My career goal is to become a leading researcher on cognitive neuroscience, with a special focus on the neural mechanisms underlying auditory perception, including how humans track and perceive the fleeting audi- tory information in speech and music. In this proposal, I outline a research program to investigate the acoustic and neural distinctions between speech and music, two specialized forms of auditory signals that are closely tied to the human mind. Despite our increasingly rich understanding of the perceptual and neural mechanisms for processing speech or music, surprisingly little is known about why and how they are treated as different au- ditory signals by the human mind and brain in the first place. Investigating these distinctions is foundational for a thorough understanding of how acoustic waveforms are transformed into meaningful information. The work will provide a more solid basis for understanding cognition and communication as well as treating people with communicative deficits, such as people with autism, Alzheimer's disease, and aphasia. I hypothesize that the temporal structure reflected in the amplitude modulation (AM) of speech and music signals is a critical distinctive feature for the brain and engages to different processing pathways, as speech and music are known to have distinct AM rates. A series of studies, combining psychophysics, MEG (magne- toencephalography), fMRI (functional magnetic resonance imaging), and machine learning approaches, will use stimuli with AM rates across the modulation frequency ranges of speech and music to address this topic at the computational (the goals), algorithmic (the representations and operations), and implementational (neural mechanism) levels. (1) Does the AM rate of a sound affect whether it will be perceived as speech or music? (2) Does the AM rate of a stimulus optimize speech and music perceptual performance at different frequencies? (3) What are the underlying neural mechanisms and the associated brain regions implementing the differentiation of speech and music? Aim 1 investigates whether the AM rate of a sound conditions it to be processed as speech or music. By manipulating the AM rate of noise-vocoded speech and music recordings, I hypothesize that the sounds with slower or faster AM rates will likely to be perceived as music or speech, respectively, the perceptual judgment will be biased by the higher or lower spectral energy of neural oscillatory activity (meas- ured by MEG) while listening to the sounds, respectively, and the associated brain regions will be revealed by fMRI with machine learning decoding approaches.
Aim 2 investigates whether the AM rate of stimuli optimizes speech and music perceptual performances at different rates. I hypothesize that the music perceptual perfor- mance is optimal at slower AM rates while the speech perceptual performance is optimal at faster AM rates, and the neural oscillatory entrainment at lower or higher frequency band has domain-specific function facilitat- ing speech or music perceptual performance.
Speech and music are two specialized forms of auditory signal that are closely tied to human mind; however, despite our increasingly rich understanding of the perceptual and neural mechanisms of human processing of speech or music, surprisingly little is known how they are treated as different auditory signals by the human mind and brain at the first place. The current proposal aims to investigate the fundamental differences between speech and music at the acoustic, perceptual, and neural levels, by combining psychophysics, neuroimaging, and machine learning approaches. Investigating their distinctions is crucial for understanding how acoustic waveforms are transformed into meaningful information, and it will provide the basis for understanding and treating people with communicative deficits, such as people with autism, Alzheimer's disease, and aphasia.