A Mechanistic Understanding of the Different Factors Affecting Adaptation and Flexibility During Probabilistic Reversal Learning: A Neurocomputational Study on Patients with Parkinson’s Disease and Control Subjects
The results provide a mechanistic explanation of the various factors that affect adaptation and flexibility in reinforcement learning, representing a first step toward characterizing and understanding the diverse behaviors on an individual basis.
Authors
- Elisa Pelosin (ORCID: https://orcid.org/0000-0002-9880-2241)
- Carola Cosentino (ORCID: https://orcid.org/0000-0001-6009-4350)
- Alessio Zizzi (ORCID: https://orcid.org/0009-0004-5772-6731)
- Federica Scarpellini (ORCID: https://orcid.org/0009-0000-9755-5309)
- Giulia Piermaria
- Luisa Sambati
- Silvana Pelle
- Mauro Ursino
- Susanna Mezzarobba
- Giovanna Calandra-Buonaura
Institutions
- Istituto delle Scienze Neurologiche di Bologna (IT)
- Azienda-Unita' Sanitaria Locale Di Cesena (IT)
- Ospedale Policlinico San Martino (IT)
- University of Genoa (IT)
- University of Bologna (IT)
Publication Details
- Journal
- Annals of Biomedical Engineering
- Published
- 2026-03-04
- DOI
- https://doi.org/10.1007/s10439-026-04038-4
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00