Music to My Ears: Neural modularity and flexibility differ in response to real-world music stimuli.

Music listening involves many simultaneous neural operations, including auditory processing, working memory, temporal sequencing, pitch tracking, anticipation, reward, and emotion, and thus, a full investigation of music cognition would benefit from whole-brain analyses. Here, we quantify whole-brain activity while participants listen to a variety of music and speech auditory pieces using two network measures that are grounded in complex systems theory: modularity, which measures the degree to which brain regions are interacting in communities, and flexibility, which measures the rate that brain regions switch the communities to which they belong. In a music and brain connectivity study that is part of a larger clinical investigation into music listening and stroke recovery at Houston Methodist Hospital's Center for Performing Arts Medicine, functional magnetic resonance imaging (fMRI) was performed on healthy participants while they listened to self-selected music to which they felt a positive emotional attachment, as well as culturally familiar music (J.S. Bach), culturally unfamiliar music (Gagaku court music of medieval Japan), and several excerpts of speech. There was a marked contrast among the whole-brain networks during the different types of auditory pieces, in particular for the unfamiliar music. During the self-selected and Bach tracks, participants' whole-brain networks exhibited modular organization that was significantly coordinated with the network flexibility. Meanwhile, when the Gagaku music was played, this relationship between brain network modularity and flexibility largely disappeared. In addition, while the auditory cortex's flexibility during the self-selected piece was equivalent to that during Bach, it was more flexible during Gagaku. The results suggest that the modularity and flexibility measures of whole-brain activity have the potential to lead to new insights into the complex neural function that occurs during music perception of real-world songs.

Similarity of individual functional brain connectivity patterns formed by music listening quantified with a data-driven approach.

INTRODUCTION: This study aims to explore the similarities in functional connectivity (FC) patterns in individuals when listening to different music genres and, in comparison, to the spoken word, using a novel data-driven approach. Our model and findings can potentially be utilized for evaluating the neurological effects of therapeutic music interventions. MATERIALS AND METHODS: Twelve healthy volunteers listened to seven different sound tracks while undergoing functional magnetic resonance imaging (fMRI) scans: music of the volunteer's choice with positive emotional attachment, two selections of unfamiliar classical music, one classical piece repeated with visual guidance and three spoken language tracks. FC network graphs were created, and selected graph properties were evaluated toward their commonalities across sound tracks. For comparison, FC patterns represented by the graph adjacency matrices were directly compared for high and low BOLD activation during listening. RESULTS: Graph properties averaged across subjects showed similar values for the same sound track compared to different sound tracks (p < 0.003). For high BOLD activation involving most areas in the auditory cortex, FC patterns for the same sound track correlated highly (0.74 ± 0.11), whereas FC patterns for different sound tracks did not (0.09 ± 0.07; p < 6e-5). For low BOLD activation involving additional brain regions, correlation of FC patterns for the sound tracks was still higher (0.43 ± 0.07) than for different sound tracks (0.09 ± 0.05; p < 8e-6). CONCLUSION: Similar music creates similar functional activation and connectivity patterns in the brain of healthy individuals as does listening to the spoken word. Direct comparison of FC patterns yielded higher correlations than indirect comparisons of graph properties derived from corresponding FC networks.

An Exploratory Pilot Study of Brain Activation and Functional Connectivity Induced by the "Goldberg" Variations 276 years after their Commission.

Around 1741, composer Johann Sebastian Bach published a long and complicated keyboard piece, calling it Aria with diverse variations for a harpsichord with two manuals. It was the capstone of a publication project called German Clavier-Übung (Keyboard Practice) where Bach wanted to show what was possible at the keyboard in terms of technical development, virtuosic finesse and compositional sophistication. The music is meticulously patterned, beginning with a highly ornamented Aria, the bass line of which fuels the 30 variations that follow. The piece is clearly divided into two parts with the second half beginning with an overture with a fanfare opening, in variation 16. The piece ends as it begins, with the return of the Aria. Here, we present an investigation into activation and connectivity in the brain of a pianist, who listened to her own recording of the "Goldberg" variation while undergoing a fMRI examination. Similarity of brain connectivity is quantified and compared with the subjective scores provided by the subject.

Graph theoretical connectivity analysis of the human brain while listening to music with emotional attachment: feasibility study.

Benefits of listening to music with emotional attachment while recovering from a cerebral ischemic event have been reported. To develop a better understanding of the effects of music listening on the human brain, an algorithm for the graph-theoretical analysis of functional magnetic resonance imaging (fMRI) data was developed. From BOLD data of two paradigms (block-design, first piece: music without emotional attachment, additional visual guidance by a moving cursor in the score sheet; second piece: music with emotional attachment), network graphs were constructed with correlations between signal time courses as edge weights. Functional subunits in these graphs were identified with the MCODE clustering algorithm and mapped back into anatomical space using AFNI. Emotional centers including the right amygdala and bilateral insula were activated by the second piece (emotional attachment) but not by the first piece. Network clustering analysis revealed two separate networks of small-world property corresponding to task-oriented and resting state conditions, respectively. Functional subunits with highest interactions were bilateral precuneus for the first piece and left middle frontal gyrus and right amygdala, bilateral insula, left middle temporal gyrus for the second piece. Our results indicate that fMRI in connection with graph theoretical network analysis is capable of identifying and differentiating functional subunits in the human brain when listening to music with and without emotional attachment.