Tuesday, December 21, 2021

Trans-Epistemological Etymologues - VOC vs VOC

Violating Organic Content - The new VOCs!

For years we have been both addicted to and suspicious of VOCs -- volatile organic compounds. They smell great, like gasoline, baked bread, or bergamot. They can also get into our bloodstream and cause health problems. They evaporate from all kinds of things, and we can measure them with special "VOC meters," although the human nose is by far the most sensitive all-purpose VOC-detector on the market. (Don't forget there are plenty of things that are bad for you that you CAN'T smell at all; and then there's anosmia too.)

But now, a new VOC is on the scene, one potentially far more serious to the survival of our cultural species. They're called "violating organic contents," and they're like little diseases floating around our collective neural network.

Perhaps "floating" is the wrong word. They're jamming your brain via high-frequency algorithms, engineered to reprogram your hardwired hormone circuits of reward and control. Like spores of a Cordyceps mushroom, they invade your neural system, changing the way you think, and using you to propagate itself throughout the network of other-people's-brains. 

You can't smell these VOCs; in fact, even the digital social networks themselves can't seem to detect them very well. We need a better detector for violating organic content (and a better immune system for our collective brain, perhaps some memetic inoculations?). 

Apple threatened Facebook ban over slavery posts on Instagram
Sep 2021, BBC News

Apple threatened to remove Facebook's products from its App Store, after the BBC found domestic "slaves" for sale on apps, including Instagram, in 2019.

"We removed 700 Instagram accounts within 24 hours, and simultaneously blocked several violating hashtags."

It added that it had also developed technology that can proactively find and take action on content related to domestic servitude - enabling it to "remove over 4,000 pieces of violating organic content in Arabic and English from January 2020 to date".

Image credit: That's not a VOC-detector, it's a radiation detector, used by NASA JPL for Mars research.

Partially Related Post Script:
Why cannabis smells skunky
Dec 2021, phys.org

Now, researchers reporting in ACS Omega have discovered a new family of prenylated volatile sulfur compounds (VSCs) that give cannabis its characteristic skunky aroma. 

Prior studies have focused mainly on terpenoids—molecules that range in odor from fuel-like to woody, citrusy or floral.

However, although terpenoids are the most abundant aroma compounds in cannabis, there is little evidence that they provide the underlying skunk-like smell of many cultivars. Skunks use several VSCs in their smelly defense sprays, so Iain Oswald and colleagues suspected that there could be similar molecules in cannabis.

One compound in particular, 3-methyl-2-butene-1-thiol, referred to as VSC3, was the most abundant VSC in the cultivars that the panel reported to be most pungent. This compound has previously been implicated in the flavor and aroma of "skunked beer"—beer that goes bad after being exposed to UV light.

via American Chemical Society: Iain W. H. Oswald et al, Identification of a New Family of Prenylated Volatile Sulfur Compounds in Cannabis Revealed by Comprehensive Two-Dimensional Gas Chromatography, ACS Omega (2021). DOI: 10.1021/acsomega.1c04196

Monday, November 29, 2021

Signal to Noise for the Win

A new model for how the brain perceives unique odors
Oct 2021, phys.org

So here is a scientist, a physicist by name, with an interest in the information-processing abilities of biological, and neurological systems. It didn't take him long, I would imagine, to realize that olfaction is a prime model for complex information-processing systems; it was the first sense, used by the first bacteria to detect chemicals in the primordial soup, later used by animals to make a big, complex mammal brain. If you want to look at how information processing happens in biological systems, this would be the ideal place to look.

But first, you have to throw into the garbage everything you know about olfaction already, which should be easy for a computational information scientist. What they did here was to look far out, all the way out -- beyond molecules and their myriad physico-chemical characteristics, of which the molecules themselves number in the billions; beyond genetics and their 30% variation across the global population; beyond cultural effects that are almost too surreal to quantify for methodical research purposes, like where Americans prefer peppermint since it's associated with candy, yet older folks from England don't like mint since it's associated with pain-relief products of their era, or the easier comparison of preference for durian fruit or Époisses de Bourgogne cheese.

Too messy, said the computational information scientist. And so they put it all in the blender, all those variables together. And they called it noise. Boil it all down, cancel it all out, all that dirty data of molecules and genes and cultural and personal association. Throw it all in the same bin, and call it noise. That's what they did.

Actually, they didn't call it noise, they called it "context" --

 "If you experience odors in a similar context, even if they were initially rather different in the responses they evoked in the nose, they begin to be represented by similar neural responses so they become the same in your head," Balasubramanian says.

The researchers found that their simplified model could be used to reproduce the same types of results seen in olfaction experiments. It's something that Balasubramanian did not expect to see, as he thought that such a complex process would require "learning and plasticity" in order to adapt and change neural synapses to modify the brain's representation of smells. "We may have found a general strategy of using certain kinds of randomized signals to entrain those effects," he says about their results. "It doesn't have to be just olfaction; it can be elsewhere, too." -medicalexpress

Did you see that? "It doesn't have to be olfaction; it can be elsewhere too." Olfactively-piqued, computational information neuroscientist, where have you been? Proving that the nose-brain is the neural model par excellence, while showing us how it actually works, both at the same time.

*If you want to know more about why olfaction is the ideal model for growing an artificial brain from scratch, it's a constant theme in Hidden Scents.

via University of Pennsylvania: Gaia Tavoni et al, Cortical feedback and gating in odor discrimination and generalization, PLOS Computational Biology (2021). DOI: 10.1371/journal.pcbi.1009479

Post Script:
This study shouldn't be mentioned without this other study, where they taught an artificial network how to smell, via Massachusetts Institute of Technology's McGovern Institute for Brain Research: Peter Y. Wang et al, Evolving the olfactory system with machine learning, Neuron (2021). DOI: 10.1016/j.neuron.2021.09.010. http://dx.doi.org/10.1016/j.neuron.2021.09.010

Post Post Script:
Might as well put this here, since it has to go somewhere -- what happens when you take an information scientist and give them an olfactory science problem? This is what happens. They come up with an answer that is so simple it just makes you look stupid. This is an example, although not a true example, of the other half of the coming dark ages. After a global pandemic, it's inevitable to experience a kind of dark ages, where lots of people died, but way more people got sick, and also a lot of people retired. That's a post-pandemic-pandemic of institutional knowledge loss, like a collective long covid brain fog on our culture -- we forget how to do stuff, because the guy who did it for the past 30 years isn't doing it anymore. That guy either died, got too sick to work, or retired for a million other reasons, of which many of them could be pandemic-related. And there's lots of those guys (and even more of them gals). Who knows what that will look like for us today or tomorrow, but it's happening as we speak, and years from now we might notice, we might even call it the great forgetting. The flip side to the dark ages is the renaissance, which comes from all the new people in new roles and at new jobs. These people are coming in new, with nobody around to teach them how to do things "right," and although that makes for a bumpy road ahead, it also gets you things like this discovery, one of the hardest problems of olfaction taken on by someone who has not much at all to do with olfaction (although he should, because olfaction has been an information science problem all along).

Wednesday, November 24, 2021

Olfaction In Silico

Artificial networks learn to smell like the brain
Nov 2021, phys.org

No kidding, the sensory apparatus that resembles a deep learning neural network can be simulated with a deep learning neural network -- "Artificial networks trained to classify odor identity recapitulate the connectivity inherent in the olfactory system."

The part of our brain that smells is also the most primitive. Before brains were a thing, bacteria performed chemosensory calculations on the primordial soup. As the soup became more complex, so did sensory equipment. Chemosensitive receptors on the surface of a bacterium became antennae, and then became noses, and those noses became seeing, hearing, even speaking brains. But the first version is the one used for smelling. So it shouldn't be a surprise that the first place we see a direct link between the mammalian brain and our artificial instantiation is via olfaction. Nonetheless, the scientists were "surprised to see it replicate biology's strategy so faithfully."

"By showing that we can match the architecture very precisely, I think that gives more confidence that these neural networks can continue to be useful tools for modeling the brain," says Robert Yang, assistant professor in MIT's departments of Brain and Cognitive Sciences and Electrical Engineering and Computer Science [and who collaborated on this project with Columbia neuroscientists Richard Axel and Larry Abbott, btw].

They use an antennae model, and the indispensable fruit fly, but it's all close enough to humans, I mean that's why we use the fruit fly in the first place. They started with some artificial neurons, of the same amount found in a fruit fly. They programmed the neurons to identify odors, and to assign valence (pleasant or unpleasant) to odors. They didn't give the neurons any structure, no information about how to talk to each other, no blueprint on how to process information. Just pre-programmed neurons, thrown into a simulated universe of chemosensation.

In minutes, and in silico, a network emerged to look just like the nose-brain of a fruit fly. All on its own, "an initially homogeneous population of neurons segregated into two populations with distinct input and output connections, resembling learned and innate pathways." 

In other words, it learned how to smell. It took evolution some billions of years to get the fruit fly olfactory system just right. The artificial network did it in minutes. Extrapolations from the study abstract: "This implies that convergent evolution reflects an underlying logic rather than shared developmental principles."

*Their structure used expansion and compression layers, similar to the pyramidal-structure of the nose-brain, and the number of inter-connections was also the exact same number as in the fruit fly, and it worked with both feedforward and recurrent network models, and the networks are plastic, meaning they can learn new odor associations over time.  

via Massachusetts Institute of Technology's McGovern Institute for Brain Research: Peter Y. Wang et al, Evolving the olfactory system with machine learning, Neuron (2021). DOI: 10.1016/j.neuron.2021.09.010

Post Script:
The book Hidden Scents talks about how olfaction is an ideal model for understanding an artificial brain, for an artificial human. 

Although artificial neural networks resemble natural neural activity patterns, like those used by the visual cortex for object recognition, we still don't understand how the visual cortex, or most mammalian neural circuits, are inter-connected. This time, we see how they connect, a connectome of the olfactory cortex.

Post Post Script:
And this study should be kept alongside this other one, where a physics-based computational neuroscientist came up with a pretty simple way to mimic the olfactory cortex, via University of Pennsylvania: Gaia Tavoni et al, Cortical feedback and gating in odor discrimination and generalization, PLOS Computational Biology (2021). DOI: 10.1371/journal.pcbi.1009479

Thursday, October 21, 2021

Nobody Is an Expert at Everyday Smells, Not Even the Smell Experts

If you find the language of smell interesting, Asifa Majid is the scientist to follow. This is a study from 2016, but it never hurts to be reminded that your ability to perform overt olfactory exploration on your environment is likely way worse than it could be. 

We don't talk about smells, and that's part of the reason why we can't identify them. A forgotten milk box in a student's locker over summer vacation may just as well be a poor rodent who happened to die under your staff refrigerator. These are pretty different smells, but they're both "bad," and that's about as much as we need to know. (They're both protein-based, so those two descriptions are not too far apart.)

Now you might think that a wine expert would be an ideal model for a chemosensing humanoid, but no. Experts are only good at smelling the things they've been trained to smell. They are only good at smelling what they already have words for. Granted, they have lots more words than your average person, but only words for odorants specific to their discipline.
Experts only have a limited, domain-specific advantage when communicating about smells and flavors:
Neither expert group was any more accurate at identifying everyday smells or tastes. Interestingly, both wine and coffee experts tended to use more source-based terms (e.g., vanilla) in descriptions of their own area of expertise whereas novices tended to use more evaluative terms (e.g., nice).
-Not All Flavor Expertise Is Equal: The Language of Wine and Coffee Experts. Ilja Croijmans, Asifa Majid. June 2016,  PLoS ONE 11(6): e0155845. https://doi.org/10.1371/journal.pone.0155845
Putting things in perspective, it should be noted that a master perfumer has a vocabulary of **thousands** of words for smells, which is ten times more than the wine or coffee expert. (You want to know some of the words are in the smell lexicon for coffee experts? Check out the World Coffee Research Sensory Lexicon and scroll down to "Publications;" and then you can compare that to the 1,000+ descriptors in the Sigma Aldrich catalog of fragrance chemicals which are purchased by perfumers to make perfume.)

If you want to be an "Everyday Smell Expert" all you have to do is start to come up with a vocabulary of your own for the smells around you, and then start paying attention. Soon you'll be able to recognize odors in your environment at really low thresholds, and maybe even be able to accurately  associate them with their source. 

Post Script:
Later in the paper, the idea of cultural difference as inhibiting our olfactory prowess:
"The difficulty people have in naming smells and flavors could be a WEIRD (Western, Educated, Industrialized, Rich, Democratic) affair. -source

So another approach to becoming a better everyday-smeller would be to try growing up in a non-WEIRD country.

Thursday, October 14, 2021

Neuromorphic Odor Translator Helps Robots Express Their Feelings

Neural network trained to properly name organic molecules
Aug 2021, phys.org

Do you ever have a problem naming that smell? It's not just you. Science has this problem too, but maybe not for long. 

Smells are volatile organic compounds that have evaporated and entered your nose. Although they almost always occur in combination with others and not in isolation, us humans want to reduce smells to their individual components, and then name them. After all, in order to think about something, you have to know it's name. (Is that true?) 

The problem is that organic molecules are big, with lots of chemicals joined together in lots of ways, so coming up with a naming convention for all these permutations is hard. IUPAC, the International Union of Pure and Applied Chemistry, sets the convention for naming molecules. And boy is it complicated.

Take sugar, a common molecule known to us by its simple name "sucrose;" in IUPAC, it's called (2R,3R,4S,5S,6R)-2-[(2S,3S,4S, 5R)-3,4-dihydroxy-2,5-bis(hydroxymethyl)oxolan-2-yl]oxy-6-(hydroxymethyl)oxane-3,4,5-triol.

Since we do live in the computer age, folks want to automate this naming process for when they discover new molecules. But as you can imagine by looking at the IUPAC name for sucrose, the algorithm at the core of that naming convention is really hard to write. So they decided to use a neural network instead.*

*I'm casually calling a neural network "neuromorphic," but in the past few years, real neuromorphic computers have forced a distinction here that I'm ignoring here for the sake of a more clickable title. 

This new artificially intelligent chemical translator is not a magical structure-to-name translator that can just look at a chemical and give it a name; that's still out of reach. It does, however, translate between IUPAC and another naming convention called SMILES.

Trained on PubChem's 100 million molecules, this translator ultimately shows how the utility of the new approach of using neural networks to help us write algorithms from the bottom up instead of the top down, which really is a revolution in computing. 

And if you think it would be cool to have robots that can smell, or to ensure that future humans maintain their sense of smell as they evolve into hyperdimensional algorithms, then making odors machine-readable is how you do that.

via Skolkovo Institute of Science and Technology, Lomonosov Moscow State University and start-up Syntelly: Lev Krasnov et al, Transformer-based artificial neural networks for the conversion between chemical notations, Scientific Reports (2021). DOI: 10.1038/s41598-021-94082-y

Thursday, October 7, 2021

On Olfactory Navigation

I purposely read this book Supernavigators (2019) hoping to get some snippets on using our sense of smell to find things, and I wasn't disappointed. 

Humans were led to a random location within a room diffused with two odors. After brief sampling and spatial disorientation, they had to return to this location. Humans located the target with higher accuracy in the olfaction-only condition than in the control condition and showed higher accuracy than chance. 
-Jacobs, L.F.; Arter, J.; Cook, A.; and Sulloway, FJ. (2015). "Olfactory orientation and navigation in humans," PLOS 'One, 10(6), e0129387. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4470656/

Note there are two different versions of olfactory navigation -- one where you track an odor to its source (this relies heavily on bilateral input, aka stereo-olfaction) and the other, much more common for modern-day humans, is when you identify a place by its odor. We usually have our eyes open, and being the ocularcentric creatures that we are, we are likely to use visual cues and not even realize the odor-identity of a place. 

But it doesn't stop here, the rabbit hole continues, and this one goes all the way back to the golden days of behavioral science, when rats told us everything we wanted to know about ourselves: 
This report is ultimately based on rat experiments, with the "men" part being only conjecture by the researcher; and he concedes, "My argument will be brief, cavalier, and dogmatic. For I am not myself a clinician or a social psychologist. What I am going to say must be considered, therefore, simply as in the nature of a rat psychologist's ratiocinations offered free.
*Ratiocinations are another word for thoughts that also happens to remind the reader that we're talking about rats (he italicized the rat in ratiocinations).

The "mapmaking" happens during what they call "Vicarious Trial and Error" or "VTE'" and described as "the hesitating, looking-back-and-forth, sort of behavior which rats can often be observed to indulge in at a choice-point before actually going one way or the other." If you're not a scientist, you can probably just call it "thinking."

via Berkeley Labs: Tolman, E.C. (1948). "Cognitive maps in rats and men," Psychological Review, 55(4), p.189.
And with that, let us not forget that olfaction is the first sense. Before all the other ways we sense our environment, bacteria and fungi were using chemotaxis, detecting and navigating their way through a world of chemical gradients. The essay at the end of Hidden Scents, called "Olfactory Space and n-Dimensionality" tells the story of the primordial eukaryote as it chemo-taxis its way through evolution, past the multi-cellular organism, the chordata (animals with vertebrate), and eventually to the big-brained, smooth-skinned monkeys that we are today.

The neocortex is an outgrowth of the nose-brain, and not the other way around, and therefore olfaction can be a useful model for understanding the n-dimensional information network in which our brains operate. The world is typically understood as a 3-dimensional space, but in fact, from the perspective of the brain, we are navigating and interacting with an infinitely-dimensional information space. 


Thursday, September 30, 2021

Temporal Patterns in Olfactory Perception

Temporality in olfactory perception is understudied. But as our ability to measure spike activity over small timescales improves, so will our understanding of olfaction, and human behavior in general.

On Time

Facebook knows what's up; they're making Time Cards for computers and networks so they can perform better, and integrate information better. They understand the mismatch between the size of today's clocks vs the speed of information. 

Today's clocks go down to the picosecond (trillionth of a second), and some things are being measured at the femtoscond (quadrillionth of a second). There's even some zepto-sensitive devices out there. The smaller the time-slice, the better your pattern recognition. Even back as far as Barabási's Bursts (2010) we knew that high resolution temporal patterns could be really informative of network behavior. More people in your study is also helpful, but networks like Facebook are running out of people* (but bots are infinite!), so they have to find another way of mining user data, hence an interest in temporal activity. 

If you think the fine-grained timing of patterns isn't that big a deal, why don't you ask the New York Stock Exchange, which is actually not located on Wall Street, but a few miles away in Carteret, New Jersey, because high frequency trading algorithms compete with each other at such high speeds (the speed of light) that they need the extra light-seconds provided by placing their servers a few miles closer to the international trunk connecting the Internet to the United States (it's called a latency advantage; and that trunk actually lands in Manasquan, a town on the Jersey Shore; still, closer to Carteret than New York).

The point here is that light travels fast, and if we want to understand it, then we will need to look at smaller and smaller slivers of the clock, and add this to the growing body of knowledge about how.

On Olfactory Timing

Think about it -- the brain is a network of billions of blinking neurons. Consciousness, or any neural activity, is an intelligent organization of these blinking neurons into meaningful patterns. But when you have billions of lights blinking on and off at the same time, you need to start slicing up the "time," so it's not all happening "at once." 

In the world of olfactory perception, a new look at the temporal side of things should supplement the intense interest we're seeing in this subject (check out the books Smellosophy or Nose Dive, and stutter at the thought of a $2 million grant in olfactory artifact research).

The author of Smellosophy, Barwich, actually gets into this aspect of olfaction. For her, it's a major distinction in the way we categorize olfactory information - between the historical approach to "mapping" the receptors of the two-dimensional olfactory bulb to "measuring" the timing of receptor activity, which includes the temporal dimension.

She argues that the measurement approach can reveal a key to the coding of the olfactory network. Olfaction is not just about identifying the different molecules present and their combinatorial patterns, but about when they appear and at what concentrations, and how these concentrations change over time. After all, olfaction is about detecting change, which implies time.

She says, "Rather than molecules, your brain depicts transient information patterns" (p246)
-Smellosophy: What the Nose Tells the Mind, A.S. Barwich, 2020, Harvard University Press

And here's a recent article on the topic:

Fast changing smells can teach mice about space
May 2021, phys.org
Mice can sense extremely fast and subtle changes in the structure of odors and use this to guide their behavior. The findings, published in Nature today, alter the current view on how odors are detected and processed in the mammalian brain.

via The Francis Crick Institute: Ackels, T., Erskine, A., Dasgupta, D. et al. Fast odour dynamics are encoded in the olfactory system and guide behaviour. Nature (2021). doi.org/10.1038/s41586-021-03514-2
Post Script:
Start with the 2014 article from Princeton (cited below) that said Facebook is losing its users like a susceptible-infected-recovered model of disease transmission, and that it would be done by 2018. Granted the article came from the unlikely Department of Mechanical and Aerospace Engineering in Princeton, and despite all the bad press, we can now fast forward to 2018 when Facebook is suspected to be more bots than people. Or is it that the people are acting more bot-like as they co-evolve with engagement algorithms in the artificial arena of natural selection. Bottom line is, social media networks, and all technologies adopted by individuals in a society, will follow a similar disease model. 

Not to mention, the bad press (possibly influenced by the same entity that took a full-page ad in the New York Times btw, and somewhere around 100K in case you were wondering) didn't age well.

But I'll let you be the judge of that:
"Facebook may be a massive drain on our attention that some people get sick of, but that doesn’t mean it actually operates like a virus." -TechCrunch, 2014
Epidemiological modeling of online social network dynamics, John Cannarell, Joshua A. Spechler. Department of Mechanical and Aerospace Engineering, Princeton University. arxiv:1401.4208v1 [cs.SI] 17 Jan 2014. https://arxiv.org/pdf/1401.4208v1.pdf

Post Post Script:
Zeptoseconds - New world record in short time measurement
Oct 2020, phys.org

Thursday, September 23, 2021

Olfacotry Camouflage

Scientists used 'fake news' to stop predators from killing endangered birds—and the result was remarkable
Mar 2021, phys.org

Amazing; you just don't hear about olfactory camouflage much:

Odors emanating from the shorebirds' feathers and eggs attract these scent-hunting mammals, which easily find the nests.

Five weeks before the shorebirds arrived for their breeding season in 2016, we mixed the odors with Vaseline and smeared the concoction on hundreds of rocks over two 1,000-hectare study sites. We did this every three days, for three months.

The predators were initially attracted to the odors. But within days, after realizing the scent would not lead to food, they lost interest and stopped visiting the site.

via: Grant L. Norbury et al. Misinformation tactics protect rare birds from problem predators, Science Advances (2021). DOI: 10.1126/sciadv.abe4164

Image credit: Lord of the Rings, scene where the Black Rider sniffs and misses.

Friday, September 10, 2021

Olfactory Training for Olfactory Dysfunction

Parking this here for future reference, and for anyone still having trouble getting their sense of smell back:

Hura N, Xie DX, Choby GW, Schlosser RJ, Orlov CP, Seal SM, Rowan NR. Treatment of post-viral olfactory dysfunction: an evidence-based review with recommendations. Int Forum Allergy Rhinol. 2020 Sep;10(9):1065-1086. doi: 10.1002/alr.22624. Epub 2020 Jun 25. PMID: 32567798; PMCID: PMC7361320. https://pubmed.ncbi.nlm.nih.gov/32567798/

Background: Post-viral olfactory dysfunction (PVOD) is one of the most common causes of olfactory loss. Despite its prevalence, optimal treatment strategies remain unclear. This article provides a comprehensive review of PVOD treatment options and provides evidence-based recommendations for their use.

Methods: A systematic review of the Medline, Embase, Cochrane, Web of Science, Scopus, and Google Scholar databases was completed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies with defined olfactory outcomes of patients treated for PVOD following medical, surgical, acupuncture, or olfactory training interventions were included. The Clinical Practice Guideline Development Manual and Conference on Guideline Standardization (COGS) instrument recommendations were followed in accordance with a previously described, rigorous, iterative process to create an evidence-based review with recommendations.

Results: From 552 initial candidate articles, 36 studies with data for 2183 patients with PVOD were ultimately included. The most common method to assess olfactory outcomes was Sniffin' Sticks. Broad treatment categories included: olfactory training, systemic steroids, topical therapies, a variety of heterogeneous non-steroidal oral medications, and acupuncture.

Conclusion: Based on the available evidence, olfactory training is a recommendation for the treatment of PVOD. The use of short-term systemic and/or topical steroids is an option in select patients after careful consideration of potential risks of oral steroids. Though some pharmacological investigations offer promising preliminary results for systemic and topical medications alike, a paucity of high-quality studies limits the ability to make meaningful evidence-based recommendations for the use of these therapies for the treatment of PVOD.

And don't forget:
Monell Center Scientists Find that Insulin is Necessary for Repairing Olfactory Neurons: Findings Point to Possible Treatment for Smell Loss
May 2021 - Monell Center

Thursday, September 9, 2021

Dark Taxa AKA Creating Taxonomies From Scratch

New norms needed to name never-seen fungi
May 2021, phys.org

There's 150,000 species of fungi known, yet a projected 2.2 to 3.8 million still waiting to be discovered (these are called dark taxa). But because of advances in DNA sequencing and microscopy, we're learning so fast that we need a new way to organize it all. 

This comes up in the context of biosecurity, where it can only work if "organisms detected can be reliably identified and have accurate names." For fungi, that's not really possible, because believe it or not, we don't have a good catalog of fungi. 
-via: Robert Lücking et al. Fungal taxonomy and sequence-based nomenclature, Nature Microbiology (2021). DOI: 10.1038/s41564-021-00888-x

We also don't have a good way to organize the words we use to describe everyday smells, and we don't have something like a "smell taxonomy." There are plenty of sub-domains that organize their relevant smells, found in subjects like coffee, wine, perfume, and culinary arts. They always seem to take the form of a wheel (not the most complex form). You can get a good start with everyday smells at the South Coast Air Quality Management District, who created a "Characterization of Odor Nuisance" odor wheel, with the help of environmental scientist Jane Curren at UCLA circa 2016. It was based on a bunch of phone calls made to the District where people were complaining about odors in their neighborhood. She took all the words they used and organized them. 

You could also look into Ann-Sophie Barwich who is a cognitive scientist who did her dissertion on olfactory categorization, and then wrote a book called Smellosophy. Probably one of the most interesting academics you will ever hear of. I mean, her master's thesis was about the relevance of  Leibniz causality on biological classification.

Image credit: Penicillin, Kew Royal Botanical Gardens for BBC

State of the World's Fungi, by the Kew Royal Botanical Gardens (2018), is the first ever State of the World's Fungi report revealing how important fungi are to all life on Earth. [pdf]
[State of the World's Fungi]

International Commission on the Taxonomy of Fungi (ICTF)

MycoBank is the on-line repository and nomenclatural registry provided in collaboration between the International Mycological Association and the Westerdijk Fungal Biodiversity Institute. It provides a free service to the mycological and scientific society by databasing mycological nomenclatural novelties (new names and combinations) and associated data, such as descriptions, illustrations and DNA barcodes. Nomenclatural novelties are each allocated a unique MycoBank number to be cited in the publication where the nomenclatural novelty is introduced, to conform with the requirements of the International Code of Nomenclature for algae, fungi and plants.

Identification and quantification of nuisance odors at a trash transfer station. Jane Curren, et al.  PubMed, Waste Manag. 2016 Dec;58:52-61. doi: 10.1016/j.wasman.2016.09.021. Epub 2016 Sep 28.

Post Script:
I'm looking at a popular science article about fungi. The first two "interesting" points, when looked at together, remind me of why I always have the feeling like fungi are from outerspace:
  • Fungi are in a kingdom of their own but are closer to animals than plants
  • They have chemicals in their cell walls shared with lobsters and crabs (you do know we're all becoming crabs, right?)

Monday, August 30, 2021

Promiscuous Pattern Recognition

Study reveals how smell receptors work
Aug 2021, phys.org

Big smell news - for the first time ever, using cryo-electron microscopy, we can see an olfactory receptor in action. And as expected, it doesn't work like any other receptor.

Odorant receptors are known for their 'promiscuous chemical sensitivity;' that's a scientific term, by the way. It means that any one receptor might be sensitive to hundreds of molecules, so it's been really hard  to figure out what makes any particular molecule match with a receptor.

They looked at the jumping bristletail (surprise - not the fruit fly) because it has only five types of receptors, and because one of those receptors (OR5) is really broad, responding to 60% of the smell molecules they presented to it (promiscuous).

So they look at this receptor in its default state, and then again as they expose it to smell molecules (either eugenol or DEET).

And? Its ion channel pore dilates. That's it. Both of the competing theories about how smells work were wrong. It turns out they work via nonspecific chemical interactions -- they are not recognizing a specific chemical characteristic, but something more general about the molecule itself.

And there you have it! Olfaction is still one of the strangest senses we have.

Don't forget to thank cryo-electron microscopy, and the hundreds of scientists who have been trying to figure this out over the past hundred years.

via Rockefeller University: del Mármol, J., Yedlin, M.A. & Ruta, V. The structural basis of odorant recognition in insect olfactory receptors. Nature (2021). https://doi.org/10.1038/s41586-021-03794-8

Tuesday, August 24, 2021

Amoore' Anosmias Get a Tune-Up

Back in the 1960's, a scientist named John Amoore tried to get a number on how much our sense of smell varies from person to person. In his study (limited mostly to Europeans), he found that half are anosmic to something. That was long before we sequenced the human genome. This study goes a bit further:

There's a gene for detecting that fishy smell, olfactory GWAS shows
Oct 2020, phys.org
9,000 people in Iceland showed that not only do they smell licorice and cinnamon differently, but there's a mutation that makes rotten fish smell a little less fishy. (The odors they used weren't limited to these three, there were also lemon, peppermint, and banana.)

One of the genes is called a "non-canonical olfactory receptor gene" or a trace amine receptor, TAAR 5 in this case. People with a particular variant of this gene were more likely to not smell anything when presented with the fish odor or to use descriptors for it that were neutral or positive and not seafood related, such as "potatoes," "caramel," and "rose."

"Carriers of the variant find the fish odor less intense, less unpleasant, and are less likely to name it accurately," Gisladottir said. 

"We discovered a common variant in a cluster of olfactory receptors which is associated with increased sensitivity to trans-anethole, found in black licorice products but also in spices and plants such as anise seed, star anise, and fennel," Gisladottir said. "Carriers of the variant find the licorice odor more intense, more pleasant, and can name it more accurately. Interestingly, the variant is much more common in East Asia than in Europe."

The cinnamon variant influenced the perception of trans-cinnamaldehyde, the major ingredient in both Chinese and Ceylon cinnamon. Carriers of the variant can name the cinnamon odor more accurately, they report. They also find it more intense.

via deCODE Genetics in Reykjavik, Iceland: Current Biology, Gisladottir et al.: "Sequence variants in TAAR5 and other loci affect human odor perception and naming. DOI: 10.1016/j.cub.2020.09.012

Post Script:
Here's another way to measure the difference in how we smell things -- we have a 30% variation from person to person:
378-dimensional individual olfactory receptor subtype genome:
Individual olfactory perception reveals meaningful nonolfactory genetic information.
Secundo L, Snitz K, Weissler K, Pinchover L, Shoenfeld Y, Loewenthal R, Agmon-Levin N, Frumin I, Bar-Zvi D, Shushan S, Sobel N. Proc Natl Acad Sci U S A. 2015 Jul 14; 112(28):8750-5.

Friday, August 20, 2021

On Handshakes and Animal Behavior

AKA Olfactory Sampling

Non-human primates Mark Zuckerberg and Pope Francis shaking hands and about to smell each other's chemosignals once they start covertly raising their hands near their face in about 20 seconds from now.

After you shake someone's hand, you smell your own hand. Sometimes the shaking hand, and sometimes the opposite, depending on the gender match. They call it "olfactory sampling," but we call it "smelling your fingers," and despite its being in poor taste while in public view, we do it almost neurotically, albeit covertly -- so covertly that even we don't notice ourselves doing it. 

I'm surprised this didn't resurface at the outset of the pandemic when we were all paying so much attention to how often we touch our face. In fact, the authors set us up thus:
Consistent with previous studies (Nicas and Best, 2008), we observed that humans often bring their hands to their noses. Of 153 subjects, 85 (55.55%) touched their nose with their hand at least once during baseline before the greet. Idle subjects had a hand (either right or left) at the vicinity of their nose for 22.14% of the time. (that's a lot of time!)
But this isn't just about how you can't keep your own hands off yourself:
Whereas facial self-touching has been considered a form of displacement stress response (Troisi, 2002), akin to rodent grooming, the novel framework we propose here for this behavior is that of olfactory sampling.
In this really carefully controlled study, they videotaped  hundreds of people after shaking hands with a greeter at the lab, and even outfitted the subjects tubes near their nose to monitor their sniffing behavior. The results were "unequivocal," and remind us that we are in fact animals, sniffing up a storm:
We found that humans often sniff their own hands*, and selectively increase this behavior after handshake. After handshakes within gender, subjects increased sniffing of their own right shaking hand by more than 100%. In contrast, after handshakes across gender, subjects increased sniffing of their own left non-shaking hand by more than 100%. Tainting participants with unnoticed odors significantly altered the effects, thus verifying their olfactory nature. Thus, handshaking may functionally serve active yet subliminal social chemosignaling, which likely plays a large role in ongoing human behavior.

*For example, by touching their nose when they were in the room on their own; ... Criterion for scoring was any application of a hand to the face, as long as touching was under the eyebrows and above the chin; n=271 down to 153.
And later on in the report, things get even more complicated:
The body odor of some of the experimenters was tainted by perfumes or gender-specific odors. Volunteers who shook hands with these tainted individuals behaved differently; when the experimenter was tainted with perfume the volunteers spent more time sniffing their own hands, but when the experimenter was tainted with a gender-specific odor they spent less time sniffing of their own hands. This shows that different smells influenced the hand sniffing behavior of the volunteers.
Now that you know, you might notice yourself doing it constantly. What would be really interesting now would be to somehow get some anosmics up in the mix, maybe congenitally, maybe some recent long covid anosmics, and see how these numbers change?

Frumin I, et al. [incl Noam Sobel] A social chemosignaling function for human handshaking. eLife. 2015 Mar 03;4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4345842/

Tuesday, August 17, 2021

Did Someone Say Cheese?

Those funky cheese smells allow microbes to 'talk' to and feed each other
Oct 2020, phys.org

The more you learn, the more complicated it gets. So we know that the funky cheese smell of isovaleric acid is produced by bacteria, and we know that (some) cheese has fungus growing on it. But now we're told that they're all talking to each other, using other odor molecules.

The "cheese microbiome." Cheese doesn't house only one bacteria species, and it doesn't make only one smell, although isovaleric acid is a pretty good representative. There's a whole cheese microbiome, made of bacteria, yeast and fungi. Each one of these organisms secretes goop that digests their food, in this case that's the cheese. Their goop is kind of like making the whole world your stomach, where your digestive juices aid your digesting al fresco. As their external digestion approach does its thing, the target nutrients get broken down, and a by-product of that breakdown are odorous volatile organic compounds. 

What these researchers have discovered is that fungi also release VOCs, but instead of being an important part of the smell of cheese, they communicate to bacteria. Some bacteria accelerate their growth in the presence of the right fungi-gas. Others get real shy and shut down. These fungus VOCs do real-time genetic modification on the bacteria, changing the way they metabolize nutrients. They also eat the VOCs themselves. They eat smells. We can't eat smells. 

Anyway, the cheese microbiome now contains a VOC-ome sub-component, and this study hints that one day we may be looking very carefully at these VOC-omes, especially in the bio-factories of the future. 

via Tufts University: Casey M. Cosetta et al, Fungal volatiles mediate cheese rind microbiome assembly, Environmental Microbiology (2020). DOI: 10.1111/1462-2920.15223

Thursday, August 12, 2021

Odeuropa's Olfactory Iconographies

€2.8M grant for research project on European olfactory heritage and sensory mining:

Odeuropa bundles expertise in sensory mining and olfactory heritage. We develop novel methods to collect information about smell from digital text and image collections. They will identify and trace olfactory information in text and image datasets using AI, and promote Europe’s tangible and intangible cultural heritage.

Here's one of their ongoing projects, seen in the picture above, an odor wheel based on art historical references to smells: The Odeuropa Art Historical Scent Wheel from the Mediamatic Aroma Lab.

The Odeuropa “Nose first art historical odour wheel” starting from scent families in the centre, connected to odorants in the second ring, and then to artworks and artefacts around that, ending with an outer ring with Iconclass codes. Iconclass is a multilingual online database that museums use to tag historical images and artworks. -link

This wheel is based on imagery like paintings that were then coded with words, allowing a machine-readable dataset of odors, which will become increasingly more popular as we apply this approach to larger and more recent datasets, such as the Wikimedia Commons, or the running corpus of Instagram's zero-liked images.
Speaking of datasets, there are many to choose, from dog breeds to aerial photographs to 3 million "Clickbait, spam, crowd-sourced headlines from 2010 to 2015," to "4,000 physical dimensions of abolone." Wikimedia commons has 7.5 million images.

Looking back at the odor wheel, there are some interesting associations here. But they do reflect the dataset. I'm having a hard time finding details on Iconoclass but it was developed by one person in the 1950's, and based I assume on Western Art. It's currently maintained by RKD Netherlands Institute for Art History.

Here's some examples -- "street scenes and horses;" not a common conjunction in today's world. "Unicorns and cinnamon," anyone? "Prostitutes and civet," less unexpected. The two "body odors" are armpit and vagina, fyi. 

The most interesting part of all this? The lead researcher Sofia Ehrich has "become familiar with detecting depictions of smell." She can smell words and pictures. 

And speaking of words and pictures: 
Ocularcentric - like a visual bias, like we as humans tend to have an ocularcentric view of the world, with our trichromatic vision and fancy visual cortices, etc. 

Mediamatic (in Amsterdam) is an art centre dedicated to new developments in the arts since 1983. We organize lectures, workshops and art projects, focusing on nature, biotechnology and art+science in a strong international network.

IconoClass dataset -  specialized library classification designed for art and iconography.

Lifting One's Hat

Layers of IconClass system

This is an example of the layers of the IconoClass system, pretty deep stuff. You can see how the image has words attached to it, making it a machine-readable cultural object. This is how we will teach robots of the future how to better understand us, and maybe we can even teach them how to smell.

Mario Klongmann x BigGAN - 2019

Mostly Unrelated Post Script:
An AI Artist’s Twitter Feed Is an Art Gallery
The images and videos Mario Klingemann posted under the hashtag #BigGAN can only be appreciated by treating his Twitter feed as a digital exhibition. (Images taken from the ImageNet dataset)
Feb 2019, Hyperallergenic

This AI Creates Art From Instagram Posts With Zero Likes
“Zero Likes” is trained to create glitchy visuals from forgotten social media images.
May 2017, Vice

Melbourne artist and coder Sam Hains created Zero Likes, an AI trained to respond only to those lost and lonely images that miss out on attention.

Tuesday, August 10, 2021

Headline Party

My first master's degree was in architecture, and I graduated the day the United States housing market collapsed. So my second master's was in public health, and I got my first job the day Planet Earth went into pandemic lockdown. Expertise in indoor air quality and occupant exposure during an airborne pandemic will make your life pretty busy. Hence, a list of smell-related headlines I've been collecting in the meantime:

Unparalleled inventory of the human gut ecosystem
Jul 2020, phys.org
The Unified Human Gastrointestinal Genome (UHGG) collection, comprising 204,938 nonredundant genomes from 4,644 gut prokaryotes. These genomes encode >170 million protein sequences, which we collated in the Unified Human Gastrointestinal Protein (UHGP) catalog. 

via the European Bioinformatics Institute: Alexandre Almeida et al. A unified catalog of 204,938 reference genomes from the human gut microbiome, Nature Biotechnology (2020). DOI: 10.1038/s41587-020-0603-3
Fresh sea spray turns 'sour' after being airborne
Jan 2021, phys.org
"The smallest particles become 100,000 times more acidic than the ocean within two minutes," said Angle, first author of the paper.

via University of California San Diego: Kyle J. Angle et al. Acidity across the interface from the ocean surface to sea spray aerosol, Proceedings of the National Academy of Sciences (2020). DOI: 10.1073/pnas.2018397118
Researchers create a highly sensitive biohybrid olfactory sensor
Jan 2021, phys.org
So we decided to combine existing biological sensors directly with artificial systems to create highly sensitive volatile organic compound (VOC) sensors. We call these biohybrid sensors."

Takeuchi and his team essentially grafted a set of olfactory receptors from an insect into a device that feeds certain odors to the receptors and also reads how the receptors respond to these odors. 

via the University of Tokyo: T. Yamada el al. Highly sensitive VOC detectors using insect olfactory receptors reconstituted into lipid bilayers. Science Advances (2021). DOI: 10.1126/sciadv.abd2013
Male butterflies mark their mates with repulsive smell during sex to 'turn off' other suitors
Jan 2021, phys.org

Butterfly genitals secrete an odor that covers female genitals, deterring other males from mating with them. Occimene - it's the anti-aphrodisiac (for moths).

via University of Cambridge: Darragh K, Orteu A, Black D, Byers KJRP, Szczerbowski D, Warren IA, et al. (2021) A novel terpene synthase controls differences in anti-aphrodisiac pheromone production between closely related Heliconius butterflies. PLoS Biol 19(1): e3001022. 

Cosmic mouthful - Tasters savor fine wine that orbited Earth
Mar 2021, phys.org
This comes via the Institute for Wine and Vine Research in Bordeaux, and of course the International Space Station.
Researchers develop new smell test for Parkinson's, Alzheimer's and COVID-19
May 2021, phys.org
A new smell test developed by Queen Mary University of London researchers has been found to be easy to use in patients with Parkinson's disease, and could also be helpful in diagnosing COVID-19 in the broader population.

via  Queen Mary, University of London: A. Said Ismail et al. A novel capsule-based smell test fabricated via coaxial dripping, Journal of The Royal Society Interface (2021). DOI: 10.1098/rsif.2021.0039
Scientists invent an artificial nose for continuous bacterial monitoring
Jun 2021, phys.org
via Americans for Ben-Gurion University: Nitzan Shauloff et al, Sniffing Bacteria with a Carbon-Dot Artificial Nose, Nano-Micro Letters (2021). DOI: 10.1007/s40820-021-00610-w

Thursday, August 5, 2021

Diabetes x Anosmia

Interesting theme here; anosmia, insulin and Covid:

It appears that long-Covid has more to do with the pancreas and insulin regulation than we thought, and this has implications for the health of our olfactory receptors.

Research from the Monell Center found that insulin may be able to treat smell loss:
1. Insulin plays a critical role in the maturation, after injury, of immature olfactory sensory neurons (OSNs). 

2. The research team induced diabetes type 1 in mice to reduce levels of circulating insulin reaching the OSNs. The reduced insulin interfered with the regeneration of OSNs, resulting in an impaired sense of smell. 

3. In addition, the team injured OSNs, which have a unique ability to regenerate in mammals. This approach allowed the investigators to ask whether OSNs required insulin to regenerate, which they found to be true. What’s more, they discovered that OSNs are highly susceptible to insulin deprivation-induced cell death eight to 13 days after an injury. This time window indicates that during a critical stage newly generated OSNs are dependent on insulin. They also found that insulin must be applied to regenerating OSNs at this critical time point in the neurons’ growth to be able to restore a mouse’s sense of smell.

4. Insulin promotes regeneration of regenerating OSNs in both type 1 diabetic and nondiabetic mice.

Monell Center Scientists Find that Insulin is Necessary for Repairing Olfactory Neurons: Findings Point to Possible Treatment for Smell Loss, May 2021
Post Script:
July 2021, phys.org
An increase in new-onset hyperglycemia and abnormal hormone levels lasting months after Covid infection in Italy; "This study is one of the first to show that COVID-19 has a direct effect on the pancreas," says Fiorina.

via Children's Hospital Boston: Laura Montefusco et al, Acute and long-term disruption of glycometabolic control after SARS-CoV-2 infection, Nature Metabolism (2021). DOI: 10.1038/s42255-021-00407-6

Sebastiano Bruno Solerte et al, Sitagliptin Treatment at the Time of Hospitalization Was Associated With Reduced Mortality in Patients With Type 2 Diabetes and COVID-19: A Multicenter, Case-Control, Retrospective, Observational Study, Diabetes Care (2020). DOI: 10.2337/dc20-1521

Tuesday, August 3, 2021

Nanon Nanoff

Please ignore the potential environmental disaster of embedding nanoparticles all over the planet, and instead focus on how we are reverse engineering the process of chemosensation.

Plants communicate with chemicals the way we use words. Many, almost all, of the chemicals that populate the aromatic repertoire of the fragrance industry are plant-derived. If they do not come from the plant itself, as an essential oil, then they are synthetically produced in chemical reactors, yet, the target product will have originated to imitate the molecule found in nature.

Now, we get one example of synthetic biology doing the work. Imagine the scaled-up version, the chemical factory is now a biological plant, like a factory, but modeled on an actual plant, like lemongrass, but then run through bacteria programmed to produce citronellol.

Granted the nanosized sensors described in this article below are not producing any molecules, only sensing them. But any synbio fragrance plant would need a good sensor network. 

Also, "nanobionic plants" 

Carbon nanotubes embedded in leaves detect chemical signals that are produced when a plant is damaged
Apr 2020, phys.org
These sensors can be embedded in plant leaves, where they report on hydrogen peroxide signaling waves.

Plants use hydrogen peroxide to communicate within their leaves, sending out a distress signal that stimulates leaf cells to produce compounds that will help them repair damage or fend off predators such as insects. The new sensors can use these hydrogen peroxide signals to distinguish between different types of stress, as well as between different species of plants.

"Plants have a very sophisticated form of internal communication, which we can now observe for the first time. That means that in real-time, we can see a living plant's response, communicating the specific type of stress that it's experiencing," says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT.

via Massachusetts Institute of Technology: Tedrick Thomas Salim Lew et al. Real-time detection of wound-induced H2O2 signalling waves in plants with optical nanosensors, Nature Plants (2020). DOI: 10.1038/s41477-020-0632-4
Unrelated image credit: Krzysztof Marczak via Deviant Art

Post Script:
Center for Strategic and International Studies Headquarters, Washington DC
February 6, 2020

Thursday, June 3, 2021

Artificial Olfactory Perception and the Olfactome

Chemical informatics, machine learning and the indispensable fruit-fly, Drosophila melanogaster have been used by researchers at University of California Riverside to predict odor perception. 

Olfactory prediction is kind of a holy grail of sensory perception. Sounds sus. Let's get into the data.

image credit: Diatom, by Dr. Jan Michels for Nikon Small World 2020

Using artificial intelligence to smell the roses
Aug 2020, phys.org

First sentence they're referencing Asifa Majid. That's a great start. Her work shows us that culture, language and experience influence individual odor perception. Nonetheless, the search for the human odor code continues.

After reducing a larger dataset of 84 olfactory receptors and 54 allelic variants (138 total), they took 34 receptors, each of which is controlled by a single gene, and trained machines to predict their descriptors. The descriptors, or "the words we would use to describe the smell," came from the Vosshall Keller Rockefeller University 2016 lexicon. They've got about 170 odorants, working on 34 receptors. 

Remember that each odor receptor gene can be activated by a number of chemicals, sometimes by only one, but usually by more than one. This is what makes things complicated. Olfaction is a combinatorial affair that breaks down at the granular level.

And they made a model for each receptor, 34 different models, and fed those models the odorants. They found that you could predict chemical properties of the molecules that match each receptor tested. So now, we can use the 450,000 library of chemicals, run them through each of the 36 artificial receptors, and predict what those receptors would perceive.

Figure 5A: Few Key ORs or Chemical Features Sensibly Cluster the Perceptual Descriptors
(A) Dendrogram representation of the Euclidean distances among perceptual descriptors based on overlap of perceptual response data (% Usage) from chemicals in the ATLAS study.
(B) Dendrogram from the top five ORs picked per perceptual descriptor.
(C) Dendrogram created from five randomly chosen ORs per perceptual descriptor.
(D) Dendrogram from the five best overall predictors including OR and chemical features per perceptual descriptor. Clustering is hierarchical and based on Euclidean distance (A) or the Jaccard distance (B–D). Cluster number (colored branches) inferred from gap statistic across bootstrap samples. [find the pdf for fine-resolution]

I think, and I could be wrong, but it seems the big deal here is that they made a model for each receptor, instead of just making one model for all receptors. Whereas others have created an n-dimensional predictive space to collapse the behemoth of the chemosphere into a single equation, this team just reverse-engineered the receptors themselves.

They haven't found the odor code, but they did write 34 of them. We have hundreds of olfactory receptors. That's not everything, but we are definitely getting there.

What it CAN do? It can help us discover new chemicals, and also to discover substitutes for other chemicals that are expensive, rare, or ethically-troublesome (fear-pheromones from tortured cats for example).

What it CAN'T do? It can't predict how an odor will smell to you, as an individual. It can approximate, however, and pretty good. They mention only getting 20% of the human olfactome, or human olfactory receptor repertoire.

via UC Riverside: Joel Kowalewski et al. Predicting Human Olfactory Perception from Activities of Odorant Receptors, iScience (2020). DOI: 10.1016/j.isci.2020.101361

Post Script:
They mention something called the ATLAS dataset, but I don't know what that is, other than a proprietary data analysis software. Maybe it's their own dataset through ATLAS?

And for fun, I'll report that they do mention "substantive portion of odor identity arises early in the processing stream" which is a good way of describing the the two-layer perception process of olfaction.

The second layer, and this is the one that Asifa Majid tells us is influenced by culture, experience, and language: "It is likely that the remaining portion depends on experience-dependent modulation, supporting a downstream model with reliance on distributed neuronal networks for human perceptual coding."

Further: "Unlike the retinotopic and tonotopic patterning observed in the visual and auditory cortices, representing spatiotemporal properties of visual and auditory stimuli as they are processed at sensory neurons, piriform activity appears randomly distributed, without a clear mapping of physicochemical features (Stettler and Axel, 2009)."

Interesting: "In our analyses, the OR specialized for musk was not a top candidate for
musk predictions but contributed strongly to predictions of 'sweaty.'"

Perhaps because the model isn't "smelling" it among other calculated fragrant mixtures such as perfumes, but rather "in the wild?" 

Post Post Script:
Can't talk about the odor code without mentioning code smell, a term for when something is wrong with your code, but we're not sure what it is. 

Also, going deep on the topic here:
The Dream of Olfaction Prediction

Thursday, May 20, 2021

Olfactory Overload

For centuries, smell has been considered the lowest sense. Even Science itself has avoided it. No more; olfaction is experiencing an absolute revolution.

Oh really? Yes. Consider for a moment, the €2.8M price tag on this European olfactory heritage and sensory mining project, called Odeuopa. That's a nice price tag for research on the history of smells.

I review a few hundred articles every week, pulling aside anything I see on olfaction. Some weeks there's a good article, maybe two, sometimes nothing. Much of the time, the article is about a development in hi-tech sensors or electronic noses, or how the East doesn't like "new car smell" and what Western car companies are doing about it... . 

But now, about once a month for seven months in a row, another piece of research surfaces to enrich our understanding of olfactory perception. Not just hype-cycle blurbles, but domain-foundation scientific breakthroughs are redefining how we think about olfaction, and our models of how it works.

The news is that each one of us employs a dynamic, combinatorial chemosensory system. It's capable of adapting in real time to an ever-changing environment, and it's using a combinatorial network of hundreds of genetically-determined olfactory receptors working in unison to identify and interpret any possible combination of odorous chemicals that we could ever be exposed to. 
First, a reminder of what it means to be using a "combinatorial" approach to perception. Epistemologically, combinatorics comes from mathematics, but combinatoric optimization and combinatorial dynamical systems are subfields of this domain, usually found in areas like graph theory or network theory. These areas overlap with the "brains" of our early 21st century artificial intelligence machines -- the deep learning neural networks you should be hearing about daily. 

But what does it mean for olfaction to be combinatorial? It means that olfaction is all gestalt. We don't use one type of neuron to smell one type of smell. We use a bunch for each, and they overlap too. In other words, it's a mess.

Some odorants, in theory, could activate (or inhibit) every receptor we have (roughly 400 functional). And it's the combination of all those excitations and inhibitions that create odor identity. That's a lot of combinations. And you would need all of them to identify that one odorant. And if you lost only one, by viral infection for example, that thing would not smell the same. In reality, this is not how it works because it's a lot more complicated, and there are so many exceptions to the rule that it's barely a rule. But it's getting clearer by the day. 

The main point of a combinatorial system is that you can't "map" it (it's a mess, remember?). This is something Science has been trying to do for a long time. Using language as an intermediary, this attempt to map the olfactory dimension started with the Dravnieks dataset, a bunch of odorous molecules mapped to descriptors produced by people who smell those molecules:

Dravnieks A. Atlas of odor character profiles. Philadelphia: ASTM; 1985.

Arctander is also used to organize the aromasphere by way of language: 

Arctander S. Perfume and flavor chemicals (aroma chemicals). Montclair, NJ: Author; 1969.

But then things changed. The DREAM dataset is produced, using huge chemoinformatics datasets for the individual molecules, mapped against equally huge semantic analysis datasets made of a bustling lexicon of odor words. This paper via Leslie Vosshall's lab in Rockefeller University sums it up:

Keller A, Vosshall LB. Olfactory perception of chemically diverse molecules. BMC Neurosci. 2016 Aug 8; 17(1):55. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4977894/

Multidimensional Folds - Lach - 2010

And now onto 2020, a big year for olfaction. Figures so much of this will be overshadowed by a raging global pandemic.

In March, a study from Hebrew University shows us that our olfactory receptors are not just activated but inhibited, and that they can change over time from one to the other. Back in 2006, Wilson and Stevenson's book Learning to Smell investigated this idea of the blank slate. The thing is, optogenetics wasn't invented yet. Well it may have been invented, but they weren't slipping glass fibers into mouse neurons to monitor their activity in real time. We're not looking at the psychology of smell anymore but the actual neurological behaviors of it. 

And they see that the receptors themselves do in fact learn, change, adapt, and even revert back to a previous state. I've repasted this description already elsewhere on this site, because it's such a big deal, but again:
The general profile of excitatory vs. inhibitory responses by mitral cells changed with learning and task demands. In naive animals, most responsive cells (71%) responded by excitation to the odours. Following the learning of the 5-decision boundary task, the ratio of excitatory/inhibitory responses reversed. After learning, the majority (71.4%) of neurons now responded by inhibitory calcium transients to the odours (Fig. 6C,E). The ratio of inhibitory vs. excitatory responses reverted back to normal after retraining the mice on the 1-decision boundary task. Specifically, 73.3% of responsive neurons were again excitatory on day 18.
via Hebrew University: Flexible Representations of Odour Categories in the Mouse Olfactory Bulb. Elena Kudryavitskaya, Eran Marom, David Pash, Adi Mizrahi. Hebrew University of Jerusalem. Mar 24 2020. BioRxiv. doi: https://doi.org/10.1101/2020.03.21.002006

April. When you hear the phrase "more than the sum of its parts," that's codeword for things combinatorial. This one doesn't use the optogenetics described above, but an imaging technique called SCAPE microscopy:

Making sense of scents - 3-D videos reveal how the nose detects odor combinations
Apr 2020, phys.org
Using a cutting-edge 3-D imaging method called SCAPE microscopy, the Columbia team monitored how thousands of different cells in the nose of a mouse responded to different odors—and mixtures of those odors. They found that the information that the nose sends to the brain about a mixture of scents is more than just the sum of its parts.
The researchers expected to see that the cells activated by mixtures of odors would be equivalent to adding together responses to individual odors. In fact, they found that in some cases an odor can actually turn off a cell's response to another odor in a mixture [previously known via violet ionones]; in other cases, a first odor could amplify a cell's response to a second odor.
The team's data challenged the traditional view that the brain makes sense of a mixture of scents by figuring out all of the individual components. It confirmed what perfumers have long known: combining different scents can create a certain experience on its own, essentially becoming an entirely new scent that can provide a completely different experience.
via Stuart Firestein's lab at Columbia University: L. Xu el al., "Widespread receptor-driven modulation in peripheral olfactory coding," Science (2020). https://science.sciencemag.org/cgi/doi/10.1126/science.aaz5390

Multidimensional - Oliver Panthsdown - 2008

Skipping May, June shows us "synthetic olfactory perception" which is exactly what it sounds like.

Researchers at New York University's Langone Health Center simulated olfactory perception with a synthetic electronic odor signal. In laymen's terms, mouse noses were tricked into thinking they smelled something when it was actually just an electrical signal. This is kind of like the way you can open someone's skull and zap certain parts of their brain, and they will feel tingles in corresponding parts of their body, even though you're not touching those parts of their body (don't try this at home though).

There are also some interesting results from this study that support the mostly-uncontroversial yet definitely misunderstood theory of information processing in the olfactory bulb, which is that the detection of odor-representations is more of a combinatorial process, and less of a one-to-one system of odor molecules and neuron receptors. And, this combinatorial perception theory is a primary reason as to why we cannot comprehensively organize olfactory experience into subsets or primary odors. (And the reason for writing a book about the language of smell.)

via NYU Langone: Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. Edmund Chong, Christopher Wilson, Shy Shoham, Stefano Panzeri, Dmitry Rinberg. Science 19, Jun 2020, Vol. 368, Issue 6497, eaba2357. DOI: 10.1126/science.aba2357

Later on, in July, Harvard Medical School releases a similar study, showing "flexible cortical representations in odor space" here:

via Harvard Medical School: Stan L. Pashkovski et al, Structure and flexibility in cortical representations of odor space, Nature (2020). DOI: 10.1038/s41586-020-2451-1. http://dx.doi.org/10.1038/s41586-020-2451-1 [alt link] https://www.newsbreak.com/news/1593236184136/structure-and-flexibility-in-cortical-representations-of-odour-space

Sum-of-its-parts strikes again, July. 

Engineering and philosophy combine for an emerging understanding of smell
Jul 2020, phys.org
Shi Nung Ching of the Preston M. Green Department of Electrical & Systems Engineering, and doctoral student Sruti Mallik developed computational models of neural circuits that mimic the sensory act of smelling. They found the models also manifest certain properties analogous to those observed in olfactory sensory processing in insect brains.

Researchers found that their sensory system model developed emergent properties—properties that are more than the sum of their parts, so to speak—similar to properties seen in an insect's antennal lobe, which is important for its sense of smell.
via Washington University in St Louis: Sruti Mallik et al. Neural Circuit Dynamics for Sensory Detection, The Journal of Neuroscience (2020). DOI: 10.1523/JNEUROSCI.2185-19.2020

Astral Fragments - Stacy Young - 2016

Onto August. They're looking at the rat hippocampus; because that's the place where memories are stored, and it's hardwired into the olfactory system, the limbic system. They're showing that the brain identifies things differently over time. In a way, saying that there is no objective reality, only subjective multitudes:

via the University of Technology Sydney: Laura A. Bradfield et al. Goal-directed actions transiently depend on dorsal hippocampus, Nature Neuroscience (2020). DOI: 10.1038/s41593-020-0693-8

September, "sum of parts" again:

Nose's response to odors more than just a simple sum of parts
Sep 2020, phys.org
"New research from Kyushu University shows that a much more complex process is occurring, with some responses being enhanced and others inhibited depending on the odors present."
via Kyushu University: Shigenori Inagaki et al, Widespread Inhibition, Antagonism, and Synergy in Mouse Olfactory Sensory Neurons In Vivo, Cell Reports (2020). DOI: 10.1016

October shows us that you can teach yourself to smell better. I am compelled to remind the reader that olfactory receptor cells are the only part of your brain that pokes outside the body, making them very vulnerable. This also makes them a great point of entry for viruses invading the body, but it's also the reason why these cells regenerate profusely throughout most of our lives. And that's a reason why you can train yourself to smell better. 

These scientists basically stopped sending odors in the air to one nostril, and found that neurogenesis slowed down (use it or lose it). The idea is that as these cells re-grow, they may be changing the cell types in order to adapt to a changing environment. This is called stimulation-dependent neurogenesis, and although it's still up in the air as to how it all works, get in on the ground floor:

Study finds odor-sensing neuron regeneration process is adaptive
Oct 2020, phys.org

via University of Colorado Anschutz Medical Campus: Carl J. van der Linden et al, Olfactory Stimulation Regulates the Birth of Neurons That Express Specific Odorant Receptors, Cell Reports (2020). DOI: 10.1016/j.celrep.2020.108210

November now. Not olfaction specifically, but memory, which is closely related. The common theory has been that each memory gets its own neuron, but now an alternative model is ascending, and it looks more like the same group of neurons store all memories.

All the data we have on this stuff comes from fMRI. But fMRI can't see individual neurons. If we look at the neurons one at a time, we see something very different happening. 

This is certainly an idea to get familiar with. It should also fill you with wonder at what else we will figure out with rapidly-advancing neuro-tech:

Human intelligence just got less mysterious, neuroscientist says
Nov 2020, phys.org

via the University of Leicester: Rey HG, Gori B, Chaure FJ, Collavini S, Blenkmann AO, Seoane P, Seoane E, Kochen S, Quian Quiroga R. Single Neuron Coding of Identity in the Human Hippocampal Formation. Current Biology : Cb. PMID 32142694 DOI: 10.1016/j.cub.2020.01.035