| A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin–Huxley models M Carlu, O Chehab, L Dalla Porta, D Depannemaecker, C Héricé, ... Journal of neurophysiology 123 (3), 1042-1051, 2020 | 50 | 2020 |
| Temporal stability of stimulus representation increases along rodent visual cortical hierarchies E Piasini, L Soltuzu, P Muratore, R Caramellino, K Vinken, H Op de Beeck, ... Nature communications 12 (1), 4448, 2021 | 35 | 2021 |
| Target spike patterns enable efficient and biologically plausible learning for complex temporal tasks P Muratore, C Capone, PS Paolucci PloS one 16 (2), e0247014, 2021 | 15 | 2021 |
| Beyond spiking networks: the computational advantages of dendritic amplification and input segregation C Capone, C Lupo, P Muratore, PS Paolucci Proceedings of the National Academy of Sciences 120 (49), e2220743120, 2023 | 13 | 2023 |
| Analysis and model of cortical slow waves acquired with optical techniques M Celotto, C De Luca, P Muratore, F Resta, AL Allegra Mascaro, ... Methods and protocols 3 (1), 14, 2020 | 11 | 2020 |
| Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks P Muratore, S Tafazoli, E Piasini, A Laio, D Zoccolan Advances in Neural Information Processing Systems 35, 30206-30218, 2022 | 10 | 2022 |
| Error-based or target-based? A unified framework for learning in recurrent spiking networks C Capone, P Muratore, PS Paolucci PLoS computational biology 18 (6), e1010221, 2022 | 10 | 2022 |
| Op de Beeck H, Balasubramanian V, Zoccolan D. 2021. Temporal stability of stimulus representation increases along rodent visual cortical hierarchies E Piasini, L Soltuzu, P Muratore, R Caramellino, K Vinken Nature Communications 12 (1), 0 | 7 | |
| Burst-dependent plasticity and dendritic amplification support target-based learning and hierarchical imitation learning C Capone, C Lupo, P Muratore, PS Paolucci International Conference on Machine Learning, 2625-2637, 2022 | 6 | 2022 |
| Intrinsic dynamics enhance temporal stability of stimulus representation along rodent visual cortical hierarchies E Piasini, L Soltuzu, P Muratore, R Caramellino, K Vinken, HO de Beeck, ... bioRxiv, 822130, 2019 | 2 | 2019 |
| Likelihood based learning rule for temporal coding in recurrent spiking neural networks P Muratore, C Capone, PS Paolucci arXiv preprint arXiv:2002.05619, 2020 | 1 | 2020 |
| Unraveling the complexity of rat object vision requires a full convolutional network and beyond P Muratore, A Alemi, D Zoccolan Patterns 6 (2), 2025 | | 2025 |
| Learning fast while changing slow in spiking neural networks C Capone, P Muratore Neuromorphic Computing and Engineering 4 (3), 034002, 2024 | | 2024 |
| Investigating neural representations in rat visual cortex and deep neural networks P Muratore SISSA, 2024 | | 2024 |
| Learning fast changing slow in spiking neural networks C Capone, P Muratore arXiv preprint arXiv:2402.10069, 2024 | | 2024 |
| Reply to Reviewers Target spike patterns enable efficient and biologically plausible learning for complex temporal tasks P Muratore, C Capone, PS Paolucci | | |
Cristiano CaponePostdoc, ISS, Rome, ItalyEmail verificata su iss.it