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Abstract #3758

Pattern classification reveals functional connectivity differences in expert and novice meditators

Roberto Guidotti1,2, Mauro Gianni Perrucci1,2, Cosimo Del Gratta1,2, Antonino Raffone3, and Gian Luca Romani1,2

1Neuroscience, Imaging, and Clinical Sciences, Gabriele D'annunzio University Chieti-Pescara, Chieti, Italy, 2Institute for Advanced Biomedical Technologies, Gabriele D'Annunzio University Chieti-Pescara, Chieti, Italy, 3Psychology, La Sapienza University Rome, Rome, Italy

In this work we explored how experience modulates ROI-based fMRI functional connectivity patterns in two different meditators groups: experts and novices. We recorded fMRI data during two styles of meditation (focused attention (Samatha), and open monitoring (Vipassana)), in two groups of subjects (Buddist Theravada Monks, and novices), and we calculated the connectivity pattern between ROIs from the AAL90 atlas. We then used a pattern classification approach to discriminate these groups and find which connections and nodes are important to classify subject experience. Regions having a role in decoding were those implicated in self-awareness and attention control.

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