Biology subjects

Cardona, A.

Publications and source records attributed to Cardona, A..

At least 19 recordsLinked to original sources

bioRxiv2026

The female larval fly CNS connectome: first draft

We release an enhanced FIB-SEM volume and associated neuron, mitochondria, synapse and glia automated segmentations for the complete, gap- and artifact-free central nervous system of the first instar female larval Drosophila melanogaster. Segmentation data is largely unproofread besides select neurons in the premotor and proprioceptive system and select subvolumes where synapses have been manually annotated, serving as training and evaluation data. The dataset represents the first complete central nervous system of the larval fly, and now awaits substantial improvement of machine vision approaches that effectively leverage domain knowledge for the automated yet data-guided proofreading, or substantial and costly human proofreading. All the data and methods are publicly available for further improvement and analysis.

neuroscience↗

bioRxiv2026

Connectomic analysis reveals the axial circuit for self-righting posture control in Drosophila

Postural control, the capacity of an animal to detect and correct an inappropriate body orientation, is a widespread and fundamental neurobiological function, yet the neural circuits that implement it remain poorly resolved in most species. The larva of Drosophila melanogaster performs a posture control stereotyped self-righting (SR) manoeuvre when turned upside-down, a behaviour previously shown to depend on a pair of segmentally repeated lateral transverse motor neurons (LT1/2-MNs) and on the normal expression of several Hox-targeting microRNAs. Here, we use a connectomics and a functional behavioural approach to trace and test the sensory, interneuronal and motor architecture of the SR circuit along the antero-posterior axis. Starting from the LT1/2-MNs, we identify a set of pre-motor interneurons, their principal upstream partners, and a population of class IV multidendritic sensory neurons as core components of the circuit, and show, through neuron-specific thermogenetic silencing, that inhibiting the great majority of these elements significantly impairs SR performance. We further find substantial overlap between the SR circuit and the previously described nociceptive rolling and touch crawling circuits, converging on shared interneurons including DnB, A02o (Wave-1) and TePn05. Network and axial connectivity analyses reveal a nested, hub-like organisation, a small number of integrator neurons bridging sensory and motor sub-networks, and a consistent decline in synapse number and density towards posterior segments. Together, these data yield the first axial wiring diagram for a postural control circuit in any animal and offer a set of structural principles including: hub organisation, shared sensory-motor structure, and antero-posterior connectivity gradients, which may extend to other segmentally organised nervous systems.

neuroscience↗

bioRxiv2026

An aorta to insulin producing cell sensor for internal state in Drosophila

The cellular circuits through which the internal state of an organism is sensed and relayed to the brain, and through which they bring about appropriate physiological and behavioral responses, remain largely unelucidated. Using whole-animal electron microscopy reconstruction of a Drosophila larva, we previously identified an Aorta sensory organ whose somata lie on the periphery of the brain, with dendritic arborizations in the wall of the anterior aorta, and whose axons project to the protocerebrum and synapse onto the insulin-producing cells (IPCs). Here we characterize the full anatomy and connectivity of this sensory organ. We show that the aorta sensory neurons make their strongest direct synaptic contacts onto IPCs and the neurosecretory cells producing Dromyosuppressin (DMS), with only weaker direct contacts to diuretic hormone 44 (DH44). They also make direct contacts to the enteric serotonergic neurons modulating swallowing (Se0ens), and to two single mushroom body neurons, DAN-j1 and MBON-d3, of the learning and memory center of Drosophila. Calcium imaging shows that the neurons are activated by fructose, and optogenetic manipulation reveals that their activity influences peptide content in IPCs, DH44 and DMS cells. Polysynaptic paths to the brain run through two morphologically distinct interneuron families. One, formed by the Hugin protocerebral neurons, targets the neuroendocrine system and is associated with bitter taste and pathogen induced feeding suppression. The other, formed by the BAmas projection neurons, targets dopaminergic input neurons and output neurons of the mushroom body. The Aorta sensory pathway therefore couples internal hemolymph state to two parallel central systems -- endocrine state control and mushroom body-associated value updating -- and provides a candidate substrate for a metabolic memory through which post-ingestive state is fed back into future feeding choice.

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bioRxiv2026

Olfactory Loss Enhances Visual Learning in Drosophila through Structural and Functional Reorganisation

Loss of a sensory modality can enhance performance in the remaining senses. However, the circuit mechanisms by which such cross-modal compensation can improve cognitive functions, including learning, are unknown. Here, we show that compromising olfaction in both larval and adult Drosophila enhances visual associative learning. Using behavioural analysis, functional imaging, and comparative connectomics, we reveal the circuit mechanisms that underlie this improvement. Animals with improved learning ability have enhanced responses to visual stimuli in the higher-order learning circuit. The complementary circuit mechanisms that can enhance these responses are structural reweighting of inputs in the larva, resulting in an increased fraction of synaptic inputs from visual pathways onto neurons in the learning circuit, and a reduction in cross-modal inhibition in the adult. Together, these findings reveal synaptic and disinhibitory circuit mechanisms that enhance learning in higher-order associative networks following sensory loss.

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bioRxiv2025

The Connectome Interpreter Toolkit

Complete synaptic wiring diagrams, or connectomes, of whole brains open new opportunities for studying the structure-function relationship of neural circuits. However, the large number of nodes and edges in the graphs makes the analysis challenging. Here, we present the Connectome Interpreter, an open-source software toolkit for efficient graph exploration to find polysynaptic pathways, compute the effective connectivity and receptive fields for arbitrarily deep neurons, slice out subcircuits, and construct non-linear but differentiable circuit models, implemented using efficient approaches tailored to large connectomes with abundant divergent and convergent connections, such as that of the fruit fly Drosophila melanogaster. Our approach delivers results orders of magnitude faster than conventional methods on consumer hardware. We demonstrate the capabilities of our toolkit with select applications, including quantifying the density of polysynaptic connections in the whole adult fruit fly brain, exploring the necessity for non-linearities in circuit modeling, and combining known function of neurons with the connectome to aid in formulating hypotheses of circuit function.

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bioRxiv2025

Descending neurons integrate learnt information from mushroom body with context to promote escape behaviour

To behave adaptively in the environment and select appropriate responses to sensory stimuli, animals integrate learnt information about the valences of stimuli with contextual information. While significant progress has been made in understanding how animals learn which stimuli predict positive and negative outcomes, how the outputs of associative learning circuits flexibly promote different behaviours, depending on context, is not well understood. Addressing this question requires mapping the pathways from learning circuits to nerve cord command neurons that promote specific actions, and understanding where and how contextual information converges with these pathways to modulate their activity. These are daunting tasks in larger brains where synaptic-resolution connectivity maps are not available. We, therefore, addressed this question in the tractable Drosophila larva using a combination of connectomic analyses, imaging and manipulation of neural activity and behavioural analysis. We characterised, with synaptic-resolution, the pathways from the higher-order learning circuit (the mushroom body, MB) all the way to a specific cord command neuron (Goro) in the nerve cord that promotes the most vigorous escape response, rolling. Rolling is the fastest, but also the most energetically costly escape response and is activated by multisensory cues in the context of predator attack. We identify a pair of brain descending neurons, Ipsigoro, that integrate learnt information (via input from MBONs) and nociceptive context (via input from ascending neurons) to facilitate rolling via direct inputs to Goro. Our study reveals the circuit mechanism by which context and learnt information are integrated by brain descending neurons to activate specific nerve cord command neurons and promote specific actions.

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bioRxiv2025

The central complex of the larval fruit fly brain

In holometabolous insects such as the fruit fly Drosophila melanogaster, the brain central complex (CX) develops during metamorphosis and serves the adult stage. Whether a form of the CX exists in the brain of the evolutionarily novel larval stages is not known. Here, we analyzed the connectome of the larval brain and, on the basis of neuronal lineages, synaptic connectivity patterns, and anatomy, identified a putative larval CX, comprising 4 key neuropils: the protocerebral bridge (PB), the ellipsoid body (EB), the fan-shaped body (FB) and the noduli (NO). Consistent with our interpretation, we found in the larval brain synaptic connectivity patterns characteristic of the adult, including (i) visual input into the PB and EB; (ii) modulation of CX neuropil inputs by the mushroom body (MB); (iii) reciprocal connectivity between CX neuropils and select MB compartments; and (iv) strong connectivity between CX neuropils. While some neuronal lineages contributing to the larval CX do not contribute to the adult CX, many others are conserved. The characterization of a larval CX brings structure to largely unexamined larval brain circuits, linking with a vast body of literature, and will inform the design of experiments to probe larval brain function.

neuroscience↗

bioRxiv2025

Beyond Agreement: Standardizing Crowdsourced Synapse Annotations through Proofreading in EM Connectomics

AO_SCPLOWBSTRACTC_SCPLOWReliable synapse identification in volumetric EM is hampered by subtle, 3D cues that yield variable human judgments. We present a standardized proofreading protocol that pairs explicit, operational criteria with machine-learning candidate generation and a two-stage calibration of annotators. In two larval Drosophila melanogaster volumes imaged at 8x8x8 nm, five raters (expert + 4 calibrated annotators) reviewed model-proposed candidates using efficient node-based labels. Multi-rater judgments were aggregated with a probabilistic Dawid-Skene (DS) model to produce consensus labels with calibrated uncertainty. Post-calibration, individual annotator accuracy versus the expert improved (McNemar p < 0.05 for all raters), DS-expert agreement increased, and DS posterior entropy decreased for true positives/negatives, indicating more decisive consensus; gains were modest and dataset-dependent in chance-corrected agreement (Krippendorffs ). By making uncertainty explicit, this protocol converts noisy judgments into auditable supervision suitable for training and evaluation, while honestly communicating residual ambiguity essential for reliable and robust connectomics at scale.

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bioRxiv2025

A multisensory, bidirectional, valence encoder guides behavioral decisions

A key function of the brain is to categorize sensory cues as repulsive or attractive and respond accordingly. While we have some understanding of how sensory information is processed in the sensory periphery, the classification of cues according to valence in central brain circuits is less well understood. Here, we addressed this question in the Drosophila larva, where we could leverage the synaptic resolution connectome to determine where innate and learnt information from distinct aversive and appetitive sensory modalities converges; and combine this with imaging and manipulation of neural activity to determine how valence information is encoded and used to guide navigation. We found that information from multiple innately aversive and attractive sensory modalities converges onto a common output neuron of the learning circuit, specifically the Mushroom Body output neuron, MBON-m1. We discovered that this neuron is required for navigating both attractive odor and aversive temperature cues and is activated by attractive cues, such as food odour and sugar, and inhibited by different aversive cues, such as cooling, salt, or non-food odors. Together, our study reveals a neuron that bi-directionally encodes valence and controls actions.

neuroscience↗

bioRxiv2025

Combining brainwide activity imaging and electron microscopy reveals novel nociceptive circuits

To understand how brains work, it is necessary to connect neural activity to synaptic-resolution circuit architecture. Recent advances in light-sheet microscopy (LSM) enable whole-brain, cellular-resolution imaging of activity of all neuronal cell bodies, however, most neurons from such datasets cannot be identified. In most organisms, neurons are identifiable based on their projections (and not based on their cell body position) which, when densely labelled, cannot be resolved using LSM. Here, we present a novel methodology to overcome this by combining whole-brain activity imaging with subsequent volume electron microscopy imaging of the same brain to visualise neuronal projections and identify neurons with interesting activity. We used this approach to identify brain neurons that process input from multisensory (nociceptive and mechanosensory) Basin interneurons that trigger vigorous escape in Drosophila larvae in response to threatening somatosensory stimuli. After whole-brain imaging of neuronal activity during Basin activation, we imaged the same brain with an enhanced focused ion-beam electron microscope (eFIB-SEM). We registered the functional and anatomical volumes and reconstructed (in the eFIB-SEM volume) the projections of neurons that responded to Basin activation to determine their developmental lineage and identity. This revealed a distributed network for processing threatening somatosensory stimuli that trigger vigorous escape spanning 25 distinct lineages and many distinct brain areas, and included direct brain targets of Basin neurons that integrate somatosensory information with other modalities, as well as brain output neurons (descending neurons [DN]) that likely contribute to action-selection. Our workflow provides a powerful framework for mapping neuronal activity onto structure across an entire brain, yielding novel insights into the distributed central processing of noxious stimuli.

neuroscience↗

bioRxiv2025

Mapping the nervous system of the Idiosepius hallami pygmy squid: insights from whole-animal X-ray nanotomography imaging.

The study of a nervous system as big as the cephalopods requires multimodal imaging approaches capable of capturing neural architecture across scales. Here, we present a whole-animal volume of the pygmy squid hatchling Idiosepius hallami, acquired using X-ray holographic nanotomography at the beamline ID16A of the European Synchrotron. The reconstructed 3D volume comprises 40 tiled scans acquired at a voxel size of 125 nm. While individual neurons are not resolved at this resolution, we segmented major body regions and mapped the large-scale connectivity by tracing afferent and efferent nerve bundles, including projections from the olfactory organs, chromatophore lobes, and arm ganglia to the brain. The acquisition of this dataset represents a significant milestone for X-ray nanotomography, being the largest whole animal volume imaged at this spatial resolution. The volume serves as a resource for comparative neuroscience and cephalopod biology.

neuroscience↗

bioRxiv2025

Morphology and ultrastructure of pharyngeal sense organs of Drosophila larvae

This study provides a comprehensive ultrastructural analysis of the pharyngeal sensory system in Drosophila melanogaster larvae, focusing on the four major pharyngeal sense organs: the ventral pharyngeal sensilla (VPS), dorsal pharyngeal sensilla (DPS), dorsal pharyngeal organ (DPO), and posterior pharyngeal sensilla (PPS). Our analysis revealed 15 sensilla across these organs, comprising four mechanosensory, nine chemosensory, and two dual-function sensilla. We identified 35 Type I neurons (six mechanosensory and 29 chemosensory) and six Type II neurons with putative chemosensory functions. Additional sensory structures, including papilla sensilla and chordotonal organs in the cephalopharyngeal region, were characterized. This detailed mapping and classification of pharyngeal sensory structures completes their structural characterization and provides a foundation for future anatomical and functional studies of sensory perception in insects. This work represents a significant step towards a complete analysis of the larval sensory system, providing new opportunities for investigating how an organism processes sensory information to navigate and interact with its environment.

neuroscience↗

bioRxiv2025

Cross-species comparative connectomics reveals the evolution of an olfactory circuit

Animal behavioural diversity ultimately stems from variation in neural circuitry, yet how central neural circuits evolve remains poorly understood. Studies of neural circuit evolution often focus on a few elements within a network. However, addressing fundamental questions in evolutionary neuroscience, such as whether some elements are more evolvable than others, requires a more global and unbiased approach. Here, we used synapse-level comparative connectomics to examine how an entire olfactory circuit evolves. We compared the full antennal lobe connectome of the larvae of two closely related Drosophila species, D. melanogaster and D. erecta, which differ in their ecological niches and odour-driven behaviours. We found that evolutionary change is unevenly distributed across the network. Some features, including neuron types, neuron numbers and interneuron-to-interneuron connectivity, are highly conserved. These conserved elements delineate a core circuit blueprint presumably required for fundamental olfactory processing. Superimposed on this scaffold, we find rewiring changes that mirror each species ecologies, including a systematic shift in the excitation-to-inhibition balance in the feedforward pathways. We further show that some neurons have changed more than others, and that even within individual neurons some synaptic elements remain conserved while others display major species-specific changes, suggesting evolutionary hot-spots within the circuit. Our findings reveal constrained and adaptable elements within olfactory networks, and establish a framework for identifying general principles in the evolution of neural circuits underlying behaviour.

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bioRxiv2024

Why do we have so many excitatory neurons?

The emerging electron microscopy connectome datasets provides connectivity maps of the brains at single cell resolution, enabling us to estimate various network statistics, such as connectedness. We desire the ability to assess how the functional complexity of these networks depends on these network statistics. To this end, we developed an analysis pipeline and a statistic, XORness, which quantifies the functional complexity of these networks with varying network statistics. We illustrate that actual connectomes have high XORness, as do generated connectomes with the same network statistics, suggesting a normative role for functional complexity in guiding the evolution of connectomes, and providing clues to guide the development of artificial neural networks.

neuroscience↗

bioRxiv2024

Invariant synaptic density across species

The nervous system scales with animal size while preserving function, yet the principles underlying this stability remain unclear. Here, we analyse the ultra-structure and connectivity of thousands of neuronal cells across species, including fly, zebrafish, mouse, and human, and found a conserved feature that stabilises neuronal responses across scales: an average of one synapse per micrometre of dendritic cable. We show that the appropriate synaptic density is shaped by correct axon-dendrite positioning and synaptic transmission during development. We find that this specific synaptic density is linked to wiring optimisation in neurons, where dendrites minimise cable length and conduction delays. Finally, simulations indicate invariant synaptic density as a neuronal design principle, conserved for its ability to synergise with other cell-intrinsic properties to stabilise voltage responses across cell types and species.

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bioRxiv2024

iTome Volumetric Serial Sectioning Apparatus for TEM

An automated ultra-microtome capable of sectioning thousands of ultrathin sections onto standard TEM slot grids was developed and used to section: a complete Drosophila melanogaster first-instar larva, three sections per grid, into 4,866 34-nm-thick sections with a cutting and pickup success rate of 99.74%; 30 microns of mouse cortex measuring roughly 400 um x 2000 um at 40 nm per slice; and a full adult Drosophila brain and ventral nerve column into 9,300 sections with a pickup success rate of 99.95%. The apparatus uses optical interferometers to monitor a reference distance between the cutting knife and multiple sample blocks. Cut sections are picked up from the knife-boat water surface while they are still anchored to the cutting knife. Blocks without embedded tissue are used to displace tissue-containing sections away from the knife edge so that the tissue regions end up in the grid slot instead of on the grid rim.

neuroscience↗

bioRxiv2024

Steering From the Rear: Coordination of Central Pattern Generators Underlying Navigation by Ascending Interneurons

Understanding how animals coordinate movements to achieve goals is a fundamental pursuit in neuroscience. Here we explore how neurons that reside in posterior lower-order regions of a locomotor system project to anterior higher-order regions to influence steering and navigation. We characterized the anatomy and functional role of a population of ascending interneurons in the ventral nerve cord of Drosophila larvae. Through electron microscopy reconstructions and light microscopy, we determined that the cholinergic 19f cells receive input primarily from premotor interneurons and synapse upon a diverse array of postsynaptic targets within the anterior segments including other 19f cells. Calcium imaging of 19f activity in isolated central nervous system (CNS) preparations in relation to motor neurons revealed that 19f neurons are recruited into most larval motor programmes. 19f activity lags behind motor neuron activity and as a population, the cells encode spatio-temporal patterns of locomotor activity in the larval CNS. Optogenetic manipulations of 19f cell activity in isolated CNS preparations revealed that they coordinate the activity of central pattern generators underlying exploratory headsweeps and forward locomotion in a context and location specific manner. In behaving animals, activating 19f cells suppressed exploratory headsweeps and slowed forward locomotion, while inhibition of 19f activity potentiated headsweeps, slowing forward movement. Inhibiting activity in 19f cells ultimately affected the ability of larvae to remain in the vicinity of an odor source during an olfactory navigation task. Overall, our findings provide insights into how ascending interneurons monitor motor activity and shape interactions amongst rhythm generators underlying complex navigational tasks.

neuroscience↗

bioRxiv2024

Local Delivery of Soluble Fractalkine (CX3CL1) Peptide Restore Ribbon Synapses After Noise-Induced Cochlear Synaptopathy

Efficacy of chemokine fractalkine isoforms was evaluated for restoration of loss of inner hair cell ribbon synapses and hearing after noise-induced cochlear synaptopathy (NICS). Previously, we have demonstrated a critical role for fractalkine signaling axis (CX3CL1-CX3CR1) in synaptic repair where in the presence of fractalkine receptor (CX3CR1) expressed by cochlear macrophages, the damaged synapses are spontaneously repaired. Here, we examined whether overexpression of fractalkine ligand (CX3CL1 or FKN) in the form of a peptide is effective in restoring the lost synapses and hearing after NICS. Remarkably, single transtympanic (TT) injection of soluble isoform of FKN (sFKN) peptide at 1 day after synaptopathic noise trauma showed significant recovery of ABR thresholds, ABR peak I amplitudes and ribbon synapses in both FKN-wildtype and knockout mice when compared to mice injected with full length membrane-bound FKN peptide (mFKN). Mechanistically, sFKN peptide treatment increased macrophage numbers in the cochlea and in the absence of those macrophages, sFKN failed to restore loss of synapses and hearing after NICS. Furthermore, sFKN treatment attenuated cochlear inflammation after noise overexposure without altering the expression of CX3CR1. Finally, sFKN peptide was detectable inside the cochlea localized to the sensory epithelium for 24 hours after TT injection. These data provide a robust proof-of-principle that local delivery of an immune factor, sFKN is effective in restoring lost ribbon synapses and hearing after NICS in a macrophage-dependent manner and highlights the potential of sFKN as an immunotherapy for cochlear synaptopathy due to noise or aging. SummaryTranstympanic delivery of soluble FKN peptide is effective in restoring lost inner hair cell ribbon synapses and hearing after noise-induced cochlear synaptopathy in a macrophage-dependent manner.

neuroscience↗