Neuropeptides (NPs) and their cognate receptors are critical molecular effectors of diverse physiological processes and behaviors. We recently reported of a non-canonical function of the Drosophila Glucose-6-Phosphatase (G6P) gene in a subset of neurosecretory cells in the CNS that governs systemic glucose homeostasis in food deprived flies. Here, we show that G6P expressing neurons define 7 groups of neuropeptide secreting cells, 5 in the brain and 2 in the thoracic ganglia. Using the glucose homeostasis phenotype as a screening tool, we show that one such group, located in the thoracic ganglia and expressing FMRFamide (FMRFaG6P) neuropeptides, is necessary and sufficient to maintain systemic glucose homeostasis in starved flies. We further show that the receptor for FMRFamides (FMRFaR) is one key target of G6P dependent NP signaling and essential for the build-up of glycogen stores in the jump muscle. Lastly, measurements of the Golgi apparatus of FMRFaG6P neurons and neuropeptide released into the hemolymph suggests that G6P enhances FMRFa signaling by increasing the capacity of the neurosecretory system. We propose a general model in which the main role of G6P is to counteract glycolysis in peptidergic neurons for the purpose of optimizing the intracellular environment best suited for the expansion of the Golgi apparatus, boosting release of neuropeptides, which through the activation of specific neuropeptide receptors, enhances signaling in respective target tissues. less

In birds and insects, females uptake sperm for a specific duration post-copulation known as the ejaculate holding period (EHP) before expelling unused sperm and the mating plug through sperm ejection. Our study uncovered that encountering males or mated females after mating substantially shortens EHP, a phenomenon we term \'male-induced EHP shortening (MIES)\'. MIES requires Or47b+ olfactory and ppk23+ gustatory neurons, activated by 2-methyltetracosane and 7-Tricosene, respectively. These odorants raise cAMP levels in pC1 neurons, responsible for processing male courtship and regulating female mating receptivity. Elevated cAMP levels in pC1 neurons reduce EHP and reinstate their responsiveness to male courtship cues, promoting re-mating with faster sperm ejection. This study establishes MIES as a genetically tractable model of sexual plasticity with a conserved neural mechanism. less

An important question in neuroscience is how sensory systems change as animals grow and interact with the environment. Exploring sensory systems in animals as they develop can reveal how networks of neurons process information as the neurons themselves grow and the needs of the animal change. Here we compared the structure and function of peripheral parts of the olfactory pathway in newly hatched and adult locusts. We found that populations of olfactory sensory neurons (OSNs) in hatchlings and adults responded with similar tunings to a panel of odors. The morphologies of local neurons (LNs) and projection neurons (PNs) in the antennal lobes (ALs) were very similar in both age groups, though they were smaller in hatchlings, they were proportional to overall brain size. The odor evoked responses of LNs and PNs were also very similar in both age groups, characterized by complex patterns of activity including oscillatory synchronization. Notably, in hatchlings, spontaneous and odor-evoked firing rates of PNs were lower, and LFP oscillations were lower in frequency, than in the adult. Hatchlings have smaller antennae with fewer OSNs; removing antennal segments from adults also reduced LFP oscillation frequency. Thus, consistent with earlier computational models, the developmental increase in frequency is due to increasing intensity of input to the oscillation circuitry. Overall, our results show that locusts hatch with a fully formed olfactory system that structurally and functionally matches that of the adult, despite its small size and lack of prior experience with olfactory stimuli. less

Animals must survive by foraging for food in an uncertain and dangerous world. Experimental tasks such as Pavlovian learning have yielded insights into how neural circuits balance these conflicting motivational drives. Neuromodulators play a fundamental role in this process, enabling flexible switching between motivational drives. The question of how neuromodulators synergistically encode motivational state is thus fundamental to systems neuroscience, yet the interplay between these neuromodulators during naturalistic decision making are not fully understood. Here, we developed a naturalistic approach/avoidance task in mice involving a tradeoff between seeking reward versus safety in the presence of looming predation risk. We utilized multi-fiber photometry, computational behavior tracking, and slice electrophysiology to understand the . Mice that experienced looming stimuli showed increased c-fos expression in regions including frontal cortex, locus coeruleus, and ventral tegmental area, but decreased expression in dorsal raphe nucleus. Moreover, by using multi-fiber photometry combined with GPCR-based sensors, we found that cortical norepinephrine (NE) plays a more prominent role in encoding looming threats while dopamine (DA) represents reward and threat. In contrast, serotonin (5HT) dynamic negatively correlates to both emotional valences. To begin to understand neuromodulatory intreractions, we used ex vivo slice physiology to understand 5HT impact on spontaneous firing of locus coeruleus NE neurons. In conclusion, monoamines such as NE, DA, 5HT can converge in their encoding of naturalistic motivated behaviors as well as dissociate from one another. By utilizing this approach, interactions between innate fear and incentive for food may be delineated in terms of basis in neurochemical signaling events during natural behavior, and may contribute to the understanding of neural mechanisms underlying emotional disorders including anxiety and post-traumatic stress disorder. less

Deep convolutional neural networks (CNNs) resemble the hierarchically organised neural representations in the primate visual ventral stream. However, these models typically disregard the temporal dynamics experimentally observed in these areas. For instance, alpha oscillations dominate the dynamics of the human visual cortex, yet the computational relevance of oscillations is rarely considered in artificial neural networks (ANNs). We propose an ANN that embraces oscillatory dynamics with the computational purpose of converting simultaneous inputs, presented at two different locations, into a temporal code. The network was trained to classify three individually presented letters. Post-training, we added semi-realistic temporal dynamics to the hidden layer, introducing relaxation dynamics in the hidden units as well as pulsed inhibition mimicking neuronal alpha oscillations. Without these dynamics, the trained network correctly classified individual letters but produced a mixed output when presented with two letters simultaneously, elucidating a bottleneck problem. When introducing refraction and oscillatory inhibition, the output nodes corresponding to the two stimuli activated sequentially, ordered along the phase of the inhibitory oscillations. Our model provides a novel approach for implementing multiplexing in ANNs. It further produces experimentally testable predictions of how the primate visual system handles competing stimuli. less

Congruent visual speech improves speech perception accuracy, particularly in noisy environments. Conversely, mismatched visual speech can alter what is heard, leading to an illusory percept known as the McGurk effect. This illusion has been widely used to study audiovisual speech integration, illustrating that auditory and visual cues are combined in the brain to generate a single coherent percept. While prior transcranial magnetic stimulation (TMS) and neuroimaging studies have identified the left posterior superior temporal sulcus (pSTS) as a causal region involved in the generation of the McGurk effect, it remains unclear whether this region is critical only for this illusion or also for the more general benefits of congruent visual speech (e.g., increased accuracy and faster reaction times). Indeed, recent correlative research suggests that the benefits of congruent visual speech and the McGurk effect reflect largely independent mechanisms. To better understand how these different features of audiovisual integration are causally generated by the left pSTS, we used single-pulse TMS to temporarily impair processing while subjects were presented with either incongruent (McGurk) or congruent audiovisual combinations. Consistent with past research, we observed that TMS to the left pSTS significantly reduced the strength of the McGurk effect. Importantly, however, left pSTS stimulation did not affect the positive benefits of congruent audiovisual speech (increased accuracy and faster reaction times), demonstrating a causal dissociation between the two processes. Our results are consistent with models proposing that the pSTS is but one of multiple critical areas supporting audiovisual speech interactions. Moreover, these data add to a growing body of evidence suggesting that the McGurk effect is an imperfect surrogate measure for more general and ecologically valid audiovisual speech behaviors. less

Stereognosis, the sense of the 3-dimensional shape of objects held in hand, requires the integration of somatosensory signals about local features -such as edges and surface curvature- with proprioceptive signals about the conformation of the fingers on the object. However, the mechanism of this integration remains unknown. Here, we investigated the spatial model that is used to integrate information about the global shape of the object with information about its local features at each point of contact. To this end, human observers judged the dissimilarity of pairs of objects that differed in their global shape, their local features, or both. We then compared the dissimilarity ratings when both global shape and local features changed to ratings when only global shape or only local features changed. We tested this with object sets of different levels of complexity, including spheres of different sizes and surface features to more varied shapes and features. For all object sets, we found that ratings when both global shape and local features changed was approximately an additive combination of the ratings when only global shape or only local features changed. For the majority of subjects, a city-block spatial model best explained their responses. Our results suggest that information about global shape is encoded independently from that about local features during interactions with objects. This implies that the neural representations of object shape and local features, though integrated, are separable. less

Insect olfactory receptor neurons (ORNs) are often co-localized within sensilla and exhibit non-synaptic reciprocal inhibition through ephaptic coupling. It has been postulated that this inhibition aids odour source discrimination, as synchronous arrival of different odour molecules (odorants) from a single source should increase ephaptic inhibition, whereas asynchronous arrival of odorants from different sources should decrease ephaptic inhibition. However, it was as yet unknown whether temporal arrival patterns of different odorants indeed modulate ephaptic inhibition, since past studies have focused on ephaptic inhibition of sustained ORN responses to prolonged and constant odour stimuli. However, most natural odour stimuli are not constant but rather transient and fluctuate as a result of dispersion in turbulent plumes in the air. To investigate the role of ephaptic inhibition in olfaction within turbulent environments, we recorded co-localized ORNs in the fruit fly Drosophila melanogaster exposed to dynamic odorant mixtures. We found that ephaptic inhibition does modulate transient ORN responses, and the strength of ephaptic inhibition decreases as the synchrony between arriving odorants decreases. These results support the hypothesis that ephaptic inhibition aids odour source discrimination. less

Numerous brain imaging studies have reported white matter alterations in schizophrenia, but the lipidome analysis of the corresponding tissue remains incomplete. In this study, we investigated the lipidome composition of six subcortical white matter regions corresponding to major axonal tracks in both control subjects and schizophrenia patients. All six regions exhibited a consistent pattern of quantitative lipidome alterations in schizophrenia, affecting specific lipid classes. These alterations partly involved myelin-forming lipid classes, particularly sphingolipids, with the extent of alterations reflecting the myelin changes previously reported in structural brain imaging studies. The other part of the schizophrenia-associated alterations, which showed a significant decrease in the disorder, involved lipid classes abundant in mitochondria. A similar significant decrease was also observed in the mitochondria-enriched membrane fraction isolated from the white matter of individuals with schizophrenia. This suggests a substantial reduction in the number of mitochondria in subcortical white matter in schizophrenia, a hypothesis supported by quantitative mitochondria staining. less

Human cognitive and linguistic generativity depends on the ability to identify abstract relationships between perceptually dissimilar items. Marcus et al. (1999) found that human infants can rapidly discover and generalize patterns of syllable repetition (reduplication) that depend on the abstract property of identity, but simple recurrent neural networks (SRNs) could not. They interpreted these results as evidence that purely associative neural network models provide an inadequate framework for characterizing the fundamental generativity of human cognition. Here, we present a series of deep long short-term memory (LSTM) models that identify abstract syllable repetition patterns and words based on training with cochleagrams that represent auditory stimuli. We demonstrate that models trained to identify individual syllable trigram words and models trained to identify reduplication patterns discover representations that support classification of abstract repetition patterns. Simulations examined the effects of training categories (words vs. patterns) and pretraining to identify syllables, on the development of hidden node representations that support repetition pattern discrimination. Representational similarity analyses (RSA) comparing patterns of regional brain activity based on MRI-constrained MEG/EEG data to patterns of hidden node activation elicited by the same stimuli showed a significant correlation between brain activity localized in primarily posterior temporal regions and representations discovered by the models. These results suggest that associative mechanisms operating over discoverable representations that capture abstract stimulus properties account for a critical example of human cognitive generativity. less