Describing the Brain’s Encoding Process

Researchers at École Polytechnique Fédérale de Lausanne (EPFL) are studying brain activity in the hopes of deciphering the mechanisms behind the brain’s decision-making process. By monitoring the activity of neurons directly after a stimulus, and using algebraic topology to visualize that activity, computers are able to recognize patterns in the overwhelming amount of data. Kathryn Hess Bellwood, PhD describes how the research output seems to show a clear delineation between when the brain is processing the stimuli and the exact moment a decision is made. This research will help us determine the brain’s encoding process, how bits of information gets transferred throughout the body.

From EPFL’s Article:

Brains of healthy rats that are the same age share many features, such as similar numbers and types of neurons present in the six layers of the cortex. But how do neurons exchange information? Which neurons are activated? How does this change with time?

To answer these questions, a team of scientists led by EPFL’s Blue Brain Project used the mathematical language of algebraic topology to describe just how rat neurons connect to each other – and respond to stimuli – providing the first geometrical insight into how information is processed in a rodent brain. The results are published 12 June 2017 in the open-access journal Frontiers in Computational Neuroscience.

“Our previous mathematical approaches struggled to make sense of the activity generated by neurons,” says EPFL neuroscientist Henry Markram who leads the Blue Brain Project. “When we map the activity into high dimensional geometries the activity starts to make sense – this exciting collaboration has opened a completely new door to understanding the brain. ”

Conducting virtual experiments on Blue Brain’s digital reconstruction of a microcircuit in the rat brain, a computer model consisting of 31 000 neurons – and a whopping 8 million connections – all based on physiological data, the scientists discovered and described quantitatively the astonishingly rich geometric organization of neurons, providing a new and powerful tool for understanding the brain. The way neurons network together can actually be described using multi-dimensional mathematical objects. Moreover, these objects respond to external stimuli with a characteristic pattern through time, never before observed.

Click here to read more on EPFL’s News Outlet.

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