Abstract

Differential activation of neuronal populations can improve the efficacy of clinical devices such as sensory or cortical prostheses. Improving stimulus specificity will facilitate targeted neuronal activation to convey biologically realistic percepts. In order to deliver more complex stimuli to a neuronal population, stimulus optimization techniques must be developed that will enable a single electrode to activate subpopulations of neurons. However, determining the stimulus needed to evoke targeted neuronal activity is challenging. To find the most selective waveform for a particular population, we apply an optimization-based search routine, Powell’s conjugate direction method, to systematically search the stimulus waveform space. This routine utilizes a 1-D sigmoid activation model and a 2-D strength–duration curve to measure neuronal activation throughout the stimulus waveform space. We implement our search routine in both an experimental study and a simulation study to characterize potential stimulus-evoked populations and the associated selective stimulus waveform spaces. We found that for a population of five neurons, seven distinct sub-populations could be activated. The stimulus waveform space and evoked neuronal activation curves vary with each new combination of neuronal culture and electrode array, resulting in a unique selectivity space. The method presented here can be used to efficiently uncover the selectivity space, focusing experiments in regions with the desired activation pattern.

Highlights

  • By developing new techniques to selectively activate particular neurons within a population, stimulation devices can better control their direct effects on activated tissue, and thereby improve stimulus efficacy

  • During deep brain stimulation (DBS), stimuli must be designed to target a baseline activity level such that the stimulus evokes sufficient activity to provide a therapeutic effect, while not excessively activating tissue leading to side effects [1,2,3,4]

  • We designed a closed-loop system [31] for optimizing stimulus pulse parameters based on a model of neuronal activation and an experimental goal

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Summary

Introduction

By developing new techniques to selectively activate particular neurons within a population, stimulation devices can better control their direct effects on activated tissue, and thereby improve stimulus efficacy. Selective activation to modulate neuronal activity is crucial for many science and clinical applications because selectivity allows stimuli to target a specific population. In applications such as deep brain stimulation (DBS), which is used in treating Parkinson’s disease and epilepsy, targeted stimulation can guide a stimulus to alleviate symptoms due to disease or injury. During DBS, stimuli must be designed to target a baseline activity level such that the stimulus evokes sufficient activity to provide a therapeutic effect, while not excessively activating tissue leading to side effects [1,2,3,4]. There is a therapeutic subspace in the strength–duration waveform

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