Characterizing and predicting cortical evoked responses to direct electrical stimulation of the human brain

Direct electrical stimulation of the human brain has been used to successfully treat several neurological disorders, but the precise effects of stimulation on neural activity are poorly understood. Characterizing the neural response to stimulation, however, could allow clinicians and researchers to more accurately predict neural responses, which could in turn lead to more effective stimulation for treatment and to fundamental knowledge regarding neural function.

Here we use a linear systems approach in order to characterize the response to electrical stimulation across cortical locations and then to predict the responses to novel inputs.

We use intracranial electrodes to directly stimulate the human brain with single pulses of stimulation using amplitudes drawn from a random distribution. Based on the evoked responses, we generate a simple model capturing the characteristic response to stimulation at each cortical site.

We find that the variable dynamics of the evoked response across cortical locations can be captured using the same simple architecture, a linear time-invariant system that operates separately on positive and negative input pulses of stimulation. We demonstrate that characterizing the response to stimulation using this simple and tractable model of evoked responses enables us to predict the responses to subsequent stimulation with single pulses with novel amplitudes, and the compound response to stimulation with multiple pulses.

Our data suggest that characterizing the response to stimulation in an approximately linear manner can provide a powerful and principled approach for predicting the response to direct electrical stimulation.