Future state prediction errors guide active avoidance behavior by adult zebrafish

Autor: Takuya Isomura, Hideaki Shimazaki, Hitoshi Okamoto, Tazu Aoki, Tanvir Islam, Hisaya Kakinuma, Tomoki Fukai, Chi Chung Alan Fung, Makio Torigoe
Rok vydání: 2019
Předmět:
DOI: 10.1101/546440
Popis: SummaryHuman predicts future. To ask if fish also has this capacity, we established the virtual reality training system with live imaging of the telencephalic neurons of adult zebrafish in the active avoidance and found that, at the onset of the trial, learned fish conceives two future conditions as the favorable status on its way to the safe goal, i.e. one with the backwardly moving landscape and the other with the color of the safe goal. And the two different neural ensembles monitor the discrepancy between these predictions and the perceived real external status. Once fish reaches the goal, another ensemble is set to work to monitor whether fish keeps staying in the safe goal. The manipulation to artificially enhance these prediction errors elevated the activities of these ensembles and induced fish to behave to correct errors, revealing that fish sets behavioral strategy to actively realize these predictions.
Databáze: OpenAIRE