Decoding Neural Signals: Invasive BMI Review

TL;DR

This review comprehensively covers invasive brain machine interfaces, discussing their biological and engineering foundations, applications, challenges, and societal implications, highlighting their transformative potential in medicine and human-AI integration.

Contribution

It provides an in-depth synthesis of invasive BMI principles, applications, and future challenges, serving as a comprehensive guide for researchers and practitioners.

Findings

Analyzes biological and engineering principles of invasive BMI

Discusses potential applications and decoding methodologies

Highlights challenges and future opportunities in invasive BMI

Abstract

Human civilization has witnessed transformative technological milestones, from ancient fire lighting to the internet era. This chapter delves into the invasive brain machine interface (BMI), a pioneering technology poised to be a defining chapter in our progress. Beyond aiding medical conditions, invasive BMI promises far reaching impacts across diverse technologies and aspects of life. The exploration begins by unraveling the biological and engineering principles essential for BMI implementation. The chapter comprehensively analyzes potential applications, methodologies for detecting and decoding brain signals, and options for stimulating signals within the human brain. It concludes with a discussion on the multifaceted challenges and opportunities for the continued development of invasive BMI. This chapter not only provides a profound understanding of the foundational elements of invasive BMI but also serves as a guide through its applications, intricacies, and potential societal implications. Navigating neurobiology, engineering innovations, and the evolving landscape of human AI symbiosis, the chapter sheds light on the promises and hurdles that define the future of invasive BMI.