Contextual effects during sensorimotor adaptation are an emergent property of population coding in a cerebellar-inspired model
Year: 2025
Type: article
Abstract: The cerebellum is crucial for sensorimotor adaptation, using error information to keep the sensorimotor system well calibrated. Here, we introduce a population-coding model to explore this process, focusing on how implicit adaptation is modulated by context. The model consists of a two-layered network, designed to capture activity in both the cerebellar cortex and deep cerebellar nuclei. A core feature of the model is that within each layer, the processing units are tuned to both movement direction and the direction of movement error. The model recapitulates a large range of contextual effects such as how prior learning, error uncertainty, or temporal delay affect the rate of adaptation. While these effects have traditionally been taken to indicate a form of meta-learning or context-dependent memory within the adaptation system, the current results show that they can emerge from the population activity of a cerebellar-like hierarchical network that does not represent context.
Source: Science Advances
Authors: Tianhe Wang, Richard B. Ivry
Institution: University of California, Berkeley
Language: English
Topic: Motor Control and Adaptation
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $4,500
OpenAlex ID: W4415673244