The MRI Lab studies the basics and application of Magnetic Resonance Imaging from different perspectives.
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.
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.
- Tiziano Squartini - IMT (Lucca, Italy)
- Andrea Gabrielli - 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, IIT Genova
- Vittorio Murino - PAVIS, IIT Genova
- 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)
- Roberto Ciccocioppo - University of Camerino, Italy
- Nazzareno Cannella - University of Camerino, Italy
The computational infrastructure of the Brain Networks lab includes two servers Dell PowerEdge, 24 CPUs Intel Xeon each and 512 GB RAM, and a cluster of high performance workstations. The Magnetic Resonance Imaging lab is equipped with a multichannel Bruker Pharmascan MR scanner at 7 Tesla, and sophisticated ancillary equipment for physiological control and monitoring; this lab has access to CiMeC in vivo facilities.
Community detection in weighted brain connectivity networks beyond the resolution limit. Nicolini C., Bordier C., Bifone A. Neuroimage (2017)
Modular structure of brain networks: breaking the resolution limit by Surprise. Nicolini C., Bifone A. Scientific Reports (2016)
Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior Zhan Y, Paolicelli RC, Sforazzini F, Weinhard L, Bolasco G, Pagani F, Vyssotski AL, Bifone A, Gozzi A, Ragozzino D, Gross CT Nat Neurosci. 2014 Mar;17(3):400-6. doi: 10.1038/nn.3641. Epub 2014 Feb 2. (2014)
USPIO-loaded Red Blood Cells as a biomimetic MR contrast agent: a relaxometric study A. Boni, D. Ceratti, A. Antonelli, C. Sfara, M. Magnani, E. Manuali, S. Salamida, A. Gozzi, and A. Bifone Contrast Media and Molecular Imaging (2014)
Reduced limbic metabolism and fronto-cortical volume in rats vulnerable to alcohol addiction A. Gozzi, F. Agosta, M. Massi, R. Ciccocioppo, and A. Bifone Neuroimage (2013)