Retinal prostheses aim to restore visual perception in patients blinded by photoreceptor degeneration, by stimulating surviving retinal ganglion cells (RGCs), causing them to send artificial visual signals to the brain. Present-day devices produce limited vision, in part due to indiscriminate and simultaneous activation of many RGCs of different types that normally signal asynchronously. To improve artificial vision, we propose a closed-loop, cellular-resolution device that automatically identifies the types and properties of nearby RGCs, calibrates its stimulation to produce a dictionary of achievable RGC activity patterns, and then uses this dictionary to optimize stimulation patterns based on the incoming visual image. To test this concept, we use a high-density multi-electrode array as a lab prototype, and deliver a rapid sequence of electrical stimuli from the dictionary, progressively assembling a visual image within the visual integration time of the brain. Greedily minimizing the error between the visual stimulus and a linear reconstruction (as a surrogate for perception) yields a realtime algorithm with an efficiency of 96% relative to optimum. This framework also provides insights for developing efficient hardware. For example, using only the most effective 50% of electrodes minimally affects performance, suggesting that an adaptive device configured using measured properties of the patient's retina may permit efficiency with accuracy.
A 43pJ/cycle non-volatile microcontroller with 4.7μs shutdown/wake-up integrating 2.3-bit/cell resistive RAM and resillence techniques.
Abstract-Enhanced performance in AlGaN/GaN Schottky barrier diodes (SBDs) is investigated using a nanowire hybrid tri-anode structure that integrates three-dimensional Schottky junctions with tri-gate transistors. The fabricated SBDs presented an increased output current density with improved linearity, above 1 A/mm at 5 V when normalized by effective anode width, over 3 orders of magnitude lower reverse leakage current and superior heat dissipation. The sidewall Schottky contacts reduced the turn-on voltage and eliminated the non-ideality caused by the AlGaN barrier. The large surface area of tri-gate architecture greatly enhanced heat dissipation and largely reduced the average temperature as well as thermal resistance of the integrated tri-gate transistors. The trench conduction near SiO2/GaN interface, formed under forward bias at both sidewalls and bottom of nanowire trenches, compensated part of the self-heating degradation and improved the output linearity of the device. Optimal design for the tri-anode structure, based on a model of critical filling factor, was proposed to surmount the issue of partial removal of two-dimensional electron gas (2DEG), unveiling the potential of nanostructured GaN devices to achieve comparable or even larger output current than counterpart planar devices.
Objective: Retinal prostheses must be able to activate cells in a selective way in order to restore high-fidelity vision. However, inadvertent activation of far-away retinal ganglion cells (RGCs) through electrical stimulation of axon bundles can produce irregular and poorly controlled percepts, limiting artificial vision. In this work, we aim to provide an algorithmic solution to the problem of detecting axon bundle activation with a bi-directional epiretinal prostheses. Methods: The algorithm utilizes electrical recordings to determine the stimulation current amplitudes above which axon bundle activation occurs. Bundle activation is defined as the axonal stimulation of RGCs with unknown soma and receptive field locations, typically beyond the electrode array. The method exploits spatiotemporal characteristics of electrically-evoked spikes to overcome the challenge of detecting small axonal spikes. Results: The algorithm was validated using large-scale, single-electrode and short pulse, ex vivo stimulation and recording experiments in macaque retina, by comparing algorithmically and manually identified bundle activation thresholds. For 88% of the electrodes analyzed, the threshold identified by the algorithm was within ±10% of the manually identified threshold, with a correlation coefficient of 0.95. Conclusion: This works presents a simple, accurate and efficient algorithm to detect axon bundle activation in epiretinal prostheses. Significance: The algorithm could be used in a closed-loop manner by a future epiretinal prosthesis to reduce poorly controlled visual percepts associated with bundle activation. Activation of distant cells via axonal stimulation will likely occur in other types of retinal implants and cortical implants, and the method may therefore be broadly applicable.
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