Project Summary
Sensorimotor learning and maintaining calibration of the motor system is essential for activities of daily living.
While the motor control literature has traditionally focused on a slow-learning, implicit process, recent work
highlights that rapid learning and readjustment of sensorimotor skills is supported by higher-order cognitive
strategies. The proposed research focuses on these cognitive strategies, and aims to understand their operation
during health and neurological disease. Based on our prior work, we propose that strategies may reflect two
broadly-classed mechanisms: an algorithm-like strategy that seeks to simulate the outcome of an intended action
before its execution and a retrieval-like mechanism that caches previously successful strategies in a short-term
memory store. We will ask whether these strategies can be improved over time, if people are sensitive to their
relative costs and constraints, and if they have differential impacts on the learning of an implicit system. All
studies will be conducted with neurologically-intact participants and individuals with spinocerebellar ataxia (SCA),
allowing us to assess the extent to which the cerebellum, which is known to play a critical role in sensorimotor
learning, supports strategy use. Importantly, we will determine if different kinds of strategies may form the basis
for viable, novel rehabilitation approaches for individuals with cerebellar damage or degeneration. These
strategies may represent an untapped or underappreciated resource for improving sensorimotor skill learning in
general, as well as a potential avenue for overcoming impairments associated with damage to the cerebellum
by exploiting extracerebellar circuits and resources not recruited by protocols that emphasize only implicit
sensorimotor learning. Alternatively, it may be that cerebellar damage also has a deleterious effect on an
individual’s ability to use cognitive strategies for sensorimotor control and learning, in line with recent findings
suggesting a prominent role for the cerebellum in cognition. In order to get to the heart of these issues, we will
systematically create conditions that require learners to adopt either an algorithmic or a retrieval-based strategy
to improve performance in a sensorimotor learning task. In addition to providing a more comprehensive account
of the nature of sensorimotor learning, the findings from the proposed work could also provide useful insights for
motor rehabilitation practices following cerebellar damage and degeneration.
