Ben Parrell, PhD

Position title: Associate Professor, Communication Sciences and Disorders

Ben T. Parrell, PhD

PhD, University of Southern California
Associate Professor, Communication Sciences and Disorders

Contact Information

Waisman Center
1500 Highland Avenue
Room 489
Madison, WI 53705
Speech Motor Action + Control

Research Statement

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:

  1. 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.
  2. 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.
  3. 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.

Selected Publications