The Ongee - A Nose-Wise Society

The Adamanese people, along with the Ongee, are from the Bay of Bengal and have a very rich vocabulary for smells.

"There is no language for smells, because it bypasses the language centers of the brain.”

This is one of the basic ideas behind Hidden Scents, and is taken from a recent interview I did. I would like to welcome public commentary of the above quote as an opportunity to mention a very special culture, The Ongee:

public commentary:

“Not true of all cultures, some have a rich language to describe smells.”

The commenter is correct in that there are cultures using a much richer vocabulary for their olfactory experience than the one used in any Western culture.

an excerpt from a concluding section in my book:

In the Bay of Bengal live the Ongee people. A “nose-wise” society, they treat olfaction with as much importance as Western vision. When the West once asked the Ongee for help in making a map of their land, the Ongee man responded: “All the places in space are constantly changing. The creek is never the same; …. Your map tells lies. Places change. Does your map say that?” (Pandya 1991). Smell is like this. Whether through the meanderings of history, or the chimerical configurations of post-modernity, smell is always changing. The Ongee are right; there are no maps, no categories, and no lexicon to show that.

Pandya V (1990). Movement and Space: Andamanese Cartography. American Ethnologist 17:775–797.

***

For those interested, I should also mention Asifa Majid, who currently does work on this precise subject. She studies the odor lexicon of the The Aslian (Austroasiatic) languages of the Malay Peninsula, Southeast Asia.

Odors are expressible in language, as long as you speak the right language. Asifa Majid and Niclas Burenhult. Cognition, November 2013.

Post Script:

Currently, there are only 94 native speakers of Ongee, confined to a single settlement in the northeast of Little Andaman island, making it an endangered language.

Ethnologue: Languages of the World

Lewis, M. Paul, Gary F. Simons, and Charles D. Fennig (eds.). 2015. Ethnologue: Languages of the World, Eighteenth edition. Dallas, Texas: SIL International.

Revisiting the Motor Cortex

All of the images here represent your somatosensory cortex, the part of your brain that senses and controls the corresponding parts of your body. The goofy image that is forever paired with this concept was illustrated by Dr. Wilder Penfield, and never changed thereafter, until, of course, Joe Scordo did it for Hidden Scents, see below.

The 'Homunculus' illustrated by Joe Scordo for Hidden Scents

Penfield's image is perhaps the most well known in representing the motor cortex. Because of the success of the image, he is confused as having discovered it. It was, in fact, discovered decades earlier.

The Penfield map has changed little in the years since its release. Whether or not scientific diagrams should be updated to withstand current aesthetic considerations is beside the point. The 'Homunculus' illustrated by Joe Scordo for Hidden Scents is another step in the sequence of representation and seriality.

Multimodal Crosstalk

Make it stop.

Got an article here in Wired where we learn about how we taste, and about how we sense everything, really. The brain doesn’t see sensory information as sense-specific, it processes everything together. In the article, psychologist Charles Spence relates it to signal processing – the brain has to process all the signals to figure out what’s good and what’s not. And what we get back is not raw sensory input; instead all the signals interfere with each other, distorting and reshaping each other. Changing the color of white wine to red makes people “taste” red wine. Changing the lights in a room makes you “hear” differently. Senses even distort themselves. White noise makes other noises seem further away; it distorts the aural space of the listener (see Beckerman below).

I bring up all of this because, why, our sense of smell is the most obvious candidate for proving the multi-modal sensory processing of our brains. Smells can be Sharp, Sour, or Green. In fact, smell is one sense that we do not experience as its own. All of the words we use to describe smells come from other senses; and it can be argued that we only experience smell by proxy of the other senses. Perhaps it is too primitive of a phenomenon to translate to the cognizant, self-reflective human – it is the first sense, after all, and made its appearance on the Tree of Life with the Vertebrates, and hence with brains (the two go together).

Lost in Translation

Notes:

Your Senses Are Talking Behind Your Back

Brendan Cole, Wired, July 2016

Professor Charles Spence, at Oxford, studies applied cognitive psychology, consumer psychology, sensory marketing, and multisensory perception. And that would make him a man of interest here at Limbic Signal. He also deals a lot with the future of food.

The Sonic Boom: How Sound Transforms the Way We Think, Feel, and Buy. Joel Beckerman. 2014.

On Space and Place

Confused John Travolta

The hypothalamus is called the seat of social behavior. The hippocampus is the thing that knows where you are, your internal GPS. Together, these brain parts, along with your olfactory system, of course, influence all of your decisions. Everything we do is dependent on where we are (or where we think we are) and who we’re with (or who we think…). Olfactory data informs these things. Places and the smell of those places are centrally located both in the memory and in the motivating, motility actuating parts of us. The emotions that drive us are informed by the smells of the places we are in.

This new report shows that there may be very specific cells that can tell who’s house you’re in. (The experiment is on male mice and other male’s habitats.) They’re looking to use this to help people with social disorders, like autism, schizophrenia, depression, and social anxiety. Anyway, this just points to the use of olfactory studies to help with larger social problems.

Smell tells intruder mice how to behave

phys.org, Jun 2016

Bed Bug Signal

The shed skin of bed bugs time-releases smell compounds that signal to other bed bugs where a good spot to bed down is located. They call it pheromones, but to me, that just makes the whole thing sound even funnier.

Shed skins of bed bugs emit pheromones that could help combat infestations of the insect

July 2016, phys.org

Deep AI Making Strides

Inceptionism Iteration

Born from my dual interest in both building systems and neural networks, this post is a bit off-track for Limbic Signal, but not really – we’re looking here at neural networks, the ones mentioned in Hidden Scents. The neural networks used to run Google’s Deep Mind are similar to the workings of the olfactory bulb in the way they use layers of feedback systems to recognize patterns.

Deep Mind is in the news because it cut the electricity bills at one of Google’s buildings by a lot. The thing about these self-learning algorithms, if you will, is that the way they work, or how they work, is really unknown to us. They are using an optimization algorithm to generate their results, which means making microtweaks on hundreds of variables and in realtime. It’s the opposite of a silver bullet approach to energy efficiency (and it's also the way we learn to smell, and why smells mean different things to different people). I’ll let the researchers themselves talk about it; this is from their blog:

DEEPMIND AI REDUCES GOOGLE DATA CENTRE COOLING BILL BY 40%

20 JULY 2016, Rich Evans, Research Engineer, DeepMind and Jim Gao, Data Centre Engineer, Google

“Each data centre has a unique architecture and environment. A custom-tuned model for one system may not be applicable to another. Therefore, a general intelligence framework is needed to understand the data centre’s interactions.

...

“We accomplished this by taking the historical data that had already been collected by thousands of sensors within the data centre -- data such as temperatures, power, pump speeds, setpoints, etc. -- and using it to train an ensemble of deep neural networks. Since our objective was to improve data centre energy efficiency, we trained the neural networks on the average future PUE (Power Usage Effectiveness), which is defined as the ratio of the total building energy usage to the IT energy usage. We then trained two additional ensembles of deep neural networks to predict the future temperature and pressure of the data centre over the next hour. The purpose of these predictions is to simulate the recommended actions from the PUE model, to ensure that we do not go beyond any operating constraints.

...

“Our machine learning system was able to consistently achieve a 40 percent reduction in the amount of energy used for cooling, which equates to a 15 percent reduction in overall PUE overhead after accounting for electrical losses and other non-cooling inefficiencies. It also produced the lowest PUE the site had ever seen.

...

And furthermore, I’ve taken a piece from another one of their posts:

DEEP REINFORCEMENT LEARNING

17TH JUNE 2016, David Silver, Google DeepMind

“However, deep Q-networks are only one way to solve the deep RL problem. We recently introduced an even more practical and effective method based on asynchronous RL. This approach exploits the multithreading capabilities of standard CPUs. The idea is to execute many instances of our agent in parallel, but using a shared model. This provides a viable alternative to experience replay, since parallelisation also diversifies and decorrelates the data. Our asynchronous actor-critic algorithm, A3C, combines a deep Q-network with a deep policy network for selecting actions. It achieves state-of-the-art results, using a fraction of the training time of DQN and a fraction of the resource consumption of Gorila. By building novel approaches to intrinsic motivation andtemporally abstract planning, we have also achieved breakthrough results in the most notoriously challenging Atari games, such as Montezuma’s Revenge.”

Post Script

I can’t talk about Deep Mind without mentioning Deep Dream though: check out what it looks like for a computer to dream, it’s basically a new artform called Inceptionism, and it comes from these neural networks.

A World Without Smells

 

Alex Grey - Dying

We’re reading about Ed Yong’s new book, I Contain Multitudes. It’s about the microbiome and how it runs our bodies.

Wired writer Sarah Fallon interviews Yong, and one of the first thing she asks is this –

“What would happen if every germ on Earth suddenly vanished?”

To which Yong responds –

“All hell would break loose. Animals that eat grass (deer, cows, horses) would starve, since they need germs in their stomachs to digest cellulose. Coral would bleach out. “In the deep oceans, many worms, shellfish, and other animals rely on bacteria for all of their energy,” Yong writes. “Without microbes, they too would die, and the entire food webs of these dark abyssal worlds would collapse.” And don’t stand there all smug, vegetarians. Microbes make nitrogen, and plants need nitrogen, so there’s the rest of the food supply shot. Also, as Yong says, “microbes are lords of decay.” There would be shit (and rotting leaves and dead bodies) everywhere.”

Cool. Now, first thing I ask is – what does this smell like? But wait, does it smell at all? And then, wait, microbes do all the decomposing, all of it. So not only is there no rotting, there’s no decomposition of any kind, isn’t that right? Everything stays in a state of suspended bacterial animation. And now I’m thinking a bit far afield and off subject, but does that mean somehow ridding a planet of its microbes is a kind of instant fossilization?

Notes:

Germs Are Magic and Other Things We Learned From Ed Yong’s New Book

Sarah Fallon, 2016 July 28, Wired

Link to Harper Collins