance of the leading characteristic state, and increasing the average interunit conduction time increases the number of states that endure for relatively long times as compared with representative times of the system. A differential in conduction time between two parallel pathways essentially tends to (1) increase the number of characteristic states in a given frequency range; (2) slightly increase the endurance of a given characteristic state; and (3) somewhat relax the conditions for stability (except for the case of two parallel excitatory pathways). 29 pp. Bibliog.
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