Nucleus Accumbens Shell Neurons Encode the Kinematics of Reward Approach Locomotion
Jazyk angličtina Země Spojené státy americké Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
R01 DA019473
NIDA NIH HHS - United States
PubMed
37330195
PubMed Central
PMC10527230
DOI
10.1016/j.neuroscience.2023.06.002
PII: S0306-4522(23)00256-7
Knihovny.cz E-zdroje
- Klíčová slova
- Nucleus accumbens, initiation of action, kinematics encoding, locomotor speed, reward approach,
- MeSH
- biomechanika MeSH
- krysa rodu Rattus MeSH
- lokomoce MeSH
- neurony * fyziologie MeSH
- nucleus accumbens * fyziologie MeSH
- odměna MeSH
- potkani Wistar MeSH
- zvířata MeSH
- Check Tag
- krysa rodu Rattus MeSH
- mužské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
The nucleus accumbens (NAc) is considered an interface between motivation and action, with NAc neurons playing an important role in promoting reward approach. However, the encoding by NAc neurons that contributes to this role remains unknown. We recorded 62 NAc neurons in male Wistar rats (n = 5) running towards rewarded locations in an 8-arm radial maze. Variables related to locomotor approach kinematics were the best predictors of the firing rate for most NAc neurons. Nearly 18% of the recorded neurons were inhibited during the entire approach run (locomotion-off cells), suggesting that reduction in firing of these neurons promotes initiation of locomotor approach. 27% of the neurons presented a peak of activity during acceleration followed by a valley during deceleration (acceleration-on cells). Together, these neurons accounted for most of the speed and acceleration encoding identified in our analysis. In contrast, a further 16% of neurons presented a valley during acceleration followed by a peak just prior to or after reaching reward (deceleration-on cells). These findings suggest that these three classes of NAc neurons influence the time course of speed changes during locomotor approach to reward.
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