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Distinct sensitivity to spectrotemporal modulation supports brain asymmetry for speech and melody

Contributor(s): Material type: TextTextWashington, DC Science 2020Online resources: In: Science 367 1043–1047 (2020) 28 February 2020Abstract: Does brain asymmetry for speech and music emerge from acoustical cues or from domain-specific neural networks? We selectively filtered temporal or spectral modulations in sung speech stimuli for which verbal and melodic content was crossed and balanced. Perception of speech decreased only with degradation of temporal information, whereas perception of melodies decreased only with spectral degradation. Functional magnetic resonance imaging data showed that the neural decoding of speech and melodies depends on activity patterns in left and right auditory regions, respectively. This asymmetry is supported by specific sensitivity to spectrotemporal modulation rates within each region. Finally, the effects of degradation on perception were paralleled by their effects on neural classification. Our results suggest a match between acoustical properties of communicative signals and neural specializations adapted to that purpose.
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Does brain asymmetry for speech and music emerge from acoustical cues or from domain-specific
neural networks? We selectively filtered temporal or spectral modulations in sung speech stimuli for
which verbal and melodic content was crossed and balanced. Perception of speech decreased only
with degradation of temporal information, whereas perception of melodies decreased only with spectral
degradation. Functional magnetic resonance imaging data showed that the neural decoding of speech
and melodies depends on activity patterns in left and right auditory regions, respectively. This
asymmetry is supported by specific sensitivity to spectrotemporal modulation rates within each
region. Finally, the effects of degradation on perception were paralleled by their effects on neural
classification. Our results suggest a match between acoustical properties of communicative signals
and neural specializations adapted to that purpose.

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