Neural Active Visual Prosthetics for Restoring Function

Periodic Reporting for period 1 - NeuraViPeR (Neural Active Visual Prosthetics for Restoring Function)

Période du rapport: 2020-09-01 au 2022-02-28

Over 300 million people world-wide are visually impaired (40 million are blind) and around 50% cannot benefit from existing and prospective treatments with gene and stem therapies, pharmaceuticals, and retinal prosthesis. Cortical neuroprostheses capable of evoking visual percepts through direct electrical stimulation of the occipital cortex are a promising approach for these patients. However, current microelectrode arrays have too few electrodes and suffer from insufficient longevity for long-term stimulation and recording of neuronal activity. Furthermore, these devices are only able to restore a limited vision, with very low spatial resolution. NeuraViPeR aims to develop an advanced technology for a functional long-life high-channel count brain stimulation and recording implant, and new algorithms that can optimize the restoration of visual experience and that can be run on a low-power portable platform. It also aims to lay ground-breaking foundation for a radically new paradigm which consists not only of constructing a neuroprosthesis with thousands of electrodes but also the creation of adaptive machine learning algorithms for a new brain-computer interfacing technology, which will remain safe and effective for decades.

In the project, we are developing innovative approaches for stimulation with high-electrode-count interfacing with the visual cortex. The work includes the creation of thin flexible probes that cause minimal tissue damage; new electrode coatings that will be stable even with long-term repeated electrical stimulation; and novel microchip methods for combining online channeling of the stimulation currents to many thousands of electrodes. It also combines stimulation with the monitoring of neuronal activity in higher cortical areas. We are also developing new deep learning algorithms that transform the camera footage into stimulation patterns for the cortex and that use feedback on recorded brain states and eye tracking to improve perception in a closed-loop approach. The software algorithms will be translated onto low-latency, power-efficient neuromorphic deep learning hardware, to create a neuroprosthesis system that is robust, and portable.

The overall objectives are to create breakthrough technology for a functional long-life high-channel count brain stimulation and recording implant, combined with powerful deep learning methods for bidirectional communication with the outside world, creating an intelligent visual cortical prosthesis for the restoration of sight.

In view of technology, we realized flexible, ultra-thin high-channel count neural probes to be interfaced with CMOS ASIC chips capable of recording neural activity and eliciting phosphenes by electrical stimulation. Different variants of electrode arrays with 64 or 128 channels were fabricated and characterized in detail in view of electrode impedance and charge injection capacity. A CMOS-compatible assembly process and a respective implantation strategy using silicon-based insertion shuttles was established.

We have designed, simulated and fabricated the first version of the recording and stimulation CMOS ASIC comprised of 8 stimulation units, 128 output stages and 64 recording channels. The stimulation units can flexibility be programmed in terms of pulse amplitude, frequency, duration and polarity. The recording channels provide low noise and low power amplification, filtering and digitization of multi-unit neural activity.

We investigated phosphene stimulation neural networks and benchmarked their performance in terms of power and latency on different embedded hardware platforms. In addition, model compression methods (e.g. weight pruning and bit quantization of parameters) are implemented on these networks and their impact on the network latency and task accuracy was investigated. We have started the development of a stimulation neuromorphic hardware accelerator that supports the required features of the stimulation neural network.

For validating the NeuraViPeR probe technology, mice were implanted with a flexible polyimide probes in the primary visual cortex (area V1). Microstimulation through the electrodes successfully evoked a behavioral response in mice trained on a go/no-go stimulation detection task. We extracted the minimal current necessary to elicit a visual percept by applying electrical currents between 1 and 25 µA. The average detection threshold was 8 µA, with one probe demonstrating a threshold as low as 2 µA. We were able to monitor the stimulation threshold over up to 13 months revealing a stable perceptual threshold. Currently we are focusing on the ex-vivo evaluation of probe biocompatibility.

On the software side we developed a Reinforcement Learning (RL) based network to optimize phosphene generation taking into account task-specific constraints. This framework is used to train novel deep networks for stimulus generation in an end-to-end fashion to optimize phosphene patterns and solve multi-stage navigation-based tasks in virtual environments. It was further used to evaluate established methods for stimulus generation. Algorithms were developed which maintain performance in the presence of perturbations in dynamical systems, using PID and recurrent neural networks as controllers.

We performed preliminary experiments to study visual percepts evoked with an intracortical microelectrode array inserted in the occipital cortex of a blind volunteer. We were able to induce reliable and stable visual perceptions enabling the identification of letters and object boundaries. The recruitment of new subjects currently studies potential blind volunteers with different pathologies and ages to investigate visual perceptions. The procedures for blind volunteer selection are improved considering possible neuroplastic changes after the onset of blindness. In addition, new protocols for defining and assessing visual function as well as a customizable platform for testing cortical visual prosthesis are being developed.

Results from the project have been disseminated through different sources and the website, participation at lectures at conferences and workshops. More details can be found at the project website.

Our preliminary results demonstrate the potential of intracortical microstimulation to restore functional vision in the blind. We have been able to perform simultaneous recordings and stimulation experiments over a 6-month period in the primary visual cortex of a blind subject after many years of complete blindness and found that both the recorded neural activity and the stimulation parameters remained stable over time. Furthermore, simultaneous stimulation via multiple electrodes evoked discriminable phosphene percepts, allowing the blind participant to identify letters and recognize object boundaries. These results have a significant scientific impact in the field and support the case for using penetrating microelectrodes. They also highlight a number of important unanswered questions that have to be solved before a cortical visual neuroprosthesis can be considered a viable clinical therapy or option. We expect that our results until the end of the project will allow us to advance the development of a technology that can enhance safety in navigation and provide greater confidence for individuals with profound blindness in many environments.

Concept of NeuraViPeR

Periodic Reporting for period 1 - NeuraViPeR (Neural Active Visual Prosthetics for Restoring Function)

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