Wireless Optogenetic Microsystems Accelerate Artificial Intelligence–Neuroscience Coevolution Through Embedded Closed-Loop System

Brain-inspired models in artificial intelligence (AI) originated from foundational insights in neuroscience. In recent years, this relationship has been moving toward a mutually reinforcing feedback loop. Currently, AI is significantly contributing to advancing our understanding of neuroscience. In particular, when combined with wireless optogenetics, AI enables experiments without physical constraints. Furthermore, AI-driven real-time analysis facilitates closed-loop control, allowing experimental setups across a diverse range of scenarios. And a deeper understanding of these neural networks may, in turn, contribute to future advances in AI. This work demonstrates the synergy between AI and miniaturized neural technology, particularly through wireless optogenetic systems designed for closed-loop neural control. We highlight how AI is now revolutionizing neuroscience experiments from decoding complex neural signals and quantifying behavior, to enabling closed-loop interventions and high-throughput phenotyping in freely moving subjects. Notably, AI-integrated wireless implants can monitor and modulate biological processes with unprecedented precision. We then recount how neuroscience insights derived from AI-integrated neuroscience experiments can potentially inspire the next generation of machine intelligence. Insights gained from these technologies loop back to inspire more efficient and robust AI systems. We discuss future directions in this positive feedback loop between AI and neuroscience, arguing that the coevolution of the two fields, grounded in technologies like wireless optogenetics and guided by reciprocal insight, will accelerate progress in both, while raising new challenges and opportunities for interdisciplinary collaboration.

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Publication Details

Journal
Micromachines
Published
2025-05-03
DOI
https://doi.org/10.3390/mi16050557
Citations
2
Primary Topic
Photoreceptor and optogenetics research
Type
article
Field-Weighted Citation Impact
1.82

Funders

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article

Wireless Optogenetic Microsystems Accelerate Artificial Intelligence–Neuroscience Coevolution Through Embedded Closed-Loop System

Sungcheol Hong
2 citations
Micromachines
Photoreceptor and optogenetics research
1.82
article

Wireless Optogenetic Microsystems Accelerate Artificial Intelligence–Neuroscience Coevolution Through Embedded Closed-Loop System

Sungcheol Hong
article en
2 citations

Abstract

Brain-inspired models in artificial intelligence (AI) originated from foundational insights in neuroscience. In recent years, this relationship has been moving toward a mutually reinforcing feedback loop. Currently, AI is significantly contributing to advancing our understanding of neuroscience. In particular, when combined with wireless optogenetics, AI enables experiments without physical constraints. Furthermore, AI-driven real-time analysis facilitates closed-loop control, allowing experimental setups across a diverse range of scenarios. And a deeper understanding of these neural networks may, in turn, contribute to future advances in AI. This work demonstrates the synergy between AI and miniaturized neural technology, particularly through wireless optogenetic systems designed for closed-loop neural control. We highlight how AI is now revolutionizing neuroscience experiments from decoding complex neural signals and quantifying behavior, to enabling closed-loop interventions and high-throughput phenotyping in freely moving subjects. Notably, AI-integrated wireless implants can monitor and modulate biological processes with unprecedented precision. We then recount how neuroscience insights derived from AI-integrated neuroscience experiments can potentially inspire the next generation of machine intelligence. Insights gained from these technologies loop back to inspire more efficient and robust AI systems. We discuss future directions in this positive feedback loop between AI and neuroscience, arguing that the coevolution of the two fields, grounded in technologies like wireless optogenetics and guided by reciprocal insight, will accelerate progress in both, while raising new challenges and opportunities for interdisciplinary collaboration.

MicromachinesVol. 16(5)
Hongik University (KR)
Hongik University
Openalex Percentile: Top 16%
Photoreceptor and optogenetics research
1.82
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Wireless Optogenetic Microsystems Accelerate Artificial Intelligence–Neuroscience Coevolution Through Embedded Closed-Loop System — Sungcheol Hong · Micromachines (2025) | TGRS Research Map | TGRS