Modeling the effects of sinusoidal stimulation and synaptic plasticity on linked neural oscillators.
The brain exhibits intrinsic oscillatory behavior, which plays a vital role in communication and information processing. Abnormalities in brain rhythms have been linked to numerous disorders, including depression and schizophrenia. Rhythmic electrical stimulation (e.g., transcranial magnetic stimulation and transcranial alternating current stimulation) has been used to modulate these oscillations and produce lasting changes in neural activity. In this computational study, we investigate the combined effects of sinusoidal stimulation and synaptic plasticity on model networks comprised of simple, tunable four-neuron oscillators. While not intended to model a specific brain circuit, this idealization was created to provide some intuition on how electrical modulation can induce plastic changes in the oscillatory state. Linked pairs of oscillators were stimulated with sinusoidal current, and their behavior was measured as a function of their intrinsic frequencies, inter-oscillator synaptic strengths, and stimulus strength and frequency. Under certain stimulus conditions, sinusoidal current can disrupt the network's natural firing patterns. Synaptic plasticity can induce weight imbalances that permanently change the characteristic firing behavior of the network. Grids of 100 oscillators with random frequencies were also subjected to a wide array of stimulus conditions. The characteristics of the post-stimulus network activity depend heavily on the stimulus frequency and amplitude as well as the initial strength of inter-oscillator connections. Synchronization arises at the network level from complex patterns of activity propagation, which are enhanced or disrupted by different stimuli. The findings may prove important to the design of novel neuromodulation treatments and techniques seeking to affect oscillatory activity in the brain.
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