TY - JOUR
T1 - Competition between parallel sensorimotor learning systems
AU - Albert, Scott T.
AU - Jang, Jihoon
AU - Modchalingam, Shanaathanan
AU - 'T Hart, Marius
AU - Henriques, Denise
AU - Lerner, Gonzalo
AU - Della-Maggiore, Valeria
AU - Haith, Adrian M.
AU - Krakauer, John W.
AU - Shadmehr, Reza
N1 - Publisher Copyright:
© 2022, eLife Sciences Publications Ltd. All rights reserved.
PY - 2022/2
Y1 - 2022/2
N2 - Sensorimotor learning is supported by at least two parallel systems: A strategic process that benefits from explicit knowledge, and an implicit process that adapts subconsciously. How do these systems interact? Does one system's contributions suppress the other, or do they operate independently? Here we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system's response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error.
AB - Sensorimotor learning is supported by at least two parallel systems: A strategic process that benefits from explicit knowledge, and an implicit process that adapts subconsciously. How do these systems interact? Does one system's contributions suppress the other, or do they operate independently? Here we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system's response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error.
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U2 - 10.7554/ELIFE.65361
DO - 10.7554/ELIFE.65361
M3 - Article
C2 - 35225229
AN - SCOPUS:85126785375
SN - 2050-084X
VL - 11
JO - eLife
JF - eLife
M1 - e65361
ER -