10.5061/DRYAD.CZ8W9GJ4S
Cohen, Jeremiah
0000-0002-4768-7124
Johns Hopkins University
Grossman, Cooper
Johns Hopkins University
Bari, Bilal
Johns Hopkins University
Serotonin neurons modulate learning rate through uncertainty
Dryad
dataset
2021
FOS: Biological sciences
2021-12-27T00:00:00Z
2021-12-27T00:00:00Z
en
https://doi.org/10.1016/j.cub.2021.12.006
https://doi.org/10.1101/2020.10.24.353508
24389081 bytes
4
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Regulating how fast to learn is critical for flexible behavior. Learning
about the consequences of actions should be slow in stable environments,
but accelerate when that environment changes. Recognizing stability and
detecting change is difficult in environments with noisy relationships
between actions and outcomes. Under these conditions, theories propose
that uncertainty can be used to modulate learning rates
("meta-learning"). We show that mice behaving in a dynamic
foraging task exhibit choice behavior that varied as a function of two
forms of uncertainty estimated from a meta-learning model. The activity of
dorsal raphe serotonin neurons tracked both types of uncertainty in the
foraging task, as well as in a dynamic Pavlovian task. Reversible
inhibition of serotonin neurons in the foraging task reproduced changes in
learning predicted by a simulated lesion of meta-learning in the model. We
thus provide a quantitative link between serotonin neuron activity,
learning, and decision making.