Mechanism for food texture preference based on grittiness

Li, Qiaoran; Montell, Craig

doi:10.1016/j.cub.2021.02.007

Cited by 39 publications

(35 citation statements)

References 45 publications

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“…Although TMEM63 proteins produce MS currents, their physiological roles remain largely unknown. A recent elegant study indicates that TMEM63 is crucial for the ability of flies to choose food based on particle size (Li and Montell, 2021). Typically, flies prefer foods with particle sizes that are typically found in fruits and budding yeast.…”

Section: Box 2 Caveats In Quantifying Ms Channel Currents In Drg Neuronsmentioning

confidence: 99%

“…This function is served by the mechanical activation of a subset of multidendritic neurons in the fly's major taste organ. Mutations disrupting TMEM63, but not other known MS channels including PIEZO, TMC, and NOMPC, abrogate the fly's ability to discriminate between food particle sizes (Li and Montell, 2021). Thus, TMEM63 is required for sensing small particles in food, which exert gentle mechanical forces on the labellum.…”

Section: Box 2 Caveats In Quantifying Ms Channel Currents In Drg Neuronsmentioning

confidence: 99%

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PIEZO channels and newcomers in the mammalian mechanosensitive ion channel family

Delmas

Parpaite

Coste

2022

Neuron

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Section: Box 2 Caveats In Quantifying Ms Channel Currents In Drg Neuronsmentioning

confidence: 99%

Section: Box 2 Caveats In Quantifying Ms Channel Currents In Drg Neuronsmentioning

confidence: 99%

PIEZO channels and newcomers in the mammalian mechanosensitive ion channel family

Delmas

Parpaite

Coste

2022

Neuron

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“…For example, chocolate with a particle size above 35 μm is usually perceived as gritty or coarse in the mouth, and it is not accepted by consumers, nor is ice creams with ice crystals larger than 40 μm (Breen et al, 2019 ; De Pelsmaeker et al, 2020 ; Puleo et al, 2020 ; Servais et al, 2002 ). Interestingly, Li and Montell ( 2021 ) recently demonstrated that the Drosophila melanogaster is endowed with the ability to discriminate smoothness versus grittiness of food texture and uses this information to decide whether a food is appealing or not. One other angle here concerns the way that certain textures may be associated with specific taste qualities, as in the case of cotton candy/candy floss (see Spence et al, 2019 ).…”

Section: Food Texture Astringency and (Oral-somatosensory) Roughnessmentioning

confidence: 99%

Roughness perception: A multisensory/crossmodal perspective

Stefano

Spence

2022

Atten Percept Psychophys

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Roughness is a perceptual attribute typically associated with certain stimuli that are presented in one of the spatial senses. In auditory research, the term is typically used to describe the harsh effects that are induced by particular sound qualities (i.e., dissonance) and human/animal vocalizations (e.g., screams, distress cries). In the tactile domain, roughness is a crucial factor determining the perceptual features of a surface. The same feature can also be ascertained visually, by means of the extraction of pattern features that determine the haptic quality of surfaces, such as grain size and density. By contrast, the term roughness has rarely been applied to the description of those stimuli perceived via the chemical senses. In this review, we take a critical look at the putative meaning(s) of the term roughness, when used in both unisensory and multisensory contexts, in an attempt to answer two key questions: (1) Is the use of the term ‘roughness’ the same in each modality when considered individually? and (2) Do crossmodal correspondences involving roughness match distinct perceptual features or (at least on certain occasions) do they merely pick-up on an amodal property? We start by examining the use of the term in the auditory domain. Next, we summarize the ways in which the term roughness has been used in the literature on tactile and visual perception, and in the domain of olfaction and gustation. Then, we move on to the crossmodal context, reviewing the literature on the perception of roughness in the audiovisual, audiotactile, and auditory-gustatory/olfactory domains. Finally, we highlight some limitations of the reviewed literature and we outline a number of key directions for future empirical research in roughness perception.

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“…The gustatory system (sense of taste) consists of approximately 5000 taste buds, each containing approximately 100 taste receptors onto which molecules bind. A mechanically activated TMEM63 channel allows sensing the texture of food [75].…”

Section: Some Human Abilitiesmentioning

confidence: 99%

Facts and Anomalies to Keep in Perspective When Designing an Artificial Intelligence

Ipe¹

2021

Preprint

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The design of any artificial intelligence is an interdisciplinary pursuit that requires keeping within perspective, the various properties of matter and life in the known universe, while remaining cautious of biases and misconceptions that arise from the limitations of prior learning, available tools and sensory capabilities. This paper curates a vast collection of human knowledge gathered during the process of exploring and questioning the fundamentals of why the mechanisms that constitute life were built in specific ways, and re-questioning those facts using anomalies that sometimes contradict or expose errors in human assumptions of life and intelligence. A meta-analysis of such knowledge at a single glance also helps identify interesting patterns in various phenomena that can in-time, spur creative solutions, alter the direction of research, assist with intelligent inferences and hopefully result in the identification and creation of artificial intelligence.<br>

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Mechanism for food texture preference based on grittiness

Cited by 39 publications

References 45 publications

PIEZO channels and newcomers in the mammalian mechanosensitive ion channel family

PIEZO channels and newcomers in the mammalian mechanosensitive ion channel family

Roughness perception: A multisensory/crossmodal perspective

Facts and Anomalies to Keep in Perspective When Designing an Artificial Intelligence

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