Retinal Prosthesis Percept Prediction Model
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Solution Overview
Problem
Current visual prostheses lack the ability to accurately predict and control the spatial position and shape of percepts induced by retinal electrical stimulation, limiting their effectiveness in providing meaningful artificial vision to the visually impaired.
Innovation Solution
A model that quantitatively predicts the apparent spatial position and shape of percepts based on retinal anatomy, allowing for the adjustment of stimulation patterns to match desired images, using a lookup table to compensate for axonal stimulation and optimize electrode placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrical stimulation is applied to retinal cells to produce visual perception, then artificial vision is achieved, but the spatial position and shape of percepts cannot be accurately controlled
Solution Approach 1:
The patent employs feedback mechanisms where subjects report their perceived spatial position and shape of phosphenes induced by electrical stimulation. This feedback is used to adjust and refine the stimulation parameters, enabling accurate prediction and control of percept characteristics. The feedback loop allows iterative optimization of electrode stimulation to achieve desired spatial precision.
Solution Approach 2:
The patent systematically varies electrical stimulation parameters including pulse duration, amplitude, and frequency to control percept characteristics. By changing these parameters, the system achieves precise control over the spatial position and shape of phosphenes. The model identifies specific parameter combinations that produce desired percept outcomes, enabling accurate artificial vision.
2Measurement precision
If electrode array is placed on retinal surface to stimulate visual neurons, then neural activation is achieved, but the distance between electrodes and neurons cannot be minimized without compression
Solution Approach 1:
The patent applies different stimulation strategies to different regions of the retina based on local anatomical characteristics. The electrode array is configured with varying spacing and orientation to match the local axonal density and orientation in different retinal regions. This local adaptation allows minimal distance between electrodes and neurons while avoiding compression, optimizing both stimulation precision and mechanical stability.
Solution Approach 2:
The retinal surface is divided into multiple stimulation zones with distinct electrode configurations. Each zone is optimized for its specific anatomical features, allowing precise control of stimulation parameters locally. This segmentation enables the system to achieve optimal electrode-neuron distance in each region without causing compression, as each zone can be independently adjusted.
3Illumination intensity
If stimulation pulse duration is increased to make phosphenes brighter, then visual perception intensity is improved, but the spatial precision of percept location deteriorates
Solution Approach 1:
The patent uses periodic electrical pulse trains with specific frequencies and durations to stimulate retinal cells. By controlling the periodicity and duration of these pulses, the system achieves optimal balance between phosphene brightness and spatial precision. The periodic action allows the nervous system to process stimulation patterns that maintain both intensity and location accuracy.
Solution Approach 2:
The stimulation parameters including pulse duration and frequency are dynamically adjusted based on the desired percept characteristics and the specific retinal region being stimulated. This dynamic control allows the system to optimize the balance between brightness and spatial precision in real-time, adapting to different visual tasks and subject requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The model successfully predicts percept shapes and positions, enabling more effective stimulation patterns that improve the representation of desired images, expanding the field of view and enhancing the visual experience for blind individuals.
Implementation Method 1
Neural tissue can be artificially stimulated and activated by prosthetic devices that pass pulses of electrical current through electrodes on such a device. The passage of current causes changes in electrical potentials across visual neuronal membranes, which can initiate visual neuron action potentials
Data Source
AI summary
Here we present the first model that quantitatively predicts the apparent spatial position and shape of percepts elicited by retinal electrical stimulation in humans based on the known anatomy of the retina. This model successfully predicts both the shape of percepts elicited by single electrode stimulation and the shape and relative positions of percepts elicited by multiple electrode stimulation. Model fits to behavioral data show that sensitivity to electrical stimulation is not confined to the axon initial segment, but does fall off rapidly with the distance between stimulation and the initial segment. Using the model, it is possible to compensate, preferably with a look up table, to match percepts to a desired image.