|Titolo||A Graph Theoretical Approach to Neurobiological Databases Comparison|
|Autore/i||Dulio, P.; Finotelli, P.|
|Link||Download full text|
|Abstract||Music 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.