Author

Michele Esposito

Centre National de la Recherche ScientifiqueORCID 0000-0002-7659-6520Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Approach:statistical model· 2 Research Focus:database / resource· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Bruno Lucio GiordanoiD· 3 shared Elia FormisanoiD· 3 shared Beatrice Tita· 1 shared Chris van der LansiD· 1 shared Christian FerreyraiD· 1 shared Giancarlo ValenteiD· 1 shared Giorgio MarinatoiD· 1 shared Maria Araújo VitóriaiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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3 shared papersNeuroscience

Bruno Lucio GiordanoORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

A behaviourally normed database of 1,377 natural sounds for auditory cognition and neuroscience

Marie Plegat, Maria Araújo Vitória, Giorgio Marinato, Beatrice Tita, Chris van der Lans, Minne Pijfers, Mia-Sara Bertovic, Michele Esposito, Elia Formisano, Bruno Lucio Giordano

The paper introduces a database of 1,377 natural sounds with behavioural norms for use in auditory cognition and neuroscience research.

bioRxiv · Aug 28, 2026 · PreprintNeuroscience

Multiscale Temporal Processing Supports Sound Recognition under Causal Constraints

Michele Esposito, Tonio Weidler, Christian Ferreyra, Bruno Lucio Giordano, Elia Formisano

This paper introduces a brain-inspired neural network model to test if multiscale temporal processing improves sound recognition under causal constraints, finding it does with limited benefit when future information is available.

bioRxiv · Jul 30, 2026 · PreprintNeuroscience

Bridging Auditory Perception and Natural Language Processing with Semantically informed Deep Neural Networks

Michele Esposito, Giancarlo Valente, Yenisel Plasencia-Calaña, Michel Dumontier, Bruno Lucio Giordano, Elia Formisano

This paper improves sound recognition by incorporating semantic information into deep neural networks, showing better alignment with human perception than traditional categorical models.

Scientific Reports · Sep 9, 2024Peer-reviewedNeuroscience