| Autor: |
Jun Huang, Sylvain Crochet, Carmen Sandi, Carl C.H. Petersen |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Heliyon, Vol 10, Iss 18, Pp e37831- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2405-8440 |
| DOI: |
10.1016/j.heliyon.2024.e37831 |
| Popis: |
The synaptic and neuronal circuit mechanisms underlying reward-based learning remain to be fully determined. In the mammalian brain, dopamine release in nucleus accumbens is thought to contribute importantly to reward signals for learning and promoting synaptic plasticity. Here, through longitudinal fiber photometry of a genetically-encoded fluorescent sensor, we investigated dopamine signals in the nucleus accumbens of thirsty head-restrained mice as they learned to lick a liquid reward spout in response to single deflections of the C2 whisker across varying reward contingencies. Reward delivery triggered by well-timed licking drove fast transient dopamine increases in nucleus accumbens. On the other hand, unrewarded licking was overall associated with reduced dopamine sensor fluorescence, especially in trials where reward was unexpectedly omitted. The dopamine reward signal upon liquid delivery decreased within individual sessions as mice became sated. As mice learned to lick the reward spout in response to whisker deflection, a fast transient sensory-evoked dopamine signal developed, correlating with the learning of the whisker detection task across consecutive training days, as well as within single learning sessions. The well-defined behavioral paradigm involving a unitary stimulus of a single whisker as a reward-predicting cue along with precisely quantified licking allows untangling of sensory, motor and reward-related dopamine signals and how they evolve across the learning of whisker-dependent goal-directed sensorimotor transformations. Our longitudinal measurements of dopamine dynamics across reward-based learning are overall consistent with the hypothesis that dopamine could play an important role as a reward signal for reinforcement learning. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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