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Related Experiment Video

Updated: Feb 27, 2026

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Deep Beats, Deep Thoughts? Predicting General Cognitive Ability from Natural Music-Listening Behavior.

Larissa Sust1, Maximilian Bergmann2, Markus Bühner1

  • 1Department of Psychology, Ludwig-Maximilians-Universität München, 80802 Munich, Germany.

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|February 26, 2026
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Summary
This summary is machine-generated.

Everyday music listening habits, especially lyrical preferences, subtly correlate with general cognitive ability (GCA). This study used smartphone data to link music behavior to cognitive insights, revealing modest predictive performance.

Keywords:
general cognitive abilitymobile sensingmusic listening

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Area of Science:

  • Cognitive Psychology
  • Computational Social Science
  • Digital Phenotyping

Background:

  • Music listening is a complex behavior engaging cognitive systems.
  • Individual differences in music listening patterns may reflect general cognitive ability (GCA).
  • Digital behavioral data offers novel avenues for cognitive assessment.

Purpose of the Study:

  • To investigate if everyday music listening patterns predict general cognitive ability (GCA).
  • To explore the utility of smartphone-based behavioral data for cognitive insights.
  • To identify which aspects of music listening behavior are most predictive of GCA.

Main Methods:

  • Collected five months of smartphone-based music listening records from 185 participants.
  • Quantified listening habits (duration) and music preferences (audio/lyrical characteristics).
  • Employed linear LASSO regression and random forest models to predict GCA scores from behavioral features.

Main Results:

  • The random forest model showed modest, reliable associations between music listening behavior and GCA.
  • Lyrics-based preferences were the most predictive feature group, followed by listening habits.
  • Audio characteristics of music contributed minimally to predicting GCA.

Conclusions:

  • Cognitive ability may be subtly reflected in micro-patterns of everyday, non-achievement-related music listening behavior.
  • Digital behavioral data can complement traditional cognitive assessments, though challenges remain.
  • Future research should refine methods for using digital footprints to understand cognition.