Biology subjects

How, J. J.

Publications and source records attributed to How, J. J..

4 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

Axons organize into micro-tracts around the cortical vasculature

Neural activity is metabolically costly and supported by local increases in cerebral blood flow. The process by which neural activity drives blood flow increase, neurovascular coupling (NVC), remains poorly understood. One persistent knowledge gap is how subcellular compartments are arranged at the vascular wall, where local signaling occurs. This requires a survey of the neurovascular interface at the nanometer scale. To this end, we analyzed a ~1 mm3 volume of mouse visual cortex imaged with serial electron microscopy. We manually labeled different vascular zones, and classified the EM segments surrounding hundreds of vessel segments across these zones. We found that capillaries and venous vessels are surrounded by more axonal volume than arteriolar vessels. Perivascular axons tended to bundle into micro-tracts, where axons ran in parallel and coursed near the vessel wall in a variety of geometric orientations. Micro-tracts cover ~60% of the surface of capillaries, but only 24-40% of every other vascular zone's surface. Finally, we show that the extensive axon arbors of basket cell inhibitor neurons are within micro-tracts. Their axons come in closest proximity to vessels, and on average, approach 2 to 3 fold more vessel segments than other neuronal subtypes. Altogether, perivascular axonal micro-tracts may be an important physical substrate for NVC signaling at capillaries.

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↗

bioRxiv2020

Neural network features distinguish chemosensory stimuli in Caenorhabditis elegans.

Nervous systems extract and process information from their environment to alter animal behavior and physiology. Despite progress in understanding how different stimuli are represented by changes in neuronal activity, less is known about how they affect broader neural network properties. We developed a framework to use graph-theoretic features of neural network activity and predict ecologically-relevant stimulus properties - namely, stimulus identity and valence. Specifically, we used the transparent nematode, Caenorhabditis elegans, with its small nervous system, to define neural network features associated with various chemosensory stimuli. We trapped animals using a microfluidic device and exposed their noses to chemical stimuli known to be attractive or repellent, while monitoring changes in neural activity in more than 40 neurons in their heads. We found that repellents trigger higher average neural activity across the network, and that the tastant salt increases neural variability. In contrast, graph-theoretic features, which capture patterns of interactions between neurons, are better suited to decode stimulus identity than measures of neural activity. Furthermore, we show that a simple machine learning classifier trained using graph-theoretic features alone or in combination with neural activity features can accurately predict stimulus identity. These results indicate that graph theory reveals network characteristics that are distinct from neural activity, confirming its utility in extracting stimulus properties from neural population data. Significance StatementChanges in the external environment (stimuli) alter patterns of neural activity in animal nervous systems. A central challenge in computational neuroscience is to identify how stimulus properties alter interactions between neurons. We recorded neural activity data from C. elegans head neurons while the animal experienced various chemosensory stimuli. We then used a combination of activity statistics (i.e., average, standard deviation, and several frequency-based measures) and graph-theoretic features of network structure (e.g., modularity - the extent to which a network can be divided into independent clusters) to define neural properties that can accurately predict stimulus identity. Our method is general and can be used across species.

neuroscience↗