Slow presynaptic mechanisms that mediate adaptation in the olfactory pathway of Drosophila

Common principles for odour coding across vertebrates and invertebrates

The olfactory system is an ideal and tractable system for exploring how the brain transforms sensory inputs into behaviour. The basic tasks of any olfactory system include odour detection, discrimination and categorization. The challenge for the olfactory system is to transform the high-dimensional space of olfactory stimuli into the much smaller space of perceived objects and valence that endows odours with meaning. Our current understanding of how neural circuits address this challenge has come primarily from observations of the mechanisms of the brain for processing other sensory modalities, such as vision and hearing, in which optimized deep hierarchical circuits are used to extract sensory features that vary along continuous physical dimensions. The olfactory system, by contrast, contends with an ill-defined, high-dimensional stimulus space and discrete stimuli using a circuit architecture that is shallow and parallelized. Here, we present recent observations in vertebrate and invertebrate systems that relate the statistical structure and state-dependent modulation of olfactory codes to mechanisms of perception and odour-guided behaviour.

Prediction error drives associative learning and conditioned behavior in a spiking model of Drosophila larva

Predicting reinforcement from sensory cues is beneficial for goal-directed behavior. In insect brains, underlying associations between cues and reinforcement, encoded by dopaminergic neurons, are formed in the mushroom body. We propose a spiking model of the Drosophila larva mushroom body. It includes a feedback motif conveying learned reinforcement expectation to dopaminergic neurons, which can compute prediction error as the difference between expected and present reinforcement. We demonstrate that this can serve as a driving force in learning. When combined with synaptic homeostasis, our model accounts for theoretically derived features of acquisition and loss of associations that depend on the intensity of the reinforcement and its temporal proximity to the cue. From modeling olfactory learning over the time course of behavioral experiments and simulating the locomotion of individual larvae toward or away from odor sources in a virtual environment, we conclude that learning driven by prediction errors can explain larval behavior.

Active smelling in the American cockroach

Motion plays an essential role in sensory acquisition. From changing the position in which information can be acquired to fine-scale probing and active sensing, animals actively control the way they interact with the environment. In olfaction, movement impacts the time and location of odour sampling as well as the flow of odour molecules around the olfactory organs. Employing a detailed spatiotemporal analysis, we investigated how insect antennae interact with the olfactory environment in a species with a well-studied olfactory system - the American cockroach. Cockroaches were tested in a wind-tunnel setup during the presentation of odours with different attractivity levels: colony extract, butanol and linalool. Our analysis revealed significant changes in antennal kinematics when odours were presented, including a shift towards the stream position, an increase in vertical movement and high-frequency local oscillations. Nevertheless, the antennal shifting occurred predominantly in a single antenna while the overall range covered by both antennae was maintained throughout. These findings hold true for both static and moving stimuli and were more pronounced for attractive odours. Furthermore, we found that upon odour encounter, there was an increase in the occurrence of high-frequency antennal sweeps and vertical strokes, which were shown to impact the olfactory environment's statistics directly. Our study lays out a tractable system for exploring the tight coupling between sensing and movement, in which antennal sweeps, in parallel to mammalian sniffing, are actively involved in facilitating odour capture and transport, generating odour intermittency in environments with low air movement where cockroaches dwell.

Multifaceted luminance gain control beyond photoreceptors in Drosophila

Animals navigating in natural environments must handle vast changes in their sensory input. Visual systems, for example, handle changes in luminance at many timescales, from slow changes across the day to rapid changes during active behavior. To maintain luminance-invariant perception, visual systems must adapt their sensitivity to changing luminance at different timescales. We demonstrate that luminance gain control in photoreceptors alone is insufficient to explain luminance invariance at both fast and slow timescales and reveal the algorithms that adjust gain past photoreceptors in the fly eye. We combined imaging and behavioral experiments with computational modeling to show that downstream of photoreceptors, circuitry taking input from the single luminance-sensitive neuron type L3 implements gain control at fast and slow timescales. This computation is bidirectional in that it prevents the underestimation of contrasts in low luminance and overestimation in high luminance. An algorithmic model disentangles these multifaceted contributions and shows that the bidirectional gain control occurs at both timescales. The model implements a nonlinear interaction of luminance and contrast to achieve gain correction at fast timescales and a dark-sensitive channel to improve the detection of dim stimuli at slow timescales. Together, our work demonstrates how a single neuronal channel performs diverse computations to implement gain control at multiple timescales that are together important for navigation in natural environments.

Temporal novelty detection and multiple timescale integration drive Drosophila orientation dynamics in temporally diverse olfactory environments

To survive, insects must effectively navigate odors plumes to their source. In natural plumes, turbulent winds break up smooth odor regions into disconnected patches, so navigators encounter brief bursts of odor interrupted by bouts of clean air. The timing of these encounters plays a critical role in navigation, determining the direction, rate, and magnitude of insects' orientation and speed dynamics. Disambiguating the specific role of odor timing from other cues, such as spatial structure, is challenging due to natural correlations between plumes' temporal and spatial features. Here, we use optogenetics to isolate temporal features of odor signals, examining how the frequency and duration of odor encounters shape the navigational decisions of freely-walking Drosophila. We find that fly angular velocity depends on signal frequency and intermittency-the fraction of time signal can be detected-but not directly on durations. Rather than switching strategies when signal statistics change, flies smoothly transition between signal regimes, by combining an odor offset response with a frequency-dependent novelty-like response. In the latter, flies are more likely to turn in response to each odor hit only when the hits are sparse. Finally, the upwind bias of individual turns relies on a filtering scheme with two distinct timescales, allowing rapid and sustained responses in a variety of signal statistics. A quantitative model incorporating these ingredients recapitulates fly orientation dynamics across a wide range of environments and shows that temporal novelty detection, when combined with odor motion detection, enhances odor plume navigation.

Olfactory receptor neurons generate multiple response motifs, increasing coding space dimensionality

Odorants binding to olfactory receptor neurons (ORNs) trigger bursts of action potentials, providing the brain with its only experience of the olfactory environment. Our recordings made in vivo from locust ORNs showed that odor-elicited firing patterns comprise four distinct response motifs, each defined by a reliable temporal profile. Different odorants could elicit different response motifs from a given ORN, a property we term motif switching. Further, each motif undergoes its own form of sensory adaptation when activated by repeated plume-like odor pulses. A computational model constrained by our recordings revealed that organizing responses into multiple motifs provides substantial benefits for classifying odors and processing complex odor plumes: each motif contributes uniquely to encode the plume's composition and structure. Multiple motifs and motif switching further improve odor classification by expanding coding dimensionality. Our model demonstrated that these response features could provide benefits for olfactory navigation, including determining the distance to an odor source.

Neuron-glia interaction at the receptor level affects olfactory perception in adult Drosophila

Some types of glia play an active role in neuronal signaling by modifying their activity although little is known about their role in sensory information signaling at the receptor level. In this research, we report a functional role for the glia that surround the soma of the olfactory receptor neurons (OSNs) in adult Drosophila. Specific genetic modifications have been targeted to this cell type to obtain live individuals who are tested for olfactory preference and display changes both increasing and reducing sensitivity. A closer look at the antenna by Ca²⁺ imaging shows that odor activates the OSNs, which subsequently produce an opposite and smaller effect in the glia that partially counterbalances neuronal activation. Therefore, these glia may play a dual role in preventing excessive activation of the OSNs at high odorant concentrations and tuning the chemosensory window for the individual according to the network structure in the receptor organ.

Efficient information coding and degeneracy in the nervous system

Efficient information coding (EIC) is a universal biological framework rooted in the fundamental principle that system responses should match their natural stimulus statistics for maximizing environmental information. Quantitatively assessed through information theory, such adaptation to the environment occurs at all biological levels and timescales. The context dependence of environmental stimuli and the need for stable adaptations make EIC a daunting task. We argue that biological complexity is the principal architect that subserves deft execution of stable EIC. Complexity in a system is characterized by several functionally segregated subsystems that show a high degree of functional integration when they interact with each other. Complex biological systems manifest heterogeneities and degeneracy, wherein structurally different subsystems could interact to yield the same functional outcome. We argue that complex systems offer several choices that effectively implement EIC and homeostasis for each of the different contexts encountered by the system.

All-optical manipulation of the Drosophila olfactory system

Thanks to its well-known neuroanatomy, limited brain size, complex behaviour, and the extensive genetic methods, Drosophila has become an indispensable model in neuroscience. A vast number of studies have focused on its olfactory system and the processing of odour information. Optogenetics is one of the recently developed genetic tools that significantly advance this field of research, allowing to replace odour stimuli by direct neuronal activation with light. This becomes a universal all-optical toolkit when spatially selective optogenetic activation is combined with calcium imaging to read out neuronal responses. Initial experiments showed a successful implementation to study the olfactory system in fish and mice, but the olfactory system of Drosophila has been so far precluded from an application. To fill this gap, we present here optogenetic tools to selectively stimulate functional units in the Drosophila olfactory system, combined with two-photon calcium imaging to read out the activity patterns elicited by these stimuli at different levels of the brain. This method allows to study the spatial and temporal features of the information flow and reveals the functional connectivity in the olfactory network.

Mechanisms of Variability Underlying Odor-Guided Locomotion

Changes in locomotion mediated by odors (odor-guided locomotion) are an important mechanism by which animals discover resources important to their survival. Odor-guided locomotion, like most other behaviors, is highly variable. Variability in behavior can arise at many nodes along the circuit that performs sensorimotor transformation. We review these sources of variability in the context of the Drosophila olfactory system. While these sources of variability are important, using a model for locomotion, we show that another important contributor to behavioral variability is the stochastic nature of decision-making during locomotion as well as the persistence of these decisions: Flies choose the speed and curvature stochastically from a distribution and locomote with the same speed and curvature for extended periods. This stochasticity in locomotion will result in variability in behavior even if there is no noise in sensorimotor transformation. Overall, the noise in sensorimotor transformation is amplified by mechanisms of locomotion making odor-guided locomotion in flies highly variable.

Sensing complementary temporal features of odor signals enhances navigation of diverse turbulent plumes

We and others have shown that during odor plume navigation, walking Drosophila melanogaster bias their motion upwind in response to both the frequency of their encounters with the odor (Demir et al., 2020), and the intermittency of the odor signal, which we define to be the fraction of time the signal is above a detection threshold (Alvarez-Salvado et al., 2018). Here we combine and simplify previous mathematical models that recapitulated these data to investigate the benefits of sensing both of these temporal features, and how these benefits depend on the spatiotemporal statistics of the odor plume. Through agent-based simulations, we find that navigators that only use frequency or intermittency perform well in some environments - achieving maximal performance when gains are near those inferred from experiment - but fail in others. Robust performance across diverse environments requires both temporal modalities. However, we also find a steep tradeoff when using both sensors simultaneously, suggesting a strong benefit to modulating how much each sensor is weighted, rather than using both in a fixed combination across plumes. Finally, we show that the circuitry of the Drosophila olfactory periphery naturally enables simultaneous intermittency and frequency sensing, enhancing robust navigation through a diversity of odor environments. Together, our results suggest that the first stage of olfactory processing selects and encodes temporal features of odor signals critical to real-world navigation tasks.

GPCR voltage dependence controls neuronal plasticity and behavior

G-protein coupled receptors (GPCRs) play a paramount role in diverse brain functions. Almost 20 years ago, GPCR activity was shown to be regulated by membrane potential in vitro, but whether the voltage dependence of GPCRs contributes to neuronal coding and behavioral output under physiological conditions in vivo has never been demonstrated. Here we show that muscarinic GPCR mediated neuronal potentiation in vivo is voltage dependent. This voltage dependent potentiation is abolished in mutant animals expressing a voltage independent receptor. Depolarization alone, without a muscarinic agonist, results in a nicotinic ionotropic receptor potentiation that is mediated by muscarinic receptor voltage dependency. Finally, muscarinic receptor voltage independence causes a strong behavioral effect of increased odor habituation. Together, this study identifies a physiological role for the voltage dependency of GPCRs by demonstrating crucial involvement of GPCR voltage dependence in neuronal plasticity and behavior. Thus, this study suggests that GPCR voltage dependency plays a role in many diverse neuronal functions including learning and memory.

Flexible filtering by neural inputs supports motion computation across states and stimuli

Sensory systems flexibly adapt their processing properties across a wide range of environmental and behavioral conditions. Such variable processing complicates attempts to extract a mechanistic understanding of sensory computations. This is evident in the highly constrained, canonical Drosophila motion detection circuit, where the core computation underlying direction selectivity is still debated despite extensive studies. Here we measured the filtering properties of neural inputs to the OFF motion-detecting T5 cell in Drosophila. We report state- and stimulus-dependent changes in the shape of these signals, which become more biphasic under specific conditions. Summing these inputs within the framework of a connectomic-constrained model of the circuit demonstrates that these shapes are sufficient to explain T5 responses to various motion stimuli. Thus, our stimulus- and state-dependent measurements reconcile motion computation with the anatomy of the circuit. These findings provide a clear example of how a basic circuit supports flexible sensory computation.

Short-Term Plasticity Regulates Both Divisive Normalization and Adaptive Responses in Drosophila Olfactory System

In Drosophila, olfactory information received by olfactory receptor neurons (ORNs) is first processed by an incoherent feed forward neural circuit in the antennal lobe (AL) that consists of ORNs (input), inhibitory local neurons (LNs), and projection neurons (PNs). This “early” olfactory information processing has two important characteristics. First, response of a PN to its cognate ORN is normalized by the overall activity of other ORNs, a phenomenon termed “divisive normalization.” Second, PNs respond strongly to the onset of ORN activities, but they adapt to prolonged or continuously varying inputs. Despite the importance of these characteristics for learning and memory, their underlying mechanisms are not fully understood. Here, we develop a circuit model for describing the ORN-LN-PN dynamics by including key neuron-neuron interactions such as short-term plasticity (STP) and presynaptic inhibition (PI). By fitting our model to experimental data quantitatively, we show that a strong STP balanced between short-term facilitation (STF) and short-term depression (STD) is responsible for the observed nonlinear divisive normalization in Drosophila. Our circuit model suggests that either STP or PI alone can lead to adaptive response. However, by comparing our model results with experimental data, we find that both STP and PI work together to achieve a strong and robust adaptive response. Our model not only helps reveal the mechanisms underlying two main characteristics of the early olfactory process, it can also be used to predict PN responses to arbitrary time-dependent signals and to infer microscopic properties of the circuit (such as the strengths of STF and STD) from the measured input-output relation. Our circuit model may be useful for understanding the role of STP in other sensory systems.

Stimulus Driven Functional Transformations in the Early Olfactory System

Olfactory stimuli are encountered across a wide range of odor concentrations in natural environments. Defining the neural computations that support concentration invariant odor perception, odor discrimination, and odor-background segmentation across a wide range of stimulus intensities remains an open question in the field. In principle, adaptation could allow the olfactory system to adjust sensory representations to the current stimulus conditions, a well-known process in other sensory systems. However, surprisingly little is known about how adaptation changes olfactory representations and affects perception. Here we review the current understanding of how adaptation impacts processing in the first two stages of the vertebrate olfactory system, olfactory receptor neurons (ORNs), and mitral/tufted cells.

Correlated decision making across multiple phases of olfactory guided search in Drosophila improves search efficiency

Nearly all motile organisms must search for food, often requiring multiple phases of exploration across heterogeneous environments. The fruit fly, Drosophila, has emerged as an effective model system for studying this behavior, however, little is known about the extent to which experiences at one point in their search might influence decisions in another. To investigate whether prior experiences impact flies' search behavior after landing, I tracked individually labelled fruit flies as they explored three odor emitting but food-barren objects. I found two features of their behavior that are correlated with the distance they travel on foot. First, flies walked larger distances when they approached the odor source, which they were almost twice as likely to do when landing on the patch farthest downwind. Computational fluid dynamics simulations suggest this patch may have had a stronger baseline odor, but only ∼15% higher than the other two. This small increase, together with flies' high olfactory sensitivity, suggests that perhaps their flight trajectory used to approach the patches plays a role. Second, flies also walked larger distances when the time elapsed since their last visit was longer. However, the correlation is subtle and subject to a large degree of variability. Using agent-based models, I show that this small correlation can increase search efficiency by 25-50% across many scenarios. Furthermore, my models provide mechanistic hypotheses explaining the variability through either a noisy or straightforward decision-making process. Surprisingly, these stochastic decision-making algorithms enhance search efficiency in challenging but realistic search scenarios compared to deterministic strategies.

Cyclic nucleotide-dependent ionic currents in olfactory receptor neurons of the hawkmoth Manduca sexta suggest pull-push sensitivity modulation

Olfactory receptor neurons (ORNs) of the hawkmoth Manduca sexta sensitize via cAMP- and adapt via cGMP-dependent mechanisms. Perforated patch clamp recordings distinguished 11 currents in these ORNs. Derivatives of cAMP and/or cGMP antagonistically affected three of five K⁺ currents and two non-specific cation currents. The Ca²⁺ -dependent K⁺ current I_K(Ca ²⁺ ₎ and the sensitive pheromone-dependent K⁺ current I_K(cGMP-) , which both express fast kinetics, were inhibited by 8bcGMP, while a slow K⁺ current, I_K(cGMP+) , was activated by 8bcGMP. Furthermore, application of 8bcAMP blocked slowly activating, zero mV-reversing, non-specific cation currents, I_LL and I_cat(PKC?) , which remained activated in the presence of 8bcGMP. Their activations pull the membrane potential towards their 0-mV reversal potentials, in addition to increasing intracellular Ca²⁺ levels voltage- and I_LL -dependently. Twenty minutes after application, 8bcGMP blocked a TEA-independent K⁺ current, I_K(noTEA) , and a fast cation current, I_cat(nRP) , which both shift the membrane potential to negative values. We conclude that conditions of sensitization are maintained at high levels of cAMP, via specific opening/closure of ion channels that allow for fast kinetics, hyperpolarized membrane potentials, and low intracellular Ca²⁺ levels. In contrast, adaptation is supported via cGMP, which antagonizes cAMP, opening Ca²⁺ -permeable channels with slow kinetics that stabilize depolarized resting potentials. The antagonistic modulation of peripheral sensory neurons by cAMP or cGMP is reminiscent of pull-push mechanisms of neuromodulation at central synapses underlying metaplasticity.

PKC98E Regulates Odorant Responses in Drosophila melanogaster

Drosophila odorant receptors (Ors) are ligand gated ion channels composed of a common receptor subunit Or co-receptor (ORCO) and one of 62 "tuning" receptor subunits that confer odorant specificity to olfactory neuron responses. Like other sensory systems studied to date, exposing Drosophila olfactory neurons to activating ligands results in reduced responses to subsequent exposures through a process called desensitization. We recently showed that phosphorylation of serine 289 on the common Or subunit ORCO is required for normal peak olfactory neuron responses. Dephosphorylation of this residue occurs on prolonged odorant exposure, and underlies the slow modulation of olfactory neuron responses we term "slow desensitization." Slow desensitization results in the reduction of peak olfactory neuron responses and flattening of dose-response curves, implicating changes in ORCO^S289 phosphorylation state as an important modulator of olfactory neuron responses. Here, we report the identification of the primary kinase responsible for ORCO^S289 phosphorylation, PKC98E. Antiserum localizes the kinase to the dendrites of the olfactory neurons. Deletion of the kinase from olfactory neurons in the naive state (the absence of prolonged odor exposure) reduces ORCO^S289 phosphorylation and reduces peak odorant responses without altering receptor localization or expression levels. Genetic rescue with a PKC98E predicted to be constitutively active restores ORCO S289 phosphorylation and olfactory neuron sensitivity to the PKC98E mutants in the naive state. However, the dominant kinase is defective for slow desensitization. Together, these findings reveal that PKC98E is an important regulator of ORCO receptors and olfactory neuron function.SIGNIFICANCE STATEMENT We have identified PKC98E as the kinase responsible for phosphorylation of the odorant receptor co-receptor (ORCO) at S289 that is required for normal odorant response kinetics of olfactory neurons. This is a significant step toward revealing the enzymology underlying the regulation of odorant response regulation in insects.

Adaptive temporal processing of odor stimuli

The olfactory system translates chemical signals into neuronal signals that inform behavioral decisions of the animal. Odors are cues for source identity, but if monitored long enough, they can also be used to localize the source. Odor representations should therefore be robust to changing conditions and flexible in order to drive an appropriate behavior. In this review, we aim at discussing the main computations that allow robust and flexible encoding of odor information in the olfactory neural pathway.

Odor response adaptation in Drosophila-a continuous individualization process

Olfactory perception is very individualized in humans and also in Drosophila. The process that individualize olfaction is adaptation that across multiple time scales and mechanisms shape perception and olfactory-guided behaviors. Olfactory adaptation occurs both in the central nervous system and in the periphery. Central adaptation occurs at the level of the circuits that process olfactory inputs from the periphery where it can integrate inputs from other senses, metabolic states, and stress. We will here focus on the periphery and how the fast, slow, and persistent (lifelong) adaptation mechanisms in the olfactory sensory neurons individualize the Drosophila olfactory system.

Muscarinic Modulation of Antennal Lobe GABAergic Local Neurons Shapes Odor Coding and Behavior

In the antennal lobe (AL), the first olfactory relay of Drosophila, excitatory neurons are predominantly cholinergic. Ionotropic nicotinic receptors play a vital role in the effects of acetylcholine in the AL. However, the AL also has a high expression level of metabotropic muscarinic acetylcholine receptors type A (mAChRs-A). Nevertheless, the neurons expressing them and their role in the AL are unknown. Elucidating their function may reveal principles in olfactory modulation. Here, we show that mAChRs-A shape AL output and affect behavior. We localized mAChRs-A effects to a sub-population of GABAergic local neurons (iLNs), where they play a dual role: direct excitation of iLNs and stabilization of the synapse between receptor neurons and iLNs, which undergoes strong short-term depression. Our results reveal modulatory functions of the AL main excitatory neurotransmitter. Striking similarities to the mammalian olfactory system predict that mammalian glutamatergic metabotropic receptors could be associated with similar modulations.

Stochastic and Arbitrarily Generated Input Patterns to the Mushroom Bodies Can Serve as Conditioned Stimuli in Drosophila

Single neurons in the brains of insects often have individual genetic identities and can be unambiguously identified between animals. The overall neuronal connectivity is also genetically determined and hard-wired to a large degree. Experience-dependent structural and functional plasticity is believed to be superimposed onto this more-or-less fixed connectome. However, in Drosophila melanogaster, it has been shown that the connectivity between the olfactory projection neurons (OPNs) and Kenyon cells, the intrinsic neurons of the mushroom body, is highly stochastic and idiosyncratic between individuals. Ensembles of distinctly and sparsely activated Kenyon cells represent information about the identity of the olfactory input, and behavioral relevance can be assigned to this representation in the course of associative olfactory learning. Previously, we showed that in the absence of any direct sensory input, artificially and stochastically activated groups of Kenyon cells could be trained to encode aversive cues when their activation coincided with aversive stimuli. Here, we have tested the hypothesis that the mushroom body can learn any stochastic neuronal input pattern as behaviorally relevant, independent of its exact origin. We show that fruit flies can learn thermogenetically generated, stochastic activity patterns of OPNs as conditioned stimuli, irrespective of glomerular identity, the innate valence that the projection neurons carry, or inter-hemispheric symmetry.

Odor-Induced Multi-Level Inhibitory Maps in Drosophila

Optical imaging of intracellular Ca²⁺ influx as a correlate of neuronal excitation represents a standard technique for visualizing spatiotemporal activity of neuronal networks. However, the information-processing properties of single neurons and neuronal circuits likewise involve inhibition of neuronal membrane potential. Here, we report spatially resolved optical imaging of odor-evoked inhibitory patterns in the olfactory circuitry of Drosophila using a genetically encoded fluorescent Cl^- sensor. In combination with the excitatory component reflected by intracellular Ca²⁺ dynamics, we present a comprehensive functional map of both odor-evoked neuronal activation and inhibition at different levels of olfactory processing. We demonstrate that odor-evoked inhibition carried by Cl^- influx is present both in sensory neurons and second-order projection neurons (PNs), and is characterized by stereotypic, odor-specific patterns. Cl^--mediated inhibition features distinct dynamics in different neuronal populations. Our data support a dual role of inhibitory neurons in the olfactory system: global gain control across the neuronal circuitry and glomerulus-specific inhibition to enhance neuronal information processing.

Odor Stimuli: Not Just Chemical Identity

In most sensory modalities the underlying physical phenomena are well understood, and stimulus properties can be precisely controlled. In olfaction, the situation is different. The presence of specific chemical compounds in the air (or water) is the root cause for perceived odors, but it remains unknown what organizing principles, equivalent to wavelength for light, determine the dimensions of odor space. Equally important, but less in the spotlight, odor stimuli are also complex with respect to their physical properties, including concentration and time-varying spatio-temporal distribution. We still lack a complete understanding or control over these properties, in either experiments or theory. In this review, we will concentrate on two important aspects of the physical properties of odor stimuli beyond the chemical identity of the odorants: (1) The amplitude of odor stimuli and their temporal dynamics. (2) The spatio-temporal structure of odor plumes in a natural environment. Concerning these issues, we ask the following questions: (1) Given any particular experimental protocol for odor stimulation, do we have a realistic estimate of the odorant concentration in the air, and at the olfactory receptor neurons? Can we control, or at least know, the dynamics of odorant concentration at olfactory receptor neurons? (2) What do we know of the spatio-temporal structure of odor stimuli in a natural environment both from a theoretical and experimental perspective? And how does this change if we consider mixtures of odorants? For both topics, we will briefly summarize the underlying principles of physics and review the experimental and theoretical Neuroscience literature, focusing on the aspects that are relevant to animals’ physiology and behavior. We hope that by bringing the physical principles behind odor plume landscapes to the fore we can contribute to promoting a new generation of experiments and models.

Odor Stimuli: Not Just Chemical Identity

In most sensory modalities the underlying physical phenomena are well understood, and stimulus properties can be precisely controlled. In olfaction, the situation is different. The presence of specific chemical compounds in the air (or water) is the root cause for perceived odors, but it remains unknown what organizing principles, equivalent to wavelength for light, determine the dimensions of odor space. Equally important, but less in the spotlight, odor stimuli are also complex with respect to their physical properties, including concentration and time-varying spatio-temporal distribution. We still lack a complete understanding or control over these properties, in either experiments or theory. In this review, we will concentrate on two important aspects of the physical properties of odor stimuli beyond the chemical identity of the odorants: (1) The amplitude of odor stimuli and their temporal dynamics. (2) The spatio-temporal structure of odor plumes in a natural environment. Concerning these issues, we ask the following questions: (1) Given any particular experimental protocol for odor stimulation, do we have a realistic estimate of the odorant concentration in the air, and at the olfactory receptor neurons? Can we control, or at least know, the dynamics of odorant concentration at olfactory receptor neurons? (2) What do we know of the spatio-temporal structure of odor stimuli in a natural environment both from a theoretical and experimental perspective? And how does this change if we consider mixtures of odorants? For both topics, we will briefly summarize the underlying principles of physics and review the experimental and theoretical Neuroscience literature, focusing on the aspects that are relevant to animals' physiology and behavior. We hope that by bringing the physical principles behind odor plume landscapes to the fore we can contribute to promoting a new generation of experiments and models.