The brain finds order in the chaos



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The brain finds order in the chaos

A synapse in the foreground, in the middle of a forest of neurons. The synapse is deformed with a pip effect to hint at the synaptic noise that affects gallbladder release. Credit: Blue Brain Project / EPFL

How does the brain find order in a sea of ​​noise and chaos? Researchers at EPFL's Blue Brain project have found the solution using advanced simulation techniques to study how neurons speak to each other. In an article published in Nature Communications, they discovered that working as a team, cortical neurons can respond even to weak inputs on the background of noise and chaos, allowing the brain to regain order.

Neurons communicate with each other by sending fast pulses of electrical signals called spikes. At first glance, the generation of these tips can be very reliable: when an isolated neuron repeatedly receives exactly the same electrical input, one finds the same pattern of spikes. Why then does the activity of cortical neurons in a living animal fluctuate and seem so variable?

There are two reasons for this. First, when transmitting a signal to another neuron, the process can sometimes fail and these failures are unpredictable – as if we were throwing a dice to decide on a result. "We estimate that the risk of synapse between two cortical pyramidal neurons transmitting a chemical neurotransmitter signal can be as low as 10%," says lead researcher Max Nolte. This uncertainty means that a neuron will hear the same message sent by neurons connected differently each time.

Second, when the two basic types of cortical neurons (excitatory and inhibitory) are interconnected in a network, small uncertainties in the patterns of activity become magnified. This leads to unpredictable patterns, a behavior called chaos.

This backdrop of noise and chaos suggests that individual cortical neurons can not find order and pull reliable spikes. The brain must therefore "average" the activity of many neurons with certainty – listen to the whole choir instead of individual singers.

The brain finds order in the chaos

Emergent cortical dynamics is shaped by various cellular and network properties, such as synaptic noise and chaos, quantified using the Blue Brain Project's neurocortical microcircuit model. Credit: Blue Brain Project / EPFL

The neuroscience of simulation finds the answer

The experimental manipulations needed to unravel the sources of noise in the brain and evaluate their impact on neuronal activity are currently impossible to achieve in an animal living in vivo, or even in separate brain tissue in vitro. "At the moment, it's simply not possible to monitor all the thousands of brain inputs in an in vivo neuron, nor to turn on or off different sources of noise," Nolte says. The closest approximation of cortical tissue to date in a model is the biologically detailed digital reconstruction of rat neocortical microcircuit performed by the Blue Brain Project (Cell, 2015). This computer model has been the ideal platform to allow researchers to study the degree of understanding of the voice of individual neurons because it contains models of unreliable data transmission between neuron signals.

With the help of this model, they found that spontaneously generated activity from interconnected neurons is extremely noisy and chaotic, describing very different peak times at each repetition. "We investigated the origin and nature of cortical internal variability with a biophysical neophysical microcircuit model with biologically realistic noise sources," reveals Nolte. "We have observed that unreliable signals from neurotransmitters are amplified by recurrent network dynamics, which causes a memory of the past to rapidly decay, a sea of ​​noise and chaos."

Reliable answers in the midst of noise and chaos

But, of course, the mammalian brain does not have fast decomposing memory. In fact, perhaps the most fascinating analysis from the results is that extremely unreliable peaks during a spontaneous activity become very reliable when the circuit receives external inputs. This phenomenon was not simply the result of a strong external contribution that leads neurons directly to reliable responses. Even low thalamocortical input could tilt the network briefly towards a regime of very reliable peaks. At this point, interactions between neurons, which otherwise magnify uncertainty and chaos, instead increase reliability and allow the brain to regain order.

"Thalasso-cortical stimuli can lead to reliable spikes with millisecond accuracy, amidst the noise and chaos," says Blue Brain's professor and founder, Henry Markram. "Surprisingly, we were able to demonstrate that this effect was based on team functioning of cortical neurons, so our model shows that noise and chaos in cortical neural networks are compatible with reliable stimulation, which allows the brain to This finding suggests that the highly fluctuating activity of cortical neurons in a living animal reflects order, not noise and chaos, "concludes Markram.


The way a neuron processes information is never the same


More information:
"Cortical reliability in the midst of noise and chaos", Max Nolte, Michael W. Reimann, James G. King, Henry Markram and Eilif B. Muller. Nature CommunicationsAugust 22, 2019, doi.org/10.1038/s41467-019-11633-8

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Brain finds order in chaos (August 22, 2019)
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