paper-with-me

홈 › Papers

Closed-loop experiments and brain machine interfaces with multiphoton microscopy

2023-08-31 · Riichiro Hira

In the field of neuroscience, the importance of constructing closed-loop experimental systems has increased in conjunction with technological advances in measuring and controlling neural activity in live animals. This paper provides an overview of recent technological advances in the field, focusing on closed-loop experimental systems where multiphoton microscopy (the only method capable of recording and controlling targeted population activity of neurons at a single-cell resolution in vivo) works through real-time feedback. Specifically, we present some examples of brain machine interfaces (BMIs) using in vivo two-photon calcium imaging and discuss applications of two-photon optogenetic stimulation and adaptive optics to real-time BMIs. We also consider conditions for realizing future optical BMIs at the synaptic level, and their possible roles in understanding the computational principles of the brain.

📄 PDF Abstract BibTeX arXiv:2309.00170

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Closed-Loop Neural Interfaces with Embedded Machine Learning

2020-10-15 · Bingzhao Zhu, Uisub Shin, Mahsa Shoaran

Neural interfaces capable of multi-site electrical recording, on-site signal classification, and closed-loop therapy are critical for the diagnosis and treatment of neurological disorders. However, deploying machine lear…

BIG-bench Machine LearningGeneral ClassificationModel Compression

MindPilot: Closed-loop Visual Stimulation Optimization for Brain Modulation with EEG-guided Diffusion

2026-02-11 · Dongyang Li, Kunpeng Xie, Mingyang Wu, Yiwei Kong 외 arxiv

Whereas most brain-computer interface research has focused on decoding neural signals into behavior or intent, the reverse challenge-using controlled stimuli to steer brain activity-remains far less understood, particula…

Image Generation

An energy-efficient spiking neural network with continuous learning for self-adaptive brain-machine interface

2025-11-27 · Zhou Biyan, Arindam Basu arxiv

The number of simultaneously recorded neurons follows an exponentially increasing trend in implantable brain-machine interfaces (iBMIs). Integrating the neural decoder in the implant is an effective data compression meth…

Reinforcement Learning

Intelligent and Miniaturized Neural Interfaces: An Emerging Era in Neurotechnology

2024-05-13 · Mahsa Shoaran, Uisub Shin, MohammadAli Shaeri

Integrating smart algorithms on neural devices presents significant opportunities for various brain disorders. In this paper, we review the latest advancements in the development of three categories of intelligent neural…

Towards Neural Co-Processors for the Brain: Combining Decoding and Encoding in Brain-Computer Interfaces

2018-11-28 · Rajesh P. N. Rao

The field of brain-computer interfaces is poised to advance from the traditional goal of controlling prosthetic devices using brain signals to combining neural decoding and encoding within a single neuroprosthetic device…