Summary Operant learning requires multiple cognitive processes, such as learning, prediction of potential outcomes, and decision-making. It is less clear how interactions of these processes lead to the behavioral adaptations that allow animals to cope with a changing environment. We show that juvenile zebrafish can perform conditioned place avoidance learning, with improving performance across development. Ablation of the dorsolateral habenula (dlHb), a brain region involved in associative learning and prediction of outcomes, leads to an unexpected improvement in performance and delayed memory extinction. Interestingly, the control animals exhibit rapid adaptation to a changing learning rule, whereas dlHb-ablated animals fail to adapt. Altogether, our results show that the dlHb plays a central role in switching animals’ strategies while integrating new evidence with prior experience.

The developing brain undergoes drastic alterations. Here, we investigated developmental changes in the habenula, a brain region that mediates behavioral flexibility during learning, social interactions, and aversive experiences. We showed that developing habenular circuits exhibit multiple alterations that lead to an increase in the structural and functional diversity of cell types, inputs, and functional modules. As the habenula develops, it sequentially transforms into a multisensory brain region that can process visual, olfactory, mechanosensory, and aversive stimuli. Moreover, we observed that the habenular neurons display spatiotemporally structured spontaneous activity that shows prominent alterations and refinement with age. These alterations in habenular activity are accompanied by sequential neurogenesis and the integration of distinct neural clusters across development. Last, we revealed that habenular neurons with distinct functional properties are born sequentially at distinct developmental time windows. Our results highlight a strong link between the functional properties of habenular neurons and their precise birthdate.

Summary Ongoing neural activity, which represents internal brain states, is constantly modulated by the sensory information that is generated by the environment. In this study, we show that the habenular circuits act as a major brain hub integrating the structured ongoing activity of the limbic forebrain circuitry and the olfactory information. We demonstrate that ancestral homologs of amygdala and hippocampus in zebrafish forebrain are the major drivers of ongoing habenular activity. We also reveal that odor stimuli can modulate the activity of specific habenular neurons that are driven by this forebrain circuitry. Our results highlight a major role for the olfactory system in regulating the ongoing activity of the habenula and the forebrain, thereby altering brain’s internal states.

Operant conditioning requires multiple cognitive processes, such as learning, consolidation, prediction of potential outcomes and decision making. It is less clear how interactions of these processes led to behavioral adaptations that allows animal to cope with changing environment. We first showed that juvenile zebrafish can perform conditioned place avoidance learning, with improving performance across development. Next, we disentangled operant conditioning from contextual fear and anxiety. Our results revealed that animals' decisions and learning performance is shaped by the available information and animals' experience. Ablation of dorsal habenula (dHb), a brain region involved in learning and prediction of outcomes, led to an unexpected improvement in animals learning performance and delayed memory extinction. Interestingly, while the control animals' exhibit rapid adaptation to changing learning rules, dHb ablated animals failed to adapt. Altogether, our results showed that dHb plays a central role in switching animals' strategies while integrating new evidences with prior experience. Eggen, M. Andresen, V. Nguyen, A Nygard and our fish facility support team for technical assistance. We thank Nathalie Jurisch-Yaksi and Stephanie Fore for helpful comments on the text. We thank all Yaksi lab members for stimulating discussions. This work was funded by ERC starting grant 335561 (F.P., R.P., E.Y.) and RCN FRIPRO Research Grant 239973 (E.Y.). Work in the E.Y. lab is funded by the Kavli Institute for Systems Neuroscience at NTNU. AUTHOR CONTRIBUTIONSConceptualization, F.P., E.Y.; Methodology and data, F.P., B.S.; Recording software F.P., R.P.; Data