Neural Computation

Research activities

The Neural Computation Laboratory is directed by Stefano Panzeri and aims at understanding how circuits of neurons in the brain exchange and transmit information and contribute to sensation and behavior.

The laboratory addresses this issue by developing advanced statistical tools for the analysis of simultaneous recordings of neural activity from multiple locations, by applying these tools to empirical data to understand how neurons encode and transmit information, and by developing biophysically plausible models of neural circuit dynamics that explain the empirical findings.


Mathematical methods for cracking the neural code using recordings of neural activity at different locations and spatio-temporal scales.

We produced original mathematical methods, based on the mathematical principles of communication theory, for the analysis of neural data recorded simultaneously from multiple sites, even at different spatial and temporal scales. These methods determine which spatial and temporal features of neural activity encode sensory stimuli, how correlations between these features affect information processing, and if and how their information is used to produce useful behavior.

The role of the temporal structure of neural responses in sensory information coding.

In collaboration with several neurophysiological laboratories, we apply the mathematical methods developed by us to provide a number of novel insights about how the cerebral cortex uses the timing of neural activity to encode information about the natural environment in visual, auditory and somatosensory neural systems. In recent work, we have demonstrated the role of the millisecond precise spike timing in encoding sensory information, the role of network-level oscillations (spanning several octaves of frequency) in encoding and transmitting sensory information, and the mechanisms for multiplexing information in spike times and oscillations at multiple concurrent temporal scales.

Recurrent neural network models of how cortical circuits encode information.

We developed biophysically plausible yet analytically tractable models of recurrent spiking neural that can be quantitatively fit to data to establish how activity of networks of excitatory and inhibitory neurons encode the time and frequency structure of their inputs, and how changes in excitation and inhibition or neuromodulation affect how cortical circuits process and transmit information.


Theoretical research in the lab is mostly carried out in the Center for Neuroscience and Cognitive Systems at IIT Rovereto. The laboratory is equipped with state of the art computational facilities. We currently feature a cluster with a total of more than 700 processors high-end Intel Xeon processors with a total of more than 2TB of RAM memory and 60 TB of disk, hosted in 16 servers.

Selected Publications


Principal investigator

Stefano Panzeri

Stefano Panzeri received a Laurea in Physics from the University of Torino, and a PhD in Computational Neuroscience from SISSA, Trieste, Italy. He has held personal Research Fellowship awards in both theoretical physics and computational neuroscience, including an INFN junior Fellowship in Theoretical Physics at Turin University, an EU Marie Curie postdoctoral Fellowship at the University of Oxford, and an MRC Research Fellowship in Neuroinformatics at the University of Newcastle. He has held tenured Faculty positions as assistant, associate and full professor at the Universities of Manchester and Glasgow. He has been visiting scientist at the Max Planck Institute for Biological Cybernetics and at Harvard Medical School. He served as Deputy Chair of the UK Medical Research Council panel for fellowships in Bioinformatics and Neuroinformatics; as a member of the UK EPSRC Review College, and as an editor of the journal Frontiers in Systems Neuroscience and of Journal of Neuroscience methods. His research lies at the interface between theory and experiment and aims at understanding the principles of cortical information processing by developing new quantitative data analysis techniques based on the principles of Information Theory and by developing computational models of neural network function. At IIT, he works as Senior Scientist (with Tenure) and directs the Laboratory of Neural Computation. He also currently serves as Coordinator of the Center for Neuroscience and Cognitive Systems of the IIT in Rovereto.