New AI reads brain signals and predicts human behavior

The new technique could speed up the search for connections between brain activity and behavior.

A new development has been created

together with the Institute of Systems NeurobiologyKavli in Trondheim and the Max Planck Institute for Cognitive and Brain Sciences in Leipzig. The authors created an ultra-precise neural network, a special type of deep learning algorithm that can decode many different behaviors and stimuli from different areas of the brain.

Neuroscientists are recording more and more data from the brain, but understanding the information contained in this data, aka reading the neural code, still remains a difficult problem. 

Markus Frey, lead author of the study

Frey notes that the team wanted to develop an automated method for analyzing various types of raw neural data without having to manually decode it.

They tested the AI ​​on the neural signals of ratsand found that their design was able to accurately predict the position, head direction and running speed of animals. Even without manual processing, the results were more accurate than what was obtained using the conventional analysis method. The AI ​​was also able to predict the movements of people's hands.

Senior Author and Professor Caswell Barry noted,that existing methods for analyzing brain signals miss a lot of potential information in neural recordings. The problem is that we can only decode the elements that we understand, he emphasizes.

However, the new AI can access much more neural code. It decodes neural data more accurately and, importantly, is not limited by existing knowledge.

The authors plan to develop the design so that it can predict higher-level cognitive processes, such as reasoning or problem solving. 

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