Toward Long-Term Communication With the Brain in the Blind by Intracortical Stimulation: Challenges and Future Prospects

Transparent and Conformal Microcoil Arrays for Spatially Selective Neuronal Activation

Micromagnetic stimulation (μMS) using small, implantable microcoils is a promising method for achieving neuronal activation with high spatial resolution and low toxicity. Herein, we report a microcoil array for localized activation of cortical neurons and retinal ganglion cells. We developed a computational model to relate the electric field gradient (activating function) to the geometry and arrangement of microcoils, and selected a design that produced an anisotropic region of activation <50 μm wide. The device was comprised of an SU-8/Cu/SU-8 tri-layer structure, which was flexible, transparent and conformal and featured four individually-addressable microcoils. Interfaced with cortex or retina explants from GCaMP6-expressing mice, we observed that individual neurons localized within 40 μm of a microcoil tip could be activated repeatedly and in a dose- (power-) dependent fashion. These results demonstrate the potential of μMS devices for brain-machine interfaces and could enable routes toward bioelectronic therapies including prosthetic vision devices.

Gaze-contingent processing improves mobility, scene recognition and visual search in simulated head-steered prosthetic vision

Objective.The enabling technology of visual prosthetics for the blind is making rapid progress. However, there are still uncertainties regarding the functional outcomes, which can depend on many design choices in the development. In visual prostheses with a head-mounted camera, a particularly challenging question is how to deal with the gaze-locked visual percept associated with spatial updating conflicts in the brain. The current study investigates a recently proposed compensation strategy based on gaze-contingent image processing with eye-tracking. Gaze-contingent processing is expected to reinforce natural-like visual scanning and reestablished spatial updating based on eye movements. The beneficial effects remain to be investigated for daily life activities in complex visual environments.Approach.The current study evaluates the benefits of gaze-contingent processing versus gaze-locked and gaze-ignored simulations in the context of mobility, scene recognition and visual search, using a virtual reality simulated prosthetic vision paradigm with sighted subjects.Main results.Compared to gaze-locked vision, gaze-contingent processing was consistently found to improve the speed in all experimental tasks, as well as the subjective quality of vision. Similar or further improvements were found in a control condition that ignores gaze-dependent effects, a simulation that is unattainable in the clinical reality.Significance.Our results suggest that gaze-locked vision and spatial updating conflicts can be debilitating for complex visually-guided activities of daily living such as mobility and orientation. Therefore, for prospective users of head-steered prostheses with an unimpaired oculomotor system, the inclusion of a compensatory eye-tracking system is strongly endorsed.

Visual Neuroprosthesis - Stimulation of Visual Cortical Centers in The Brain. Design of Non-Invasive Transcranial Stimulation of Functional Neurons

PURPOSE

The purpose of the article is to present the history and current status of visual cortical neuroprostheses, and to present a new method of stimulating intact visual cortex cells.

METHODS

This paper contains an overview of the history and current status of visual cortex stimulation in severe visual impairment, but also highlights its shortcomings. These include mainly the stimulation of currently damaged cortical cells over a small area and, from a morphological point of view, possible damage to the stimulated neurons by the electrodes and their encapsulation by gliotic tissue.

RESULTS

The paper also presents a proposal for a new technology of image processing and its transformation into a form of non-invasive transcranial stimulation of undamaged parts of the brain, which is protected by a national and international patent.

CONCLUSION

The paper presents a comprehensive review of the current options for compensating for lost vision at the level of the cerebral cortex and a proposal for a new non-invasive method of stimulating the functional neurons of the visual cortex.

An in-silico framework for modeling optimal control of neural systems

Introduction

Brain-machine interfaces have reached an unprecedented capacity to measure and drive activity in the brain, allowing restoration of impaired sensory, cognitive or motor function. Classical control theory is pushed to its limit when aiming to design control laws that are suitable for large-scale, complex neural systems. This work proposes a scalable, data-driven, unified approach to study brain-machine-environment interaction using established tools from dynamical systems, optimal control theory, and deep learning.

Methods

To unify the methodology, we define the environment, neural system, and prosthesis in terms of differential equations with learnable parameters, which effectively reduce to recurrent neural networks in the discrete-time case. Drawing on tools from optimal control, we describe three ways to train the system: Direct optimization of an objective function, oracle-based learning, and reinforcement learning. These approaches are adapted to different assumptions about knowledge of system equations, linearity, differentiability, and observability.

Results

We apply the proposed framework to train an in-silico neural system to perform tasks in a linear and a nonlinear environment, namely particle stabilization and pole balancing. After training, this model is perturbed to simulate impairment of sensor and motor function. We show how a prosthetic controller can be trained to restore the behavior of the neural system under increasing levels of perturbation.

Discussion

We expect that the proposed framework will enable rapid and flexible synthesis of control algorithms for neural prostheses that reduce the need for in-vivo testing. We further highlight implications for sparse placement of prosthetic sensor and actuator components.

Toward a personalized closed-loop stimulation of the visual cortex: Advances and challenges

Current cortical visual prosthesis approaches are primarily unidirectional and do not consider the feed-back circuits that exist in just about every part of the nervous system. Herein, we provide a brief overview of some recent developments for better controlling brain stimulation and present preliminary human data indicating that closed-loop strategies could considerably enhance the effectiveness, safety, and long-term stability of visual cortex stimulation. We propose that the development of improved closed-loop strategies may help to enhance our capacity to communicate with the brain.

Restored vision-augmented vision: arguments for a cybernetic vision

In this paper, we present some thoughts about the recent developments, made possible by technological advances and miniaturisation of connected visual prostheses, linked to the visual system, operating at different level of this one, on the retina as well as in the visual cortex. While these objects represent a great hope for people with impaired vision to recover partial vision, we show how this technology could also act on the functional vision of well sighted persons to improve or increase their visual performance. In addition to the impact on our cognitive and attentional mechanisms, such an operation when it originates outside the natural real visual field (e.g. cybernetics) raises a number of questions about the development and use of such implants or prostheses in the future.

Implications of Neural Plasticity in Retinal Prosthesis

Retinal degenerative diseases such as retinitis pigmentosa cause a progressive loss of photoreceptors that eventually prevents the affected person from perceiving visual sensations. The absence of a visual input produces a neural rewiring cascade that propagates along the visual system. This remodeling occurs first within the retina. Then, subsequent neuroplastic changes take place at higher visual centers in the brain, produced by either the abnormal neural encoding of the visual inputs delivered by the diseased retina or as the result of an adaptation to visual deprivation. While retinal implants can activate the surviving retinal neurons by delivering electric current, the unselective activation patterns of the different neural populations that exist in the retinal layers differ substantially from those in physiologic vision. Therefore, artificially induced neural patterns are being delivered to a brain that has already undergone important neural reconnections. Whether or not the modulation of this neural rewiring can improve the performance for retinal prostheses remains a critical question whose answer may be the enabler of improved functional artificial vision and more personalized neurorehabilitation strategies.

Energy efficiency of pulse shaping in electrical stimulation: the interdependence of biophysical effects and circuit design losses

Power efficiency in electrical stimulator circuits is crucial for developing large-scale multichannel applications like bidirectional brain-computer interfaces and neuroprosthetic devices. Many state-of-the-art papers have suggested that some non-rectangular pulse shapes are more energy-efficient for exciting neural excitation than the conventional rectangular shape. However, additional losses in the stimulator circuit, which arise from employing such pulses, were not considered. In this work, we analyze the total energy efficiency of a stimulation system featuring non-rectangular stimuli, taking into account the losses in the stimulator circuit. To this end, activation current thresholds for different pulse shapes and durations in cortical neurons are modeled, and the energy required to generate the pulses from a constant voltage supply is calculated. The proposed calculation reveals an energy increase of 14-51% for non-rectangular pulses compared to the conventional rectangular stimuli, instead of the decrease claimed in previous literature. This result indicates that a rectangular stimulation pulse is more power-efficient than the tested alternative shapes in large-scale multichannel electrical stimulation systems.

Time stability and connectivity analysis with an intracortical 96-channel microelectrode array inserted in human visual cortex

OBJECTIVE

Microstimulation via electrodes that penetrate the visual cortex creates visual perceptions called phosphenes. Besides providing electrical stimulation to induce perceptions, each electrode can be used to record the brain signals from the cortex region under the electrode which contains brain state information. Since the future visual prosthesis interfaces will be implanted chronically in the visual cortex of blind people, it is important to study the long-term stability of the signals acquired from the electrodes. Here, we studied the changes over time and the repercussions of electrical stimulation on the brain signals acquired with an intracortical 96-channel microelectrode array implanted in the visual cortex of a blind volunteer for 6 months.

APPROACH

We used variance, power spectral density, correlation, coherence, and phase coherence to study the brain signals acquired in resting condition before and after the administration of electrical stimulation during a period of 6 months.

MAIN RESULTS

Variance and power spectral density up to 750 Hz do not show any significant trend in the 6 months, but correlation coherence and phase coherence significantly decrease over the implantation time and increase after electrical stimulation.

SIGNIFICANCE

The stability of variance and power spectral density in time is important for long-term clinical applications based on the intracortical signals collected by the electrodes. The decreasing trends of correlation, coherence, and phase coherence might be related to plasticity changes in the visual cortex due to electrical microstimulation.

End-to-end optimization of prosthetic vision

Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most useful features from a visual scene is a nontrivial task and optimal preprocessing choices strongly depend on the context. Despite rapid advancements in deep learning, research currently faces a difficult challenge in finding a general and automated preprocessing strategy that can be tailored to specific tasks or user requirements. In this paper, we present a novel deep learning approach that explicitly addresses this issue by optimizing the entire process of phosphene generation in an end-to-end fashion. The proposed model is based on a deep auto-encoder architecture and includes a highly adjustable simulation module of prosthetic vision. In computational validation experiments, we show that such an approach is able to automatically find a task-specific stimulation protocol. The results of these proof-of-principle experiments illustrate the potential of end-to-end optimization for prosthetic vision. The presented approach is highly modular and our approach could be extended to automated dynamic optimization of prosthetic vision for everyday tasks, given any specific constraints, accommodating individual requirements of the end-user.

Real-world indoor mobility with simulated prosthetic vision: The benefits and feasibility of contour-based scene simplification at different phosphene resolutions

Neuroprosthetic implants are a promising technology for restoring some form of vision in people with visual impairments via electrical neurostimulation in the visual pathway. Although an artificially generated prosthetic percept is relatively limited compared with normal vision, it may provide some elementary perception of the surroundings, re-enabling daily living functionality. For mobility in particular, various studies have investigated the benefits of visual neuroprosthetics in a simulated prosthetic vision paradigm with varying outcomes. The previous literature suggests that scene simplification via image processing, and particularly contour extraction, may potentially improve the mobility performance in a virtual environment. In the current simulation study with sighted participants, we explore both the theoretically attainable benefits of strict scene simplification in an indoor environment by controlling the environmental complexity, as well as the practically achieved improvement with a deep learning-based surface boundary detection implementation compared with traditional edge detection. A simulated electrode resolution of 26 × 26 was found to provide sufficient information for mobility in a simple environment. Our results suggest that, for a lower number of implanted electrodes, the removal of background textures and within-surface gradients may be beneficial in theory. However, the deep learning-based implementation for surface boundary detection did not improve mobility performance in the current study. Furthermore, our findings indicate that, for a greater number of electrodes, the removal of within-surface gradients and background textures may deteriorate, rather than improve, mobility. Therefore, finding a balanced amount of scene simplification requires a careful tradeoff between informativity and interpretability that may depend on the number of implanted electrodes.

Visual percepts evoked with an Intracortical 96-channel microelectrode array inserted in human occipital cortex

BACKGROUND

A long-held dream of scientists is to transfer information directly to the visual cortex of blind individuals, thereby restoring a rudimentary form of sight. However, no clinically available cortical visual prosthesis yet exists.

METHODS

We implanted an intracortical microelectrode array consisting of 96 electrodes in the visual cortex of a 57-year-old person with complete blindness for a six- month period. We measured thresholds and the characteristics of the visual percepts elicited by intracortical microstimulation.

RESULTS

Implantation and subsequent explantation of intracortical microelectrodes were carried out without complications. The mean stimulation threshold for single electrodes was 66.8 ± 36.5 μA. We consistently obtained high-quality recordings from visually deprived neurons and the stimulation parameters remained stable over time. Simultaneous stimulation via multiple electrodes were associated with a significant reduction in thresholds (p<0.001, ANOVA test) and evoked discriminable phosphene percepts, allowing the blind participant to identify some letters and recognize object boundaries. Furthermore, we observed a learning process that helped the subject to recognize complex patterns over time.

CONCLUSIONS

Our results demonstrate the safety and efficacy of chronic intracortical microstimulation via a large number of electrodes in human visual cortex, showing its high potential for restoring functional vision in the blind.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT02983370.

FUNDING

Funding was provided by grant RTI2018-098969-B-100 from the Spanish Ministerio de Ciencia Innovación y Universidades, by grant PROMETEO/2019/119 from the Generalitat Valenciana (Spain), by the Bidons Egara Research Chair of the University Miguel Hernández (Spain) and by the John Moran Eye Center of the University of Utah (US).

Visual cortical prosthesis: an electrical perspective

The electrical stimulation of the visual cortices has the potential to restore vision to blind individuals. Until now, the results of visual cortical prosthetics have been limited as no prosthesis has restored a full working vision but the field has shown a renewed interest these last years, thanks to wireless and technological advances. However, several scientific and technical challenges are still open to achieve the therapeutic benefit expected by these new devices. One of the main challenges is the electrical stimulation of the brain itself. In this review, we analyse the results in electrode-based visual cortical prosthetics from the electrical point of view. We first describe what is known about the electrode-tissue interface and safety of electrical stimulation. Then we focus on the psychophysics of prosthetic vision and the state-of-the-art on the interplay between the electrical stimulation of the visual cortex and the phosphene perception. Lastly, we discuss the challenges and perspectives of visual cortex electrical stimulation and electrode array design to develop the new generation implantable cortical visual prostheses.