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News and events

11/12/2013

At the MEG lab meeting, Danilo Benozzo gives a presentation entitled "Imaginary part of coherency as a measure of functional connectivity".

10/12/2013

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.

09/12/2013

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.

29/11/2013

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.

22/11/2013

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.

11/11/2013

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.

08/11/2013

Paolo Avesani and Vittorio Iacovella presented Neurocloud project to a pool of physicians coming from Azienda Provinciale Servizi Sanitari (APSS).

20/10/2013

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

15/10/2013

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.

08/10/2013

In the course of the tutorial, Alexandre Gramfort gave an introduction to Python and NumPy, as well as an intorduction to machine learning with scikit-learn + hands-on session on MEG data. Finally, he introduced MNE/mne-python - a tool for analyzing MEG data and, and guided the participants through a hands-on session on MEG sensor vs. source space analysis.

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