Armin Bahl

Animals integrate information over time and maintain persistent internal representations of cues to guide decision-making. How the underlying behavioral algorithms of individual animals depend on factors such as experience, developmental stage, or genotype remains poorly understood. Drift-diffusion models provide a powerful theoretical framework to describe and predict performance metrics across a wide range of species. The stochastic nature of these models and the typically limited throughput of most experimental designs challenge the automatic inference of latent variables. Here, we combine high-throughput behavioral assays in larval zebrafish with drift-diffusion modeling, revealing that larvae progressively develop more persistent, self-reinforcing integration dynamics during early development. This effect is reduced in fish carrying mutations in genes linked to human epilepsy and schizophrenia. Our results show that behavior-based drift-diffusion modeling can offer a scalable, automated approach to generate experimentally testable hypotheses about the algorithmic implementation of sensorimotor integration in health and disease.

Sleep is a fundamental behavioral state found across the animal kingdom, yet most of what we know about sleep is heavily vertebrate-biased. Studies are scarce or nonexistent in all but a few invertebrate lineages. A recent study of an REM sleep-like behavior in a jumping spider has reported unexpected parallels to sleep expression in vertebrates. So far, experimental evidence that these behavioral indicators truly represent sleep was lacking in spiders. Here, we present a comprehensive investigation into sleep behavior in the spider Portia fimbriata (Salticidae). We demonstrate diurnal activity, a free-running circadian rhythm, robust sleep architecture, regularly occurring REM-like behaviors, elevated arousal thresholds during those REM-like states, as well as rebound effects following sleep disruption. We conclude that the behavior we observe in spiders is behavioral sleep, providing evidence for an REM-like sleep substate in a terrestrial invertebrate. These results contribute to fundamental questions about the evolution and function of sleep across animals.

SUMMARY: The vertebrate hindbrain sustains functions essential for survival and behavioral control, yet how it operates as a whole remains poorly understood. Here we map its functional organization in larval zebrafish, whose transparency permits imaging of the entire hindbrain. We first curate established functional populations from the literature into an atlas annotated with putative mammalian counterparts. We then complement this library with ensembles of co-active neurons extracted without prior labels from whole-hindbrain light-field recordings in behaving larvae. We identify 70 ensembles that recur across individuals and recover most of them in independent light-sheet datasets. Ensembles also align with spatial gene-expression patterns and share their bilateral symmetry. Behavioral characterization identifies known eye- and tail-movement-related populations and reveals new associations with fin and mouth movements. Combining co-activity, molecular signatures, and neuronal projections suggests a candidate recurrent inter-regional circuit. Our atlas thus provides a common spatial reference for linking functional, molecular, and anatomical data to guide circuit discovery. HIGHLIGHTS: hindbrain ensembles recur across fish, and most are robustly detected across methods ensembles match gene expression and share its bilateral symmetry track movement of multiple body parts around swimming onset maps link activity, molecular and projection data to guide circuit discovery

Variability is a prominent feature of animal behavior across species. Despite highly controlled experimental conditions, the same individual often responds differently to repeated identical stimulation. Part of this variability can be explained by the sequence of previous sensory stimuli and decision-making events – the trial history. Most studies about trial history are limited to animals that have a cortex, such as rodents or primates, observed as they perform learned cognitive tasks. It is currently unknown whether trial history can shape the behavior of animals lacking cortical structures during untrained, naturalistic behaviors. Here, we address this question in larval zebrafish, performing the optomotor response, an innate sensorimotor behavior in which animals turn in the direction of whole-field visual motion. We observed that a substantial proportion of variability can be explained by recent stimulation and decision-making events, with influences lasting for tens of minutes. Intriguingly, sensory and response histories bias the current response in opposite directions – repulsive and attractive, respectively – analogous to what has been previously reported in humans and rodents. An integrator model operating across multiple timescales explains a considerable fraction of response variability based on trial history alone. Our findings demonstrate that history dependency in animal behavior is not an exclusive feature of higher-order cortical computation after learning, but that it reflects a fundamental and evolutionarily shared property of vertebrate sensorimotor systems. SIGNIFICANCE STATEMENT: Behavioral variability is often attributed to noise in sensory and neural processing. We show instead that much of this variability can arise predictably from an animal’s recent sensory and response history. In freely swimming larval zebrafish performing an innate visual behavior, previous stimuli and responses exert opposing, long-lasting influences: sensory history biases behavior away from the past, whereas response history promotes repetition. Such trial-to-trial effects are increasingly recognized in cognitive neuroscience but, to our knowledge, have not previously been demonstrated in a nonmammalian vertebrate. Their presence in zebrafish, a model system offering brain-wide neural access and powerful molecular tools, creates new opportunities to identify potentially conserved circuit mechanisms underlying persistent sensorimotor computations. HIGHLIGHTS: Visual motion and response histories have opposing influences on behavior Stimulus history negatively biases response direction over tens of seconds Animals tend to repeat responses across trials, a positive bias that slowly increases over minutes A deterministic model applied to experimental sessions explains considerable fractions of response variability

Animals are capable of internally modulating behavior as a function of internal state, environmental sensory conditions, and context. Classical models often assume that sensorimotor decisions are driven primarily by external stimuli, with individual biases treated as either constant or evolving monotonically over time. Here, we show that 5-day-old zebrafish larvae display slowly changing directional swim biases even in stable, homogeneous environments, with fluctuations unfolding over many hours. Computational modeling suggests that these biases arise from a non-stationary Markovian process, with two largely independent internal input streams modulating the tendency to repeat swim directions across consecutive swim bouts. These slow fluctuations are present across sensory conditions, including different light intensities and global motion cues, although the switching statistics are modulated by these conditions. Our findings reveal an intrinsic, context-sensitive source of behavioral variability and provide a framework for further study of computational principles that generate spontaneous and adaptive behavior.

Experience-dependent plasticity enables the developing brain to adapt to repeated sensory input while maintaining stability. However, how such plasticity is coordinated across behavior, transcription, and network dynamics remains unclear. Here, using larval zebrafish, we identify the pannexin channel homolog, Panx1a as a regulator of multiscale adaptations during visual habituation. Panx1a loss selectively impairs long-term habituation without affecting baseline sensorimotor responses. This behavioral deficit is accompanied by disrupted activity-dependent transcription across distributed brain regions and altered excitation-inhibition balance. At the network level, Panx1a deficiency attenuates experience-dependent modulation of gamma activity, cross-frequency coupling, and inter-regional coherence. We further show that sharp wave-ripple-like events are present in vivo at an early developmental stage and exhibit selective refinement of their sharp-wave component following experience, while ripple features remain largely unchanged. This refinement is reduced in panx1a mutants, indicating a role for Panx1a in shaping network dynamics rather than event generation. Together, these findings identify Panx1a as a mediator linking extracellular signaling to coordinated behavioral, molecular, and circuit-level plasticity during early brain development.

Animals continuously extract and evaluate diverse sensory information from the environment to guide behavior. Yet, how neural circuits integrate multiple, potentially conflicting, inputs remains poorly understood. Here, we use larval zebrafish to address this question, leveraging their robust optomotor response to coherent random dot motion and phototaxis towards light. We demonstrate that animals employ an additive behavioral algorithm of three visual features: motion coherence, luminance level, and changes in luminance. Using brain-wide two-photon imaging, we identify the loci of these computations, with the anterior hindbrain emerging as a multifeature integration hub. Through single-cell neurotransmitter and morphological analyses of functionally identified neurons, we characterize potential connections within and across computational nodes. These experiments reveal three parallel and converging computational pathways, matching our behavioral results. Our study provides a mechanistic brain-wide account of how a vertebrate brain integrates multiple features to drive sensorimotor decisions, bridging behavioral algorithms with their neural implementation.

SUMMARY: Animals integrate information over time and maintain persistent internal representations of cues to guide decision-making. How the underlying behavioral algorithms of individual animals depend on factors such as experience, developmental stage, or genotype remains poorly understood. Drift-diffusion models provide a powerful theoretical framework to describe and predict performance metrics across a wide range of species. The stochastic nature of these models and the typical limited throughput of most experimental designs challenge the automatic inference of latent variables. Here, we combine high-throughput behavioral assays in larval zebrafish with drift-diffusion modeling, revealing that larvae progressively develop more persistent, self-reinforcing integration dynamics during early development. This effect is reduced in fish carrying mutations in genes linked to human epilepsy and schizophrenia. Our results show that behavior-based drift-diffusion modeling can offer a scalable, automated approach to generate experimentally testable hypotheses about the algorithmic implementation of sensorimotor integration in health and disease. LINK TO VIDEOS: https://cloud.uni-konstanz.de/index.php/s/qx9DSFciAey3aD7 TEASER: Evidence-integration dynamics in zebrafish mature during development and are selectively altered by disease-associated mutations.

Brightness and contrast are fundamental features of vision, crucial for object detection, environmental navigation, and feeding. Here, we identify a brightness- and contrast-processing circuit in the zebrafish visual system and uncover the role of leucine-rich repeat neuronal (Lrrn) cell adhesion molecules (CAMs) in regulating its assembly. We show that deep-projecting retinal ganglion cells serve as the first synaptic relay to the brain, requiring Lrrn2 and Lrrn3a for precise axonal targeting within the optic tectum. Using a new reporter line, we achieved high-resolution mapping of this previously undercharacterized vertebrate visual circuit. Genetic disruption of Lrrn CAMs leads to disorganization of the circuit and impairments in brightness and contrast sensitivity, resulting in deficits in visually guided behavior. Additionally, ultrastructural circuit reconstruction and functional imaging analysis identified both its synaptic partners and revealed its critical role in luminance processing. These studies define a core visual processing pathway and establish Lrrn CAMs as essential molecular drivers of its assembly.