Reward signaling in a recurrent circuit of dopaminergic neurons and peptidergic Kenyon cells

Analysis of fast calcium dynamics of honey bee olfactory coding

Odour processing exhibits multiple parallels between vertebrate and invertebrate olfactory systems. Insects, in particular, have emerged as relevant models for olfactory studies because of the tractability of their olfactory circuits. Here, we used fast calcium imaging to track the activity of projection neurons in the honey bee antennal lobe (AL) during olfactory stimulation at high temporal resolution. We observed a heterogeneity of response profiles and an abundance of inhibitory activities, resulting in various response latencies and stimulus-specific post-odour neural signatures. Recorded calcium signals were fed to a mushroom body (MB) model constructed implementing the fundamental features of connectivity between olfactory projection neurons, Kenyon cells (KC), and MB output neurons (MBON). The model accounts for the increase of odorant discrimination in the MB compared to the AL and reveals the recruitment of two distinct KC populations that represent odorants and their aftersmell as two separate but temporally coherent neural objects. Finally, we showed that the learning-induced modulation of KC-to-MBON synapses can explain both the variations in associative learning scores across different conditioning protocols used in bees and the bees' response latency. Thus, it provides a simple explanation of how the time contingency between the stimulus and the reward can be encoded without the need for time tracking. This study broadens our understanding of olfactory coding and learning in honey bees. It demonstrates that a model based on simple MB connectivity rules and fed with real physiological data can explain fundamental aspects of odour processing and associative learning.

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.

A new GRAB sensor reveals differences in the dynamics and molecular regulation between neuropeptide and neurotransmitter release

The co-existence and co-transmission of neuropeptides and small molecule neurotransmitters in the same neuron is a fundamental aspect of almost all neurons across various species. However, the differences regarding their in vivo spatiotemporal dynamics and underlying molecular regulation remain poorly understood. Here, we developed a GPCR-activation-based (GRAB) sensor for detecting short neuropeptide F (sNPF) with high sensitivity and spatiotemporal resolution. Furthermore, we explore the differences of in vivo dynamics and molecular regulation between sNPF and acetylcholine (ACh) from the same neurons. Interestingly, the release of sNPF and ACh shows different spatiotemporal dynamics. Notably, we found that distinct synaptotagmins (Syt) are involved in these two processes, as Syt7 and Sytα for sNPF release, while Syt1 for ACh release. Thus, this new GRAB sensor provides a powerful tool for studying neuropeptide release and providing new insights into the distinct release dynamics and molecular regulation between neuropeptides and small molecule neurotransmitters.

The neuropeptide pigment-dispersing factor signals independently of Bruchpilot-labelled active zones in daily remodelled terminals of Drosophila clock neurons

The small ventrolateral neurons (sLNvs) are key components of the central clock in the Drosophila brain. They signal via the neuropeptide pigment-dispersing factor (PDF) to align the molecular clockwork of different central clock neurons and to modulate downstream circuits. The dorsal terminals of the sLNvs undergo daily morphological changes that affect presynaptic sites organised by the active zone protein Bruchpilot (BRP), a homolog of mammalian ELKS proteins. However, the role of these presynaptic sites for PDF release is ill-defined. Here, we combined expansion microscopy with labelling of active zones by endogenously tagged BRP to examine the spatial correlation between PDF-containing dense-core vesicles and BRP-labelled active zones. We found that the number of BRP-labelled puncta in the sLNv terminals was similar while their density differed between Zeitgeber time (ZT) 2 and 14. The relative distance between BRP- and PDF-labelled puncta was increased in the morning, around the reported time of PDF release. Spontaneous dense-core vesicle release profiles of sLNvs in a publicly available ssTEM dataset (FAFB) consistently lacked spatial correlation to BRP-organised active zones. RNAi-mediated downregulation of brp and other active zone proteins expressed by the sLNvs did not affect PDF-dependent locomotor rhythmicity. In contrast, down-regulation of genes encoding proteins of the canonical vesicle release machinery, the dense-core vesicle-related protein CADPS, as well as PDF impaired locomotor rhythmicity. Taken together, our study suggests that PDF release from the sLNvs is independent of BRP-organised active zones, while BRP may be redistributed to active zones in a time-dependent manner.

Future avenues in Drosophila mushroom body research

How does the brain translate sensory information into complex behaviors? With relatively small neuronal numbers, readable behavioral outputs, and an unparalleled genetic toolkit, the Drosophila mushroom body (MB) offers an excellent model to address this question in the context of associative learning and memory. Recent technological breakthroughs, such as the freshly completed full-brain connectome, multiomics approaches, CRISPR-mediated gene editing, and machine learning techniques, led to major advancements in our understanding of the MB circuit at the molecular, structural, physiological, and functional levels. Despite significant progress in individual MB areas, the field still faces the fundamental challenge of resolving how these different levels combine and interact to ultimately control the behavior of an individual fly. In this review, we discuss various aspects of MB research, with a focus on the current knowledge gaps, and an outlook on the future methodological developments required to reach an overall view of the neurobiological basis of learning and memory.

Roles of feedback and feed-forward networks of dopamine subsystems: insights from Drosophila studies

Across animal species, dopamine-operated memory systems comprise anatomically segregated, functionally diverse subsystems. Although individual subsystems could operate independently to support distinct types of memory, the logical interplay between subsystems is expected to enable more complex memory processing by allowing existing memory to influence future learning. Recent comprehensive ultrastructural analysis of the Drosophila mushroom body revealed intricate networks interconnecting the dopamine subsystems-the mushroom body compartments. Here, we review the functions of some of these connections that are beginning to be understood. Memory consolidation is mediated by two different forms of network: A recurrent feedback loop within a compartment maintains sustained dopamine activity required for consolidation, whereas feed-forward connections across compartments allow short-term memory formation in one compartment to open the gate for long-term memory formation in another compartment. Extinction and reversal of aversive memory rely on a similar feed-forward circuit motif that signals omission of punishment as a reward, which triggers plasticity that counteracts the original aversive memory trace. Finally, indirect feed-forward connections from a long-term memory compartment to short-term memory compartments mediate higher-order conditioning. Collectively, these emerging studies indicate that feedback control and hierarchical connectivity allow the dopamine subsystems to work cooperatively to support diverse and complex forms of learning.

Rewarding Capacity of Optogenetically Activating a Giant GABAergic Central-Brain Interneuron in Larval Drosophila

Larvae of the fruit fly Drosophila melanogaster are a powerful study case for understanding the neural circuits underlying behavior. Indeed, the numerical simplicity of the larval brain has permitted the reconstruction of its synaptic connectome, and genetic tools for manipulating single, identified neurons allow neural circuit function to be investigated with relative ease and precision. We focus on one of the most complex neurons in the brain of the larva (of either sex), the GABAergic anterior paired lateral neuron (APL). Using behavioral and connectomic analyses, optogenetics, Ca2+ imaging, and pharmacology, we study how APL affects associative olfactory memory. We first provide a detailed account of the structure, regional polarity, connectivity, and metamorphic development of APL, and further confirm that optogenetic activation of APL has an inhibiting effect on its main targets, the mushroom body Kenyon cells. All these findings are consistent with the previously identified function of APL in the sparsening of sensory representations. To our surprise, however, we found that optogenetically activating APL can also have a strong rewarding effect. Specifically, APL activation together with odor presentation establishes an odor-specific, appetitive, associative short-term memory, whereas naive olfactory behavior remains unaffected. An acute, systemic inhibition of dopamine synthesis as well as an ablation of the dopaminergic pPAM neurons impair reward learning through APL activation. Our findings provide a study case of complex circuit function in a numerically simple brain, and suggest a previously unrecognized capacity of central-brain GABAergic neurons to engage in dopaminergic reinforcement.SIGNIFICANCE STATEMENT The single, identified giant anterior paired lateral (APL) neuron is one of the most complex neurons in the insect brain. It is GABAergic and contributes to the sparsening of neuronal activity in the mushroom body, the memory center of insects. We provide the most detailed account yet of the structure of APL in larval Drosophila as a neurogenetically accessible study case. We further reveal that, contrary to expectations, the experimental activation of APL can exert a rewarding effect, likely via dopaminergic reward pathways. The present study both provides an example of unexpected circuit complexity in a numerically simple brain, and reports an unexpected effect of activity in central-brain GABAergic circuits.

A cognitive account of trace conditioning in insects

Trace conditioning is a form of Pavlovian learning in which the conditioned stimulus (CS) and the unconditioned stimulus (US) are separated by a temporal gap. Insects learn trace associations of variable nature (appetitive, aversive) and involving CSs of different sensory modalities (olfactory, visual). The accessibility of the insect neural system in behaving animals allowed identifying neural processes driving trace conditioning: the existence of prolonged neural responses to the CS after stimulus offset and the anticipation of US responses during the free-stimulus gap. Specific brain structures, such as the mushroom bodies seem to be allocated to this learning form. Here, we posit that a further component facilitating trace conditioning in insects relates to neuromodulatory mechanisms underlying enhanced attention. We thus propose a model based on different types of mushroom-body neurons, which provides a cognitive account of trace conditioning in insects.

The connectome of an insect brain

Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain's most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.

In Utero Electroporation for Manipulation of Specific Neuronal Populations

The complexity of brain functions is supported by the heterogeneity of brain tissue and millisecond-scale information processing. Understanding how complex neural circuits control animal behavior requires the precise manipulation of specific neuronal subtypes at high spatiotemporal resolution. In utero electroporation, when combined with optogenetics, is a powerful method for precisely controlling the activity of specific neurons. Optogenetics allows for the control of cellular membrane potentials through light-sensitive ion channels artificially expressed in the plasma membrane of neurons. Here, we first review the basic mechanisms and characteristics of in utero electroporation. Then, we discuss recent applications of in utero electroporation combined with optogenetics to investigate the functions and characteristics of specific regions, layers, and cell types. These techniques will pave the way for further advances in understanding the complex neuronal and circuit mechanisms that underlie behavioral outputs.

Long-Term Observation of Locomotion of Drosophila Larvae Facilitates Feasibility of Food-Choice Assays

Animal behavior is reflected by locomotor patterns. To decipher the underlying neural circuitry locomotion has to be monitored over often longer time periods. Here a simple adaptation is described to constrain movement of third instar Drosophila larvae to a defined area and use Frustrated total internal reflection based imaging method (FIM) imaging to monitor larval movements up to 1 h. It is demonstrated that the combination of FIM imaging and long analysis periods facilitates the conduction of food choice assays and provides the means to easily quantify food preferences.

Switch-like and persistent memory formation in individual Drosophila larvae

Associative learning allows animals to use past experience to predict future events. The circuits underlying memory formation support immediate and sustained changes in function, often in response to a single example. Larval Drosophila is a genetic model for memory formation that can be accessed at molecular, synaptic, cellular, and circuit levels, often simultaneously, but existing behavioral assays for larval learning and memory do not address individual animals, and it has been difficult to form long-lasting memories, especially those requiring synaptic reorganization. We demonstrate a new assay for learning and memory capable of tracking the changing preferences of individual larvae. We use this assay to explore how activation of a pair of reward neurons changes the response to the innately aversive gas carbon dioxide (CO2). We confirm that when coupled to CO2 presentation in appropriate temporal sequence, optogenetic reward reduces avoidance of CO2. We find that learning is switch-like: all-or-none and quantized in two states. Memories can be extinguished by repeated unrewarded exposure to CO2 but are stabilized against extinction by repeated training or overnight consolidation. Finally, we demonstrate long-lasting protein synthesis dependent and independent memory formation.

Assessing the cognitive status of Drosophila by the value-based feeding decision

Decision-making is considered an important aspect of cognitive function. Impaired decision-making is a consequence of cognitive decline caused by various physiological conditions, such as aging and neurodegenerative diseases. Here we exploited the value-based feeding decision (VBFD) assay, which is a simple sensory-motor task, to determine the cognitive status of Drosophila. Our results indicated the deterioration of VBFD is notably correlated with aging and neurodegenerative disorders. Restriction of the mushroom body (MB) neuronal activity partly blunted the proper VBFD. Furthermore, using the Drosophila polyQ disease model, we demonstrated the impaired VBFD is ameliorated by the dinitrosyl iron complex (DNIC-1), a novel and steady nitric oxide (NO)-releasing compound. Therefore we propose that the VBFD assay provides a robust assessment of Drosophila cognition and can be used to characterize additional neuroprotective interventions.

Appetitive olfactory learning suffers in ants when octopamine or dopamine receptors are blocked

Associative learning relies on the detection of coincidence between a stimulus and a reward or punishment. In the insect brain, this process is carried out in the mushroom bodies under the control of octopaminergic and dopaminergic neurons. It was assumed that appetitive learning is governed by octopaminergic neurons, while dopamine is required for aversive learning. This view has recently been challenged: both neurotransmitters are involved in both types of learning in bees and flies. Here, we tested which neurotransmitters are required for appetitive learning in ants. We trained Lasius niger workers to discriminate two mixtures of linear hydrocarbons and to associate one of them with a sucrose reward. We analysed the walking paths of the ants using machine learning and found that the ants spent more time near the rewarded odour than near the other, a preference that was stable for at least 24 h. We then treated the ants before learning with either epinastine, an octopamine receptor blocker, or flupentixol, a dopamine receptor blocker. Ants with blocked octopamine receptors did not prefer the rewarded odour. Octopamine signalling is thus necessary for appetitive learning of olfactory cues, probably because it signals information about odours or reward to the mushroom body. In contrast, ants with blocked dopamine receptors initially learned the rewarded odour but failed to retrieve this memory 24 h later. Dopamine is thus probably required for long-term memory consolidation, independent of short-term memory formation. Our results show that appetitive olfactory learning depends on both octopamine and dopamine signalling in ants.

A neuronal ensemble encoding adaptive choice during sensory conflict in Drosophila

Feeding decisions are fundamental to survival, and decision making is often disrupted in disease. Here, we show that neural activity in a small population of neurons projecting to the fan-shaped body higher-order central brain region of Drosophila represents food choice during sensory conflict. We found that food deprived flies made tradeoffs between appetitive and aversive values of food. We identified an upstream neuropeptidergic and dopaminergic network that relays internal state and other decision-relevant information to a specific subset of fan-shaped body neurons. These neurons were strongly inhibited by the taste of the rejected food choice, suggesting that they encode behavioral food choice. Our findings reveal that fan-shaped body taste responses to food choices are determined not only by taste quality, but also by previous experience (including choice outcome) and hunger state, which are integrated in the fan-shaped body to encode the decision before relay to downstream motor circuits for behavioral implementation.

Ethanol-guided behavior in Drosophila larvae

Chemosensory signals allow vertebrates and invertebrates not only to orient in its environment toward energy-rich food sources to maintain nutrition but also to avoid unpleasant or even poisonous substrates. Ethanol is a substance found in the natural environment of Drosophila melanogaster. Accordingly, D. melanogaster has evolved specific sensory systems, physiological adaptations, and associated behaviors at its larval and adult stage to perceive and process ethanol. To systematically analyze how D. melanogaster larvae respond to naturally occurring ethanol, we examined ethanol-induced behavior in great detail by reevaluating existing approaches and comparing them with new experiments. Using behavioral assays, we confirm that larvae are attracted to different concentrations of ethanol in their environment. This behavior is controlled by olfactory and other environmental cues. It is independent of previous exposure to ethanol in their food. Moreover, moderate, naturally occurring ethanol concentration of 4% results in increased larval fitness. On the contrary, higher concentrations of 10% and 20% ethanol, which rarely or never appear in nature, increase larval mortality. Finally, ethanol also serves as a positive teaching signal in learning and memory and updates valence associated with simultaneously processed odor information. Since information on how larvae perceive and process ethanol at the genetic and neuronal level is limited, the establishment of standardized assays described here is an important step towards their discovery.

The Role of Dopamine in Associative Learning in Drosophila: An Updated Unified Model

Learning to associate a positive or negative experience with an unrelated cue after the presentation of a reward or a punishment defines associative learning. The ability to form associative memories has been reported in animal species as complex as humans and as simple as insects and sea slugs. Associative memory has even been reported in tardigrades [1], species that diverged from other animal phyla 500 million years ago. Understanding the mechanisms of memory formation is a fundamental goal of neuroscience research. In this article, we work on resolving the current contradictions between different Drosophila associative memory circuit models and propose an updated version of the circuit model that predicts known memory behaviors that current models do not. Finally, we propose a model for how dopamine may function as a reward prediction error signal in Drosophila, a dopamine function that is well-established in mammals but not in insects [2, 3].

Identification of FoxP circuits involved in locomotion and object fixation in Drosophila

The FoxP family of transcription factors is necessary for operant self-learning, an evolutionary conserved form of motor learning. The expression pattern, molecular function and mechanisms of action of the Drosophila FoxP orthologue remain to be elucidated. By editing the genomic locus of FoxP with CRISPR/Cas9, we find that the three different FoxP isoforms are expressed in neurons, but not in glia and that not all neurons express all isoforms. Furthermore, we detect FoxP expression in, e.g. the protocerebral bridge, the fan-shaped body and in motor neurons, but not in the mushroom bodies. Finally, we discover that FoxP expression during development, but not adulthood, is required for normal locomotion and landmark fixation in walking flies. While FoxP expression in the protocerebral bridge and motor neurons is involved in locomotion and landmark fixation, the FoxP gene can be excised from dorsal cluster neurons and mushroom-body Kenyon cells without affecting these behaviours.

Serotonin receptor 5-HT7 in Drosophila mushroom body neurons mediates larval appetitive olfactory learning

Serotonin (5-HT) and dopamine are critical neuromodulators known to regulate a range of behaviors in invertebrates and mammals, such as learning and memory. Effects of both serotonin and dopamine are mediated largely through their downstream G-protein coupled receptors through cAMP-PKA signaling. While the role of dopamine in olfactory learning in Drosophila is well described, the function of serotonin and its downstream receptors on Drosophila olfactory learning remain largely unexplored. In this study we show that the output of serotonergic neurons, possibly through points of synaptic contacts on the mushroom body (MB), is essential for training during olfactory associative learning in Drosophila larvae. Additionally, we demonstrate that the regulation of olfactory associative learning by serotonin is mediated by its downstream receptor (d5-HT7) in a cAMP-dependent manner. We show that d5-HT7 expression specifically in the MB, an anatomical structure essential for olfactory learning in Drosophila, is critical for olfactory associative learning. Importantly our work shows that spatio-temporal restriction of d5-HT7 expression to the MB is sufficient to rescue olfactory learning deficits in a d5-HT7 null larvae. In summary, our results establish a critical, and previously unknown, role of d5-HT7 in olfactory learning.

Useful road maps: studying Drosophila larva's central nervous system with the help of connectomics

The larva of Drosophila melanogaster is emerging as a powerful model system for comprehensive brain-wide understanding of the circuit implementation of neural computations. With an unprecedented amount of tools in hand, including synaptic-resolution connectomics, whole-brain imaging, and genetic tools for selective targeting of single neuron types, it is possible to dissect which circuits and computations are at work behind behaviors that have an interesting level of complexity. Here we present some of the recent advances regarding multisensory integration, learning, and action selection in Drosophila larva.

Rewarding compounds identified from the medicinal plant Rhodiola rosea

Preparations of Rhodiola rosea root are widely used in traditional medicine. They can increase life span in worms and flies, and have various effects related to nervous system function in different animal species and humans. However, which of the compounds in R. rosea is mediating any one of these effects has remained unknown in most cases. Here, an analysis of the volatile and non-volatile low-molecular-weight constituents of R. rosea root samples was accompanied by an investigation of their behavioral impact on Drosophila melanogaster larvae. Rhodiola rosea root samples have an attractive smell and taste to the larvae, and exert a rewarding effect. This rewarding effect was also observed for R. rosea root extracts, and did not require activity of dopamine neurons that mediate known rewards such as sugar. Based on the chemical profiles of R. rosea root extracts and resultant fractions, a bioactivity-correlation analysis (AcorA) was performed to identify candidate rewarding compounds. This suggested positive correlations for - among related compounds - ferulic acid eicosyl ester (FAE-20) and β-sitosterol glucoside. A validation using these as pure compounds confirmed that the correlations were causal. Their rewarding effects can be observed even at low micromolar concentrations and thus at remarkably lower doses than for any known taste reward in the larva. We discuss whether similar rewarding effects, should they be observed in humans, would indicate a habit-forming or addictive potential.

Recurrent architecture for adaptive regulation of learning in the insect brain

Dopaminergic neurons (DANs) drive learning across the animal kingdom, but the upstream circuits that regulate their activity and thereby learning remain poorly understood. We provide a synaptic-resolution connectome of the circuitry upstream of all DANs in a learning center, the mushroom body of Drosophila larva. We discover afferent sensory pathways and a large population of neurons that provide feedback from mushroom body output neurons and link distinct memory systems (aversive and appetitive). We combine this with functional studies of DANs and their presynaptic partners and with comprehensive circuit modeling. We find that DANs compare convergent feedback from aversive and appetitive systems, which enables the computation of integrated predictions that may improve future learning. Computational modeling reveals that the discovered feedback motifs increase model flexibility and performance on learning tasks. Our study provides the most detailed view to date of biological circuit motifs that support associative learning.

Cellular and circuit mechanisms of olfactory associative learning in Drosophila

Recent years have witnessed significant progress in understanding how memories are encoded, from the molecular to the cellular and the circuit/systems levels. With a good compromise between brain complexity and behavioral sophistication, the fruit fly Drosophila melanogaster is one of the preeminent animal models of learning and memory. Here we review how memories are encoded in Drosophila, with a focus on short-term memory and an eye toward future directions. Forward genetic screens have revealed a large number of genes and transcripts necessary for learning and memory, some acting cell-autonomously. Further, the relative numerical simplicity of the fly brain has enabled the reverse engineering of learning circuits with remarkable precision, in some cases ascribing behavioral phenotypes to single neurons. Functional imaging and physiological studies have localized and parsed the plasticity that occurs during learning at some of the major loci. Connectomics projects are significantly expanding anatomical knowledge of the nervous system, filling out the roadmap for ongoing functional/physiological and behavioral studies, which are being accelerated by simultaneous tool development. These developments have provided unprecedented insight into the fundamental neural principles of learning, and lay the groundwork for deep understanding in the near future.

Food restriction reconfigures naïve and learned choice behavior in Drosophila larvae

In many animals, the establishment and expression of food-related memory is limited by the presence of food and promoted by its absence, implying that this behavior is driven by motivation. In the past, this has already been demonstrated in various insects including honeybees and adult Drosophila. For Drosophila larvae, which are characterized by an immense growth and the resulting need for constant food intake, however, knowledge is rather limited. Accordingly, we have analyzed whether starvation modulates larval memory formation or expression after appetitive classical olfactory conditioning, in which an odor is associated with a sugar reward. We show that odor-sugar memory of starved larvae lasts longer than in fed larvae, although the initial performance is comparable. 80 minutes after odor fructose conditioning, only starved but not fed larvae show a reliable odor-fructose memory. This is likely due to a specific increase in the stability of anesthesia-resistant memory (ARM). Furthermore, we observe that starved larvae, in contrast to fed ones, prefer sugars that offer a nutritional benefit in addition to their sweetness. Taken together our work shows that Drosophila larvae adjust the expression of learned and naïve choice behaviors in the absence of food. These effects are only short-lasting probably due to their lifestyle and their higher internal motivation to feed. In the future, the extensive use of established genetic tools will allow us to identify development-specific differences arising at the neuronal and molecular level.