Scientists discover hidden patterns of brain activity

If you look at a movie of neural
activity with neural spiking here and here and here and here, it’s very
difficult if not impossible to detect any pattern in the firing. But when you
look at this pattern of firing through the filter algebraic topology, different
structures emerge in terms of which families of neurons are firing in which
order and then more complex structures when you look at how these different
families are related to each other. When one looks at the evolution of such
a pattern through time, it gives us a mathematical signature that describes
this pattern that was hidden in the seemingly chaotic firing of the network.
The big question is, you know, you’re looking at the brain after a stimulus
and it has this activity pattern and somehow it should be encoding
information about what came in and then coming to the sort of decision about
what to do next. What I think that we’re seeing here is a way of interpreting or
visualizing the brain’s own code for what it’s doing. It processes the
information, it’s encoding the input signal and then it’s coming to some sort
of decision, and what algebraic topology enables us to do is to describe that
encoding process and perhaps even to visualize the moment at which the brain
is making a decision. So there are more and more intricate structure s among these neurons that are building up and as it’s thinking as its processing
the information then boom we come to a decision “phoop” and that’s… that’s what we’re
detecting, we’re detecting the information processing and decision
making process of the brain.

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