Neural Computation Lab @ SISSA

The Neural Computation Lab lab is part of the PhD program in Cognitive Neuroscience at the International School for Advanced Studies (SISSA) in Trieste, Italy.


We are interested in the computational principles that underlie the ability of the animal brain to perform efficient inference and prediction under tight resource constraints. We study behavior and cognition in animals and humans, and information processing in neuronal circuits.

We develop and employ techniques that draw from a broad range of approaches, including statistical learning, information theory, artificial neural networks, and Bayesian statistics. We care about open and reproducible science.


Eugenio Piaisni Eugenio Piasini, Principal Investigator ( Eugenio got his PhD from University College London, with a thesis on information processing in the input stage of the cerebellar cortex. After his PhD he was a postdoctoral researcher at the Italian Institute of Technology, working on neural coding and information theory. Later on, he was a Fellow of the Computational Neuroscience Initiative at the University of Pennsylvania. He joined SISSA in 2021.

Selected publications

Piasini et al ACAIN 2021 Piasini E, Balasubramanian V, Gold J I. Effect of Geometric Complexity on Intuitive Model Selection. First International Symposium on Artificial Intelligence and Neuroscience (ACAIN), 2021. Best paper award. doi:10.1007/978-3-030-95467-31

Caramellino, Piasini et al eLife 2021 Caramellino R*, Piasini E*, Buccellato A, Carboncino A, Balasubramanian V, Zoccolan D. Rat sensitivity to multipoint statistics is predicted by efficient coding of natural scenes. eLife 2021. doi:10.7554/eLife.72081

Piasini, Soltuzu et al Nature Communications 2021 Piasini E*, Soltuzu L*, Muratore P, Caramellino R, Vinken K, Op de Beeck H, Balasubramanian V, Zoccolan D. Temporal stability of stimulus representation increases along rodent visual cortical hierarchies. Nature Communications 2021. doi:10.1038/s41467-021-24456-3

Molano-Mazon et al ICLR 2018 Molano-Mazon M, Onken A, Piasini E*, Panzeri S*. Synthesizing realistic neural population activity patterns using generative adversarial networks. ICLR 2018. arXiv:1803.00338

Pica et al NeurIPS 2017 Pica G, Piasini E, Safaai H, Runyan C A, Diamond M E, Fellin T, Kayser C, Harvey C D, Panzeri S. Quantifying how much sensory information in a neural code is relevant for behavior. NeurIPS 2017. arXiv:1712.02449

Pica et al Entropy 2017 Pica G, Piasini E, Chicharro D, Panzeri S. Invariant components of synergy, redundancy, and unique information among three variables. Entropy 2017. doi:10.3390/e19090451

Panzeri et al Neuron 2017 Panzeri S, Harvey C D, Piasini E, Latham P E, Fellin T. Cracking the neural code for sensory perception by combining statistics, intervention, and behavior. Neuron 2017. doi:10.1016/j.neuron.2016.12.036

Runyan, Piasini et al Nature 2017 Runyan C*, Piasini E*, Panzeri S, Harvey C. Distinct timescales of population coding across cortex. Nature 2017. doi:10.1038/nature23020

Billings et al Neuron 2014 Billings G, Piasini E, Lőrincz A, Nusser Z, Silver R A. Network structure within the cerebellar input layer enables lossless sparse encoding. Neuron 2014. doi:10.1016/j.neuron.2014.07.020

Author: Eugenio Piasini

Created: 2022-02-02 Wed 23:40