The causal inference of cortical neural networks during music improvisations

12.09.2014
The causal inference of cortical neural networks during music improvisations

Wan X1, Crüts B2, Jensen HJ1 
1 Department of Mathematics and Centre for Complexity Science, Imperial College London, London, UK; 2 Brainmarker BV, Molenweg 15a, Gulpen, The Netherlands

“We present an EEG study of two music improvisation experiments. Professional musicians with high level of improvisation skills were asked to perform music either according to notes (composed music) or in improvisation. Each piece of music was performed in two different modes: strict mode and “let-go” mode. Synchronized EEG data was measured from both musicians and listeners. We used one of the most reliable causality measures: conditional Mutual Information from Mixed Embedding (MIME), to analyze directed correlations between different EEG channels, which was combined with network theory to construct both intra-brain and cross-brain networks. Differences were identified in intra-brain neural networks between composed music and improvisation and between strict mode and “let-go” mode. Particular brain regions such as frontal, parietal and temporal regions were found to play a key role in differentiating the brain activities between different playing conditions. By comparing the level of degree centralities in intra-brain neural networks, we found a difference between the response of musicians and the listeners when comparing the different playing conditions.”

For our Italian friends:

Gli Autori presentano uno studio EEG da due esperimenti di improvvisazione musicale. Ai musicisti professionisti, con un grande livello di capacità di improvvisazione, veniva chiesto di eseguire musica composta o di improvvisare. Ogni pezzo musicale veniva eseguito in due modalità differenti: “preciso” e “rilassato”. I dati di sincronizzazione EEG sono stati registrati sia sui musicisti sia sugli ascoltatori. Gli Autori utilizzano una delle più attendibili misure di causalità, l’Informazione reciproca da embedding misto (MIME) condizionale, per analizzare le correlazioni dirette tra differenti canali EEG, che sono stati combinati con la teoria dei network per costruire circuiti sia intra-cerebrali che cross-cerebrali. Sono state identificate differenze nei network intra-neurali tra la musica composta e l’improvvisazione e tra il modo “preciso” e il modo “rilassato”. Particolari regioni cerebrali come quella frontale, parietale e temporale sono state identificate come regioni chiave nella distinzione delle attività cerebrali tra le differenti condizioni di esecuzione. Comparando i diversi gradi di centralità nei network intra-cerebrali, si è riscontrata una differenza tra la risposta dei musicisti e quella degli ascoltatori quando si comparavano le differenti condizioni di esecuzione.

For full article, please visit Cornell University Library.

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