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The world is filled with millions and millions of distinct smells, but the way the mammalian brain has evolved to differentiate them is something of a mystery.
Two neuroscientists at the Salk Institute and UC San Diego have discovered that at least six types of mammals – from mice to cats – distinguish odors in the same way, using circuits in the brain preserved over time. some change.
"The study provides information on the organizational principles underlying brain circuits of mammalian olfaction that could be applied to other parts of the brain and to other species" said Charles Stevens, distinguished professor emeritus of Salk's neurobiology lab and co-author of the research published in July 18, issue 2019 of Current biology.
In summary, the study reveals that the size of each of the three components of the neural network of olfaction is substantially the same for each species, starting with the receptors at the nose that transmit signals to a group of neurons located at the same time. 'before the brain, called receptors. the olfactory bulb which, in turn, relays the signals to a "higher functioning" region for the identification of odors, called the piriform cortex.
"These three steps are staggered, with the ratio of the number of neurons in each stage being the same for all species," says Shyam Srinivasan, project scientist at the Kavli Institute for Brain and Mind. University of San Diego, and co-author of the paper. "So, if you told me the number of neurons in the nose, I could predict the number in the piriform cortex or in the bulb."
The present study builds on the same duo research, published in 2018, which described how the mouse brain transforms and distinguishes odors using what is called "distributed circuits". Unlike the visual system, for example, where information is transmitted in an orderly fashion to specific parts of the visual cortex, researchers have found that the mouse olfactory system relies on a combination of distributed connections in the piriform cortex.
After this article, Stevens and Srinivasan sought to determine whether distributed neuronal circuits revealed in mice were similar in other mammals. For the work in progress, the researchers badyzed brains of mammals of different sizes and types. Their calculations, as well as previous studies in recent years, have been used to estimate brain volumes. Stevens and Srinivasan used various microscopy techniques to visualize different types of neurons forming synapses (connections) in the olfactory circuits.
"We could not count each neuron, so we conducted an investigation," says Srinivasan. "The idea is to take samples of different areas represented to detect irregularities."
The new study revealed that the average number of synapses connecting each functional unit of the olfactory bulb (a glomerulus) to the neurons of the piriform cortex is invariant from one species to another.
"It was remarkable to see how they were kept," says Stevens.
Specifically, the identification of individual odors is related to the strength and combination of trigger neurons of the circuit, which can be likened to the music of a piano whose notes come from the depression of several keys to create chords or arrangement of the letters that form the words. on this page.
"Odor discrimination is based on the rate of fire, the electrical impulse that travels through the neuron axon," says Srinivasan. "An odor, for example for coffee, can cause a slow response in a neuron, while the same neuron can react to chocolate faster."
This code used for the olfaction is different from that of other parts of the brain.
"We have shown that the connectivity parameters and the relationship between the different stages of the olfactory circuit are conserved in mammals, suggesting that evolution has used the same pattern for the circuit among species, but that is not the same. it has simply changed in size to adapt to the environmental niche of animals, "Stevens says.
In the future, Stevens plans to examine other brain regions in search of other distributed circuits whose function is based on a similar coding found in this study.
Srinivasan says that he will focus on how the noise or variability in odor coding determines the balance between discrimination and learning, explaining that the variability found by the duo in their work might be a mechanism allowing to distinguish odors, which could be applied to a better machine learning. AI systems.
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