Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.09.16.676544

A groove brain-music interface for enhancing individual experience of urge to move

Abstract

When we listen to music, we often feel a pleasurable urge to move to music, known as groove. While previous studies have identified musical features that contribute to the groove experience, such as syncopation and tempo, they also report individual differences in which kinds of music people experience groove. Therefore, recommending groove-eliciting music requires accounting for individual differences. In this study, we aimed to develop a groove brain-music interface (G-BMI) that generates personalized playlists to maximize each individuals groove experience, using a neurofeedback system based on in-ear EEG. Twenty-four participants listened to three high-groove and three low-groove musical excerpts and rated their "urge to move." Using these ratings and the recorded EEG, we trained two LASSO models to build the G-BMI. Model 1 predicted urge to move from acoustic features extracted with VGGish, a pretrained neural network. Model 2 classified EEG data as recorded during listening to high-groove or low-groove music. Using Model 1, we ranked 7,225 candidate songs by predicted groove and assembled one groove-augmenting and one groove-diminishing playlist. Using Models 1 and 2, we created two additional playlists that updated Model 1 and the ranking in real-time based on in-ear EEG. Participants then listened to all four playlists and rated them on items including "urge to move." The groove-augmenting playlist that incorporated EEG achieved the highest "urge to move" ratings. These findings suggest that a personalized neurofeedback system employing EEG can help maximize individual groove experience.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Etani, T., Kondoh, S., Sakakibara, Y., Yoshida, K., Naruse, Y., Imamura, Y., Ibaraki, T., Fujii, S.. 2025-09-18. A groove brain-music interface for enhancing individual experience of urge to move. https://doi.org/10.1101/2025.09.16.676544

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Attention Across Scales: From Individual Variation to Social Hierarchies and Brain Networks in Semi-Free-Ranging Macaques

Attention is a fundamental brain function supporting perception, decision-making, and social behavior, and its dysfunction profoundly impairs daily life. It is both dynamic and stable, varying across observations and individuals, changing across the lifespan, and being shaped by social and environmental experience. Yet capturing this complexity remains a central challenge in neuroscience. Here, we integrated longitudinal behavioral assessments of semi-free-ranging macaques living in naturalistic social groups with resting-state fMRI. We quantified performance across days, ages, and social hierarchies and related it to intrinsic brain organization. Distinct attentional phenotypes emerged, including individuals with reduced attentional control. Performance followed an inverted-U lifespan trajectory, improving from childhood to adulthood before declining. Social status modulated attentional performance. Critically, nonlinear lifespan trajectories and associations with individual attentional differences were most clearly expressed in frontoparietal connectivity. Together, these findings reveal how sustained attention is organized across scales, providing a biological framework for its individual diversity, social modulation, and neural basis.

neuroscience↗

Decoding natural scenes from patterned optogenetic responses in mouse visual cortex

A central challenge in developing visual cortical prostheses is to determine how visual stimuli should be transformed into effective patterns of cortical stimulation. Although advances in stimulation technologies, including optogenetics, provide increasingly precise control over cortical activity, it remains unclear whether artificially evoked activity can reproduce the information content of naturally evoked visual representations. Here we establish a quantitative framework for evaluating visual encoding strategies by decoding cortical responses evoked by natural vision and patterned optogenetic stimulation. We developed a novel dual-modal paradigm in awake mice to bridge the gap between endogenous photostimulation and artificial network driving. By co-expressing the high-performance calcium indicator GCaMP6s and the red-shifted, ultra-sensitive opsin rsChRmine-oScarlet in the primary visual cortex (V1), we successfully translated dynamic natural movie frames into patterned, spatiotemporal optogenetic stimulation. Quantitative comparisons of macro-scale dynamics demonstrated that this patterned optogenetic injection evokes cortical states highly comparable and representationally aligned with those driven by actual visual photostimulation. To systematically evaluate the fidelity of these responses, we developed STAR, a deep learning model featuring spatial and temporal attention mechanisms, and successfully reconstructed the frames of natural movies from V1 signals under both experimental modalities. Collectively, our results demonstrate that complex sensory information can be both naturally encoded and synthetically injected into V1 circuits with high decoding fidelity. This work provides an empirical and computational proof-of-concept for intelligent, closed-loop biomimetic encoders, establishing a robust framework for next-generation cortical visual neuroprostheses and bidirectional brain-machine interfaces.

neuroscience↗

Why Is Spontaneous Blink Timing Informative? An Adaptive Scheduling Perspective

Spontaneous eye blinks have long been linked to cognitive processing, yet how task demands shape blink timing and its relationship to behavioral performance remains unclear. We examined spontaneous blink behavior in 576 adults performing two variants of the Continuous Performance Task (CPT). Blink occurrence and timing were most strongly modulated by the experimental condition in the more demanding CPT-AX task, whereas their association with response time was stronger in the CPT-X task, where more consistent blink timing predicted faster responses. This dissociation suggests that task structure changes not only blink behavior but also the behavioral relevance of blink timing. These findings are consistent with an adaptive scheduling account of spontaneous blinking and provide a conceptual framework for understanding when and why blink timing contains chronometric information about ongoing cognition.

neuroscience↗