TY - JOUR T1 - A quantitative method for evaluating cortical responses to electrical stimulation JF - Journal of Neuroscience Methods Y1 - 2019 A1 - Lawrence J. Crowther A1 - Peter Brunner A1 - Christoph Kapeller A1 - Christoph Guger A1 - Kyousuke Kamada A1 - Marjorie E. Bunch A1 - Bridget K. Frawley A1 - Timothy M. Lynch A1 - Anthony L. Ritaccio A1 - Gerwin Schalk KW - Connectivity KW - Cortico-cortical evoked potentials KW - Electrical stimulation KW - Electrocorticography AB - Background Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations. New method We developed an automated and quantitative method called SIGNI (Stimulation-Induced Gamma-based Network Identification) to evaluate cortical population-level responses to electrical stimulation that minimizes the impact of electrical artifacts. We applied SIGNI to electrocorticographic (ECoG) data from eight human subjects who were implanted with a total of 978 subdural electrodes. Across the eight subjects, we delivered 92 trains of approximately 200 discrete electrical stimuli each (amplitude 4–15 mA) to a total of 64 electrode pairs. Results We verified SIGNI's efficacy by demonstrating a relationship between the magnitude of evoked cortical activity and stimulation amplitude, as well as between the latency of evoked cortical activity and the distance from the stimulated locations. Conclusions SIGNI reveals the timing and amplitude of cortical responses to electrical stimulation as well as the structural connectivity supporting these responses. With these properties, it enables exploration of new and important questions about the neurophysiology of cortical communication and may also be useful for pre-surgical planning. VL - 311 UR - http://www.sciencedirect.com/science/article/pii/S0165027018302796 ER -