📰 How does the brain learn?

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

An international research team thatUniversity of Montreal (The University of Montreal is one of four educational institutions…) made a major breakthrough by accurately simulating synaptic changes in the neocortex thought to be responsible for theTo learn (Learning is the acquisition of know-how, i.e. the process…)which paves the way for a better understanding of how the works Brain (The brain is the main organ of the central nervous system of animals. The brain processes…).

The study of the scientists – which is based on a model with Source code (The source code (or sources, or even source) is a set of instructions written in a…) open – published on 1ah June a nature communication.

A world full of new directions

“It opens up a world of new directions for investigation. scientific (A scientist is a person who is dedicated to the study of one or more sciences and who…) about how we learn,” says Eilif Muller, assistant professor at the Institute for neuroscience (The neurosciences correspond to the totality of all biological disciplines and…) by UdeM, viewfinder (A researcher (female researcher) refers to a person whose job is to conduct research…) at IVADO – theinstitute (An institute is a permanent organization created for a specific purpose. It is…) rating of Data (In information technology (IT), data is an elementary description, often…) – and holder of an ICRA-Canada Chair in artificial intelligence (Artificial Intelligence or Cognitive Computing is the “finding of means…) (IA), who co-led the study at the Blue Brain Project at the École polytechnique fédérale de Lausanne (EPFL), Switzerland.

Eilif Müller followed suit Montreal (Montreal is both an administrative region and a metropolitan area of ​​Quebec[2]. So big…) in 2019 and continues his research in the laboratory architectures (Architectures is a documentary series by Frédéric Campain and Richard Copans,…) of Biological Learning, which he teaches at the Center for research (Scientific research primarily refers to all measures taken to …) of the CHU Sainte-Justine in collaboration with UdeM and Mila, the Quebec Institute of Artificial Intelligence.

“Neurons are shaped like a tree (A tree is a terrestrial plant capable of elevating itself in…) and the synapses are the leaves on the branches, explained Professor Muller, co-lead author of the study. Previous approaches to modeling plasticity ignored this tree structure, but now we have the computational tools to test the idea that synaptic interactions on branches play a fundamental role in controlling learning. live (In vivo (Latin: “in the living”) is a Latin expression…).”

“This has important implications for understanding the mechanisms of neurodevelopmental disorders such asautism (Today the term autism rather refers to a disorder that affects the human being in three…) and the schizophrenia (The term schizophrenia generally encompasses a range of…)but also for development Point (Graphic) powerful new approaches to AI inspired by neuroscience”.

employees in five countries

Eilif Muller worked with a group of scientists from EPFL’s Blue Brain Project toUniversity of Paris (The University of Paris was one of the largest and…)of’Hebrew University of Jerusalem (The Hebrew University of Jerusalem (in Hebrew…)Instituto Cajal (Spain) and Harvard Medical School to develop a model of synaptic plasticity in the neocortex based on the dynamic (The word dynamic is often used to designate or qualify what refers to motion. It…) out calcium (Calcium is a chemical element, symbol Ca and atomic number 20.) postsynaptically under data limitation.

How does it work? Easier than you might think.

The brain is made up of billions of neurons that communicate with each other training (In intonation, fundamental frequency changes are perceived as variations of….) trillions of synapses. These junctions between neurons are complex molecular machines that are constantly changing under the influence of external stimuli and internal dynamics, a process commonly referred to as synaptic plasticity.

In the neocortex, a key area associated with learning high-level cognitive functions in mammals, pyramidal cells represent 80-90% of neurons and are known to play an important role in learning. Despite their importance, the long-term dynamics of their synaptic changes have only been experimentally characterized between a few of their types and have been shown to be diverse.

Limited understanding

Therefore, understanding of the complex neural circuits formed is limited, particularly by the stereotyped cortical layers that determine how the different regions of the neocortex interact. The innovation of Eilif Muller and his colleagues was modeling computer science (IT – contraction of information and automation – is the domain…) to gain a more comprehensive view of the dynamics of synaptic plasticity that controls learning in these neocortical circuits.

By comparing their results with the available experimental data, they showed in their study that their model of synaptic plasticity can explain the different plasticity dynamics of the different pyramidal cells that make up the neocortical microcirculation. They accomplished this by resorting to a single one together (In set theory, a set intuitively denotes a collection…) Model parameters suggesting that neocortical plasticity rules are shared by all pyramidal cell types and are therefore predictable.

Most of these plasticity experiments were performed on rodent brain slices in vitro (In vitro (Latin: “in the glass”) means tube test, or, more…), where the calcium dynamics that control synaptic transmission and plasticity are significantly altered compared to learning in the intact brain in vivo. Importantly, the study predicts plasticity dynamics that are qualitatively different from benchmark experiments conducted in vitro.

If confirmed by future experiments, the implications for our understanding of brain plasticity and learning would be significant, Eilif Muller and his team believe.

“What’s exciting about this study is that it provides further confirmation for scientists that we can fill experimental knowledge gaps by using a modeling approach when studying the brain,” said EPFL neuroscientist Henry Markram, founder and director of the Blue Brain Project.

It’s open science

“Moreover, the model is open-source and available on the Zenedo platform,” he added. Here we have shared hundreds of plastic connections of pyramidal cells of different types. It is not just the model of plasticity that has been most widely validated in this regard Day (The day or day is the interval separating sunrise from sunset; it is that…)but it also represents the most complete prediction of the differences between plasticity observed in a petri dish and in an intact brain.

Henry Markram concluded by saying, “This leap forward is rendered (Rendering is a computer process that calculates the 2D image (equivalent to a photograph)…) possible thanks to our team-based collaborative scientific approach. In addition, the community can go further and design their own versions by modifying or adding to them. It’s open science and will accelerate progress.”

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