Abstract
Background:
The brain’s function changes during various activities, and numerous studies have explored this field. An intriguing and significant area of research is the brain’s functioning during imagination and periods of inactivity.
Objective:
This study explores the differences in brain connectivity during music listening and imagination: by identifying distinct neural connectivity patterns and providing insights into the cognitive mechanisms underlying auditory imagination.
Methods:
Effective connectivity matrices were generated using generalized partial directed coherence (GPDC) and directed Directed Transfer Function (dDTF) methods applied to non-invasive electroencephalography data from these two conditions. Statistical tests were performed to illustrate the differences in brain connectivity, followed by the creation of brain graphs and the application of a non-parametric permutation test to demonstrate statistical significance. Data classification between listening to music and imagining it was performed using an Support Vector Machine (SVM) classifier with different feature vectors.
Results:
Combining features extracted from GPDC and dDTF achieved an accuracy of 71.3% while using GPDC and dDTF features individually yielded accuracies of 60% and 62.1%, respectively. Among all the graph’s global features, only modularity and small-worldness showed statistically significant differences in dDTF and GPDC. Overall, findings reveal that information flows from the left hemisphere to the right hemisphere increases during music imagination compared with listening, highlighting distinct neural connectivity patterns associated with imaginative processes.
Conclusion:
The study provides novel insights into the distinct neural connectivity patterns during music listening and imagination, contributing to the broader understanding of cognitive processes associated with auditory imagination and perception.
Impact Statement
This research provides a novel analysis of brain connectivity patterns during music listening and imagination using electroencephalography data, employing advanced techniques like generalized partial directed coherence and directed Directed Transfer Function. The findings reveal distinct neural connectivity differences between these cognitive states, enhancing our understanding of imaginative processes. By highlighting specific brain regions involved, this study paves the way for further research in cognitive neuroscience and potential applications in neurorehabilitation and brain–computer interfaces. These insights could significantly influence approaches to studying brain connectivity and developing new interventions for cognitive and neurological disorders.
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