Non-overlapping Neural Networks in Hydra vulgaris

Jellyfish for the study of nervous system evolution and function

Jellyfish comprise a diverse clade of free-swimming predators that arose prior to the Cambrian explosion. They play major roles in ocean ecosystems via a suite of complex foraging, reproductive, and defensive behaviors. These behaviors arise from decentralized, regenerative nervous systems composed of body parts that generate the appropriate part-specific behaviors autonomously following excision. Here, we discuss the organization of jellyfish nervous systems and opportunities afforded by the recent development of a genetically tractable jellyfish model for systems and evolutionary neuroscience.

Adaptive robustness through incoherent signaling mechanisms in a regenerative brain

Animal behavior emerges from collective dynamics of neurons, making it vulnerable to damage. Paradoxically, many organisms exhibit a remarkable ability to maintain significant behavior even after large-scale neural injury. Molecular underpinnings of this extreme robustness remain largely unknown. Here, we develop a quantitative pipeline to measure long-lasting latent states in planarian flatworm behaviors during whole-brain regeneration. By combining >20,000 animal trials with neural network modeling, we show that long-range volumetric peptidergic signals allow the planarian to rapidly restore coarse behavior output after large perturbations to the nervous system, while slow restoration of small-molecule neuromodulator functions refines precision. This relies on the different time and length scales of neuropeptide and small-molecule transmission to generate incoherent patterns of neural activity that competitively regulate behavior. Controlling behavior through opposing communication mechanisms creates a more robust system than either alone and may serve as a generalizable approach for constructing robust neural networks.

A neural circuit architecture for rapid learning in goal-directed navigation

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.

Satiety controls behavior in Hydra through an interplay of pre-enteric and central nervous system-like neuron populations

Hunger and satiety can have an influence on decision-making, sensory processing, and motor behavior by altering the internal state of the brain. This process necessitates the integration of peripheral sensory stimuli into the central nervous system. Here, we show how animals without a central nervous system such as the cnidarian Hydra measure and integrate satiety into neuronal circuits and which specific neuronal populations are involved. We demonstrate that this simple nervous system, previously referred to as diffuse, has an endodermal subpopulation (N4) similar to the enteric nervous system (feeding-associated behavior) and an ectodermal population (N3) that performs central nervous system-like functions (physiology/motor). This view of a supposedly simple nervous system could open an important window into the origin of more complex nervous systems.

CRASH2p: Closed-loop Two Photon Imaging in Freely Moving Animals

Direct measurement of neural activity in freely moving animals is essential for understanding how the brain controls and represents behaviors. Genetically encoded calcium indicators report neural activity as changes in fluorescence intensity, but brain motion confounds quantitative measurement of fluorescence. Translation, rotation, and deformation of the brain and the movements of intervening scattering or auto-fluorescent tissue all alter the amount of fluorescent light captured by a microscope. Compared to single-photon approaches, two photon microscopy is less sensitive to scattering and off-target fluorescence, but more sensitive to motion, and two photon imaging has always required anchoring the microscope to the brain. We developed a closed-loop resonant axial-scanning high-speed two photon (CRASH2p) microscope for real-time 3D motion correction in unrestrained animals, without implantation of reference markers. We complemented CRASH2p with a novel scanning strategy and a multistage registration pipeline. We performed volumetric ratiometrically corrected functional imaging in the CNS of freely moving Drosophila larvae and discovered previously unknown neural correlates of behavior.

Breaking the neural code of a cnidarian: Learning principles of neuroscience from the "vulgar" Hydra

The cnidarian Hydra vulgaris is a small polyp with a nervous system of few hundred neurons belonging to a dozen cell types, organized in two nerve nets without cephalization or ganglia. Using this simple neural "chassis", Hydra can maintain a stable repertoire of behaviors, even performing complex fixed-action patterns, such as somersaulting and feeding. The ability to image the activity of Hydra's entire neural and muscle tissue has revealed that Hydra's nerve nets are divided into coactive ensembles of neurons, associated with specific movements. These ensembles can be activated by neuropeptides and interact using cross-inhibition circuits and implement integrate-to-threshold algorithms. In addition, Hydra's nervous system can self-assemble from dissociated cells in a stepwise modular architecture. Studies of Hydra and other cnidarians could enable the systematic deciphering of the neural basis of its behavior and help provide perspective on basic principles of neuroscience.

Division of labor for defensive retaliation and preemption by the peripheral and central nervous systems in the nudibranch Berghia

Relatively little is known about how peripheral nervous systems (PNSs) contribute to the patterning of behavior in which their role transcends the simple execution of central motor commands or mediation of reflexes. We sought to draw inferences to this end in the aeolid nudibranch Berghia stephanieae, which generates a rapid, dramatic defense behavior, "bristling." This behavior involves the coordinated movement of cerata, dozens of venomous appendages emerging from the animal's mantle. Our investigations revealed that bristling constitutes a stereotyped but non-reflexive two-stage behavior: an initial adduction of proximate cerata to sting the offending stimulus (stage 1) followed by a coordinated radial extension of remaining cerata to create a pincushion-like defensive screen around the animal (stage 2). In decerebrated specimens, stage 1 bristling was preserved, while stage 2 bristling was replaced by slower, uncoordinated ceratal movements. We conclude from these observations that, first, the animal's PNS and central nervous system (CNS) mediate stages 1 and 2 of bristling, respectively; second, the behavior propagates through the body utilizing both peripheral- and central-origin nerve networks that support different signaling kinetics; and third, the former network inhibits the latter in the body region being stimulated. These findings extend our understanding of the PNS' computational capacity and provide insight into a neuroethological scheme in which the CNS and PNS both independently and interactively pattern different aspects of non-reflexive behavior.

Neuronal ensembles: Building blocks of neural circuits

Neuronal ensembles, defined as groups of neurons displaying recurring patterns of coordinated activity, represent an intermediate functional level between individual neurons and brain areas. Novel methods to measure and optically manipulate the activity of neuronal populations have provided evidence of ensembles in the neocortex and hippocampus. Ensembles can be activated intrinsically or in response to sensory stimuli and play a causal role in perception and behavior. Here we review ensemble phenomenology, developmental origin, biophysical and synaptic mechanisms, and potential functional roles across different brain areas and species, including humans. As modular units of neural circuits, ensembles could provide a mechanistic underpinning of fundamental brain processes, including neural coding, motor planning, decision-making, learning, and adaptability.

Automatic monitoring of neural activity with single-cell resolution in behaving Hydra

The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris. We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron's calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra, and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.

Nonlinear elasticity and short-range mechanical coupling govern the rate and symmetry of mouth opening in Hydra

Hydra has a tubular bilayered epithelial body column with a dome-shaped head on one end and a foot on the other. Hydra lacks a permanent mouth: its head epithelium is sealed. Upon neuronal activation, a mouth opens at the apex of the head which can exceed the body column diameter in seconds, allowing Hydra to ingest prey larger than itself. While the kinematics of mouth opening are well characterized, the underlying mechanism is unknown. We show that Hydra mouth opening is generated by independent local contractions that require tissue-level coordination. We model the head epithelium as an active viscoelastic nonlinear spring network. The model reproduces the size, timescale and symmetry of mouth opening. It shows that radial contractions, travelling inwards from the outer boundary of the head, pull the mouth open. Nonlinear elasticity makes mouth opening larger and faster, contrary to expectations. The model correctly predicts changes in mouth shape in response to external forces. By generating innervated : nerve-free chimera in experiments and simulations, we show that nearest-neighbour mechanical signalling suffices to coordinate mouth opening. Hydra mouth opening shows that in the absence of long-range chemical or neuronal signals, short-range mechanical coupling is sufficient to produce long-range order in tissue deformations.

A new look at the architecture and dynamics of the Hydra nerve net

The Hydra nervous system is the paradigm of a 'simple nerve net'. Nerve cells in Hydra, as in many cnidarian polyps, are organized in a nerve net extending throughout the body column. This nerve net is required for control of spontaneous behavior: elimination of nerve cells leads to polyps that do not move and are incapable of capturing and ingesting prey (Campbell, 1976). We have re-examined the structure of the Hydra nerve net by immunostaining fixed polyps with a novel antibody that stains all nerve cells in Hydra. Confocal imaging shows that there are two distinct nerve nets, one in the ectoderm and one in the endoderm, with the unexpected absence of nerve cells in the endoderm of the tentacles. The nerve nets in the ectoderm and endoderm do not contact each other. High-resolution TEM (transmission electron microscopy) and serial block face SEM (scanning electron microscopy) show that the nerve nets consist of bundles of parallel overlapping neurites. Results from transgenic lines show that neurite bundles include different neural circuits and hence that neurites in bundles require circuit-specific recognition. Nerve cell-specific innexins indicate that gap junctions can provide this specificity. The occurrence of bundles of neurites supports a model for continuous growth and differentiation of the nerve net by lateral addition of new nerve cells to the existing net. This model was confirmed by tracking newly differentiated nerve cells.

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional neural network with ground-truth (GT) annotations of images representing different brain postures. For 3D images, this is very labor intensive. We introduce 'targeted augmentation', a method to automatically synthesize artificial annotations from a few manual annotations. Our method ('Targettrack') learns the internal deformations of the brain to synthesize annotations for new postures by deforming GT annotations. This reduces the need for manual annotation and proofreading. A graphical user interface allows the application of the method end-to-end. We demonstrate Targettrack on recordings where neurons are labeled as key points or 3D volumes. Analyzing freely moving animals exposed to odor pulses, we uncover rich patterns in interneuron dynamics, including switching neuronal entrainment on and off.

Multiple neuronal populations control the eating behavior in Hydra and are responsive to microbial signals

Although recent studies indicate the impact of microbes on the central nervous systems and behavior, it remains unclear how the relationship between the functionality of the nervous system, behavior, and the microbiota evolved. In this work, we analyzed the eating behavior of Hydra, a host that has a simple nervous system and a low-complexity microbiota. To identify the neuronal subpopulations involved, we used a subpopulation-specific cell ablation system and calcium imaging. The role of the microbiota was uncovered by manipulating the diversity of the natural microbiota. We show that different neuronal subpopulations are functioning together to control eating behavior. Animals with a drastically reduced microbiome had severe difficulties in mouth opening due to a significantly increased level of glutamate. This could be reversed by adding a full complement of the microbiota. In summary, we provide a mechanistic explanation of how Hydra's nervous system controls eating behavior and what role microbes play in this.

Evolution: Neuronal control of an archaic mouth

Cnidarians (corals, hydras, jellyfish, sea anemones) are prey-devouring creatures with a simple nervous system, the function of which is largely unknown. A new study on the freshwater polyp Hydra has now uncovered the neuronal circuits that control its feeding behavior.

On being a Hydra with, and without, a nervous system: what do neurons add?

The small freshwater cnidarian Hydra has been the subject of scientific inquiry for over 300 years due to its remarkable regenerative capacities and apparent immortality. More recently, Hydra has been recognized as an excellent model system within neuroscience because of its small size, transparency, and simple nervous system, which allow high-resolution imaging of its entire nerve net while behaving. In less than a decade, studies of Hydra's nervous system have yielded insights into the activity of neural circuits in vivo unobtainable in most other animals. In addition to these unique attributes, there is yet another lesser-known feature of Hydra that makes it even more intriguing: it does not require its neural hardware to live. The extraordinary ability to survive the removal and replacement of its entire nervous system makes Hydra uniquely suited to address the question of what neurons add to an extant organism. Here, I will review what early work on nerve-free Hydra reveals about the potential role of the nervous system in these animals and point towards future directions for this work.

In vivo neuromodulation of animal behavior with organic semiconducting oligomers

Modulating neural activity with electrical or chemical stimulus can be used for fundamental and applied research. Typically, neuronal stimulation is performed with intracellular and extracellular electrodes that deliver brief electrical pulses to neurons. However, alternative wireless methodologies based on functional materials may allow clinical translation of technologies to modulate neuronal function. Here, we show that the organic semiconducting oligomer 4-[2-{2,5-bis(2,3-dihydrothieno[3,4-b][1,4]dioxin-5-yl)thiophen-3-yl}ethoxy]butane-1-sulfonate (ETE-S) induces precise behaviors in the small invertebrate Hydra, which were dissected through pharmacological and electrophysiological approaches. ETE-S-induced behavioral response relies on the presence of head neurons and calcium ions and is prevented by drugs targeting ionotropic channels and muscle contraction. Moreover, ETE-S affects Hydra's electrical activity enhancing the contraction burst frequency. The unexpected neuromodulatory function played by this conjugated oligomer on a simple nerve net opens intriguing research possibilities on fundamental chemical and physical phenomena behind organic bioelectronic interfaces for neuromodulation and on alternative methods that could catalyze a wide expansion of this rising technology for clinical applications.

Automatic monitoring of whole-body neural activity in behaving Hydra

The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris. We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron's calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra, and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.

Universal calcium fluctuations inHydramorphogenesis

Understanding the collective physical processes that drive robust morphological transitions in animal development necessitates the characterization of the relevant fields involved in morphogenesis. Calcium (Ca2+) is recognized as one such field. In this study, we demonstrate that the spatial fluctuations of Ca2+duringHydraregeneration exhibit universal characteristics. To investigate this phenomenon, we employ two distinct controls, an external electric field andheptanol, a gap junction-blocking drug. Both lead to the modulation of the Ca2+activity and a reversible halting of the regeneration process. The application of an electric field enhances Ca2+activity in theHydra's tissue and increases its spatial correlations, while the administration ofheptanolinhibits its activity and diminishes the spatial correlations. Remarkably, the statistical characteristics of Ca2+spatial fluctuations, including the coefficient of variation and skewness, manifest universal shape distributions across tissue samples and conditions. We introduce a field-theoretic model, describing fluctuations in a tilted double-well potential, which successfully captures these universal properties. Moreover, our analysis reveals that the Ca2+activity is spatially localized, and theHydra's tissue operates near the onset of bistability, where the local Ca2+activity fluctuates between low and high excited states in distinct regions. These findings highlight the prominent role of the Ca2+field inHydramorphogenesis and provide insights into the underlying mechanisms governing robust morphological transitions.

Two-photon manipulation of neuronal activity and behavior in Hydra vulgaris

The introduction of calcium imaging has rendered cnidarians, such as Hydra vulgaris, valuable model organisms for investigating neuronal activity and behavior. Here, we present a comprehensive protocol to image and manipulate neuronal activity and behavior of Hydra. We describe steps for wide-field imaging and two-photon simulation and ablation of neurons. We then detail imaging behavior and post-ablation analysis. We address challenges that may arise during the preparation and execution of the experiments.

Molecular machines stimulate intercellular calcium waves and cause muscle contraction

Intercellular calcium waves (ICW) are complex signalling phenomena that control many essential biological activities, including smooth muscle contraction, vesicle secretion, gene expression and changes in neuronal excitability. Accordingly, the remote stimulation of ICW could result in versatile biomodulation and therapeutic strategies. Here we demonstrate that light-activated molecular machines (MM)-molecules that perform mechanical work on the molecular scale-can remotely stimulate ICW. MM consist of a polycyclic rotor and stator that rotate around a central alkene when activated with visible light. Live-cell calcium-tracking and pharmacological experiments reveal that MM-induced ICW are driven by the activation of inositol-triphosphate-mediated signalling pathways by unidirectional, fast-rotating MM. Our data suggest that MM-induced ICW can control muscle contraction in vitro in cardiomyocytes and animal behaviour in vivo in Hydra vulgaris. This work demonstrates a strategy for directly controlling cell signalling and downstream biological function using molecular-scale devices.

Cnidofest 2022: hot topics in cnidarian research

The second annual Cnidarian Model Systems Meeting, aka "Cnidofest", took place in Davis, California from 7 to 10th of September, 2022. The meeting brought together scientists using cnidarians to study molecular and cellular biology, development and regeneration, evo-devo, neurobiology, symbiosis, physiology, and comparative genomics. The diversity of topics and species represented in presentations highlighted the importance and versatility of cnidarians in addressing a wide variety of biological questions. In keeping with the spirit of the first meeting (and its predecessor, Hydroidfest), almost 75% of oral presentations were given by early career researchers (i.e., graduate students and postdocs). In this review, we present research highlights from the meeting.

Neural division of labor: the gastropod Berghia defends against attack using its PNS to retaliate and its CNS to erect a defensive screen

Relatively little is known about how the peripheral nervous system (PNS) contributes to the patterning of behavior, in which its role transcends the simple execution of central motor commands or mediation of reflexes. We sought to draw inferences to this end in the aeolid nudibranch Berghia stephanieae, which generates a rapid, dramatic defense behavior, "bristling." This behavior involves the coordinated movement of cerata, dozens of venomous appendages emerging from the animal's mantle. Our investigations revealed that bristling constitutes a stereotyped but non-reflexive two-stage behavior: an initial adduction of proximate cerata to sting the offending stimulus (Stage 1), followed by a coordinated radial extension of remaining cerata to create a pincushion-like defensive screen around the animal (Stage 2). In decerebrated specimens, Stage 1 bristling was preserved, while Stage 2 bristling was replaced by slower, uncoordinated, and ultimately maladaptive ceratal movements. We conclude from these observations that 1) the PNS and central nervous system (CNS) mediate Stages 1 and 2 of bristling, respectively; 2) the behavior propagates through the body utilizing both peripheral- and central-origin nerve networks that support different signaling kinetics; and 3) the former network inhibits the latter in the body region being stimulated. These findings extend our understanding of the PNS's computational capacity and provide insight into a neuroethological scheme that may generalize across cephalized animals, in which the CNS and PNS both independently and interactively pattern different aspects of non-reflexive behavior.

Multi-neuronal recording in unrestrained animals with all acousto-optic random-access line-scanning two-photon microscopy

To understand how neural activity encodes and coordinates behavior, it is desirable to record multi-neuronal activity in freely behaving animals. Imaging in unrestrained animals is challenging, especially for those, like larval Drosophila melanogaster, whose brains are deformed by body motion. A previously demonstrated two-photon tracking microscope recorded from individual neurons in freely crawling Drosophila larvae but faced limits in multi-neuronal recording. Here we demonstrate a new tracking microscope using acousto-optic deflectors (AODs) and an acoustic GRIN lens (TAG lens) to achieve axially resonant 2D random access scanning, sampling along arbitrarily located axial lines at a line rate of 70 kHz. With a tracking latency of 0.1 ms, this microscope recorded activities of various neurons in moving larval Drosophila CNS and VNC including premotor neurons, bilateral visual interneurons, and descending command neurons. This technique can be applied to the existing two-photon microscope to allow for fast 3D tracking and scanning.

Neuroethology: Generating complex behavioral sequences with distributed nerve nets

How are animals equipped with only diffusely distributed nerve nets able to generate complex behaviors? A new study in Hydra vulgaris proposes that a peptide-based 'wireless connectome' works in concert with two familiar network-coordinating mechanisms to generate the animal's remarkable somersault behavior.

The Hydra stem cell system - Revisited

Cnidarians are >600 million years old and are considered the sister group of Bilateria based on numerous molecular phylogenetic studies. Apart from Hydra, the genomes of all major clades of Cnidaria have been uncovered (e.g. Aurelia, Clytia, Nematostella and Acropora) and they reveal a remarkable completeness of the metazoan genomic toolbox. Of particular interest is Hydra, a model system of aging research, regenerative biology, and stem cell biology. With the knowledge gained from scRNA research, it is now possible to characterize the expression profiles of all cell types with great precision. In functional studies, our picture of the Hydra stem cell biology has changed, and we are in the process of obtaining a clear picture of the homeostasis and properties of the different stem cell populations. Even though Hydra is often compared to plant systems, the new data on germline and regeneration, but also on the dynamics and plasticity of the nervous system, show that Hydra with its simple body plan represents in a nutshell the prototype of an animal with stem cell lineages, whose properties correspond in many ways to Bilateria. This review provides an overview of the four stem cell lineages, the two epithelial lineages that constitute the ectoderm and the endoderm, as well as the multipotent somatic interstitial lineage (MPSC) and the germline stem cell lineage (GSC), also known as the interstitial cells of Hydra.

Differentiation trajectories of the Hydra nervous system reveal transcriptional regulators of neuronal fate

The small freshwater cnidarian polyp Hydra vulgaris uses adult stem cells (interstitial stem cells) to continually replace neurons throughout its life. This feature, combined with the ability to image the entire nervous system (Badhiwala et al., 2021; Dupre & Yuste, 2017) and availability of gene knockdown techniques (Juliano, Reich, et al., 2014; Lohmann et al., 1999; Vogg et al., 2022), makes Hydra a tractable model for studying nervous system development and regeneration at the whole-organism level. In this study, we use single-cell RNA sequencing and trajectory inference to provide a comprehensive molecular description of the adult nervous system. This includes the most detailed transcriptional characterization of the adult Hydra nervous system to date. We identified eleven unique neuron subtypes together with the transcriptional changes that occur as the interstitial stem cells differentiate into each subtype. Towards the goal of building gene regulatory networks to describe Hydra neuron differentiation, we identified 48 transcription factors expressed specifically in the Hydra nervous system, including many that are conserved regulators of neurogenesis in bilaterians. We also performed ATAC-seq on sorted neurons to uncover previously unidentified putative regulatory regions near neuron-specific genes. Finally, we provide evidence to support the existence of transdifferentiation between mature neuron subtypes and we identify previously unknown transition states in these pathways. All together, we provide a comprehensive transcriptional description of an entire adult nervous system, including differentiation and transdifferentiation pathways, which provides a significant advance towards understanding mechanisms that underlie nervous system regeneration.

Peptide-driven control of somersaulting in Hydra vulgaris

The cnidarian Hydra vulgaris has a simple nervous system with a few hundred neurons in distributed networks. Yet Hydra can perform somersaults, a complex acrobatic locomotion. To understand the neural mechanisms of somersaulting we used calcium imaging and found that rhythmical potential 1 (RP1) neurons activate before somersaulting. Decreasing RP1 activity or ablating RP1 neurons reduced somersaulting, while two-photon activation of RP1 neurons induced somersaulting. Hym-248, a peptide synthesized by RP1 cells, selectively generated somersaulting. We conclude that RP1 activity, via release of Hym-248, is necessary and sufficient for somersaulting. We propose a circuit model to explain the sequential unfolding of this locomotion, using integrate-to-threshold decision making and cross-inhibition. Our work demonstrates that peptide-based signaling is used by simple nervous systems to generate behavioral fixed action patterns.

A complete biomechanical model of Hydra contractile behaviors, from neural drive to muscle to movement

How does neural activity drive muscles to produce behavior? The recent development of genetic lines in Hydra that allow complete calcium imaging of both neuronal and muscle activity, as well as systematic machine learning quantification of behaviors, makes this small cnidarian an ideal model system to understand and model the complete transformation from neural firing to body movements. To achieve this, we have built a neuromechanical model of Hydra's fluid-filled hydrostatic skeleton, showing how drive by neuronal activity activates distinct patterns of muscle activity and body column biomechanics. Our model is based on experimental measurements of neuronal and muscle activity and assumes gap junctional coupling among muscle cells and calcium-dependent force generation by muscles. With these assumptions, we can robustly reproduce a basic set of Hydra's behaviors. We can further explain puzzling experimental observations, including the dual timescale kinetics observed in muscle activation and the engagement of ectodermal and endodermal muscles in different behaviors. This work delineates the spatiotemporal control space of Hydra movement and can serve as a template for future efforts to systematically decipher the transformations in the neural basis of behavior.

An electrophysiological and kinematic model of Paramecium, the "swimming neuron"

Paramecium is a large unicellular organism that swims in fresh water using cilia. When stimulated by various means (mechanically, chemically, optically, thermally), it often swims backward then turns and swims forward again in a new direction: this is called the avoiding reaction. This reaction is triggered by a calcium-based action potential. For this reason, several authors have called Paramecium the "swimming neuron". Here we present an empirically constrained model of its action potential based on electrophysiology experiments on live immobilized paramecia, together with simultaneous measurement of ciliary beating using particle image velocimetry. Using these measurements and additional behavioral measurements of free swimming, we extend the electrophysiological model by coupling calcium concentration to kinematic parameters, turning it into a swimming model. In this way, we obtain a model of autonomously behaving Paramecium. Finally, we demonstrate how the modeled organism interacts with an environment, can follow gradients and display collective behavior. This work provides a modeling basis for investigating the physiological basis of autonomous behavior of Paramecium in ecological environments.

Adaptive robustness through incoherent signaling mechanisms in a regenerative brain

Animal behavior emerges from collective dynamics of interconnected neurons, making it vulnerable to connectome damage. Paradoxically, many organisms maintain significant behavioral output after large-scale neural injury. Molecular underpinnings of this extreme robustness remain largely unknown. Here, we develop a quantitative behavioral analysis pipeline to measure previously uncharacterized long-lasting latent memory states in planarian flatworms during whole-brain regeneration. By combining >20,000 animal trials with neural population dynamic modeling, we show that long-range volumetric peptidergic signals allow the planarian to rapidly reestablish latent states and restore coarse behavior after large structural perturbations to the nervous system, while small-molecule neuromodulators gradually refine the precision. The different time and length scales of neuropeptide and small-molecule transmission generate incoherent patterns of neural activity which competitively regulate behavior and memory. Controlling behavior through opposing communication mechanisms creates a more robust system than either alone and may serve as a generic approach to construct robust neural networks.

Nine insights from internet engineering that help us understand brain network communication

Philosophers have long recognized the value of metaphor as a tool that opens new avenues of investigation. By seeing brains as having the goal of representation, the computer metaphor in its various guises has helped systems neuroscience approach a wide array of neuronal behaviors at small and large scales. Here I advocate a complementary metaphor, the internet. Adopting this metaphor shifts our focus from computing to communication, and from seeing neuronal signals as localized representational elements to seeing neuronal signals as traveling messages. In doing so, we can take advantage of a comparison with the internet's robust and efficient routing strategies to understand how the brain might meet the challenges of network communication. I lay out nine engineering strategies that help the internet solve routing challenges similar to those faced by brain networks. The internet metaphor helps us by reframing neuronal activity across the brain as, in part, a manifestation of routing, which may, in different parts of the system, resemble the internet more, less, or not at all. I describe suggestive evidence consistent with the brain's use of internet-like routing strategies and conclude that, even if empirical data do not directly implicate internet-like routing, the metaphor is valuable as a reference point for those investigating the difficult problem of network communication in the brain and in particular the problem of routing.

Fast, efficient, and accurate neuro-imaging denoising via supervised deep learning

Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applied to denoise images, their applications to downstream analyses, such as recovering high-SNR calcium traces, have been limited. Further, these methods require temporally-sequential pre-registered data acquired at ultrafast rates. Here, we demonstrate a supervised deep-denoising method to circumvent these tradeoffs for several applications, including whole-brain imaging, large-field-of-view imaging in freely moving animals, and recovering complex neurite structures in C. elegans. Our framework has 30× smaller memory footprint, and is fast in training and inference (50-70 ms); it is highly accurate and generalizable, and further, trained with only small, non-temporally-sequential, independently-acquired training datasets (∼500 pairs of images). We envision that the framework will enable faster and long-term imaging experiments necessary to study neuronal mechanisms of many behaviors.

Dissociation and reaggregation of Hydra vulgaris for studies of self-organization

The remarkable regenerative abilities of the small cnidarian Hydra vulgaris include the capacity to reassemble itself after dissociation into individual cells. Here, we present a robust protocol for the dissociation and reaggregation of Hydra tissue that addresses many common challenges encountered during the preparation and execution of the dissociation, as well as the formation and care of regenerating cellular aggregates. Analysis of the process provides insight into the mechanisms of nervous system self-organization.

For complete details on the use and execution of this protocol, please refer to Lovas and Yuste (2021).

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Amplify experimental Hydra and prepare for the animal’s dissociation

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Dissociate Hydra into individual cells, aggregate, and monitor their reassembly

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Follow Hydra’s epithelial layer segregation and neural circuit formation

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A new polyp emerges from the cellular aggregate after one week of development

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Neural Cell Type Diversity in Cnidaria

Neurons are the fundamental building blocks of nervous systems. It appears intuitive that the human brain is made up of hundreds, if not thousands different types of neurons. Conversely, the seemingly diffuse nerve net of Cnidaria is often assumed to be simple. However, evidence that the Cnidaria nervous system is indeed simple is sparse. Recent technical advances make it possible to assess the diversity and function of neurons with unprecedented resolution. Transgenic animals expressing genetically encoded Calcium sensors allow direct physiological assessments of neural responses within the nerve net and provide insight into the spatial organization of the nervous system. Moreover, response and activity patterns allow the characterization of cell types on a functional level. Molecular and genetic identities on the other hand can be assessed combining single-cell transcriptomic analysis with correlations of gene expression in defined neurons. Here I review recent advances on these two experimental strategies focusing on Hydra, Nematostella, and Clytia.

A systematic review on toxicity assessment of persistent emerging pollutants (EPs) and associated microplastics (MPs) in the environment using the Hydra animal model

Emerging pollutants (EPs) are causative for teratogenic and reproductive effects. EPs are detected in all the environmental matrices at higher levels. A suitable model for aquatic toxicity assessment is Hydra, because of morphological, behavioral, reproductive (sexual and asexual), and biochemical changes. Many researchers have used Hydra for toxicity assessment of organic chemicals (BPA), heavy metals, pharmaceuticals, nanomaterials and microplastics. Various Hydra species were used for environmental toxicity studies; however H. magnipapillata was predominantly used due to the availability of its genome and proteome sequences. Teratogenic and reproductive changes in Hydra are species specific. Teratogenic effects were studied using sterozoom dissecting microscope, acridine orange (AO) and 4',6-diamidino-2-phenylindole (DPAI) staining. Reactive oxygen species (ROS) generation by EPs had been understood by the Dichlorodihydrofluorescein Diacetate (DCFDA) staining and comet assay. Multiple advanced techniques would aid to understand the effects at molecular level, such as real-time PCR, rapid amplification of cDNA end- PCR. EPs modulated the major antioxidant enzyme levels, therefore, defense mechanism was affected by the higher generation of reactive oxygen species. Genome sequencing helps to know the mode of action of pollutants, role of enzymes in detoxification, defense genes and stress responsive genes. Molecular techniques were used to obtain the information for evolutionary changes of genes and modulation of gene expression by EPs.

In vivo lensless microscopy via a phase mask generating diffraction patterns with high-contrast contours

The simple and compact optics of lensless microscopes and the associated computational algorithms allow for large fields of view and the refocusing of the captured images. However, existing lensless techniques cannot accurately reconstruct the typical low-contrast images of optically dense biological tissue. Here we show that lensless imaging of tissue in vivo can be achieved via an optical phase mask designed to create a point spread function consisting of high-contrast contours with a broad spectrum of spatial frequencies. We built a prototype lensless microscope incorporating the 'contour' phase mask and used it to image calcium dynamics in the cortex of live mice (over a field of view of about 16 mm2) and in freely moving Hydra vulgaris, as well as microvasculature in the oral mucosa of volunteers. The low cost, small form factor and computational refocusing capability of in vivo lensless microscopy may open it up to clinical uses, especially for imaging difficult-to-reach areas of the body.

Imaging whole-brain activity to understand behavior

The brain evolved to produce behaviors that help an animal inhabit the natural world. During natural behaviors, the brain is engaged in many levels of activity from the detection of sensory inputs to decision-making to motor planning and execution. To date, most brain studies have focused on small numbers of neurons that interact in limited circuits. This allows analyzing individual computations or steps of neural processing. During behavior, however, brain activity must integrate multiple circuits in different brain regions. The activities of different brain regions are not isolated, but may be contingent on one another. Coordinated and concurrent activity within and across brain areas is organized by (1) sensory information from the environment, (2) the animal's internal behavioral state, and (3) recurrent networks of synaptic and non-synaptic connectivity. Whole-brain recording with cellular resolution provides a new opportunity to dissect the neural basis of behavior, but whole-brain activity is also mutually contingent on behavior itself. This is especially true for natural behaviors like navigation, mating, or hunting, which require dynamic interaction between the animal, its environment, and other animals. In such behaviors, the sensory experience of an unrestrained animal is actively shaped by its movements and decisions. Many of the signaling and feedback pathways that an animal uses to guide behavior only occur in freely moving animals. Recent technological advances have enabled whole-brain recording in small behaving animals including nematodes, flies, and zebrafish. These whole-brain experiments capture neural activity with cellular resolution spanning sensory, decision-making, and motor circuits, and thereby demand new theoretical approaches that integrate brain dynamics with behavioral dynamics. Here, we review the experimental and theoretical methods that are being employed to understand animal behavior and whole-brain activity, and the opportunities for physics to contribute to this emerging field of systems neuroscience.

Naturalising Agent Causation

The idea of agent causation—that a system such as a living organism can be a cause of things in the world—is often seen as mysterious and deemed to be at odds with the physicalist thesis that is now commonly embraced in science and philosophy. Instead, the causal power of organisms is attributed to mechanistic components within the system or derived from the causal activity at the lowest level of physical description. In either case, the ‘agent’ itself (i.e., the system as a whole) is left out of the picture entirely, and agent causation is explained away. We argue that this is not the right way to think about causation in biology or in systems more generally. We present a framework of eight criteria that we argue, collectively, describe a system that overcomes the challenges concerning agent causality in an entirely naturalistic and non-mysterious way. They are: (1) thermodynamic autonomy, (2) persistence, (3) endogenous activity, (4) holistic integration, (5) low-level indeterminacy, (6) multiple realisability, (7) historicity, (8) agent-level normativity. Each criterion is taken to be dimensional rather than categorical, and thus we conclude with a short discussion on how researchers working on quantifying agency may use this multidimensional framework to situate and guide their research.

The Brain Observatory Storage Service and Database (BossDB): A Cloud-Native Approach for Petascale Neuroscience Discovery

Technological advances in imaging and data acquisition are leading to the development of petabyte-scale neuroscience image datasets. These large-scale volumetric datasets pose unique challenges since analyses often span the entire volume, requiring a unified platform to access it. In this paper, we describe the Brain Observatory Storage Service and Database (BossDB), a cloud-based solution for storing and accessing petascale image datasets. BossDB provides support for data ingest, storage, visualization, and sharing through a RESTful Application Programming Interface (API). A key feature is the scalable indexing of spatial data and automatic and manual annotations to facilitate data discovery. Our project is open source and can be easily and cost effectively used for a variety of modalities and applications, and has effectively worked with datasets over a petabyte in size.

The Aquatic Invertebrate Hydra vulgaris Releases Molecular Messages Through Extracellular Vesicles

Recent body of evidence demonstrates that extracellular vesicles (EVs) represent the first language of cell-cell communication emerged during evolution. In aquatic environments, transferring signals between cells by EVs offers protection against degradation, allowing delivering of chemical information in high local concentrations to the target cells. The packaging of multiple signals, including those of hydrophobic nature, ensures target cells to receive the same EV-conveyed messages, and the coordination of a variety of physiological processes across cells of a single organisms, or at the population level, i.e., mediating the population’s response to changing environmental conditions. Here, we purified EVs from the medium of the freshwater invertebrate Hydra vulgaris, and the molecular profiling by proteomic and transcriptomic analyses revealed multiple markers of the exosome EV subtype, from structural proteins to stress induced messages promoting cell survival. Moreover, positive and negative regulators of the Wnt/β-catenin signaling pathway, the major developmental pathway acting in body axial patterning, were identified. Functional analysis on amputated polyps revealed EV ability to modulate both head and foot regeneration, suggesting bioactivity of the EV cargo and opening new perspectives on the mechanisms of developmental signalling. Our results open the path to unravel EV biogenesis and function in all cnidarian species, tracing back the origin of the cell-cell, cross-species or cross-kingdom communication in aquatic ecosystems.

Characterisation of geometric variance in the epithelial nerve net of the ctenophore Pleurobrachia pileus

Neuroscience lacks a diverse repertoire of model organisms, resulting in an incomplete understanding into the general principles of neural function. Ctenophores display many neurobiological and experimental features which make them a promising candidate to fill this gap. They possess a nerve net distributed across their body surface, in the epithelial layer. There is a long-held assumption that nerve nets are 'simple' and lack distinct organisational principles. We want to challenge this assumption and determine how stereotyped the structure of this network is. We estimated body surface area in Pleurobrachia pileus using custom Optical Projection Tomography and Light Sheet Morphometry imaging systems. Using an antibody against tyrosinated α-tubulin we visualised the nerve net in situ and quantified the geometric properties using an automated segmentation approach. We characterised organisational rules of the epithelial nerve net in animals of different sizes and at different regions of the body. We found that specific morphological features within the nerve net are largely unchanged during growth. These properties must be essential to the functionality of the nervous system and therefore are maintained during a change in body size. We have also established the principles of organisation of the network and showed that some of the geometric properties are variable across different parts of the body. This suggests that there may be different functions occurring in regions with different structural characteristics. This is the most comprehensive structural description of a ctenophore nerve net to date and demonstrates the amenability of P. pileus for whole organism network analysis. This article is protected by copyright. All rights reserved.

Seamless integration of bioelectronic interface in an animal model via in vivo polymerization of conjugated oligomers

Leveraging the biocatalytic machinery of living organisms for fabricating functional bioelectronic interfaces, in vivo, defines a new class of micro-biohybrids enabling the seamless integration of technology with living biological systems. Previously, we have demonstrated the in vivo polymerization of conjugated oligomers forming conductors within the structures of plants. Here, we expand this concept by reporting that Hydra, an invertebrate animal, polymerizes the conjugated oligomer ETE-S both within cells that expresses peroxidase activity and within the adhesive material that is secreted to promote underwater surface adhesion. The resulting conjugated polymer forms electronically conducting and electrochemically active μm-sized domains, which are inter-connected resulting in percolative conduction pathways extending beyond 100 μm, that are fully integrated within the Hydra tissue and the secreted mucus. Furthermore, the introduction and in vivo polymerization of ETE-S can be used as a biochemical marker to follow the dynamics of Hydra budding (reproduction) and regeneration. This work paves the way for well-defined self-organized electronics in animal tissue to modulate biological functions and in vivo biofabrication of hybrid functional materials and devices.

A genetically tractable jellyfish model for systems and evolutionary neuroscience

Jellyfish are radially symmetric organisms without a brain that arose more than 500 million years ago. They achieve organismal behaviors through coordinated interactions between autonomously functioning body parts. Jellyfish neurons have been studied electrophysiologically, but not at the systems level. We introduce Clytia hemisphaerica as a transparent, genetically tractable jellyfish model for systems and evolutionary neuroscience. We generate stable F1 transgenic lines for cell-type-specific conditional ablation and whole-organism GCaMP imaging. Using these tools and computational analyses, we find that an apparently diffuse network of RFamide-expressing umbrellar neurons is functionally subdivided into a series of spatially localized subassemblies whose synchronous activation controls directional food transfer from the tentacles to the mouth. These data reveal an unanticipated degree of structured neural organization in this species. Clytia affords a platform for systems-level studies of neural function, behavior, and evolution within a clade of marine organisms with growing ecological and economic importance.

Internal State: Dynamic, Interconnected Communication Loops Distributed Across Body, Brain, and Time

Internal state profoundly alters perception and behavior. For example, a starved fly may approach and consume foods that it would otherwise find undesirable. A socially engaged newt may remain engaged in the presence of a predator, whereas a solitary newt would otherwise attempt to escape. Yet, the definition of internal state is fluid and ill-defined. As an interdisciplinary group of scholars spanning five career stages (from undergraduate to full professor) and six academic institutions, we came together in an attempt to provide an operational definition of internal state that could be useful in understanding the behavior and the function of nervous systems, at timescales relevant to the individual. In this perspective, we propose to define internal state through an integrative framework centered on dynamic and interconnected communication loops within and between the body and the brain. This framework is informed by a synthesis of historical and contemporary paradigms used by neurobiologists, ethologists, physiologists, and endocrinologists. We view internal state as composed of both spatially distributed networks (body-brain communication loops), and temporally distributed mechanisms that weave together neural circuits, physiology, and behavior. Given the wide spatial and temporal scales at which internal state operates-and therefore the broad range of scales at which it could be defined-we choose to anchor our definition in the body. Here we focus on studies that highlight body-to-brain signaling; body represented in endocrine signaling, and brain represented in sensory signaling. This integrative framework of internal state potentially unites the disparate paradigms often used by scientists grappling with body-brain interactions. We invite others to join us as we examine approaches and question assumptions to study the underlying mechanisms and temporal dynamics of internal state.

Tracking calcium dynamics from individual neurons in behaving animals

Measuring the activity of neuronal populations with calcium imaging can capture emergent functional properties of neuronal circuits with single cell resolution. However, the motion of freely behaving animals, together with the intermittent detectability of calcium sensors, can hinder automatic monitoring of neuronal activity and their subsequent functional characterization. We report the development and open-source implementation of a multi-step cellular tracking algorithm (Elastic Motion Correction and Concatenation or EMC2) that compensates for the intermittent disappearance of moving neurons by integrating local deformation information from detectable neurons. We demonstrate the accuracy and versatility of our algorithm using calcium imaging data from two-photon volumetric microscopy in visual cortex of awake mice, and from confocal microscopy in behaving Hydra, which experiences major body deformation during its contractions. We quantify the performance of our algorithm using ground truth manual tracking of neurons, along with synthetic time-lapse sequences, covering a wide range of particle motions and detectability parameters. As a demonstration of the utility of the algorithm, we monitor for several days calcium activity of the same neurons in layer 2/3 of mouse visual cortex in vivo, finding significant turnover within the active neurons across days, with only few neurons that remained active across days. Also, combining automatic tracking of single neuron activity with statistical clustering, we characterize and map neuronal ensembles in behaving Hydra, finding three major non-overlapping ensembles of neurons (CB, RP1 and RP2) whose activity correlates with contractions and elongations. Our results show that the EMC2 algorithm can be used as a robust and versatile platform for neuronal tracking in behaving animals.