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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.

Research Laboratories

This laboratory is organized into the following 3 divisions:


The combination of anatomical and functional information afforded by neuroimaging methods, like Magnetic Resonance Imaging, provides a powerful means to investigate the brain structural and functional organization. Indeed, neuroimaging data can be represented in terms of networks, or graphs, with anatomically or functionally defined districts representing the nodes, and the edges reflecting a measure of similarity or connectivity between different brain regions. The BraiNets lab leverages recent developments in graph theory and statistical physics to unravel structural and topological features of complex brain networks. Specific problems we are tackling at the moment include the:

  • Investigation of the modular structure of brain functional and structural connectivity beyond the resolution limit that affects current graph partitioning methods;
  • Identification and classification of connector hubs, i.e. brain regions responsible for the integration of brain activity;
  • Comparison of brain networks in healthy subjects and patients to identify connectivity-based markers of neurological and psychiatric disease;
  • Study of the interplay between structural and functional connectivity, particularly in the presence of severe alterations of white matter structure;
  • Investigation of the inception of functional connectivity networks in newborn babies.


Andrea Gabrielli - CNR Institute of Complex Systems (Rome. Italy)

  • Tiziano Squartini - CNR Institute of Complex Systems (Rome, Italy)
  • Guido Caldarelli – IMT (Lucca, Italy)
  • Sandro Vega-Pons - NILab, FBK-CIMeC (Trento, Italy)
  • Emanuele Olivetti  - NILab, FBK-CIMeC (Trento, Italy)
  • Paolo Avesani - NILab, FBK-CIMeC (Trento, Italy)
  • Matteo Caffini – CIMeC, University of Trento, Italy
  • Giorgio Vallortigara - CIMeC, University of Trento, Italy
  • Diego Sona – PAVIS
  • Vittorio Murino - PAVIS
  • Massimo Pasqualetti – University of Pisa, Italy

Neuroimaging of addiction

This line of research focuses on the application of functional Magnetic Resonance Imaging methods to map and investigate brain circuits involved in drug and alcohol addiction. Specifically, we pursue a translational, systems-based approach to understand the alterations in brain function, structure and connectivity in patients, and in animal models of drug dependence. Moreover, we apply neuroimaging methods, dubbed phMRI, to probe the effects of approved and new pharmacological treatments of addiction. This research effort is funded by the EC within the H2020 framework through the project System Biology of Alcohol Addiction (Sybil-AA).


  • Wolfgang Sommer - Central Institute of Mental Health (Mannheim, Germany)
  • Hamid Noori - Central Institute of Mental Health (Mannheim, Germany)
  • and the Sybil-AA Consortium
  • Roberto Ciccocioppo – University of Camerino, Italy
  • Nazzareno Cannella – University of Camerino, Italy

Optically Detected Magnetic Resonance

This ODMR laboratory focuses on the development and application of diamond nanoprobes for biological applications. This novel and promising technology exploits the unique properties of negatively-charged Nitrogen-Vacancy centers in diamond. The spin-dependent fluorescence of NV centers makes it possible to perform ultrahigh-sensitivity magnetometry experiments, thus probing cellular activity and microenvironment with unprecedented accuracy and resolution. Our laboratory develops and deploys new methods and diamond-based materials for optically detected NMR, optical pumping for NMR enhancement, and direct measurement of time-varying magnetic fields in living cells and tissues.


  • Alex Pines – Berkeley University, CA, USA
  • Claudia Avalos – Berkeley University, CA, USA
  • Antonio Miotello – University of Trento, Italy
  • Massimo Cazzanelli – University of Trento, Italy

The Functional Neuroimaging Laboratory focuses on the study of mammalian brain organization at the macroscale. We are interested in understanding how large scale functional activity and network dynamics originate, develop and govern behavioural states. A major goal of our research is to unravel the elusive neurophysiological basis of macroscale functional connectivity as measured with neuroimaging methods, and the underpinnings of its aberrations observed in human brain disorders such as autism spectrum disorders.

To achieve these goals, we have pioneered the use of advanced magnetic resonance magnetic (MRI) methods to image the structure and function of the living mouse brain under resting conditions, or upon pharmacological, neuromodulatory or genetic preconditioning. The combined use of high resolution structural (e.g. Diffusion Tensor imaging – DTI and voxel-based morphometry - VBM) and functional MRI (fMRI) defines a novel investigational platform that we have successfully employed to describe the intrinsic organization of the mouse brain in unprecedented detail. We aim to combine these novel approaches with cell type-specific optogenetic manipulations to establish causal relationship between local activity and its propagation at the systems level.

Macroscale functional organization of the mouse brain

This research leverages on the use of resting-state fMRI to obtain an integrated portrayal of the macroscale mouse functional connectome, i.e. the complex network of elements and connections that govern and compose the brain at the macroscale. As part of this effort, we provided the first demonstration of the presence of distributed resting-state functional connectivity networks in the mouse brain including a plausible homologue of the human salience and “default mode network” (DMN).

We are now using multidisciplinary approaches to investigate the function, behavioural relevance and directional topology of the mouse DMN and other connectivity networks via the use of canonical and advanced computational frameworks, including multivariate Granger Causality and dynamic causal modelling. Our efforts complement ongoing activities aimed at mapping the macroscale organization of the laboratory mouse, with the final goal of describe brain function as the integration of processes occurring at multiple scales.

Altered functional connectivity networks in acallosal and socially impaired BTBR mice)

Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior)


  • Stefano Panzeri  – Neural Computation Lab, IIT
  • Michele Caselle – University of Torino

Neurobiological basis of aberrant functional connectivity in autism

Deficits in large-scale structural and functional connectivity have been highlighted for autistic patient populations, but investigational approaches to unravel the elusive pathophysiological basis and significance of these phenomena are limited. By using fMRI in transgenic mouse lines mouse we have begun to establish causal relationships between genetic ASD-related mutations, neurodevelopmental processes and functional connectivity alterations. This line of research will provide testable hypotheses concerning the mechanisms underlying a key patho-physiological feature of autism, thus shedding light into the origin and clinical significance of these aberrations. Importantly, the use of readouts commonly used in the clinic offers a means to translate our findings from and to analogous patient populations

Altered functional connectivity networks in acallosal and socially impaired BTBR mice

Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior


  • Massimo Pasqualetti  – University of Pisa
  • Alessandro Usiello –Cienge, Napoli
  • Maria Luisa Scattoni – ISS, University of Torino

Endogenous neuromodulation of functional connectivity

At the cellular level, local functional connections giving rise to a specific circuit output are ‘configured’ by neuromodulatory environment. According to this view, axonal connectivity itself only establishes potential circuit configurations, whose availability and properties depend critically on local neuromodulatory state. However the degree to which similar dynamics may shape macroscale intrinsic brain function remains unknown. We are using optogenetic methods to determine the role of endogenous neuromodulation in shaping network activity as measured with resting state fMRI. Our research will help understand how local neuronal perturbation propagate at the network level, and the degree to which alterations in internal states affect macroscale network configurations


  • Massimo Pasqualetti  – University of Pisa
  • Ferruccio Pisanello – IIT, Lecce

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. Example projects include:

  • Information theoretic methods to study neural representations
  • Role of neural dynamics (spike timing, oscillations) in encoding and transmitting information
  • Role of gamma oscillations in dynamical routing communication across circuits information transfer
  • Role of noradrenaline in shaping cortical information processing Measures of information flow and functional connectivity from mesoscopic and macroscopic measures of neural activity
  • Theory of how causal manipulations can be used to crack the neural code

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.

We are interested in all aspects of vision and visual perception studied in the healthy and in the pathological brain. In particular we use transcranial magnetic stimulation (TMS) to study the mechanisms of intracortical inhibition and excitation that guide human response to visual stimuli and perceptual decision making.

Our overarching goal is to determine what cortical areas are necessary for tasks of visual attention and visual integration in space and time. All these functions can be severely impaired in cerebral lesion patients. Therefore our main goal is to develop new techniques of rehabilitation using TMS and transcranial direct current stimulation (tDCS).

The two main goals of the Active Vision Laboratory are:

  • developing sophisticated rendering systems that will allow the generation of more realistic and ecologically valid displays;
  • developing computational models of 3D perceptual processes and testing the biological validity of these models with the rendering tools.

The research activities are:

3D Information for perception and action

The main goal of the Active Vision Laboratory is to developi experimental paradigms that will allow us to have a more complete control over 3D cues to depth. The aim is to understand how 3D cues influence perceptual and motor judgments.

Motor judgments will be studied by having observers reach-to-grasp virtual or real objects. We will monitor the observers movements, typically the movement of their hand and fingers, through an OPTOTRAK system.

Full cue environments and "real objects"

Computer generated displays can be easily manipulated by the experimenter and therefore constitute a useful tool for controlling 3D cues in the 2D rendered images. However, residual and uncontrolled cues are present in these displays, which specify the true flat surface of the monitor.

Real surfaces produce a richer stimulation, which includes less studied but nevertheless effective cues like the blurring gradient, motion parallax, accommodation cues and ocular convergence cues. In this research project we intend to study the influence of these cues on the perception of 3D shape by utilizing real objects of which we can control with high precision the 3D structure.

In collaboration with the Robotics Unit of IIT we built a mechanical device that will control the mutual 3D position of metal rods. This apparatus will be combined with a traditional rendering apparatus and, through the use of half-reflective mirrors, we will be able to superimpose virtual images to the real objects and scenes. This hybrid combination of virtual and real objects will allow us to fully understand the effectiveness of the cues-to-flatness that are commonly present in traditional displays.

Active vision

When an observer moves, the retinal projections of 3D objects in the world change accordingly. This investigation is aimed at understanding how the sensing of body movements.

The Neural Computer Interaction Laboratory is interested in developing a theoretical framework, including a set of specifically designed and optimized mathematical algorithms, that can be used to analyze and decode Electrocorticographic signals (ECoGs) recorded form human subjects in order to increase our knowledge about the dynamics of the brain processes toward clinical applications of such knowledge.

Example projects include:

  • Time and frequency-domain multivariate analysis to understand what the spatiotemporal dynamics of ECoGs during specific tasks can reveal about neural information processing and how information is distributed across neural frequencies
  • Use ECoG grid recordings to understand dynamic communication across neural populations
  • Explore how to use state dependence from ECOGs to better decode neural activity and drive external devices online.


  • Neural Computation Lab in IIT (S. Panzeri)
  • National Center for Adaptive Neurotechnologies at Wadsworth Center of Albany (G. Schalk)
  • Albany Medical Center (A. Ritaccio)