Elsevier

Neural Networks

Volume 11, Issues 7–8, October–November 1998, Pages 1159-1174
Neural Networks

1998 Special Issue
A neural model of the saccade generator in the reticular formation

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Abstract

A neural model is developed of the neural circuitry in the reticular formation that is used to generate saccadic eye movements. The model simulates the behavior of identified cell types—such as long-lead burst neurons, short-lead excitatory and inhibitory burst neurons, omnipause neurons, and tonic neurons—under many experimental conditions. Simulated phenomena include: saccade staircases, duration and amplitude of cell discharges for saccades of variable amplitude, component stretching to achieve straight oblique saccades, saturation of saccade velocity after saturation of saccade amplitude in response to high stimulation frequencies, trade-offs between saccade velocity and duration to generate constant saccade amplitude, conservation of saccade amplitude in response to sufficiently brief stimulation of omnipause neurons, and high velocity smooth eye movements evoked by high levels of electrical stimulation of the superior colliculus. Previous saccade generator models have not explained this range of data. These models have also invoked mechanisms for which no neurophysiological evidence has been forthcoming, such as resetable integrators, perfect integrators, or target position movement commands. The present model utilizes only known reticular formation neurons. It suggests that a key part of the feedback loop within the saccade generator is realized by inhibitory feedback from short-lead to long-lead burst neurons, in response to excitatory feedforward signals from long-lead to short-lead burst neurons. When this property is combined with opponent interactions between agonist and antagonist muscle-controlling neurons, and motor error, or vector, inputs from the superior colliculus and other saccade-controlling brain regions, all of the above data can be explained. Taken together, these components generate a saccade reset cycle whereby activation of long-lead burst neurons inhibits omnipause neurons and thereby disinhibits short-lead excitatory burst neurons. The excitatory short-lead burst neurons can then respond to excitatory inputs from the long-lead burst neurons. Outputs from the excitatory short-lead burst neurons are integrated by the tonic cells while they also inhibit the long-lead burst neurons via inhibitory burst interneurons. When this inhibition is complete, the omnipause neurons are disinhibited. The omnipause neurons can then, once again, inhibit the short-lead burst neurons, whose inhibition of the long-lead burst neurons is thereby removed. The saccadic cycle can then begin again. In response to sustained electrical input, this cycle generates a staircase of identical saccades whose properties match the data much better than the staircases proposed by alternative models. A comparative analysis of the hypotheses and predictive capabilities of other saccade generator models is provided.

Keywords

Eye movements
Saccade generator
Reticular formation
Burst neurons
Saccade staircase
Neural network

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