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Circadian rhythms allow animals to coordinate behavioral and physiological processes with respect to one another and to synchronize these processes to external environmental cycles. In most animals, circadian rhythms are produced by core clock neurons in the brain that generate and transmit time-of-day signals to downstream tissues, driving overt rhythms. The neuronal pathways controlling clock outputs, however, are not well understood. Furthermore, it is unclear how the central clock modulates multiple distinct circadian outputs. Identifying the cellular components and neuronal circuitry underlying circadian regulation is increasingly recognized as a critical step in the effort to address health pathologies linked to circadian disruption, including heart disease and metabolic disorders. Here, building on the conserved components of circadian and metabolic systems in mammals and Drosophila melanogaster, we used a recently developed feeding monitor to characterize the contribution to circadian feeding rhythms of two key neuronal populations in the Drosophila pars intercerebralis (PI), which is functionally homologous to the mammalian hypothalamus. We demonstrate that thermogenetic manipulations of PI neurons expressing the neuropeptide SIFamide (SIFa) as well as mutations of the SIFa gene degrade feeding:fasting rhythms. In contrast, manipulations of a nearby population of PI neurons that express the Drosophila insulin-like peptides (DILPs) affect total food consumption but leave feeding rhythms intact. The distinct contribution of these two PI cell populations to feeding is accompanied by vastly different neuronal connectivity as determined by trans-Tango synaptic mapping. These results for the first time identify a non-clock cell neuronal population in Drosophila that regulates feeding rhythms and furthermore demonstrate dissociable control of circadian and homeostatic aspects of feeding regulation by molecularly-defined neurons in a putative circadian output hub., Author summary Circadian (~24-hr) rhythms allow organisms to organize behavioral and physiological processes with respect to one another and the external environment. Circadian information is generated by central clock neurons in the brain that keep time through the presence of molecular clocks. To modulate behavioral processes, circadian signals must be transmitted through output pathways to control relevant downstream neuronal populations. We have investigated control of feeding behavior by two molecularly-distinct populations of neurons in a putative circadian output center in the fruit fly, Drosophila melanogaster. We identify for the first time a population of neurons, marked by expression of the SIFa peptide, that act as part of the circadian output circuit controlling feeding:fasting rhythms, and furthermore show that SIFa expression within these cells is necessary for normal feeding rhythms. Interestingly, manipulation of a nearby population of neurons that express the Drosophila insulin-like peptides alters the amount of feeding independent of effects on feeding rhythms, indicating that circadian and homeostatic aspects of feeding behavior are regulated by independent neuronal subsets. These findings have important implications for our understanding of how the central clock coordinately modulates distinct behavioral outputs.

All animals must eat in order to survive but first they must successfully locate and appraise food resources in a manner consonant with their needs. To accomplish this, external sensory information, in particular olfactory food cues, need to be detected and appropriately categorized. Recent advances in Drosophila point to the existence of parallel processing circuits within the central brain that encode odor valence, supporting approach and avoidance behaviors. Strikingly, many elements within these neural systems are subject to modification as a function of the fly’s satiety state. In this review we describe those advances and their potential impact on the decision to feed.

We previously showed that in a two-alternative choice (2AC) task, olfactory bulb (OB) gamma oscillations (∼70 Hz in rats) were enhanced during discrimination of structurally similar odorants (fine discrimination) versus discrimination of dissimilar odorants (coarse discrimination). In other studies (mostly employing go/no-go tasks) in multiple labs, beta oscillations (15–35 Hz) dominate the local field potential (LFP) signal in olfactory areas during odor sampling. Here we analyzed the beta frequency band power and pairwise coherence in the 2AC task. We show that in a task dominated by gamma in the OB, beta oscillations are also present in three interconnected olfactory areas (OB and anterior and posterior pyriform cortex). Only the beta band showed consistently elevated coherence during odor sniffing across all odor pairs, classes (alcohols and ketones), and discrimination types (fine and coarse), with stronger effects in first than in final criterion sessions (>70% correct). In the first sessions for fine discrimination odor pairs, beta power for incorrect trials was the same as that for correct trials for the other odor in the pair. This pattern was not repeated in coarse discrimination, in which beta power was elevated for correct relative to incorrect trials. This difference between fine and coarse odor discriminations may relate to different behavioral strategies for learning to differentiate similar versus dissimilar odors. Phase analysis showed that the OB led both pyriform areas in the beta frequency band during odor sniffing. We conclude that the beta band may be the means by which information is transmitted from the OB to higher order areas, even though task specifics modify dominance of one frequency band over another within the OB.

Several studies have shown that memory consolidation relies partly on interactions between sensory and limbic areas. The functional loop formed by the olfactory system and the hippocampus represents an experimentally tractable model that can provide insight into this question. It had been shown previously that odor-learning associated beta band oscillations (15–30 Hz) of the local field potential in the rat olfactory system are enhanced with criterion performance, but it was unknown if these involve networks beyond the olfactory system. We recorded local field potentials from the olfactory bulb (OB) and dorsal and ventral hippocampus during acquisition of odor discriminations in a go/no-go task. These regions showed increased beta oscillation power during odor sampling, accompanied by a coherence increase in this frequency band between the OB and both hippocampal subfields. This coherence between the OB and the hippocampus increased with the onset of the first rule transfer to a new odor set and remained high for all learning phases and subsequent odor sets. However, coherence between the two hippocampal fields reset to baseline levels with each new odor set and increased again with criterion performance. These data support hippocampal involvement in the network underlying odor-discrimination learning and also suggest that cooperation between the dorsal and ventral hippocampus varies with learning progress. Oscillatory activity in the beta range may thus provide a mechanism by which these areas are linked during memory consolidation, similar to proposed roles of beta oscillations in other systems with long-range connections.

Fast oscillations in neural assemblies have been proposed as a mechanism to facilitate stimulus representation in a variety of sensory systems across animal species. In the olfactory system, intervention studies suggest that oscillations in the gamma frequency range play a role in fine odor discrimination. However, there is still no direct evidence that such oscillations are intrinsically altered in intact systems to aid in stimulus disambiguation. Here we show that gamma oscillatory power in the rat olfactory bulb during a two-alternative choice task is modulated in the intact system according to task demands with dramatic increases in gamma power during discrimination of molecularly similar odorants in contrast to dissimilar odorants. This elevation in power evolves over the course of criterion performance, is specific to the gamma frequency band (65–85 Hz), and is independent of changes in the theta or beta frequency band range. Furthermore, these high amplitude gamma oscillations are restricted to the olfactory bulb, such that concurrent piriform cortex recordings show no evidence of enhanced gamma power during these high-amplitude events. Our results display no modulation in the power of beta oscillations (15–28 Hz) shown previously to increase with odor learning in a Go/No-go task, and we suggest that the oscillatory profile of the olfactory system may be influenced by both odor discrimination demands and task type. The results reported here indicate that enhancement of local gamma power may reflect a switch in the dynamics of the system to a strategy that optimizes stimulus resolution when input signals are ambiguous.

Odors are highly evocative, yet how and where in the brain odors derive meaning remains unknown. Our analysis of theDrosophilabrain extends the role of a small number of hunger-sensing neurons to include food-odor value representation.In vivotwo-photon calcium imaging shows the amplitude of food odor-evoked activity in neurons expressing Drosophila neuropeptide F (dNPF), the neuropeptide Y homolog, strongly correlates with food-odor attractiveness. Hunger elevates neural and behavioral responses to food odors only, although food odors that elicit attraction in the fed state also evoke heightened dNPF activity in fed flies. Inactivation of a subset of dNPF-expressing neurons or silencing dNPF receptors abolishes food-odor attractiveness, whereas genetically enhanced dNPF activity not only increases food-odor attractiveness but promotes attraction to aversive odors. Varying the amount of presented odor produces matching graded neural and behavioral curves, which can function to predict preference between odors. We thus demonstrate a possible motivationally scaled neural “value signal” accessible from uniquely identifiable cells.

Olfactory system oscillations play out with beautiful temporal and behavioral regularity on the oscilloscope and seem to scream ‘meaning’. Always there is the fear that, although attractive, these symbols of dynamic regularity might be just seductive epiphenomena. There are now many studies that have isolated some of the neural mechanisms involved in these oscillations, and recent work argues that they are functional and even necessary at the physiological and cognitive levels. However, much remains to be done for a full understanding of their functions.

The Drosophila mushroom body (MB) is a higher olfactory center where olfactory and other sensory information are thought to be associated. However, how MB neurons of Drosophila respond to sensory stimuli other than odor is not known. Here, we characterized the responses of MB neurons to a change in airflow, a stimulus associated with odor perception. In vivo calcium imaging from MB neurons revealed surprisingly strong and dynamic responses to an airflow stimulus. This response was dependent on the movement of the 3(rd) antennal segment, suggesting that Johnston's organ may be detecting the airflow. The calyx, the input region of the MB, responded homogeneously to airflow on. However, in the output lobes of the MB, different types of MB neurons responded with different patterns of activity to airflow on and off. Furthermore, detailed spatial analysis of the responses revealed that even within a lobe that is composed of a single type of MB neuron, there are subdivisions that respond differently to airflow on and off. These subdivisions within a single lobe were organized in a stereotypic manner across flies. For the first time, we show that changes in airflow affect MB neurons significantly and these effects are spatially organized into divisions smaller than previously defined MB neuron types.

In this issue of Neuron, Rinberg et al. show that mice use a speed-accuracy tradeoff in odor discrimination. Shorter sampling results in high performance for easy problems, and enforced longer sampling results in higher accuracy for difficult problems, but mice freely choose intermediate sampling durations and accuracy varies with difficulty. Reward value and task requirements may determine sampling time choice and performance levels.