Ben Parrell, PhD
Position title: Assistant Professor, Communication Sciences and Disorders
PhD, University of Southern California
Assistant Professor, Communication Sciences and Disorders
I study speech production, focusing the relationship between the abstract, cognitive system (language), speech motor behavior, and brain function. Speech production is perhaps the most complicated motor activity humans produce, requiring control of a complex neuromuscular system to produce movements that achieve millimeter-level precision and that are coordinated with millisecond-level accuracy. Moreover, these movements are not produced just to reach some target position in space at a particular time; rather, multiple movements must be controlled together to convey a linguistic, communicative message. Despite this complexity, healthy speakers are able to produce speech fluently and effortlessly. My research has three main branches:
- Neurobiology of speech production: My major focus in this area has been to understand the functional role of the cerebellum in speech motor control. This includes understanding both its typical function in healthy speakers as well as what goes wrong when the cerebellum is damaged in patients with ataxic dysarthria. The role of the cerebellum in speech motor control, both in healthy speakers and patients with ataxic dysarthria, a motor speech disorder associated with damage to or degeneration of the cerebellum.
- Mechanisms of learning in speech motor control and their neural substrates: Speech control is not fixed: speakers contend with a changing vocal tract during childhood, readily adapt their production to match interlocutors even in the course of a short conversation, and show practice-based improvement in producing novel sound sequences. These abilities are well established, yet the mechanisms that underlie this flexibility remain poorly understood. My research in this area explores how people are able to learn from sensory errors (differences between what they expect to hear and what they actually hear) as well as from reward-based feedback from an external source.
- Development of a computation model of speech motor control based on feedback control: The process through which the central nervous system organizes and controls the complex anatomical structure of the vocal tract to produce speech remains poorly understood. One approach to better understanding this speech motor control system is through the use of computational models. Importantly, models can serve to test hypothesis about the computational processes in human speech. The model we are developing is based on the concept of optimal feedback control. In this framework, motor commands are not preplanned, as in other theories of speech motor control. Rather, they are generated based on both the current state of the vocal tract and the production goal. To allow for fast control in the presence of feedback delays, the current state is estimated from both sensory (auditory, somatosensory) information as well as an internal estimate of the vocal tract state, which is generated based on a copy of previous motor commands. This framework has provided powerful insights in other motor domains, and makes some unique predictions about speech motor control that we are currently testing.
I have other projects on the use of feedforward and feedback systems in speech motor control, control of time and movement duration in speech, and feedback control in motor systems more generally.
Karlin, R., & Parrell, B. (2022). Speakers monitor auditory feedback for temporal alignment and linguistically relevant duration. The Journal of the Acoustical Society of America, 152(6), 3142. https://doi.org/10.1121/10.0015247
Tang, D. L., Parrell, B., & Niziolek, C. A. (2022). Movement variability can be modulated in speech production. Journal of neurophysiology, 128(6), 1469–1482. https://doi.org/10.1152/jn.00095.2022
Compton, A., Roop, B. W., Parrell, B., & Lammert, A. C. (2022). Stimulus whitening improves the efficiency of reverse correlation. Behavior research methods, 10.3758/s13428-022-01946-w. Advance online publication. https://doi.org/10.3758/s13428-022-01946-w
Hantzsch, L., Parrell, B., & Niziolek, C. A. (2022). A single exposure to altered auditory feedback causes observable sensorimotor adaptation in speech. eLife, 11, e73694. https://doi.org/10.7554/eLife.73694
Gaines, J. L., Kim, K. S., Parrell, B., Ramanarayanan, V., Nagarajan, S. S., & Houde, J. F. (2021). Discrete constriction locations describe a comprehensive range of vocal tract shapes in the Maeda model. JASA express letters, 1(12), 124402. https://doi.org/10.1121/10.0009058
Parrell, B., Kim, H. E., Breska, A., Saxena, A., & Ivry, R. B. (2021). Differential effects of cerebellar degeneration on feedforward versus feedback control across speech and reaching movements. The Journal of neuroscience: the official journal of the Society for Neuroscience, 41(42), 8779–8789. https://doi.org/10.1523/JNEUROSCI.0739-21.2021
Karlin, R., Naber, C., & Parrell, B. (2021). Auditory Feedback Is Used for Adaptation and Compensation in Speech Timing. Journal of speech, language, and hearing research : JSLHR, 64(9), 3361–3381. https://doi.org/10.1044/2021_JSLHR-21-00021
Parrell, B., & Niziolek, C. A. (2021). Increased speech contrast induced by sensorimotor adaptation to a nonuniform auditory perturbation. Journal of neurophysiology, 125(2), 638–647. https://doi.org/10.1152/jn.00466.2020
Parrell B, Narayanan S. (2018). Explaining coronal reduction: prosodic structure and articulatory posture. Phonetica, 75(2):151-181. doi: 10.1159/000481099.
Parrell B, Goldstein L, Lee S, Byrd D. (2014) Spatiotemporal coupling between speech and manual motor actions. Journal of Phonetics. 42:1-11.
Parrell B, Agnew Z, Nagarajan S, Houde J, Ivry RB. (2017) Impaired feedforward control and enhanced feedback control of speech in patients with cerebellar degeneration. Journal of Neuroscience, 20;37(38):9249-9258. doi:10.1523/JNEUROSCI.3363-16.2017.