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

Bernstein Conference of Computational Neuroscience (2024)
Talk: Linking Spontaneous Synaptic Activity to Learning

iBhevae Summer School (2024)
Talk: Predictive Power of Behavior: Robust Low-dimensional Representation from Pose Data

Conference of the Italian Network for Computational Neuroscience (INCN) (2024)
Talk: Linking Spontaneous Synaptic Activity to Learning

Bonn Brain Meeting (2024)
Talk: Predictive Power of Behavior: Robust Low-dimensional Representation from Pose Data

FENS Forum 2024 (2024)
Talk: Astrocyte-mediated D-serine Regulation Bridges the Gap between BCM Theory, Neurobiology and Behavior

Emergent AI Conference (2023)
Talk: Beyond Invasive Monitoring: A Machine Learning Framework for Video-Driven Seizure Forecasting

Emergent AI Retreat (2022)
Talk: Everything is a Computer (if You are Brave Enough)

International Joint Conference on Neural Networks (IJCNN) (2021)
Talk: On the Role of Synchronization in Reservoir Computing

Dynamics Internal Seminar (University of Exeter) (2020)
Talk: Learning Dynamical Systems Using Dynamical Systems

Symposium on Machine Learning and Dynamical Systems (2020)
Talk: Learn to Synchronize, Synchronize to Learn: Measuring the Echo State Property

International Conference on Artificial Neural Networks (ICANN) (2019)
Talk: Hyper-spherical Reservoirs for Echo State Networks

Workshop on Dynamical Systems and Brain-inspired Information Processing (2019)
Talk: Echo State Networks with Self-Normalizing Activations on the Hyper-sphere

Machine Learning for Signal Processing (MLSP) (2018)
Talk: A characterization of the edge of criticality in binary echo state networks

Neural Coding (2018)
Talk: A study of dependency features of spike trains through copula