Biology subjects

Ceffa, N.

Publications and source records attributed to Ceffa, N..

3 recordsLinked to original sources

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.

neuroscience↗

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.

neuroscience↗