How does the brain learn? | UdeMNews

Everyone knows that the human brain is extremely complex. But how exactly does he learn? Well, the answer may be much simpler than you think.

An international research team, including the University of Montreal, has made great strides in correctly mimicking synaptic changes in the neocortex that are thought to be essential for learning, paving the way for a better understanding of brain function.

Scientists’ research – which is based on an open source model – was published in 1er In June Communication with nature.

A world of new directions

“This opens up a whole new world for scientific research into how we learn,” said Elif Mueller, an assistant professor in the Department of Neuroscience at UDM and researcher at the Ivado Institute for Data Valorization, and CIFAR-Canada Chair in AI (AI). Who co-led the research on the Blue Brain Project at the Ecole Polytechnic Federal de Lausanne (EPFL) in Switzerland.

Elif Mueller moved to Montreal in 2019 and continued his research at the Architecture of Biological Learning Laboratory, which he founded at CHU Sainte-Justine Research Center in collaboration with UdeM and Mila, Quebec Institute of Artificial Intelligence.

“The neurons are shaped like a tree and the synapses are the leaves of the branches,” explained Professor Mueller, co-lead author of the study. Earlier approaches to modeling plasticity ignored the structure of this tree, but now we have computational tools to test the notion that synaptic interactions in branches play a fundamental role in guiding learning in vivo. “

According to him, “it has important implications for understanding the mechanisms of neurodevelopmental disorders such as autism and schizophrenia, but also for the development of powerful new approaches to neuroscience-inspired AI.”

Employees in five countries

Eilif Muller’s EPFL’s Blue Brain Project, University of Paris, Hebrew University of Jerusalem, Instituto Cajal (Spain) and a group of Harvard Medical School scientists have jointly developed a model of synaptic plastics in Newcortex based on data Consynamic. .

How does it work? Easier than you might think.

The brain is made up of billions of neurons that communicate with each other, creating trillions of synapses. These connecting points between neurons are complex molecular machines that constantly change under the influence of external stimuli and internal dynamics, a process commonly known as synaptic plasticity.

In the neocortex, a key area related to learning high-level cognitive functions in mammals, pyramidal cells represent 80-90% of neurons and are known to play a major role in learning. Despite their importance, the long-term dynamics of their synaptic changes have only been experimentally identified and varied among a few of them.

Limited understanding

Therefore, the understanding of complex neural circuits, especially through stereotyped cortical layers, which indicate how different regions of the neocortex interact, is limited. The invention of Eilif Muller and his colleagues was to use computer modeling to gain a more comprehensive view of the dynamics of synaptic plastics controlling learning in these neocortical circuits.

By comparing their results with the available experimental data, they have shown in their research that their synaptic plasticity model may be responsible for the varied plasticity dynamics of different pyramidal cells that make up neocortical microcircuits. They achieved this using a single unified set of model parameters, indicating that the rules of neocortical plasticity can be divided by all pyramidal cells and are therefore predictable.

Most of these plasticity experiments were performed on rat brain fragments in vitro, where the calcium dynamics that control synaptic transmission and plasticity vary dramatically compared to learning in vivo intact brain. Importantly, the study predicts plastics dynamics that are qualitatively different from benchmark tests performed in vitro.

If this is confirmed by future experiments, the effects of plasticity and learning comprehension on our brains will be major, Elif Mueller and his team believe.

EPFL neuroscientist Henry Markram, founder and director of the Blue Brain Project, said: “What’s exciting about this study is the further confirmation for scientists that we can bridge the gaps in experimental knowledge by using modeling methods while studying the brain.”

It is open science

“Also, the model is available on the open source, Genedo platform,” he added. Here we have shared hundreds of plastic connections of different types of pyramidal cells. It is by far the most widely validated model of plasticity, but it also presents the most comprehensive prediction of the difference between plasticity observed in a Petri dish and an intact brain. “

Henry Markram concludes, “This quantum leap has been made possible by our team-based collaborative science approach. In addition, communities can go further and design by modifying or supplementing their own versions. It is open science and it will accelerate progress.” “

About this study

The study, by Giuseppe Chindemi and his colleagues, was entitled “A model of calcium-based plasticity to predict long-term potential and depression in the neocortex” Published 1er In June 2022 Communication with nature. Funding for the Blue Brain project was provided by the Swiss Federal Institute of Technology Council. Eilif Muller’s work has been funded by the CHU Sainte-Justine Research Center, IVADO – The Data Valuation Institute -, Quebec Research Fund – Health, Canada – CIFAR AI Chairs Program, Mila – Quebec Institute of Artificial Intelligence – and Google. .

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