Nicolò G. Ceffa

The paper releases a complete larval Drosophila CNS connectome with automated segmentations and highlights the need for improved machine vision for proofreading.

This study shows that losing olfaction in Drosophila enhances visual learning through structural and functional changes in neural circuits.

The paper identifies a putative larval central complex in Drosophila melanogaster, showing structural and connectivity similarities to the adult CX.

The paper identifies a circuit mechanism in Drosophila larvae where descending neurons integrate learned information and contextual cues to activate specific escape behaviors.

The paper introduces a standardized proofreading protocol for improving synapse annotations in EM connectomics by combining machine learning with multi-rater calibration and probabilistic modeling.