Author

Mahdi Enan

Maastricht UniversityORCID 0000-0002-6986-4830Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:Bayesian inference· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Federico De MartinoiD· 2 shared Ryszard AuksztulewicziD· 2 shared Caspar M. SchwiedrzikiD· 1 shared Fabrizio EspositoiD· 1 shared Lucía MelloniiD· 1 shared Mario SendeniD· 1 shared Nicola VanelloiD· 1 shared Paulina Janik· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersNeuroscience

Federico De MartinoORCID

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2 papers

Recent·Most cited

Learned Audiovisual Predictability Modulates Depth-Resolved Hippocampal-Cortical Functional Coupling

Santa Sozzi, Mahdi Enan, Ryszard Auksztulewicz, Caspar M. Schwiedrzik, Lucía Melloni, Fabrizio Esposito, Nicola Vanello, Federico De Martino

The paper investigates how learned auditory predictability affects depth-resolved functional coupling between hippocampal subfields and cortical regions using 7T fMRI.

bioRxiv · Oct 20, 2026 · PreprintNeuroscience

Predictive perception via simultaneous learning and inference

Mahdi Enan, Mario Senden, Paulina Janik, Yamil Vidal, Ryszard Auksztulewicz, Federico De Martino

This paper introduces a model that performs exact Bayesian inference over a discrete state space using a local Hebbian rule, demonstrating its ability to account for perception and decision-making under noise.

bioRxiv · Sep 28, 2026 · PreprintNeuroscience