At the MEG lab meeting, Danilo Benozzo gives a presentation entitled "Imaginary part of coherency as a measure of functional connectivity".
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At the Machine Learning and Interpretation in Neuroimaging conference Paolo Avesani presented a poster entitled "Disentanglement of Session and Plasticity Effects in Longitudinal fMRI Studies", the result of joint work with Vittorio Iacovella and Gabriele Miceli.
Paolo Avesani gave an invited lecture, entitled "Dissimilarity Representation for Unsupervised and Supervised Tract Segmentation", at the Machine Learning and Interpretation in Neuroimaging 2013 conference.
Angelo Bifone, coordinator at the Center for Neuroscience & Cognitive System (Italian Institute of Technology, Rovereto (TN)) presented research activities of the Center to NIlab members.
Paolo Avesani presented the work at NILab to the FBK Scientific Committee. The event represents the annual scientific and general review of the Center of Information Technology. Below is the agenda of the meeting.
The tutorial was organized for CIMEC members. The topics covered included version control, Git, GitHub.com, setting up a local repository on your machine, accessing a remote shared repository and contributing to it.
Paolo Avesani and Vittorio Iacovella presented Neurocloud project to a pool of physicians coming from Azienda Provinciale Servizi Sanitari (APSS).
Reference: V Iacovella, P Avesani, G Miceli (2013), Disentanglement of Session and Plasticity Effects in Longitudinal fMRI Studies - Machine Learning in Medical Imaging, 155-162 - doi: 10.1007/978-3-319-02267-3_20
Diana Porro has presented and defended a disertation entitled "Classification of continuous multi-way data via dissimilarity representation", being awarded with the degree of Doctor at Delft University of Technology, The Netherlands.
Alexandre Gramfort is currently assistant professor at Telecom ParisTech. His research interests include mathematical modeling and the computational aspects of brain imaging (MEG, EEG, fMRI, dMRI). He is generally interested in biomedical signal and image processing with the methods of scientific computing, data mining and machine learning.