Author

Marialaura De Grazia

University of PaviaORCID 0009-0004-6158-1707Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:electronic health records· 1 Approach:simulation· 1 Research Focus:software / tool· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Claudia CasellatoiD· 2 shared Egidio Ugo D'AngeloiD· 2 shared Claudia A. M. Gandini Wheeler‐KingshottiD· 1 shared Danilo BenozzoiD· 1 shared Dimitri RodarieiD· 1 shared Filippo MarchettiiD· 1 shared Fulvia PalesiiD· 1 shared Roberta Maria LorenziiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 19 mutual co-author links

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2 shared papersNeuroscience

Claudia CasellatoORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintMay 14, 2026

A biologically-grounded cerebellar spiking network model with realistic synaptic transmission captures complex circuit dynamics.

Marialaura De Grazia, Danilo Benozzo, Dimitri Rodarie…·Claudia Casellato

DOI 10.64898/2026.05.12.724100

electronic health recordsstatistical model

𝕏 PostBluesky

NeurosciencebioRxivPreprintMar 20, 2026

Automated derivation of mean field models from spiking neural networks for the simulation of brain dynamics

Roberta Maria Lorenzi, Marialaura De Grazia, Claudia A. M. Gandini Wheeler‐Kingshott…·Claudia Casellato

The paper introduces Auto-MFM, a tool that automatically derives mean field models from spiking neural networks, accurately reproducing population dynamics and enabling exploration of physiological and pathological brain circuits.

1 citation

spatial transcriptomicsstatistical model

𝕏 PostBluesky