Distinct signals in medial and lateral VTA dopamine neurons modulate fear extinction at different times
Abstract
Dopamine (DA) neurons are known to encode reward prediction error (RPE), in addition to other signals, such as salience. While RPE is known to support learning, the role of salience in supporting learning remains less clear. To address this, we recorded and manipulated VTA DA neurons in mice during fear extinction, a behavior we observed to generate spatially segregated RPE and salience signals. We applied deep learning to classify mouse freezing behavior, eliminating the need for human scoring. Our fiber photometry recordings showed that DA neurons in medial and lateral VTA have distinct activity profiles during fear extinction: medial VTA activity more closely reflected RPE, while lateral VTA activity more closely reflected a salience-like signal. Optogenetic inhibition of DA neurons in either region slowed fear extinction, with the relevant time period for inhibition differing across regions. Our results indicate that salience-like signals can have similar downstream consequences to RPE-like signals, although with different temporal dependencies.
Data availability
All data generated or analysed during this study will be included in the manuscript as supporting files. Code for all steps is available on GitHub:https://github.com/neurocaience/deepfreeze/ (Cai et al. 2020)
Article and author information
Author details
Funding
NIH (T32MH065214)
- Lili X Cai
NYSCF
- Ilana B Witten
ARO (W911NF1710554)
- Ilana B Witten
NIH (1R01MH106689-01A1)
- Ilana B Witten
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All experiments followed guidelines established by the National Institutes of Health and reviewed by Princeton University Institutional Animals Care and Use Committee (IACUC protocol 1876-18).
Copyright
© 2020, Cai et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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