Currently the Center studies with systems level neuroscience in human subjects an in animal models, including psychophysical techniques, functional imaging, trans-cranial stimulation and computational approaches. Research includes examining how sensory cues and active movements of the body are integrated to support perception, studying brain mechanisms for attention and timing, studying functional connectivity in the brain, devising advanced methods for decoding/encoding neurophysiological signals.
The Functional Neuroimaging Laboratory focuses on the study of mammalian brain organization at the macroscale in order to understand how large scale functional activity and network dynamics originate, develop and govern behavioural states.
The Neural Computation Laboratory 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.
The research line in Systems Neurobiology searches for the design principles of biological neural systems Our quest for general rules is substantiated by the observation that neural circuits evolved to perform specific functions and therefore they are far from random. General rules must exist, which govern the choice of a biological design in each neural system.
We also share a research activity with Tommaso Fellin at Center for Convergent Technologies (Genoa)
The Neural Coding Laboratory is a shared interdisciplinary initiative between Stefano Panzeri and Tommaso Fellin. The laboratory aims to crack the neural code by understanding the cellular mechanisms underlying the encoding, processing and transfer of information in neuronal circuits.
To achieve these goals, we combine state-of-the-art recording of neural activity (single and multiple unit activity, local field potentials, patch-clamp recordings, two-photon imaging) and causal manipulation of neural activity (single- and two-photon patterned optogenetics) with advanced analytical approaches (information theory, causal analysis) and realistic modeling of neural network dynamics.