Watch: Scientists Using AI Visualize What Mouse Sees In Real-Time

The researchers of EPFL has created the novel machine learning algorithm is called CEBRA (pronounced Zebra) to construct brain signals in real-time.

New Delhi: The emergence of Artificial Intelligence (AI) has pushed the boundaries of possibilities to make possible things that are limited to fiction, movies, and imagination. For ages, humanity has wondered how it feels to look through the eyes of an animal, be it a dog, a mouse, or anything else. Until now, there was a limit in technology that hindered developing a device that can do this work. The AI boom at the end of 2022 and early 2023 ushered in the breakthrough age.

Who Was Behind It?

A team of researchers from Ecole Polytechnique Federale De Lausanne (EPFL) created an AI tool that interprets a mouse's brain signals in real-time and reconstructs the video clip the mouse is watching.

EPFL Shares The Video - Watch Here

EPFL has shared the video on the YouTube channel.

How Does It Work?

The researchers have made a step in this direction by introducing a new algorithm for building artificial neural network models that capture brain dynamics with an impressive degree of accuracy. The novel machine learning algorithm is called CEBRA (pronounced Zebra) and learns the hidden structure in the neural code.

"This work is just one step towards the theoretically-backed algorithms that are needed in neurotechnology to enable high-performance BMIs," says Mackenzie Mathis, EPFL's Bertarelli Chair of Integrative Neuroscience and PI of the study.

What's The Purpose?

The CEBRA might catalyze the effort to understand the most complex system in the Universe – the brain.

"The goal of CEBRA is to uncover structure in complex systems. And, given the brain is the most complex structure in our universe, it's the ultimate test space for CEBRA. It can also give us insight into how the brain processes information and could be a platform for discovering new principles in neuroscience by combining data across animals, and even species," says Mathis. "This algorithm is not limited to neuroscience research, as it can be applied to many datasets involving time or joint information, including animals."