Thermal modulation of Zebrafish exploratory statistics reveals constraints on individual behavioral variability.

BACKGROUND: Variability is a hallmark of animal behavior. It contributes to survival by endowing individuals and populations with the capacity to adapt to ever-changing environmental conditions. Intra-individual variability is thought to reflect both endogenous and exogenous modulations of the neural dynamics of the central nervous system. However, how variability is internally regulated and modulated by external cues remains elusive. Here, we address this question by analyzing the statistics of spontaneous exploration of freely swimming zebrafish larvae and by probing how these locomotor patterns are impacted when changing the water temperatures within an ethologically relevant range. RESULTS: We show that, for this simple animal model, five short-term kinematic parameters - interbout interval, turn amplitude, travelled distance, turn probability, and orientational flipping rate - together control the long-term exploratory dynamics. We establish that the bath temperature consistently impacts the means of these parameters, but leave their pairwise covariance unchanged. These results indicate that the temperature merely controls the sampling statistics within a well-defined kinematic space delineated by this robust statistical structure. At a given temperature, individual animals explore the behavioral space over a timescale of tens of minutes, suggestive of a slow internal state modulation that could be externally biased through the bath temperature. By combining these various observations into a minimal stochastic model of navigation, we show that this thermal modulation of locomotor kinematics results in a thermophobic behavior, complementing direct gradient-sensing mechanisms. CONCLUSIONS: This study establishes the existence of a well-defined locomotor space accessible to zebrafish larvae during spontaneous exploration, and quantifies self-generated modulation of locomotor patterns. Intra-individual variability reflects a slow diffusive-like probing of this space by the animal. The bath temperature in turn restricts the sampling statistics to sub-regions, endowing the animal with basic thermophobicity. This study suggests that in zebrafish, as well as in other ectothermic animals, ambient temperature could be used to efficiently manipulate internal states in a simple and ethological way.

Effects of Asparagopsis taxiformis metabolites on the feeding behaviour of post-larval Acanthurus triostegus.

Our study highlights the effect of the macroalgae Asparagopsis taxiformis on the feeding behaviour of the tropical surgeonfish Acanthurus triostegus. The presence of A. taxiformis chemical cues reduced A. triostegus feeding, suggesting that the presence of this algae could affect not only the survival of fish in the post-larval stage, but also alter the grazing pressure on coral reefs.

Evolutionary divergence of locomotion in two related vertebrate species.

Locomotion exists in diverse forms in nature; however, little is known about how closely related species with similar neuronal circuitry can evolve different navigational strategies to explore their environments. Here, we investigate this question by comparing divergent swimming pattern in larval Danionella cerebrum (DC) and zebrafish (ZF). We show that DC displays long continuous swimming events when compared with the short burst-and-glide swimming in ZF. We reveal that mesencephalic locomotion maintenance neurons in the midbrain are sufficient to cause this increased swimming. Moreover, we propose that the availability of dissolved oxygen and timing of swim bladder inflation drive the observed differences in the swim pattern. Our findings uncover the neural substrate underlying the evolutionary divergence of locomotion and its adaptation to their environmental constraints.

From behavior to circuit modeling of light-seeking navigation in zebrafish larvae.

Bridging brain-scale circuit dynamics and organism-scale behavior is a central challenge in neuroscience. It requires the concurrent development of minimal behavioral and neural circuit models that can quantitatively capture basic sensorimotor operations. Here, we focus on light-seeking navigation in zebrafish larvae. Using a virtual reality assay, we first characterize how motor and visual stimulation sequences govern the selection of discrete swim-bout events that subserve the fish navigation in the presence of a distant light source. These mechanisms are combined into a comprehensive Markov-chain model of navigation that quantitatively predicts the stationary distribution of the fish's body orientation under any given illumination profile. We then map this behavioral description onto a neuronal model of the ARTR, a small neural circuit involved in the orientation-selection of swim bouts. We demonstrate that this visually-biased decision-making circuit can capture the statistics of both spontaneous and contrast-driven navigation.