Biology subjects

Raccuglia, D.

Publications and source records attributed to Raccuglia, D..

4 recordsLinked to original sources

bioRxiv2025

An inhibitory feedback circuit mediating sleep need and sensory gating in Drosophila

Many animals integrate sensory information during the day and sleep at night. How sensory processing during wakefulness contributes to making an organism tired at night, however, remains elusive. Here, we investigate the role of excitatory helicon cells in Drosophila (ExR1), a distinct neural population dedicated to processing sensory information. Using combined optogenetics and voltage imaging, we show that helicon cells excite sleep-promoting R3m ring neurons and trigger a subsequent autoinhibition of R3m via voltage- and Ca2+-gated K+ channels such as Slowpoke. Investigating the flies sleep patterns, we found that blocking synaptic output from helicon as well as RNAi-mediated knockdown of Slowpoke in R3m reduces sleep quality and leads to loss of nocturnal sleep, indicating that sleep need is generated via this route. Further, we show that excitation of R3m induces feedback inhibition of helicon cells via ionotropic GABA receptors. Knockdown of the ionotropic GABA receptor subunit Rdl in helicon cells increases sleep latency and causes sleep loss at the beginning of the night. We show that inhibition via Rdl facilitates nocturnal slow-wave activity which forms a sensory filter and prevents sleep disruption through auditory stimuli. We therefore uncover an inhibitory feedback circuit, in which neurons processing sensory information directly activate sleep promoting neurons to generate sleep need. At night, this sleep need is then converted into actual sleep, facilitated by the formation of a neural filter that stabilizes sleep/wake transition.

neuroscience↗

bioRxiv2022

Coherent network oscillations regulate quiescence and behavioral responsiveness in Drosophila

For all animals, undisturbed periods of rest are essential for undergoing recuperative processes. How neural interactions create brain states capable of dissociating an animal from its external world to promote quiescence remains a fundamental question. Here, we show how coherent network oscillations can create neural filters that favor a quiescent brain state over a state that promotes navigation. Circadian regulation and excitability of the Drosophila sleep homeostat (dFSB) generate nighttime specific slow-wave coherence between neural networks mediating sleep need (R5) and networks gating locomotion (helicon cells). Optogenetically mimicking coherent activity reveals that temporally fine-tuned R5 oscillations promote a quiescent state and reduce responsiveness to visual stimuli by hierarchically overruling locomotion-promoting helicon cells. We uncover that R5 and helicon bidirectionally regulate behavioral responsiveness by providing antagonistic inputs to head direction targets (EPG). Thus, coherent oscillations can form the mechanistic basis of neural filters by temporally associating antagonistic inputs and therefore reducing the functional connectivity between locomotion gating and navigational networks.

neuroscience↗

bioRxiv2020

NOSA, an analytical toolbox for multicellular optical electrophysiology

Understanding how neural networks generate activity patterns and communicate with each other requires monitoring the electrical activity from many neurons simultaneously. Perfectly suited tools for addressing this challenge are genetically encoded voltage indicators (GEVIs) because they can be targeted to specific cell types and optically report the electrical activity of individual, or populations of neurons. However, analyzing and interpreting the data from voltage imaging experiments is challenging because high recording speeds and properties of current GEVIs yield only low signal-to-noise ratios, making it necessary to apply specific analytical tools. Here, we present NOSA (Neuro-Optical Signal Analysis), a novel open source software designed for analyzing voltage imaging data and identifying temporal interactions between electrical activity patterns of different origin. In this manuscript we explain the challenges that arise during voltage imaging experiments and provide hands-on analytical solutions. We demonstrate how NOSAs baseline fitting, filtering algorithms and movement correction can compensate for shifts in baseline fluorescence and extract electrical patterns from low signal-to-noise recordings. Moreover, NOSA contains powerful features to identify oscillatory frequencies in electrical patterns and extract neuronal firing characteristics. NOSA is the first open-access software to provide an option for analyzing simultaneously recorded optical and electrical data derived from patch-clamp or other electrode-based recordings. To identify temporal relations between electrical activity patterns we implemented different options to perform cross correlation analysis, demonstrating their utility during voltage imaging in Drosophila and mice. All features combined, NOSA will facilitate the first steps into using GEVIs and help to realize their full potential for revealing cell-type specific connectivity and functional interactions. If you would like to test NOSA, please send an email to the lead contact.

neuroscience↗

bioRxiv2019

Network-specific synchronization of electrical slow-wave oscillations regulates sleep in Drosophila

Slow-wave rhythms characteristic of deep sleep oscillate in the delta band (0.5-4 Hz) and can be found across various brain regions in vertebrates. Across systems it is however unclear how oscillations arise and whether they are the causal functional unit steering behavior. Here, for the first time in any invertebrate, we discover sleep-relevant delta oscillations in Drosophila. We find that slow-wave oscillations in the sleep-regulating R2 network increase with sleep need. Optical multi-unit voltage recordings reveal that single R2 neurons get synchronized by sensory and circadian input pathways. We show that this synchronization depends on NMDA receptor (NMDARs) coincidence detector function and on an interplay of cholinergic and glutamatergic inputs setting a resonance frequency. Genetically targeting the coincidence detector function of NMDARs in R2, and thus the uncovered mechanism underlying synchronization, abolished network-specific slow-wave oscillations. It also disrupted sleep and facilitated light-induced wakening, directly establishing a causal role for slow-wave oscillations in regulating sleep and sensory gating. We therefore propose that the synchronization-based increase in oscillatory power likely represents an evolutionarily conserved, potentially optimal, strategy for constructing sleep-regulating sensory gates.

neuroscience↗