Algorithm Decodes Mouse Vision from Brain Signals, Say Scientists
Swiss Scientists Develop New Algorithm to Decode Brain Signals
A group of researchers from the Swiss Federal Institute of Technology has developed a new algorithm that can be used in artificial neural network models to capture brain dynamics and signals. The machine learning algorithm, called CEBRA, was able to decipher the codes in the brain’s nerves and examine the brain signals of a rat shown a black and white video clip from the 1960s.
The researchers measured the brain signals of the mice with electrode probes placed directly in the visual cortex and optical probes created with the help of genetically modified mice. With the aid of CEBRA, the researchers were able to reproduce almost exactly the same images watched by the mouse on another screen.
Although CEBRA is not capable of fully reconstructing what people see, it represents a significant step forward in this area. The study is expected to enable high-performance brain-machine interfaces and the development of algorithms needed in neurotechnology.
Mackenzie Mathis, Head of Integrative Neuroscience at Bertarelli, led the research and stated that the success of the new algorithm lies in its ability to combine brain signals with movie data. The research results were published in the journal “Nature”.
This discovery could have important implications for the development of brain-computer interfaces, which require a thorough understanding of how the brain interprets information. The research also highlights the potential for advancements in neurotechnology, as scientists continue to unlock the mysteries of the human brain and explore ways to manipulate its functions.
