Abstract #3758

Pattern classification reveals functional connectivity differences in expert and novice meditators

Roberto Guidotti^1,2, Mauro Gianni Perrucci^1,2, Cosimo Del Gratta^1,2, Antonino Raffone³, and Gian Luca Romani^1,2

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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