TitoloA Graph Theoretical Approach to Neurobiological Databases Comparison
Autore/iDulio, P.; Finotelli, P.
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AbstractMusic is one of the best tools to evoke emotions and feelings in people. Generally, people like classical music, hip hop, house, disco, underground or other kinds of music. People choose songs basing on their preferences. For example, a subject while performing an action such as running, studying or relaxing tends to listen to songs that give her or him a pleasant feeling. Interesting issues emerge: First, collecting the brain reactions when the brain is stimulated by songs (classified as pleasant). Second, comparing them with the resting state condition, and third representing the neural network changes in terms of emergent subgraphs. We propose a general methodology concerning phase transitions analysis of an arbitrary number of conditions. We also apply such a methodology to real acoustic data and, though our findings generally seem to agree with others available in the literature, they also point out the existence of functional connectivity between pairs of cerebral areas, usually not immediately associated to an acoustical task. Our results may explain why people when listening to pleasant music activated emotional cerebral areas in spite of the fact that the music they classify as pleasant is different for each subject. Possible applications to Neuropsychiatry are discussed.