The premiere of
the movie Scent of Mystery in 1960 marked a singular event in the annals of
cinema: the first, and last, motion picture debut “in glorious Smell-O-Vision.”
Hoping to wow moviegoers with a dynamic olfactory experience alongside the
familiar spectacles of sight and sound, select theaters were outfitted with a
Rube Goldberg-esque device that piped different scents directly to seats.
Audiences and critics quickly concluded that the experience
stunk. Fraught with technical issues, Smell-O-Vision was panned and became a
running gag that holds a unique place in entertainment history. The flop of
Smell-O-Vision, however, failed to deter entrepreneurs from continuing to chase
the dream of delivering smells to consumers, particularly in recent years,
through digital scent technologies.
Such efforts have generated news headlines but scant
success, due in part to a limited understanding of how the brain translates
odor chemistry into perceptions of smell — a phenomenon that in many ways
remains opaque to scientists.
A study by neurobiologists at
Harvard Medical School now provides new insights into the mystery of scent.
Reporting in Nature on July 1, the researchers describe for
the first time how relationships between different odors are encoded in the
olfactory cortex, the region of brain responsible for processing smell.
By delivering odors with carefully selected molecular
structures and analyzing neural activity in awake mice, the team showed that
neuronal representations of smell in the cortex reflect chemical similarities
between odors, thus enabling scents to be placed into categories by the brain.
Moreover, these representations can be rewired by sensory experiences.
The findings suggest a neurobiological mechanism that
may explain why individuals have common but highly personalized experiences
with smell.
“All of us share a common frame of reference with
smells. You and I both think lemon and lime smell similar and agree that they
smell different from pizza, but until now, we didn’t know how the brain
organizes that kind of information,” said senior study author Sandeep Robert
Datta, associate professor of neurobiology in the Blavatnik Institute at HMS.
The results open new avenues of study to better
understand how the brain transforms information about odor chemistry into the
perception of smell.
“This is the first demonstration of how the olfactory
cortex encodes information about the very thing that it’s responsible for,
which is odor chemistry, the fundamental sensory cues of olfaction,” Datta
said.
Computing
odor
The sense of smell allows animals to identify the
chemical nature of the world around them. Sensory neurons in the nose detect
odor molecules and relay signals to the olfactory bulb, a structure in the
forebrain where initial odor processing occurs. The olfactory bulb primarily
transmits information to the piriform cortex, the main structure of the
olfactory cortex, for more comprehensive processing.
Unlike light or sound, stimuli easily controlled by
tweaking characteristics such as frequency and wavelength, it is difficult to
probe how the brain builds neural representations of the small molecules that
transmit odor. Often, subtle chemical changes — a few carbon atoms here or
oxygen atoms there — can lead to significant differences in smell perception.
Datta, along with study first author Stan Pashkovski,
research fellow in neurobiology at HMS, and colleagues approached this
challenge by focusing on the question of how the brain identifies related but
distinct odors.
“The fact that we all think a lemon and lime smell
similar means that their chemical makeup must somehow evoke similar or related
neural representations in our brains,” Datta said.
To investigate, the researchers developed an approach
to quantitatively compare odor chemicals analogous to how differences in
wavelength, for example, can be used to quantitatively compare colors of light.
They used machine learning to look at thousands of
chemical structures known to have odors and analyzed thousands of different
features for each structure, such as the number of atoms, molecular weight,
electrochemical properties and more. Together, these data allowed the
researchers to systematically compute how similar or different any odor was
relative to another.
From this library, the team designed three sets of
odors: a set with high diversity; one with intermediate diversity, with odors
divided into related clusters; and one of low diversity, where structures
varied only by incremental increases in carbon-chain length.
They then exposed mice to various combinations of
odors from the different sets and used multiphoton microscopy to image patterns
of neural activity in the piriform cortex and olfactory bulb.
Smell
prediction
The experiments revealed that similarities in odor
chemistry were mirrored by similarities in neural activity. Related odors
produced correlated neuronal patterns in both the piriform cortex and olfactory
bulb, as measured by overlaps in neuron activity. Weakly related odors, by
contrast, produced weakly related activity patterns.
In the cortex, related odors led to more strongly
clustered patterns of neural activity compared with patterns in the olfactory
bulb. This observation held true across individual mice. Cortical
representations of odor relationships were so well-correlated that they could
be used to predict the identity of a held-out odor in one mouse based on
measurements made in a different mouse.
Additional analyses identified a diverse array of
chemical features, such as molecular weight and certain electrochemical
properties, that were linked to patterns of neural activity. Information
gleaned from these features was robust enough to predict cortical responses to
an odor in one animal based on experiments with a separate set of odors in a
different animal.
The researchers also found that these neural
representations were flexible. Mice were repeatedly given a mixture of two
odors, and over time, the corresponding neural patterns of these odors in the
cortex became more strongly correlated. This occurred even when the two odors
had dissimilar chemical structures.
The ability of the cortex to adapt was generated in
part by networks of neurons that selectively reshape odor relationships. When
the normal activity of these networks was blocked, the cortex encoded smells
more like the olfactory bulb.
“We presented two odors as if they’re from the same
source and observed that the brain can rearrange itself to reflect passive
olfactory experiences,” Datta said.
Part of the reason why things like lemon and lime
smell alike, he added, is likely because animals of the same species have
similar genomes and therefore similarities in smell perception. But each
individual has personalized perceptions as well.
“The plasticity of the cortex may help explain why
smell is on one hand invariant between individuals, and yet customizable
depending on our unique experiences,” Datta said.
Together, the results of the study demonstrate for the
first time how the brain encodes relationships between odors. In comparison to
the relatively well-understood visual and auditory cortices, it is still
unclear how the olfactory cortex converts information about odor chemistry into
the perception of smell.
Identifying how the olfactory cortex maps similar
odors now provides new insights that inform efforts to understand and
potentially control the sense of smell, according to the authors.
“We don’t fully understand how chemistries translate
to perception yet,” Datta said. “There’s no computer algorithm or machine that
will take a chemical structure and tell us what that chemical will smell like.”
“To actually build that machine and to be able to
someday create a controllable, virtual olfactory world for a person, we need to
understand how the brain encodes information about smells,” Datta said. “We
hope our findings are a step down that path.”
Source: https://myfusimotors.com/2020/07/04/sniffing-out-smell-how-the-brain-organizes-information-about-odors/
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