4.8 Article

A neural population selective for song in human auditory cortex

Journal

CURRENT BIOLOGY
Volume 32, Issue 7, Pages 1470-+

Publisher

CELL PRESS
DOI: 10.1016/j.cub.2022.01.069

Keywords

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Funding

  1. National Institutes of Health [DP1 HD091947, P41-EB018783, P50-MH109429, R01-EB026439, U24-NS109103, U01-NS108916, R25-HD088157, K99DC018051-01A1]
  2. US Army Research Office [W911NF-15-1-0440]
  3. National Science Foundation [BCS-1634050]
  4. NSF Science and Technology Center for Brains, and Machines [CCF-1231216]
  5. Fondazione Neurone
  6. Howard Hughes Medical Institute (LSRF Postdoctoral Fellowship)
  7. Kristin R. Pressman and Jessica J. Pourian '13 Fund at MIT

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This study developed a new method to investigate the neural code for music in the human auditory cortex using intracranial responses and fMRI. The results revealed that representations of music are fractionated into subpopulations selective for different types of music, with one subpopulation specialized for the analysis of songs.
How is music represented in the brain? While neuroimaging has revealed some spatial segregation between responses to music versus other sounds, little is known about the neural code for music itself. To address this question, we developed a method to infer canonical response components of human auditory cortex using intracranial responses to natural sounds, and further used the superior coverage of fMRI to map their spatial distribution. The inferred components replicated many prior findings, including distinct neural selectivity for speech and music, but also revealed a novel component that responded nearly exclusively to music with singing. Song selectivity was not explainable by standard acoustic features, was located near speech- and music-selective responses, and was also evident in individual electrodes. These results suggest that representations of music are fractionated into subpopulations selective for different types of music, one of which is specialized for the analysis of song.

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