Molecular complexity determines the number of olfactory notes and the pleasantness of smells

Kermen, Florence; Chakirian, Amandine; Sezille, Caroline; Joussain, Pauline; Goff, Gaëlle Le; Ziessel, Anne; Chastrette, M.; Mandairon, Nathalie; Didier, Anne; Rouby, Catherine; Bensafi, Moustafa

doi:10.1038/srep00206

Cited by 93 publications

(33 citation statements)

References 28 publications

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“…When human smells an odorant, olfactory neurons (as receptor cells) detect odor molecules and transmit information about the odor to the brain in a process called sensory transduction which yields to perception46. Based on the research done by Kermen et al 47,. high complexity odorants activate more types of olfactory receptor than low complexity odorants.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Fractal Based Analysis of the Influence of Odorants on Heart Activity

Namazi

Kulish

2016

Sci Rep

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An important challenge in heart research is to make the relation between the features of external stimuli and heart activity. Olfactory stimulation is an important type of stimulation that affects the heart activity, which is mapped on Electrocardiogram (ECG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the ECG signal. This study investigates the relation between the structures of heart rate and the olfactory stimulus (odorant). We show that the complexity of the heart rate is coupled with the molecular complexity of the odorant, where more structurally complex odorant causes less fractal heart rate. Also, odorant having higher entropy causes the heart rate having lower approximate entropy. The method discussed here can be applied and investigated in case of patients with heart diseases as the rehabilitation purpose.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Fractal Based Analysis of the Influence of Odorants on Heart Activity

Namazi

Kulish

2016

Sci Rep

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“…The dotted line represents the p < 0.05 significance threshold with respect to random predictions. The performance of four equations for pleasantness prediction suggested by Zarzo (10) [from top to bottom: equations (10, 9, 11, 7, 12)] and of a linear model based on the first seven principal components inspired by Khan et al (8) are shown.…”

Section: Figmentioning

confidence: 99%

“…Pleasantness was predicted most accurately using a mix of both Dragon and Morgan/NSPDK features. For example, pleasantness correlated with both molecular size (r = .160 p < 10 −3 ) (9), and similarity to paclitaxel (r = 0.184 p < 10 −4 ) and citronellyl phenylacetate (r = 0.178 p < 10 −4 )(Fig. S6b).…”

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confidence: 99%

Predicting human olfactory perception from chemical features of odor molecules

Keller

Gerkin

Guan

et al. 2017

Science

253

289

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It is still not possible to predict whether a given molecule will have a perceived odor, or what olfactory percept it will produce. We therefore organized the crowd-sourced DREAM Olfaction Prediction Challenge. Using a large olfactory psychophysical dataset, teams developed machine learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models accurately predicted odor intensity and pleasantness, and also successfully predicted eight among 19 rated semantic descriptors (“garlic”, “fish”, “sweet”, “fruit,” “burnt”, “spices”, “flower”, “sour”). Regularized linear models performed nearly as well as random-forest-based ones, with a predictive accuracy that closely approaches a key theoretical limit. These models help to predict the perceptual qualities of virtually any molecule with high accuracy and also reverse-engineer the smell of a molecule.

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“…Whereas psychophysical investigations have shown that such hedonic processing of smells is influenced by physicochemical properties (Khan et al, 2007; Mandairon et al, 2009; Poncelet et al, 2010; Joussain et al, 2011; Kermen et al, 2011; Zarzo, 2011), many other experiments, however, showed that odor pleasantness can be modulated by physiological (Fernandez et al, 2013; Joussain et al, 2013a,b) or cognitive factors (Herz, 2003; Rolls, 2004; de Araujo et al, 2005; Barkat et al, 2008; Rinck et al, 2011). For example, it has been shown that pleasantness judgments are enhanced when subjects are able to identify the odorant source (Ayabe-Kanamura et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

Hedonic appreciation and verbal description of pleasant and unpleasant odors in untrained, trainee cooks, flavorists, and perfumers

et al. 2014

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Olfaction is characterized by a salient hedonic dimension. Previous studies have shown that these affective responses to odors are modulated by physicochemical, physiological, and cognitive factors. The present study examined expertise influenced processing of pleasant and unpleasant odors on both perceptual and verbal levels. For this, performance on two olfactory tasks was compared between novices, trainee cooks, and experts (perfumers and flavorists): Members of all groups rated the intensity and pleasantness of pleasant and unpleasant odors (perceptual tasks). They were also asked to describe each of the 20 odorants as precisely as possible (verbal description task). On a perceptual level, results revealed that there were no group-related differences in hedonic ratings for unpleasant and pleasant odors. On a verbal level, descriptions of smells were richer (e.g., chemical, olfactory qualities, and olfactory sources terms) and did not refer to pleasantness in experts compared to untrained subjects who used terms referring to odor sources (e.g., candy) accompanied by terms referring to odor hedonics. In conclusion, the present study suggests that as novices, experts are able to perceptually discriminate odors on the basis of their pleasantness. However, on a semantic level, they conceptualize odors differently, being inclined to avoid any reference to odor hedonics.

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Molecular complexity determines the number of olfactory notes and the pleasantness of smells

Cited by 93 publications

References 28 publications

Fractal Based Analysis of the Influence of Odorants on Heart Activity

Fractal Based Analysis of the Influence of Odorants on Heart Activity

Predicting human olfactory perception from chemical features of odor molecules

Hedonic appreciation and verbal description of pleasant and unpleasant odors in untrained, trainee cooks, flavorists, and perfumers

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