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Shan T, Cappelloni MS, Maddox RK. Subcortical responses to music and speech are alike while cortical responses diverge. Sci Rep 2024; 14:789. [PMID: 38191488 PMCID: PMC10774448 DOI: 10.1038/s41598-023-50438-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 12/20/2023] [Indexed: 01/10/2024] Open
Abstract
Music and speech are encountered daily and are unique to human beings. Both are transformed by the auditory pathway from an initial acoustical encoding to higher level cognition. Studies of cortex have revealed distinct brain responses to music and speech, but differences may emerge in the cortex or may be inherited from different subcortical encoding. In the first part of this study, we derived the human auditory brainstem response (ABR), a measure of subcortical encoding, to recorded music and speech using two analysis methods. The first method, described previously and acoustically based, yielded very different ABRs between the two sound classes. The second method, however, developed here and based on a physiological model of the auditory periphery, gave highly correlated responses to music and speech. We determined the superiority of the second method through several metrics, suggesting there is no appreciable impact of stimulus class (i.e., music vs speech) on the way stimulus acoustics are encoded subcortically. In this study's second part, we considered the cortex. Our new analysis method resulted in cortical music and speech responses becoming more similar but with remaining differences. The subcortical and cortical results taken together suggest that there is evidence for stimulus-class dependent processing of music and speech at the cortical but not subcortical level.
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Affiliation(s)
- Tong Shan
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA
- Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY, USA
- Center for Visual Science, University of Rochester, Rochester, NY, USA
| | - Madeline S Cappelloni
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA
- Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY, USA
- Center for Visual Science, University of Rochester, Rochester, NY, USA
| | - Ross K Maddox
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA.
- Del Monte Institute for Neuroscience, University of Rochester, Rochester, NY, USA.
- Center for Visual Science, University of Rochester, Rochester, NY, USA.
- Department of Neuroscience, University of Rochester, Rochester, NY, USA.
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