Graded error signals in eyeblink conditioning
Rasmussen, Anders LU
(2020)
In Neurobiology of Learning and Memory
170.
- Abstract
Minimizing errors is an important aspect of learning. However, it is not enough merely to record if an error occurred. For efficient learning, information about the magnitude of errors is critical. Did my tennis swing completely miss the target or did I hit the ball, but not quite in the sweet spot? How can neurons – which have traditionally been thought of as binary units – signal the magnitude of an error? Here I review evidence that eyeblink conditioning – a basic form of motor learning – depends on graded signals from the inferior olive which guides plasticity in the cerebellum and ultimately tunes behavior. Specifically, evidence suggests that: (1)Error signals are conveyed to the cerebellum via the inferior olive; (2)Signals from... (More)
Minimizing errors is an important aspect of learning. However, it is not enough merely to record if an error occurred. For efficient learning, information about the magnitude of errors is critical. Did my tennis swing completely miss the target or did I hit the ball, but not quite in the sweet spot? How can neurons – which have traditionally been thought of as binary units – signal the magnitude of an error? Here I review evidence that eyeblink conditioning – a basic form of motor learning – depends on graded signals from the inferior olive which guides plasticity in the cerebellum and ultimately tunes behavior. Specifically, evidence suggests that: (1)Error signals are conveyed to the cerebellum via the inferior olive; (2)Signals from the inferior olive are graded; (3)The strength of the olivary signal affects learning; (4)Cerebellar feedback influences the strength of the olivary signal. I end the review by exploring how graded error signals might explain some behavioral learning phenomena.
(Less)
- author
- Rasmussen, Anders
LU
- organization
- publishing date
- 2020-04
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Cerebellum, Climbing fibers, Error signals, Eyeblink conditioning, Inferior olive, Learning, Nucleo-Olivary pathway, Plasticity, Rescorla-Wagner
- in
- Neurobiology of Learning and Memory
- volume
- 170
- article number
- 107023
- publisher
- Elsevier
- external identifiers
-
- scopus:85064743227
- pmid:31028891
- ISSN
- 1074-7427
- DOI
- 10.1016/j.nlm.2019.04.011
- language
- English
- LU publication?
- yes
- id
- 739260ee-6b38-44fd-ac09-c4ca1f6884f6
- date added to LUP
- 2019-05-04 17:24:04
- date last changed
- 2024-04-30 06:09:13
@article{739260ee-6b38-44fd-ac09-c4ca1f6884f6,
abstract = {{<p>Minimizing errors is an important aspect of learning. However, it is not enough merely to record if an error occurred. For efficient learning, information about the magnitude of errors is critical. Did my tennis swing completely miss the target or did I hit the ball, but not quite in the sweet spot? How can neurons – which have traditionally been thought of as binary units – signal the magnitude of an error? Here I review evidence that eyeblink conditioning – a basic form of motor learning – depends on graded signals from the inferior olive which guides plasticity in the cerebellum and ultimately tunes behavior. Specifically, evidence suggests that: (1)Error signals are conveyed to the cerebellum via the inferior olive; (2)Signals from the inferior olive are graded; (3)The strength of the olivary signal affects learning; (4)Cerebellar feedback influences the strength of the olivary signal. I end the review by exploring how graded error signals might explain some behavioral learning phenomena.</p>}},
author = {{Rasmussen, Anders}},
issn = {{1074-7427}},
keywords = {{Cerebellum; Climbing fibers; Error signals; Eyeblink conditioning; Inferior olive; Learning; Nucleo-Olivary pathway; Plasticity; Rescorla-Wagner}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Neurobiology of Learning and Memory}},
title = {{Graded error signals in eyeblink conditioning}},
url = {{http://dx.doi.org/10.1016/j.nlm.2019.04.011}},
doi = {{10.1016/j.nlm.2019.04.011}},
volume = {{170}},
year = {{2020}},
}