LAUSR

Zebrafish larvae are traditionally used to study vertebrate development and are increasingly being employed in drug discovery and in the study of human diseases (Patton et al., 2021). In recent years, however, zebrafish, the socalled “alternative” model, has emerged as a popular organism specifically for basic and translational neuroscience (Kalueff et al., 2014). Particularly, zebrafish behavior paradigms have gained the distinct attention of neuroscientists and ecologists (Gerlai, 2020). However, the model has not been as extensively used to study memory and learning, even though it has unlimited potential to provide insights to drive novel research. Memory is the fascinating ability of an organism to encode, store, and retrieve information about its dynamic environments (Klein, 2015). The inquest to identify physical correlates of memory is debatably the forerunner in learning and memory research. These correlates in the brain are termed as “engrams.” Semon coined this term in 1904. In his words, engrams are the “enduring, though primarily latent modifications in the irritable substance produced by a stimulus” (Semon, 1904, 1921). Karl Lashley later explored this concept experimentally by studying the retention of habits after selectively ablating the cerebral areas. He proved unsuccessful in this venture and concluded that “there is no demonstrable localization of a memory trace” (Franz & Lashley, 1917; Lashley, 1950). With the advent of cuttingedge electrophysiological, cellular and molecular techniques, contemporary scientists have endeavored (although inconclusively) to show the existence of engrams in many model organisms (Roy & Tonegawa, 2017). Literature about engram research exists in different models like Drosophila (Miyashita et al., 2018), honeybee (Menzel, 2013), birds (Zhao, 2019), and even in humans (Axmacher, 2016). However, rodents have been the leading model in the search for engrams since Lashley began more than a century ago. As the systems, cellular and molecular level of complexity that intertwines the neural ensemble remains elusive, the venture to find engrams has been challenging. Whether engrams are synaptic or cellular is not a straightforward question to answer. Memory storage is hypothesized to involve LTP (longterm potentiation) potentially with Hebbian characteristics (Abraham et al., 2019). LTP inherently links engram at the network level to the molecular level of memory storage. From a reductionist point of view, plastic changes that encompass the formation of the engram complex at the molecular level are crucial to define engrams (Mayford, 2014). Over the years, several attempts have been made to define engrams in terms of a few defining characteristics (Gerber et al., 2004; Josselyn et al., 2015; Kim et al., 2016; Mayford, 2014; Najenson, 2021; Roy & Tonegawa, 2017; Tonegawa et al., 2018). One of the simplest defining properties is that they are sufficient and necessary for memory expression (Kim et al., 2016). From another perspective, three characteristics: contiguity (persistent change in the brain), similarity (overlap of content in engram neurons during encoding and retrieval), and specificity (storage in specific neural ensembles) are the main characteristics of an engram (Najenson, 2021). Semon, however, had come up with four essential attributes of an engram— persistence, ecphory, content, and dormancy. Josselyn et al. described these defining properties in detail. According to them, some experience or event can induce persistent changes in the brain (persistence) that exist in the inactive phase between encoding and retrieval (dormancy). Because of retrieval cues, engrams can be behaviorally expressed (ecphory) as they are a reflection of what happened during encoding and what will happen during retrieval (content) (Josselyn et al., 2015). These characteristics are widely used to define an engram.