Animals consolidate some, but not all, learning experiences into long-term memory. Across the animal kingdom, sleep has been found to have a beneficial effect on the consolidation of recently formed memories into long-term storage. However, the underlying mechanisms of sleep dependent memory consolidation are poorly understood. Here, we show that consolidation of courtship long-term memory in is mediated by reactivation during sleep of dopaminergic neurons that were earlier involved in memory acquisition. We identify specific fan-shaped body neurons that induce sleep after the learning experience and activate dopaminergic neurons for memory consolidation. Thus, we provide a direct link between sleep, neuronal reactivation of dopaminergic neurons, and memory consolidation.

The behavioral state of an animal can dynamically modulate visual processing. In flies, the behavioral state is known to alter the temporal tuning of neurons that carry visual motion information into the central brain. However, where this modulation occurs and how it tunes the properties of this neural circuit are not well understood. Here, we show that the behavioral state alters the baseline activity levels and the temporal tuning of the first directionally selective neuron in the ON motion pathway (T4) as well as its primary input neurons (Mi1, Tm3, Mi4, Mi9). These effects are especially prominent in the inhibitory neuron Mi4, and we show that central octopaminergic neurons provide input to Mi4 and increase its excitability. We further show that octopamine neurons are required for sustained behavioral responses to fast-moving, but not slow-moving, visual stimuli in walking flies. These results indicate that behavioral-state modulation acts directly on the inputs to the directionally selective neurons and supports efficient neural coding of motion stimuli.

Understanding memory formation, storage and retrieval requires knowledge of the underlying neuronal circuits. In Drosophila, the mushroom body (MB) is the major site of associative learning. We reconstructed the morphologies and synaptic connections of all 983 neurons within the three functional units, or compartments, that compose the adult MB’s α lobe, using a dataset of isotropic 8-nm voxels collected by focused ion-beam milling scanning electron microscopy. We found that Kenyon cells (KCs), whose sparse activity encodes sensory information, each make multiple en passant synapses to MB output neurons (MBONs) in each compartment. Some MBONs have inputs from all KCs, while others differentially sample sensory modalities. Only six percent of KC>MBON synapses receive a direct synapse from a dopaminergic neuron (DAN). We identified two unanticipated classes of synapses, KC>DAN and DAN>MBON. DAN activation produces a slow depolarization of the MBON in these DAN>MBON synapses and can weaken memory recall.

We describe a fluorescence in situ hybridization method that permits detection of the localization and abundance of single mRNAs (smFISH) in cleared whole-mount adult Drosophila brains. The approach is rapid and multiplexable and does not require molecular amplification; it allows facile quantification of mRNA expression with subcellular resolution on a standard confocal microscope. We further demonstrate single-mRNA detection across the entire brain using a custom Bessel beam structured illumination microscope (BB-SIM).

The perception of visual motion is critical for animal navigation, and flies are a prominent model system for exploring this neural computation. In Drosophila, the T4 cells of the medulla are directionally selective and necessary for ON motion behavioral responses. To examine the emergence of directional selectivity, we developed genetic driver lines for the neuron types with the most synapses onto T4 cells. Using calcium imaging, we found that these neuron types are not directionally selective and that selectivity arises in the T4 dendrites. By silencing each input neuron type, we identified which neurons are necessary for T4 directional selectivity and ON motion behavioral responses. We then determined the sign of the connections between these neurons and T4 cells using neuronal photoactivation. Our results indicate a computational architecture for motion detection that is a hybrid of classic theoretical models.

It is unclear how regulatory genes establish neural circuits that compose sex-specific behaviors. The Drosophila melanogaster male courtship song provides a powerful model to study this problem. Courting males vibrate a wing to sing bouts of pulses and hums, called pulse and sine song, respectively. We report the discovery of male-specific thoracic interneurons—the TN1A neurons—that are required specifically for sine song. The TN1A neurons can drive the activity of a sex-non-specific wing motoneuron, hg1, which is also required for sine song. The male-specific connection between the TN1A neurons and the hg1 motoneuron is regulated by the sexual differentiation gene doublesex. We find that doublesex is required in the TN1A neurons during development to increase the density of the TN1A arbors that interact with dendrites of the hg1motoneuron. Our findings demonstrate how a sexual differentiation gene can build a sex-specific circuit motif by modulating neuronal arborization.

•Doublesex-expressing TN1 neurons are necessary and sufficient for the male sine song•A subclass of TN1 neurons, TN1A, contributes to the sine song•TN1A neurons are functionally coupled to a sine song motoneuron, hg1•Doublesex regulates the connectivity between the TN1A and hg1 neurons

It is unclear how developmental regulatory genes specify sex-specific behaviors. Shirangi et al. demonstrate that the Drosophila sexual differentiation gene doublesex encodes a sex-specific behavior—male song—by promoting the connectivity between the male-specific TN1A neurons and the sex-non-specific hg1 neurons, which are required for production of the song.

Multi-modal image registration is a challenging task that is vital to fuse complementary signals for subsequent analyses. Despite much research into cost functions addressing this challenge, there exist cases in which these are ineffective. In this work, we show that (1) this is true for the registration of in-vivo Drosophila brain volumes visualizing genetically encoded calcium indicators to an nc82 atlas and (2) that machine learning based contrast synthesis can yield improvements. More specifically, the number of subjects for which the registration outright failed was greatly reduced (from 40% to 15%) by using a synthesized image.