On the 15th, reporters learned from the Institute of Automation, Chinese Academy of Sciences, that researchers from this institute and the Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, have developed a real-feel intelligent computing-control platform. Utilizing this platform, they have, for the first time internationally, achieved real-time monitoring of 100,000-level neurons in zebrafish brains. The related research findings were published online in the journal Nature Neuroscience.
The technology for imaging single-neuron activity across the whole brain is a powerful tool for deciphering the principles of parallel and distributed computing in the brain. However, due to limitations in real-time data processing capabilities, it has been challenging to analyze and conduct closed-loop control and study of brain functions on a large scale in real-time.
Inspired by the technology for detecting fast radio bursts in the field of astronomy, the researchers established an optical neural signal preprocessing system, namely the real-feel intelligent computing-control platform. This platform successfully managed real-time registration, signal extraction, and analysis of neural function data streams up to 500MB/s.
Using this platform, the research team first monitored the whole-brain neurons of zebrafish in real-time. They then quickly extracted and analyzed the neural activities of the entire zebrafish brain. Furthermore, they decoded the activities of any selected groups of neurons to control external devices. This achievement marks a significant step forward in the application of technologies such as virtual reality and optogenetic control based on whole-brain single-cell optical imaging in the field of closed-loop brain science research.
Real-World Intelligence Computing - The performance of the control platform has been demonstrated in multiple closed-loop research scenarios in neuroscience. For example, using this platform, researchers can in real time reduce the high-dimensional activity of all neurons in the brain to the activities of several neuronal clusters. They also managed to link the activity of any one cluster with the visual environment in a closed loop, creating a virtual reality system based on optical imaging that directly connects brain neural activity with the visual environment. Within this virtual reality, the interaction between neural activity and the environment can be freely adjusted, enabling the neuron clusters controlling the environment to adaptively modify their output according to changes in the environment.
It's reported that, leveraging real-time analysis of massive data streams and high-throughput whole-brain imaging technology, the research team will further investigate and select the characteristics of neural group activities suitable for optical brain-computer interfaces. This effort aims to reveal their mechanisms and develop more efficient optical brain-computer interface technologies, pushing forward the development of neuroscience research paradigms.
(Provided by the Institute of Automation, Chinese Academy of Sciences)
(Original Title: Chinese Scientists Achieve Real-Time Monitoring of Hundreds of Thousands of Neurons in the Whole Brain of Zebrafish for the First Time)
