The brain accelerates perception, guessing what will happen next

Imagine that you pick up a glass withapple juice, as you suspect, to take a sip and discover that it is actually a light beer. Even if you usually don’t mind beer, this time a sip tastes terrible. Because context and internal states, including expectation, affect how all animals perceive and process sensory information, explains Alfredo Fontanini, a neurobiologist at Stony Brook University in New York. In this case, waiting for the wrong stimulus leads to a surprise and negative reaction.

But this is not limited to the quality of perception. Among other effects, a sensory system that expects incoming data, good or bad, may also increase the speed at which the animal detects, identifies and responds to them.

A few years ago, Fontanini and his teamfound direct neural evidence of this acceleration effect in the taste cortex, the part of the brain that is responsible for taste perception. Since then, they have tried to determine the structure of the cortical scheme that led them to such results. And now, it is found. Last month, they published their findings in Nature Neuroscience: a network model with a special type of architecture that not only provides new insights into how expectations work, but also delves into broader questions about how scientists should view perception more broadly. More than this, it keeps up with decision-making theory, which assumes that the brain really makes hasty conclusions, rather than building them.

Quick feelings and active states

Taste - the least studied feeling - has becomeperfect to start your search. After the taste gets on the tongue, it takes several hundred milliseconds and the activity in the taste crust begins to reflect the incoming data. "By the standards of the brain, eternity passes," says Don Katz, a neuroscientist at Brandeis University in Massachusetts. “In the visual cortex, this takes less time”, which makes it difficult to determine the effect of expectation, which scientists wanted to study.

In 2012, Fontanini and his colleagues conductedan experiment in which rats heard a sound ("pre-emptive signal"), and then received a small portion of taste through a tube in the mouth. The taste itself could be sweet, salty, sour, or bitter, and the pre-emptive signal did not indicate which of the four could follow.

However, scientists have found that such commonexpectations can cause the neurons of the gustatory bark to recognize the stimulus almost two times faster than when rats received a taste without hearing a sound first. The delay period is reduced from approximately 200 milliseconds to 120 milliseconds.

Fontanini wanted to know what type of neural networkcan theoretically provide faster coding. And this was helped by his colleague on Stony Brooke, the neuroscientist Giancarlo La Camera, who had previously worked on modeling spontaneous brain activity that occurs even in the absence of stimuli.

In the past few decades, increasinglyit is emphasized that most of the activity in sensor networks is generated more from within than under the influence of external stimuli. If you compare the activity of the visual cortex of an animal in total darkness with the activity of an animal that looks around, the difference will be small. Even in the absence of light, sets of neurons in the cortex begin to work together, either simultaneously or in predictable waves. This joint triggering is saved as a so-called metastable state from a few hundred milliseconds to a few seconds, and then the activity picture switches. Metastability, or the tendency to jump between transition states, continues after the introduction of a stimulus (stimulus), but some states, like rules, appear more often for certain stimuli and therefore are considered as “coding states”.

La Camera and others (including Katz) earliersimulated metastability, creating a so-called cluster network. In it, the excitatory neuron groups were strongly interconnected, but the inhibitory neurons were randomly connected with individual excitatory neurons. “This cluster architecture is essential for creating metastability,” says Fontanini.

Scientists have discovered that the same network structurewas also needed to recreate the effects of waiting. In a metastable model with a cluster architecture, scientists imitated a common anticipatory signal with the subsequent appearance of a certain taste stimulus. Having done this, they successfully reproduced the accelerated coding pattern that Fontanini observed in rats in 2012: transitions from one metastable state to another became faster than also allowing the system to reach coding states faster.

These results showed that by simply creating a networkshowing these metastable activity patterns, “you can catch a lot of neurological reactions when imitating taste sensations,” says Fontanini.

The work of scientists was remarkable in thatprovided information on which architecture to look for in the taste crust, and also, possibly, in other sensory cortical layers. Neuroscientists are now deciding how a taste is processed: some say that a number of neurons can encode “sweet” and another “salty”, creating very specific neural signatures for certain tastes. Others attribute this to broader models in which most neurons respond to most tastes. The work done by Fontanini and his colleagues supports the latter theory, while at the same time providing predictions on how this relationship should look.

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