Journals and Proceedings
Astrocytes enhance plasticity response during reversal learning.L. Squadrani, C. Wert-Carvajal, D. Mueller-Komorowska, K. Bohmbach, C. Henneberger, P. Verzelli *, T. Tchumatchenko*.
Communications Biology (2024).
DOI
Physics-Informed Graph Neural Cellular Automata: An Application to Compartmental Modelling..
N.Navarin, P. Frazzetto, L. Pasa, P. Verzelli, F. Visentin, A. Sperduti, C. Alippi.
International Joint Conference on Neural Networks (IJCNN) (2024).
DOI
Editorial overview: Computational neuroscience as a bridge between artificial intelligence, modeling and data.
P. Verzelli, T. Tchumatchenko, J. Kotaleski.
Current Opinion in Neurobiology (2024).
DOI
Unbiased choice of global clustering parameters for single-molecule localization microscopy.
P. Verzelli, A. Nolds, C. Sun, M. Heilemann, E. Schuman , T. Tchumatchenko.
Scientific Reports (2022).
DOI
Learn to Synchronize, Synchronize to Learn.
P. Verzelli, C. Alippi, L. Livi.
Chaos: An Interdisciplinary Journal of Nonlinear Science (2021).
DOI
Input-to-State Representation in Linear Reservoirs Dynamics.
P. Verzelli, C. Alippi, L. Livi, P. Tino.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (2021).
DOI
Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere.
P. Verzelli, C. Alippi, L. Livi.
Scientific Reports (2019).
DOI
Hyper-spherical Reservoirs for Echo State Networks.
P. Verzelli, C. Alippi, L. Livi.
International Conference on Artificial Neural Networks (ICANN) (2019).
DOI
A study of Dependency Features of Spike Trains Through Copulas.
P. Verzelli, L. Sacerdote.
Biosystems (2019).
DOI
A characterization of the Edge of Criticality in Binary Echo State Networks.
P. Verzelli, L. Livi, C. Alippi.
International Workshop on Machine Learning for Signal Processing (MLSP) (2018).
DOI
Conference Talks and Posters
Bonn Brain Meeting (2026)Poster: Behavioral Biomarkers of Epilepsy: A Machine Learning Approach to Seizure Prediction
Computational and Systems Neuroscience (Cosyne) conference (2026)
Poster: Modelling Neural Population Dynamics in C. elegans to Reveal Behaviour-Embedded Manifold Structures
iBehave Science Retreat (2025)
Contributed Talk: Linking Behavior and Brain activity in C. Elegans
Bernstein Conference of Computational Neuroscience (2025)
Poster: Behavioral Biomarkers of Epilepsy: A Machine Learning Approach to Seizure Prediction
Computational and Systems Neuroscience (Cosyne) conference (2025)
Poster: Stable Learning in the Presence of Synaptic Variation
Bernstein Conference of Computational Neuroscience (2024)
Poster: Linking Spontaneous Synaptic Activity to Learning
iBehave Summer School (2024)
Contributed Talk: Predictive Power of Behavior: Robust Low-dimensional Representation from Pose Data
Conference of the Italian Network for Computational Neuroscience (INCN) (2024)
Poster: Linking Spontaneous Synaptic Activity to Learning
Bonn Brain Meeting (2024)
Poster: Predictive Power of Behavior: Robust Low-dimensional Representation from Pose Data
FENS Forum 2024 (2024)
Poster: Astrocyte-mediated D-serine Regulation Bridges the Gap between BCM Theory, Neurobiology and Behavior
Emergent AI Conference (2023)
Invited Talk: Beyond Invasive Monitoring: A Machine Learning Framework for Video-Driven Seizure Forecasting
Bernstein Conference of Computational Neuroscience (2023)
Poster: Beyond Invasive Monitoring: A Machine Learning Framework for Video-Driven Seizure Forecasting
Bonn Brain Meeting (2023)
Poster: Beyond Invasive Monitoring: A Machine Learning Framework for Video-Driven Seizure Forecasting
Emergent AI Retreat (2022)
Invited Talk: Everything is a Computer (if You are Brave Enough)
International Joint Conference on Neural Networks (IJCNN) (2021)
Contributed Talk: On the Role of Synchronization in Reservoir Computing
Dynamics Internal Seminar (University of Exeter) (2020)
Invited Talk: Learning Dynamical Systems Using Dynamical Systems
Symposium on Machine Learning and Dynamical Systems (2020)
Contributed Talk: Learn to Synchronize, Synchronize to Learn: Measuring the Echo State Property
International Conference on Artificial Neural Networks (ICANN) (2019)
Contributed Talk: Hyper-spherical Reservoirs for Echo State Networks
Workshop on Dynamical Systems and Brain-inspired Information Processing (2019)
Poster: Echo State Networks with Self-Normalizing Activations on the Hyper-sphere
Machine Learning for Signal Processing (MLSP) (2018)
Poster: A characterization of the edge of criticality in binary echo state networks
Neural Coding (2018)
Poster: A study of dependency features of spike trains through copula