Basis profile curve identification to understand electrical stimulation effects in human brain networks

Abstract

Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine characteristic spatiotemporal structure in these response shapes, summarized by a set of unique “basis profile curves” (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome.Author summaryWe present a new machine learning framework to probe how brain regions interact using single-pulse electrical stimulation. Unlike previous studies, this approach does not assume a form for how one brain area will respond to stimulation in another area, but rather discovers the shape of the response in time from the data. We call the set of characteristic discovered response shapes “basis profile curves” (BPCs), and show how these can be mapped back onto the brain quantitatively. An illustrative example is included from one of our human patients to characterize inputs to the parahippocampal gyrus. A code package is downloadable from https://purl.stanford.edu/rc201dv0636 so the reader may explore the technique for own data, or study sample data provided to reproduce the illustrative case presented in the manuscript.

Impact of stimulation location relative to grey and white matter on single pulse electrical stimulation responses in the human brain

“…Attempts to better understand the mechanisms underlying DES neuromodulation are complicated by near infinite parameter possibilities as well as numerous hypotheses for why certain stimulation parameters are effective while others are not [2,6,8,13,[34][35][36][37][38]. Adding to this challenge is that there are only a handful of studies that systematically examine the physiological effects of invasive brain stimulation in humans [24,28,[39][40][41][42][43][44][45][46]. Not fully understanding the input-output relationships between DES and human cortical responses makes it difficult to predict which parameters, if adjusted properly, will optimize therapeutic effects.…”