Closed-loop optimization of extracellular electrical stimulation for targeted neuronal activation

Selective stimulation;Extracellular electrical stimulation;MEA;Microelectrode array;Optical recording;Stochastic response;Probabilistic activation

Kuykendal, Michelle Lea ; DeWeerth, Stephen P. Electrical and Computer Engineering Grover, Martha A. Potter, Steve M. McIntyre, Cameron C. Stanley, Garrett B. ; DeWeerth, Stephen P.

University:Georgia Institute of Technology

Department:Electrical and Computer Engineering

关键词: Selective stimulation;    Extracellular electrical stimulation;    MEA;    Microelectrode array;    Optical recording;    Stochastic response;    Probabilistic activation;   

Others  :  https://smartech.gatech.edu/bitstream/1853/52303/1/KUYKENDAL-DISSERTATION-2014.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

We have developed a high-throughput system of closed-loop electrical stimulation and optical recording that facilitates the rapid characterization of extracellular stimulus-evoked neural activity. The ability to selectively stimulate a neuron is a defining characteristic of next-generation neural prostheses. Greater stimulus control and differential activation of specific neuronal populations allows for prostheses that better mimic their biological counterparts.In our system, we deliver square current pulses using a microelectrode array; automated real-time image processing of high-speed digital video identifies the neuronal response; and a feedback controller alters the applied stimulus to achieve a targeted response. The system controller performs directed searches within the strength-duration (SD) stimulus parameter space to build probabilistic neuronal activation curves. An important feature of this closed-loop system is a reduction in the number of stimuli needed to derive the activation curves when compared to the more commonly used open-loop system: this allows the closed-loop system to spend more time probing stimulus regions of interest in the multi-parameter waveform space, facilitating high resolution analysis.The stimulus-evoked activation data were well-fit to a sigmoid model in both the stimulus strength (current) and duration (pulse width) slices through the waveform space. The 2-D analysis produced a set of probability isoclines corresponding to each neuron-electrode pairing, which were fit to the SD threshold model described by Lapique (1907). We show that stimulus selectivity within a given neuron pair is possible in the one-parameter search space by using multiple stimulation electrodes. Additionally, by applying simultaneous stimuli to adjacent electrodes, the interaction between stimuli alters the neuronal activation threshold. The interaction between simultaneous multi-electrode multi-parameter stimulus waveforms creates an opportunity for increased stimulus selectivity within a population.We demonstrated that closed-loop imaging and micro-stimulation technology enable the study of neuronal excitation across a large parameter space, which is requisite for controlling neuronal activation in next generation clinical solutions.