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.

Willfully controlling the focus of an extracellular stimulus remains a significant challenge in the development of neural prosthetics and therapeutic devices. In part, this challenge is due to the vast set of complex interactions between the electric fields induced by the microelectrodes and the complex morphologies and dynamics of the neural tissue. Overcoming such issues to produce methodologies for targeted neural stimulation requires a system that is capable of (1) delivering precise, localized stimuli a function of the stimulating electrodes and (2) recording the locations and magnitudes of the resulting evoked responses a function of the cell geometry and membrane dynamics. In order to improve stimulus delivery, we developed microfabrication technologies that could specify the electrode geometry and electrical properties. Specifically, we developed a closed-loop electroplating strategy to monitor and control the morphology of surface coatings during deposition, and we implemented pulse-plating techniques as a means to produce robust, resilient microelectrodes that could withstand rigorous handling and harsh environments. In order to evaluate the responses evoked by these stimulating electrodes, we developed microscopy techniques and signal processing algorithms that could automatically identify and evaluate the electrical response of each individual neuron. Finally, by applying this simultaneous stimulation and optical recording system to the study of dissociated cortical cultures in multielectode arrays, we could evaluate the efficacy of excitatory and inhibitory waveforms. Although we found that the proximity of the electrode is a poor predictor of individual neural excitation thresholds, we have shown that it is possible to use inhibitory waveforms to globally reduce excitability in the vicinity of the electrode. Thus, the developed system was able to provide very high resolution insight into the complex set of interactions between the stimulating electrodes and populations of individual neurons.

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