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

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.Ph.D

Targeted Stimulation Using Differences in Activation Probability across the Strength–Duration Space

Electrical stimulation is ubiquitous as a method for activating neuronal tissue, but there is still significant room for advancement in the ability of these electrical devices to implement smart stimulus waveform design to more selectively target populations of neurons. The capability of a device to encode more complicated and precise messages to a neuronal network greatly increases if the stimulus input space is broadened to include variable shaped waveforms and multiple stimulating electrodes. The relationship between a stimulating electrode and the activated population is unknown; a priori. For that reason, the population of excitable neurons must be characterized in real-time and for every combination of stimulating electrodes and neuronal populations. Our automated experimental system allows investigation into the stimulus-evoked neuronal response to a current pulse using dissociated neuronal cultures grown atop microelectrode arrays (MEAs). The studies presented here demonstrate that differential activation is achievable between two neurons using either multiple stimulating electrodes or variable waveform shapes. By changing the aspect ratio of a rectangular current pulse; the stimulus activated neurons in the strength–duration (SD) waveform space with differing probabilities. Additionally, in the case when two neuronal activation curves intersect each other in the SD space; one neuron can be selectively activated with short-pulse-width; high-current stimuli while the other can be selectively activated with long-pulse-width; low-current stimuli. Exploring the capabilities and limitations of electrical stimulation allows for improvements to the delivery of stimulus pulses to activate neuronal populations. Many state-of-the-art research and clinical stimulation solutions, including those using a single microelectrode, can benefit from waveform design methods to improve stimulus efficacy. These findings have even greater import into multi-electrode systems because spatially distributed electrodes further enhance accessibility to differential neuronal activation

Optimization of Stimulation Parameters for Targeted Activation of Multiple Neurons Using Closed-Loop Search Methods

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

Closed-Loop Characterization of Neuronal Activation Using Electrical Stimulation and Optical Imaging

We have developed a closed-loop, high-throughput system that applies electrical stimulation and optical recording to facilitate the rapid characterization of extracellular, stimulus-evoked neuronal activity. In our system, a microelectrode array delivers current pulses to a dissociated neuronal culture treated with a calcium-sensitive fluorescent dye; automated real-time image processing of high-speed digital video identifies the neuronal response; and an optimized search routine alters the applied stimulus to achieve a targeted response. Action potentials are detected by measuring the post-stimulus, calcium-sensitive fluorescence at the neuronal somata. The system controller performs directed searches within the strength–duration (SD) stimulus-parameter space to build probabilistic neuronal activation curves. This closed-loop system reduces the number of stimuli needed to estimate the activation curves when compared to the more commonly used open-loop approach. This reduction allows the closed-loop system to probe the stimulus regions of interest in the multi-parameter waveform space with increased resolution. A sigmoid model was fit to the stimulus-evoked activation data in both current (strength) and pulse width (duration) parameter slices through the waveform space. The two-dimensional analysis results in a set of probability isoclines corresponding to each neuron–electrode pair. An SD threshold model was then fit to the isocline data. We demonstrate that a closed-loop methodology applied to our imaging and micro-stimulation system enables the study of neuronal excitation across a large parameter space