Biophysical Mechanisms of Cortical MicroStimulation

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Direct local electrical stimulation (DLES) is an increasingly important therapeutic tool for treating brain disorders such as Parkinson’s, epilepsy, and OCD. There is considerable disagreement, however, as to how neural stimulation, especially at the scale of neurons, affects human brain function. This lack of understanding hampers the design and implementation of more effective stimulation approaches, particularly in the cortex. To deliver on the precise, inclusive, and effective therapeutic promise of DLES, a more mechanistic understanding of the biophysics of cortical stimulation is required. This project combines single-cell electrophysiology in both human and mouse cortex, both ex-vivo and in vivo with pharmacology, optical physiology, and sophisticated computational modeling to identify the mechanisms underlying electrical stimulation. In a truly translational approach, these multiple research angles will allow us to test in-depth mechanistic hypotheses in the mouse and whether these results hold true in the human. We will test the hypothesis that DLES induces a dynamic sequence of excitatory (E) neuron output countered by subsequent inhibitory (I) neuron. We will evaluate stimulation intensity, frequency, phase, distance, and species as key parameters in modulating the timing and strength of this E-I dynamic sequence. These data on neuronal dynamics will be leveraged into actionable knowledge through an integrate-and-fire based recurrent neuronal network model which we will use to predict cortical responses to novel stimuli and develop specific stimulation patterns to evoke desired neural outputs. Specifically, we will identify the biophysical mechanisms by which DLES recruits different neuronal populations in acute brain slices of human and mouse cortex using whole-cell electrophysiology and pharmacology (Aim 1). We will then characterize neuron and population responses to DLES in vivo, using Neuropixels probes in awake human and mouse cortex, complemented by optical recordings in the awake mouse (Aim 2). This extensive and detailed data set will be used to refine and validate a trainable neural network model we have developed to assess stimulation effects on E and I cell types (Aim 3). The model will be the testing ground to develop specific patterns of stimulation based on desired outputs such as targeting either E or I cells. The model will also be used to test novel input stimuli including amplitude and frequency ramps, chirps, and step functions to predict neural responses. Testing these model-predicted outputs, or responses, will then be carried out through further ex- and in-vivo physiology. Not only will we connect dynamics of a primary model system to activity in the human brain, but this work will also provide a unique route toward predictable modulation of activity in individual neurons and local circuits to design tailored neuromodulation therapies. Our multi-scale analyses of the neural mechanisms of electrical stimulation will catalyze novel, targeted, and mechanistically driven therapeutic approaches that could revolutionize stimulation-based treatment for memory disorders, depression, stroke recovery, and a host of other neuropsychiatric ailments.