We developed an unsupervised clustering method that can robustly identify different swim bout categories based on a combination of kinematic similarity and behavioral usage (Marques et al., 2018; Marques and Orger, 2019). We found that larvae show a small set of preferred swim patterns, which systematically tile the space of bout kinematics. While some patterns are used broadly across many conditions, others are used only in very specific contexts. By analyzing the sensory stimuli preceding different bout types in freely swimming fish in social or feeding contexts, we could identify the natural stimuli that trigger different bout types. This quantitative analysis of behavior provides a crucial framework for subsequent investigations of neural circuit function. We have also recently used this framework to investigate the effects of experience on social avoidance in zebrafish larvae (Groneberg et al., 2020). Week old larvae avoid each other at short distances, but, for larvae reared in isolation, this distance is increased. We found that isolation reared larvae use different bout types in response to social stimuli that are sensed by the lateral line. This work establishes a powerful paradigm to investigate the effect of experience on the development of social circuits. To interpret whole-brain activity maps, and propose realistic circuit models, it is critical to know not just where active neurons are, but also their morphology, projection patterns and neurotransmitter phenotypes. Genetic makers for particular functional classes make it possible to target them for more detailed functional and morphological analysis, and optical and genetic perturbations that allow us to probe their role in generating behaviour. We have generated transgenic lines targeting different neurotransmitter classes and cell-types. We pass each line that we generated through a 2-photon and light-sheet imaging pipeline in which we record systematically the responses of labeled neurons to a suite of behaviorally relevant stimuli, including drifting and rotating patterns, luminance changes, threating looms and prey-like stimuli. We register the expression pattern of each line to an in-house template brain from which bridging transformations can be made to publically available brain atlases. This “functional screening” approach has yielded markers for many of the key populations implicated in larval visual behaviours. Significantly, we also identified groups of neurons overlooked in experiments based on pan-neuronal drivers. This work provides an important foundation for future investigations of neural circuits by our group, and will also be an important resource for the zebrafish neuroscience community. We plan to make the data set freely accessible, and integrated with existing atlas projects.