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Visual Cortical Prostheses: Bridging Technology, AI and Human Vision for the Future

This repository contains the source files for a research proposal on visual cortical prostheses, focusing on the integration of AI and virtual reality to optimize prosthetic vision. The proposal outlines the development and validation of AI algorithms aimed at enhancing phosphene patterns and real-time image processing.

Structure

  • Main Document: proposal_main.pdf - This PDF document contains the full research proposal, detailing the objectives, methodology, and phases of the study. It includes figures such as the graphical abstract and the Visual Prosthesis Simulation Framework.
  • Bibliography: references.bib - This BibTeX file includes all the citation information for the references used in the proposal.
  • Images: imgs directory - Contains images used in the proposal, including diagrams and schematics of the proposed research phases and experimental setups.

Building

To build the proposal document from LaTeX source files, ensure you have a LaTeX distribution installed. Compile the LaTeX files to produce a PDF of the proposal:

pdflatex proposal_main.tex
bibtex proposal_main
pdflatex proposal_main.tex
pdflatex proposal_main.tex

Contents Overview

Abstract

The proposal explores visual cortical prostheses, emphasizing the use of AI to enhance functionality and effectiveness. It aims to develop AI algorithms for optimizing phosphene patterns and real-time image processing, ultimately improving visual representations for users.

Key Sections

  1. Introduction

    • Background on visual cortical prostheses and their significance.
    • Research questions addressed in the proposal.

  2. Technological Advances

    • Advancements in biomaterials and electrode design.
    • Improved signal processing and integration techniques.
    • Software and algorithmic enhancements, including real-time data processing.

  3. AI Integration

    • The role of AI in optimizing stimulation patterns and image processing.
    • Overview of deep learning algorithms used in prosthetic vision.

  4. Research Phases

    • Phase 1: Development of initial AI algorithms for scene simplification and phosphene generation.
    • Phase 2: Advancement of AI models and neurophysiological studies to assess impact on visual perception.
    • Phase 3: Full-scale experiments and validation of AI systems for real-world application.

  5. Clinical Applications

    • Clinical trials and personalized prosthetic solutions.
    • Rehabilitation strategies leveraging neuroplasticity.

  6. Limitations and Challenges

    • Current drawbacks and areas for improvement in visual cortical prosthesis technology.

  7. Future Perspectives

    • Future research directions and potential advancements.
    • Ethical and societal implications of advanced neural interfacing technology.

Figures and Diagrams

  • Graphical Abstract: Figure illustrating the three phases of the research proposal on simulated phosphene vision for visual cortical prostheses.
  • Visual Prosthesis Simulation Framework: Detailed block diagram illustrating the framework for simulating and optimizing prosthetic vision using AI.
  • VR Obstacle Course Setup: Diagram showing the experimental setup for testing AI algorithms in dynamic environments.

Risk Assessment and Feasibility

The proposal addresses potential risks and challenges, including technical difficulties, variability in neurophysiological responses, and logistical complexities. Ethical considerations and the phased approach ensure the feasibility and reliability of the research.

Future Impact

The research aims to significantly enhance the user experience of visual prosthetics, potentially transforming the field by enabling accurate, dynamic visual representations through advanced AI solutions. It underscores the importance of interdisciplinary collaboration in advancing neuroprosthetic technology.

Call to Action

The proposal highlights the need for continued interdisciplinary research and collaboration between neuroscience, engineering, and AI to advance visual prosthesis technology and improve the quality of life for individuals with visual impairments.