Digitising Smell: From Natural Statistics of Olfactory Perceptual Space to Digital Transmission of Odors
The project aims to digitize smell by filling scientific gaps and developing a model to recreate odors, culminating in a proof of concept for remote odor transmission and public data sharing.
Projectdetails
Introduction
This proposal is framed by a technological goal: We aim to digitize smell. Achieving this is currently prevented by gaps in basic science. We aim to fill these gaps, culminating in a proof of concept for our model.
Identifying the Primary Gap
The primary gap we identify is the lack of data on what humans typically smell. Phrased conceptually, in Aim 1 we ask what are the natural statistics of human olfactory perceptual space.
Experimental Approach
We address this in a series of three experiments, highlighted by one where we equip participants with a wearable sampling apparatus we designed and built for this proposal. The apparatus:
- Measures sniffing behavior to identify odor sampling
- Measures neural activity to verify olfactory perception
- Takes video of the visual scene
- Analyzes total levels of volatile organic compounds in real time
- Collects odor samples for detailed analysis offline
In other words, we generate an olfactory equivalent of Google Street View, with the addition of chemical, perceptual, and neural data. Using this, we will characterize the natural statistics of human olfactory perceptual space.
Data Accessibility
Moreover, a major contribution of this proposal will be in posting this massive data as a publicly available resource.
Aim 2: Digitizing Olfactory Perception
Next, in Aim 2 we will use this data to digitize human olfactory perceptual space. We build on a model that allows us to recreate odors using a restricted set of odor primaries.
Frameworks for Testing
We will test our model in two frameworks:
- SmelloVision: We develop the algorithmic framework to generate an odor to match any digital image.
- TelleSmell: We develop a device to sense the environment, the algorithmic framework to transfer the data, and a device to generate the corresponding odor remotely.
Pilot Data
We provide pilot data for Aim 2 where we sensed an odor in Mainz (Germany), transmitted the data over IP to Rehovot (Israel), where we successfully recreated the smell. This was, as far as we know, the first transmission of odor over IP.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 11.835.892 |
Totale projectbegroting | € 11.835.892 |
Tijdlijn
Startdatum | 1-2-2024 |
Einddatum | 31-1-2030 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- WEIZMANN INSTITUTE OF SCIENCEpenvoerder
- KUNGLIGA TEKNISKA HOEGSKOLAN
- MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
- KAROLINSKA INSTITUTET
Land(en)
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Vergelijkbare projecten uit andere regelingen
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A circuit perspective on olfaction – how learning and context shape the propagation of information between brain areasThis project investigates how learning and context influence the propagation of sensory information in the olfactory system to the entorhinal-hippocampal network in mice. | ERC STG | € 1.500.000 | 2024 | Details |
Olfactormativity: Exploring the Intervening Performativity of SmellOLFAC investigates the performative power of smell in arts and politics to challenge social norms and explore its potential for change amidst issues of identity and power dynamics. | ERC COG | € 1.739.250 | 2024 | Details |
Smart Electronic Olfaction for Body Odor Diagnostics
SMELLODI aims to digitize and synthesize olfactory information for remote disease diagnostics and assist individuals with olfactory disorders using advanced sensor technology and machine learning.
Temporally complex odour information encoding
This project aims to uncover how the mammalian olfactory system processes dynamic odour information to inform navigation behavior through a multidisciplinary approach combining physiology and neuroscience.
A circuit perspective on olfaction – how learning and context shape the propagation of information between brain areas
This project investigates how learning and context influence the propagation of sensory information in the olfactory system to the entorhinal-hippocampal network in mice.
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