Decoding stimulation intensity from evoked ECoG activity

Cortical stimulation is used for therapeutic applications and research into neural processes. Cortical evoked responses to stimulation yield important information about neural connectivity and cortical excitability but are sensitive to changes in stimulation parameters. So far, the relationship between the stimulation parameters and the evoked responses has been reported only descriptively. In this paper we propose the use of regression analysis to train models that infer the stimulation intensity from the shape of the evoked activity. Using Support Vector Regression and electrocorticogram (ECoG) responses to electrical stimulation via epidural electrodes collected from two stroke patients, we show that the models can capture this relationship and generalize to intensities not used during the training process.