UCSF

When we speak, there’s a complex sequence of events occurring within us. A symphony, if you will, with the brain as the conductor; the respiratory muscles pushing air out of our bellow-like lungs; this exhaled air setting the vocal cords into vibration like the strings of a musical instrument; the tongue, lips, nose, teeth and jaw acting as an ensemble and obstructing this air flow to produce speech sounds. The smooth execution of this sequence of events requires the human brain to monitor sensory feedback during speech, correct for any errors and learn from any past errors. This phenomenon is called sensorimotor integration and is essential for efficient speech motor control. Various theoretical and computational models of speech production explain how sensorimotor integration occurs but many aspects of this process still remain underexplored. This dissertation starts by investigating how sensorimotor learning of vowels depends on the complex relationship between articulatory dimensions and acoustic space. Specifically, formant adaptation or response to altered formant frequency feedback depends on the direction of the shift in two-dimensional F1-F2 vowel space. Using magnetoencephalographic imaging, I then investigate how sensorimotor integration is affected during speaking in a voice disorder called Laryngeal Dystonia (or Spasmodic Dysphonia). Significant differences in neural activity at various nodes of the speech motor control network were observed in patients with Laryngeal Dystonia at various time points around the act ofphonation. Lastly, the dissertation describes cortical dynamics of the speech motor control network in a neurodegenerative disorder affecting speech and language called the non-fluent variant of Primary Progressive Aphasia (nfvPPA). These patients have significant motor speech impairments which were investigated using a pitch perturbation experimental paradigm. Neural and behavioural results showed that sensorimotor integration is severely impacted in patients with nfvPPA. Taken together, the work in this dissertation aims to help inform current computational models of speech production and underlines the important role of sensorimotor integration in human speech.