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Scholarly Works (4 results)

  • Thesis
  • Peer Reviewed
UC Merced Electronic Theses and Dissertations (2021)

Despite being a common activity, singing is a complex behavior. It involves processes such as: maintaining mental imagery of desired tones, activating a motor plan to make a vocal production, coordinating different parts of the vocal apparatus and respiratory system, and monitoring the auditory and kinesthetic output for accuracy. While singing can be achieved by a majority of people, some cannot do it accurately. In this dissertation, I investigate one of the posited causes of poor pitch matching and experimentally test it.The inverse-model deficit of poor pitch matching suggests that poor singing results from the brain’s inability to instantiate a precise motor plan with one’s vocal apparatus when one tries to vocally reproduce a pitch. This hypothesis is motivated by previous work in sensorimotor control suggesting that in order to perform an action in an environment, one relies on two distinct internal models. These internal models are thought to be instantiated by the cerebellum. In this dissertation, I embed this hypothesis within the larger context of cerebellar cognition and the Bayesian brain hypothesis.

First, I present multiple findings of the involvement of the cerebellum in cognitive tasks, including in musical production. This will provide some support for the role of the cerebellum in cognition, in addition to its role in motor control. This first part will also allow for an understanding of some of the neural underpinnings involved in implementing internal models.

Next, I present recent findings which could support the notion of internal models within the Bayesian brain framework. This will provide an understanding of these internal models at an algorithmic level (Marr, 1982).

Finally, I test one of the key predictions of the inverse-model deficit of poor pitch matching i.e. perturbing the cerebellum during singing task would lead to poorer pitch matching performance. Adult participants had to perform various singing assessment tasks before and after brain stimulations on different brain regions. I did not observe a decrease in pitch matching accuracy (relative to the individuals’ baseline) after stimulation of the cerebellum. While these results were inconclusive, further research using TMS to investigate pitch accuracy should be undertaken so as to better understand the role of internal models in vocal production such as singing.

    Cover page: Sensorimotor Control of Human Singing
    • Article
    • Peer Reviewed
    Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 38 (2016)
    Both speech and music can be organized as hierarchical, nested groupings of units. In speech, for instance, phonemescan group to form syllables, which group to form words, which group to form sentences, and so on. In music, notes can groupto form phrases, which group to form chord progressions, which group to form verses, and so on. We present a new methodfor extracting events (amplitude peaks in Hilbert envelopes of filter banks) from speech and music recordings, and quantifyingthe degree of nesting in temporal clusters of events across timescales (using Allan Factor analysis). We apply this method tomonologue recordings of speech (TED talks) and also to solo musical performances of similar lengths. We found that bothtypes of recordings exhibit nested clustering, revealing similar organizational principles, but that clustering is more pronouncedon shorter timescales (milliseconds) for speech, but longer timescales (seconds+) for music.
      Cover page: Temporal event clustering in speech versus music
      • Article
      • Peer Reviewed
      UC Merced Previously Published Works (2017)
      Humans talk, sing and play music. Some species of birds and whales sing long and complex songs. All these behaviours and sounds exhibit hierarchical structure-syllables and notes are positioned within words and musical phrases, words and motives in sentences and musical phrases, and so on. We developed a new method to measure and compare hierarchical temporal structures in speech, song and music. The method identifies temporal events as peaks in the sound amplitude envelope, and quantifies event clustering across a range of timescales using Allan factor (AF) variance. AF variances were analysed and compared for over 200 different recordings from more than 16 different categories of signals, including recordings of speech in different contexts and languages, musical compositions and performances from different genres. Non-human vocalizations from two bird species and two types of marine mammals were also analysed for comparison. The resulting patterns of AF variance across timescales were distinct to each of four natural categories of complex sound: speech, popular music, classical music and complex animal vocalizations. Comparisons within and across categories indicated that nested clustering in longer timescales was more prominent when prosodic variation was greater, and when sounds came from interactions among individuals, including interactions between speakers, musicians, and even killer whales. Nested clustering also was more prominent for music compared with speech, and reflected beat structure for popular music and self-similarity across timescales for classical music. In summary, hierarchical temporal structures reflect the behavioural and social processes underlying complex vocalizations and musical performances.
        Cover page: Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes
        • Article
        • Peer Reviewed
        UC Merced Previously Published Works (2020)
        In this article, we review recent advances in research on rhythm and musical beat perception, focusing on the role of predictive processes in auditory motor interactions. We suggest that experimental evidence of the motor system's role in beat perception, including in passive listening, may be explained by the generation and maintenance of internal predictive models, concordant with the Active Inference framework of sensory processing. We highlight two complementary hypotheses for the neural underpinnings of rhythm perception: The Action Simulation for Auditory Prediction hypothesis (Patel and Iversen, 2014) and the Gradual Audiomotor Evolution hypothesis (Merchant and Honing, 2014) and review recent experimental progress supporting each of these hypotheses. While initial formulations of ASAP and GAE explain different aspects of beat-based timing-the involvement of motor structures in the absence of movement, and physical entrainment to an auditory beat respectively-we suggest that work under both hypotheses provide converging evidence toward understanding the predictive role of the motor system in the perception of rhythm, and the specific neural mechanisms involved. We discuss future experimental work necessary to further evaluate the causal neural mechanisms underlying beat and rhythm perception.
          Cover page: Motor and Predictive Processes in Auditory Beat and Rhythm Perception
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