The human brain issues commands to produce movement. However, relying solely on the sensations that result from movement would be insufficient to quickly adjust and update future motor plans due to the inherent delays in the communication and processing within the central nervous system. There is strong behavioral evidence that to ensure sufficient control the brain uses information about the issued motor commands to form a prediction of the expected sensations that result from body motion. Despite this evidence, it remains largely unknown how the brain combines these predictions of sensory feedback with actual motion-induced sensations for movement control and self-movement perception. This CAREER proposal, through student involvement and outreach activities, lays the foundation for a long-term research and educational career to address these gaps in knowledge. Utilizing a diverse set of techniques, the investigator will systematically examine the contributions of actual and predicted sensory feedback to upper limb behavior.
Corollary discharge (CD, also referred to as efference copy) is the internal duplicate of a motor command made at the same time the motor signal is generated. This signal is used to predict the future state of the body and the expected sensory consequences due to movement. The integration of this internal state information with delayed sensory signals is critical for accurate movement control and motion perception. However, little is known about the properties of this signal in humans or how this internal movement information is integrated with reafferent sensory feedback. Despite being poorly understood, internal state estimation remains a critical feature of computational models of limb movement and feedforward control. To directly address the current gaps in knowledge, the proposed studies aim to (1) quantify the accuracy and sensitivity of proprioception and internal limb state estimation, (2) computationally describe how these signals are combined to aid perception and motor coordination, and (3) determine the causal relationships between behavior and the neural processing of these signals through the application of transcranial magnetic stimulation to areas within the parietal cortex and cerebellum. Pursuing the project goals will utilize different techniques (computational modeling, noninvasive neural stimulation and quantitative behavioral analysis) in order to advance the computational frameworks for sensorimotor integration and control. Increasing the understanding of this neural integration could potentially (1) provide the foundation for understanding how actual and predicted sensory information contribute to complex behaviors (e.g., eye-hand and bimanual coordination), (2) help define the constraints (e.g., timing and acuity) of the different sensory information required for effective neural prostheses and brain?machine interface control and (3) assist in distinguishing the basis of feedforward motor control deficits in several neurological diseases. Importantly, the project promotes the inclusion and training of students from various backgrounds, particularly minority students, and encourages the outreach and dissemination of the scientific research to a broad spectrum of participants within the community, from grade school students to retired individuals.
