| RRC ID |
70164
|
| 著者 |
Torigoe M, Islam T, Kakinuma H, Fung CCA, Isomura T, Shimazaki H, Aoki T, Fukai T, Okamoto H.
|
| タイトル |
Zebrafish capable of generating future state prediction error show improved active avoidance behavior in virtual reality.
|
| ジャーナル |
Nat Commun
|
| Abstract |
Animals make decisions under the principle of reward value maximization and surprise minimization. It is still unclear how these principles are represented in the brain and are reflected in behavior. We addressed this question using a closed-loop virtual reality system to train adult zebrafish for active avoidance. Analysis of the neural activity of the dorsal pallium during training revealed neural ensembles assigning rules to the colors of the surrounding walls. Additionally, one third of fish generated another ensemble that becomes activated only when the real perceived scenery shows discrepancy from the predicted favorable scenery. The fish with the latter ensemble escape more efficiently than the fish with the former ensembles alone, even though both fish have successfully learned to escape, consistent with the hypothesis that the latter ensemble guides zebrafish to take action to minimize this prediction error. Our results suggest that zebrafish can use both principles of goal-directed behavior, but with different behavioral consequences depending on the repertoire of the adopted principles.
|
| 巻・号 |
12(1)
|
| ページ |
5712
|
| 公開日 |
2021-9-29
|
| DOI |
10.1038/s41467-021-26010-7
|
| PII |
10.1038/s41467-021-26010-7
|
| PMID |
34588436
|
| PMC |
PMC8481257
|
| MeSH |
Animals
Avoidance Learning / physiology*
Behavior, Animal / physiology*
Intravital Microscopy
Microscopy, Fluorescence, Multiphoton
Neocortex / cytology
Neocortex / physiology*
Neural Networks, Computer
Neurons / physiology
Photic Stimulation / methods
Reward*
Stereotaxic Techniques
Virtual Reality
Zebrafish / physiology*
|
| IF |
12.121
|
| リソース情報 |
| ゼブラフィッシュ |
Tg(vglut2a:Gal4)
TgBAC(camk2a:GAL4VP16)rw0154a
Tg(UAS:G-CaMP7) rw0155 |
