Take time: odor coding capacity across sensory neurons increases over time in Drosophila

Münch, Daniel; Galizia, C. Giovanni

doi:10.1007/s00359-017-1209-1

Cited by 8 publications

(8 citation statements)

References 60 publications

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“…What is the neural correlate of odor source segregation based on odorant onset asynchrony? In the antennal lobe, synchronous odorant mixtures often induce neural activity patterns that lack part of the component information (synthetic mixture representation) (Deisig et al., 2006, Krofczik et al., 2009, Meyer and Galizia, 2012, Münch et al., 2013, Münch and Galizia, 2017, Silbering and Galizia, 2007). In contrast, asynchronous mixtures induce spatiotemporal activity patterns across projection neurons that partly match those evoked by the individual odorants (analytic mixture representation), and this asynchrony-induced shift from synthetic to more analytic mixture processing could support odor source segregation (Broome et al., 2006, Saha et al., 2013, Stierle et al., 2013) (for a modeling approach see Nowotny et al., 2013).…”

Section: Discussionmentioning

confidence: 99%

Olfactory Object Recognition Based on Fine-Scale Stimulus Timing in Drosophila

et al. 2019

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Summary Odorants of behaviorally relevant objects (e.g., food sources) intermingle with those from other sources. Therefore to determine whether an odor source is good or bad—without actually visiting it—animals first need to segregate the odorants from different sources. To do so, animals could use temporal stimulus cues, because odorants from one source exhibit correlated fluctuations, whereas odorants from different sources are less correlated. However, the behaviorally relevant timescales of temporal stimulus cues for odor source segregation remain unclear. Using behavioral experiments with free-flying flies, we show that (1) odorant onset asynchrony increases flies' attraction to a mixture of two odorants with opposing innate or learned valence and (2) attraction does not increase when the attractive odorant arrives first. These data suggest that flies can use stimulus onset asynchrony for odor source segregation and imply temporally precise neural mechanisms for encoding odors and for segregating them into distinct objects.

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Section: Discussionmentioning

confidence: 99%

Olfactory Object Recognition Based on Fine-Scale Stimulus Timing in Drosophila

et al. 2019

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“…Active sniffing or odor sampling strategies also dramatically alter synaptic interactions in the olfactory bulb, the first central synaptic processing site for odor-elicited sensory input [ 9 , 10 ]. The temporal dynamics of olfactory receptor neuron (ORN) responses during odor sampling is a critical determinant of the information available to the olfactory bulb [ 11 – 13 ] or its analog, the antennal lobe in insects [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Dynamics of odor sampling strategies in mice

et al. 2020

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Mammalian olfactory receptor neurons in the nasal cavity are stimulated by odorants carried by the inhaled air and their activation is therefore tied to and driven by the breathing or sniffing frequency. Sniffing frequency can be deliberately modulated to alter how odorants stimulate olfactory receptor neurons, giving the animal control over the frequency of odorant exposure to potentially aid odorant detection and discrimination. We monitored sniffing behaviors and odorant discrimination ability of freely-moving mice while they sampled either decreasing concentrations of target odorants or sampled a fixed target odorant concentration in the presence of a background of increasing odorant concentrations, using a Go-NoGo behavioral paradigm. This allowed us to ask how mice alter their odorant sampling duration and sampling (sniffing) frequency depending on the demands of the task and its difficulty. Mice showed an anticipatory increase in sniffing rate prior to odorant exposure and chose to sample for longer durations when exposed to odorants as compared to the solvent control odorant. Similarly, mice also took more odorant sampling sniffs when exposed to target odorants compared to the solvent control odorant. In general, odorant sampling strategies became more similar the more difficult the task was, e.g. the lower the target odorant concentration or the lower the target odorant contrast relative to the background odorant, suggesting that sniffing patterns are not preset, but are dynamically modulated by the particular task and its difficulty.

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“…In natural environments, animals encounter different temporal patterns of odor stimuli. D. melanogaster ORNs show diversity in their temporal response dynamics (Hernandez-Nunez et al 2015;Mathew et al 2013;Montague et al 2011;Munch and Galizia 2017;Nagel and Wilson 2011). A systematic analysis of the temporal dynamics of ORNs revealed that the response dynamics of an ORN depend on the combination of sensory neuron and odor (Munch and Galizia 2017).…”

Section: Section 3: Implications Of Neuronal Diversity For Circuit Functionmentioning

confidence: 99%

Strength in diversity: functional diversity among olfactory neurons of the same type

Slankster

Odell

Mathew

2019

J Bioenerg Biomembr

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Most animals depend upon olfaction to find food, mates, and to avoid predators. An animal's olfactory circuit helps it sense its olfactory environment and generate critical behavioral responses. The general architecture of the olfactory circuit, which is conserved across species, is made up of a few different neuronal types including first-order receptor neurons, second-and third-order neurons, and local interneurons. Each neuronal type differs in their morphology, physiology, and neurochemistry. However, several recent studies have suggested that there is intrinsic diversity even among neurons of the same type and that this diversity is important for neural function. In this review, we first examine instances of intrinsic diversity observed among individual types of olfactory neurons. Next, we review potential genetic and experience-based plasticity mechanisms that underlie this diversity. Finally, we consider the implications of intrinsic neuronal diversity for circuit function. Overall, we hope to highlight the importance of intrinsic diversity as a previously underestimated property of circuit function.

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Take time: odor coding capacity across sensory neurons increases over time in Drosophila

Cited by 8 publications

References 60 publications

Olfactory Object Recognition Based on Fine-Scale Stimulus Timing in Drosophila

Olfactory Object Recognition Based on Fine-Scale Stimulus Timing in Drosophila

Dynamics of odor sampling strategies in mice

Strength in diversity: functional diversity among olfactory neurons of the same type

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