Biology subjects

Haesemeyer, M.

Publications and source records attributed to Haesemeyer, M..

12 recordsLinked to original sources

bioRxiv2026

A mechanical parameter of coasting varies bout to bout and predicts swim timing in larval zebrafish

Most animals move intermittently. Of these, animals that fly and swim move in two stages: during active propulsion, when they beat their wings or swing their tails, and right after, when they glide or coast through the air or water. The kinematics of active movements are typically well studied, but the coasting period afterwards is less understood. We used larval zebrafish as a model of intermittent locomotion. Larval zebrafish swim in discrete bouts lasting ~200 ms, coast for short durations and distances, and then are largely stationary for ~800 ms. We find that larval zebrafish do not coast like a passive object. While they coast for distances that are correlated with the prior swim's strength, as expected from physics, they seem to be able to modulate the mechanics of their coasting: the time constant is not a constant, but varies from coast-to-coast. Furthermore, the time constant is correlated with the duration of the interval between swim bouts. This suggests that larval zebrafish can either shorten or extend their coasting duration, and that coasting inhibits the initiation of the next swim. Finally, the time constant changes quickly, while other swimming kinematics (e.g., distance swum) are autocorrelated over the course of at least several seconds. Altogether, this suggests that fish, and perhaps other animals that move intermittently, actively modulate their post-propulsion movement, possibly to gather sensory feedback in the absence of blurry visual feedback associated with fast locomotion.

neuroscience↗

bioRxiv2026

PGE2 modulation of stimulus valence directs zebrafish behavioral fever

Animals seek warmth during fever, but whether this behavior reflects altered temperature perception or interpretation remains unresolved. A prevailing view holds that fever reduces perceived temperature, making the environment feel colder. Here, we use behavior, modeling, and calcium imaging in larval zebrafish to test these hypotheses. We find that viral immune signals drive larval zebrafish to seek warmer temperatures in a PGE2-dependent manner. We localized PGE2 receptors to thermoregulatory brain regions that are conserved across vertebrates. Through comparative behavioral modeling we show that contrary to the prevailing view, fever does not reduce the perception of warmth. Instead, PGE2 alters the valence of temperature changes, such that heating becomes attractive while cooling turns aversive. Calcium imaging reveals that modulation of medullary activity by immune signals directs these changes in stimulus valence. Together, these results identify PGE2-driven changes in stimulus valence as a key principle of the sensorimotor basis of fever.

neuroscience↗

bioRxiv2026

A neuron-glia circuit anticipates hypoxia to regulate organismal oxygen use

Organisms must regulate metabolic resources such as oxygen (O2) and nutrients despite environmental variability and the energetic costs of their own actions1-3. Such regulation can occur reactively, through homeostatic corrections of recent imbalances, or predictively, through allostatic adjustments that anticipate future demand4,5. Predictive regulation is particularly important because metabolic resources often continue to be consumed for seconds to minutes after motor actions cease as tissues repay incurred costs, making it advantageous to prevent depletion before it occurs6. However, the cellular and circuit mechanisms for allostatic control remain largely unknown5,7,8. Using whole-brain neuronal and astroglial imaging and O2 measurements in behaving zebrafish, we identified a noradrenergic-astroglial circuit that detects, anticipates, and prevents internal O2 depletion. We found that swimming exacerbated internal hypoxia with a multi-second delay, but behavioral adaptations occurred before such self-generated hypoxia manifested, suggesting predictive control, confirmed using computational modeling. Noradrenergic neurons in the nucleus of the solitary tract directly detected brain hypoxia and received efference copies of swimming actions; these inputs summed at the level of membrane voltage to increase spiking and norepinephrine release when actions and resource scarcity co-occurred. Astroglia integrated noradrenergic input into prolonged Ca2+ elevation that tracked the O2 cost of recent actions and thereby predicted O2 debt relative to O2 availability, rising ~8 s before O2 fell. This astroglial prediction reorganized brain-wide activity to suppress locomotion and promote respiration, preempting O2 depletion. Silencing noradrenergic neurons or astroglial signaling abolished these hypoxia coping behaviors, whereas selective activation evoked them. This neuronal-astroglial mechanism constitutes a predictive control system that integrates physiological state with behavioral intent to avert metabolic crisis, revealing a cellular substrate for proactive energy management.

neuroscience↗

bioRxiv2025

Markov models bridge behavioral strategies and circuit principles facilitating thermoregulation

Behavioral thermoregulation is critical for survival across animals, including endothermic mammals. However, we do not understand how neural circuits control navigation towards preferred temperatures. Zebrafish exclusively regulate body temperature via behavior, making them ideal for studying thermal navigation. Here, we combine behavioral analysis, machine learning and calcium imaging to understand how larval zebrafish seek out preferred temperatures within thermal gradients. By developing a stimulus-controlled Markov model of thermal navigation we find that hot avoidance largely relies on the modulation of individual swim decisions. The avoidance of cold temperatures, a particular challenge in ectotherms, however relies on a deliberate strategy combining gradient alignment and directed reversals. Calcium imaging identified neurons within the medulla encoding thermal stimuli that form a place-code like representation of the gradient. Our findings establish a key link between neural activity and thermoregulatory behavior, elucidating the neural basis of how animals seek out preferred temperatures.

neuroscience↗

bioRxiv2024

Sensorimotor integration enhances temperature stimulus processing

Animals optimize behavior by integrating sensory input with motor actions. We hypothe-sized that coupling thermosensory information with motor output enhances the brains capacity to process temperature changes, leading to more precise and adaptive behaviors. To test this, we developed a virtual "thermal plaid" environment where zebrafish either actively controlled temperature changes (sensorimotor feedback) or passively experienced the same thermal fluctuations. Our findings demonstrate that sensorimotor feedback amplifies the influence of thermal stimuli on swim initiation, resulting in more structured and organized motor output. We show that previously identified mixed-selectivity neurons that simultaneously encode thermal cues and motor activity enable the integration of sensory and motor feedback to optimize behavior. These results highlight the role of sensorimotor integration in refining thermosensory processing, revealing critical neural mechanisms underlying flexible thermoregulatory behavior. Our study offers new insights into how animals adaptively process environmental stimuli and adjust their actions, contributing to a deeper understanding of the neural circuits driving goal-directed behavior in dynamic environments.

neuroscience↗

bioRxiv2022

A model-free approach to link neural activity to behavioral tasks

Brains are not engineered solutions to a well-defined problem but arose through selective pressure acting on random variation. It is therefore unclear how well a model chosen by an experimenter can relate neural activity to experimental conditions. Here we developed "Model identification of neural encoding (MINE)." MINE is an accessible framework using convolutional neural networks (CNN) to discover and characterize a model that relates aspects of tasks to neural activity . Although flexible, CNNs are difficult to interpret. We use Taylor decomposition approaches to understand the discovered model and how it maps task features to activity. We apply MINE to a published cortical dataset as well as experiments designed to probe thermoregulatory circuits in zebrafish. MINE allowed us to characterize neurons according to their receptive field and computational complexity, features which anatomically segregate in the brain. We also identified a new class of neurons that integrate thermosensory and behavioral information which eluded us previously when using traditional clustering and regression-based approaches.

neuroscience↗

bioRxiv2022

Molecular and functional mechanisms of long-term visual habituation in larval zebrafish

Habituation allows animals to learn to ignore persistent but inconsequential stimuli. Despite being the most basic form of learning, a consensus model on the underlying mechanisms has yet to emerge. To probe relevant mechanisms we took advantage of a visual habituation paradigm in larval zebrafish, where larvae reduce their reactions to abrupt global dimming (a dark flash). We used Ca2+ imaging during repeated dark flashes and identified 12 functional classes of neurons that differ based on their rate of adaptation, stimulus response shape, and anatomical location. While most classes of neurons depressed their responses to repeated stimuli, we identified populations that did not adapt, or that potentiated their response. These neurons were distributed across brain areas, consistent with a distributed learning process. Using a small molecule-screening approach, we confirmed that habituation manifests from multiple distinct molecular mechanisms, and we have implicated molecular pathways in habituation, including: Melatonin, Estrogen and GABA signaling. However, by combining anatomical analyses and pharmacological manipulations with Ca2+ imaging, we failed to identify a simple relationship between pharmacology, altered activity patterns, and habituation behaviour. Collectively, our work indicates that habituation occurs via a complex and distributed plasticity processes that cannot be captured by a simple model. Therefore, untangling the mechanisms of habituation will likely require dedicated approaches aimed at sub-component mechanisms underlying this multidimensional learning process.

neuroscience↗

bioRxiv2021

Functional and ultrastructural analysis of reafferent mechanosensation in larval zebrafish

All animals need to differentiate between exafferent stimuli, which are caused by the environment, and reafferent stimuli, which are caused by their own movement. In the case of mechanosensation in aquatic animals, the exafferent inputs are water vibrations in the animals proximity, which need to be distinguished from the reafferent inputs arising from fluid drag due to locomotion. Both of these inputs are detected by the lateral line, a collection of mechanosensory organs distributed along the surface of the body. In this study, we characterize in detail how the hair cells, which are the receptor cells of the lateral line, discriminate between such reafferent and exafferent signals in zebrafish larvae. Using dye labeling of the lateral line nerve, we visualize two parallel descending inputs that can influence lateral line sensitivity. We combine functional imaging with ultra-structural EM circuit reconstruction to show that cholinergic signals originating from the hindbrain transmit efference copies that cancel out self-generated reafferent stimulation during locomotion, and that dopaminergic signals from the hypothalamus may have a role in threshold modulation both in response to locomotion and salient stimuli. We further gain direct mechanistic insight into the core components of this circuit by loss-of-function perturbations using targeted ablations and gene knockouts. We propose that this simple circuit is the core implementation of mechanosensory reafferent suppression in these young animals and that it might form the first instantiation of state-dependent modulation found at later stages in development.

neuroscience↗

bioRxiv2019

Elements of a stochastic 3D prediction engine in larval zebrafish prey capture

Many predatory animals rely on accurate sensory perception, predictive models, and precise pursuits to catch moving prey. Larval zebrafish intercept paramecia during their hunting behavior, but the precise trajectories of their prey have never been recorded in relation to fish movements in three dimensions.\n\nAs a means of uncovering what a simple organism understands about its physical world, we have constructed a 3D-imaging setup to simultaneously record the behavior of larval zebrafish, as well as their moving prey, during hunting. We show that zebrafish robustly transform their 3D displacement and rotation according to the position of their prey while modulating both of these variables depending on prey velocity. This is true for both azimuth and altitude, but particulars of the hunting algorithm in the two planes are slightly different to accommodate an asymmetric strike zone. We show that the combination of position and velocity perception provides the fish with a preferred future positional estimate, indicating an ability to project trajectories forward in time. Using computational models, we show that this projection ability is critical for prey capture efficiency and success. Further, we demonstrate that fish use a graded stochasticity algorithm where the variance around the mean result of each swim scales with distance from the target. Notably, this strategy provides the animal with a considerable improvement over equivalent noise-free strategies.\n\nIn sum, our quantitative and probabilistic modeling shows that zebrafish are equipped with a stochastic recursive algorithm that embodies an implicit predictive model of the world. This algorithm, built by a simple set of behavioral rules, allows the fish to optimize their hunting strategy in a naturalistic three-dimensional environment.

animal behavior and cognition↗

bioRxiv2018

Distributed plasticity drives visual habituation learning in larval zebrafish

Habituation is a simple form of learning, where animals learn to reduce their responses to repeated innocuous stimuli. While habituation is simple in concept, its exact implementation in the vertebrate brain is not clear. It could occur via a single plasticity event at a singular site in the circuit, or alternatively via more complex strategies that combine multiple mechanisms at various processing stages and sites. Here, we use a visual habituation assay in larval zebrafish, where larvae habituate to sudden reductions in illumination (dark flashes). We find that 8 different components of this response habituate, including the probability of executing a response, its latency, and measures of its magnitude. Through behavioural analyses, we find that habituation of these different behavioural components occurs independently of each other and at different locations in the circuit. Further, we use genetic and pharmacological manipulations to show that habituation of different behavioural components are molecularly distinct. These results are consistent with a model by which visual habituation originates from the combination of multiple independent processes, which each act to adapt specific components of behaviour. This may allow animals to more specifically habituate behaviour based on stimulus context or internal state.

neuroscience↗

bioRxiv2018

Convergent temperature representations in artificial and biological neural networks

While discoveries in biological neural networks (BNN) shaped artificial neural networks (ANN) it is unclear if representations and algorithms are shared between ANNs and BNNs performing similar tasks. Here, we designed and trained an ANN to perform heat gradient navigation and found striking similarities in computation and heat representation to a known zebrafish BNN. This included shared ON and OFF type representations of absolute temperature and rates of change. Importantly, ANN function critically relied on zebrafish like units. We could furthermore use the accessibility of the ANN to discover a new temperature responsive cell type in the zebrafish cerebellum. Finally, our approach generalized since training the same ANN constrained by the C. elegans motor repertoire resulted in distinct neural representations matching features observed in the worm. Together, these results emphasize convergence of ANNs and BNNs on canonical representations and that ANNs form a powerful tool to understand their biological counterparts.

neuroscience↗

bioRxiv2017

A brain wide circuit model of heat evoked swimming behavior in larval zebrafish

Thermosensation provides crucial information but it is poorly understood how temperature representation is transformed from sensation to behavior. Here, we report a preparation that allows control of heat delivery to zebrafish larvae while monitoring motor output and imaging whole-brain calcium signals, thereby uncovering algorithmic and computational rules that couple dynamics of heat modulation, neural activity and swimming behavior. This approach identifies a critical step in the transformation of temperature representation between the sensory trigeminal ganglia and the hindbrain: A simple sustained trigeminal stimulus representation is transformed into a representation of absolute temperature as well as temperature changes in the hindbrain that explains the observed motor output. An activity constrained dynamic circuit model captures the most prominent aspects of these sensori-motor transformations and predicts both behavior and neural activity in response to novel heat stimuli. These findings provide the first algorithmic description of heat processing from sensory input to behavioral output.

neuroscience↗