Proprioceptive coupling within motor neurons drives C. elegans forward locomotion

Biophysical modeling and experimental analysis of the dynamics of C. elegans body-wall muscle cells

This study combines experimental techniques and mathematical modeling to investigate the dynamics of C. elegans body-wall muscle cells. Specifically, by conducting voltage clamp and mutant experiments, we identify key ion channels, particularly the L-type voltage-gated calcium channel (EGL-19) and potassium channels (SHK-1, SLO-2), which are crucial for generating action potentials. We develop Hodgkin-Huxley-based models for these channels and integrate them to capture the cells' electrical activity. To ensure the model accurately reflects cellular responses under depolarizing currents, we develop a parallel simulation-based inference method for determining the model's free parameters. This method performs rapid parallel sampling across high-dimensional parameter spaces, fitting the model to the responses of muscle cells to specific stimuli and yielding accurate parameter estimates. We validate our model by comparing its predictions against cellular responses to various current stimuli in experiments and show that our approach effectively determines suitable parameters for accurately modeling the dynamics in mutant cases. Additionally, we discover an optimal response frequency in body-wall muscle cells, which corresponds to a burst firing mode rather than regular firing mode. Our work provides the first experimentally constrained and biophysically detailed muscle cell model of C. elegans, and our analytical framework combined with robust and efficient parametric estimation method can be extended to model construction in other species.

Comprehensive analysis of the C. elegans connectome reveals novel circuits and functions of previously unstudied neurons

Despite decades of research on the Caenorhabditis elegans nervous system based on an anatomical description of synaptic connectivity, the circuits underlying behavior remain incompletely described and the functions of many neurons are still unknown. Updated and more complete chemical and gap junction connectomes of both adult sexes covering the entire animal including the muscle end organ have become available recently. Here, these are analyzed to gain insight into the overall structure of the connectivity network and to suggest functions of individual neuron classes. Modularity analysis divides the connectome graph into 10 communities that can be correlated with broad categories of behavior. A significant role of the body wall musculature end organ is emphasized as both a site of significant information convergence and as a source of sensory input in a feedback loop. Convergence of pathways for multisensory integration occurs throughout the network-most interneurons have similar indegrees and outdegrees and hence disperse information as much as they aggregate it. New insights include description of a set of high degree interneurons connected by many gap junctions running through the ventral cord that may represent a previously unrecognized locus of information processing. There is an apparent mechanosensory and proprioceptive field covering the entire body formed by connectivity of the many mechanosensory neurons of multiple types to 2 interneurons with output connections across the nervous system. Several additional significant, previously unrecognized circuits and pathways are uncovered, some involving unstudied neurons. The insights are valuable for guiding theoretical investigation of network properties as well as experimental studies of the functions of individual neurons, groups of neurons, and circuits.

An integrative data-driven model simulating C. elegans brain, body and environment interactions

The behavior of an organism is influenced by the complex interplay between its brain, body and environment. Existing data-driven models focus on either the brain or the body-environment. Here we present BAAIWorm, an integrative data-driven model of Caenorhabditis elegans, which consists of two submodels: the brain model and the body-environment model. The brain model was built by multicompartment models with realistic morphology, connectome and neural population dynamics based on experimental data. Simultaneously, the body-environment model used a lifelike body and a three-dimensional physical environment. Through the closed-loop interaction between the two submodels, BAAIWorm reproduced the realistic zigzag movement toward attractors observed in C. elegans. Leveraging this model, we investigated the impact of neural system structure on both neural activities and behaviors. Consequently, BAAIWorm can enhance our understanding of how the brain controls the body to interact with its surrounding environment.

Hierarchical behavior control by a single class of interneurons

Animal behavior is organized into nested temporal patterns that span multiple timescales. This behavior hierarchy is believed to arise from a hierarchical neural architecture: Neurons near the top of the hierarchy are involved in planning, selecting, initiating, and maintaining motor programs, whereas those near the bottom of the hierarchy act in concert to produce fine spatiotemporal motor activity. In Caenorhabditis elegans, behavior on a long timescale emerges from ordered and flexible transitions between different behavioral states, such as forward, reversal, and turn. On a short timescale, different parts of the animal body coordinate fast rhythmic bending sequences to produce directional movements. Here, we show that Sublateral Anterior A (SAA), a class of interneurons that enable cross-communication between dorsal and ventral head motor neurons, play a dual role in shaping behavioral dynamics on different timescales. On a short timescale, SAA regulate and stabilize rhythmic bending activity during forward movements. On a long timescale, the same neurons suppress spontaneous reversals and facilitate reversal termination by inhibiting Ring Interneuron M (RIM), an integrating neuron that helps maintain a behavioral state. These results suggest that feedback from a lower-level cell assembly to a higher-level command center is essential for bridging behavioral dynamics at different levels.

Peripheral cranio-spinal nerve communication for trapezius muscle control using axonal profiling through immunostaining

Accessory nerve (CNXI) has been known to be the primary conduit for motor control of the trapezius, while the supplementary cervical nerves (C3 and C4) are responsible for processing sensory information from muscle. However, the lack of substantial direct evidence has led to these conclusions being regarded as mere speculation. This study used immunostaining (using antibodies against neurofilament 200 for all axons, choline acetyltransferase for cholinergic axons, tyrosine hydroxylase for sympathetic axons, and alpha 3 sodium potassium ATPase for proprioceptive afferent axons) of human samples to verify the functional contributions of nerves. Study highlights the pivotal role of C3 and C4 in regulating precise movements of trapezius, contributing to motor control, proprioceptive feedback, and sympathetic modulation. CNXI is composed primarily of somatic efferent fibers, with significant numbers of sympathetic or sensory fibers. Furthermore, C3-4 have both cholinergic and non-cholinergic axons, suggesting their involvement in proprioceptive feedback and somatic efferent functions. Although less common, mechanosensors such as nociceptive sensor and sympathetic fibers are also supplied by these cervical nerves. The study demonstrated that these nerves contain motor fibers and significant proprioceptive and sympathetic axons, challenging the long-held notion that CNXI are motor and upper spinal nerves are sensory.

Segmentation-free measurement of locomotor frequency in Caenorhabditis elegans using image invariants

An animal's locomotor rate is an important indicator of its motility. In studies of the nematode Caenorhabditis elegans (C. elegans), assays of the frequency of body bending waves have often been used to discern the effects of mutations, drugs, or aging. Traditional manual methods for measuring locomotor frequency are low in throughput and subject to human error. Most current automated methods depend on image segmentation, which requires high image quality and is prone to errors. Here, we describe an algorithm for automated estimation of C. elegans locomotor frequency using image invariants, i.e. shape-based parameters that are independent of object translation, rotation, and scaling. For each video frame, the method calculates a combination of 8 Hu's moment invariants and a set of maximally stable extremal regions (MSER) invariants. The algorithm then calculates the locomotor frequency by computing the autocorrelation of the time sequence of the invariant ensemble. Results of our method show excellent agreement with manual or segmentation-based results over a wide range of frequencies. We show that compared to a segmentation-based method that analyzes a worm's shape and a method based on video covariance, our technique is more robust to low image quality and background noise. We demonstrate the system's capabilities by testing the effects of serotonin and serotonin pathway mutations on C. elegans locomotor frequency.

Track-A-Worm 2.0: A Software Suite for Quantifying Properties of C. elegans Locomotion, Bending, Sleep, and Action Potentials

Comparative analyses of locomotor behavior and cellular electrical properties between wild-type and mutant C. elegans are crucial for exploring the gene basis of behaviors and the underlying cellular mechanisms. Although many tools have been developed by research labs and companies, their application is often hindered by implementation difficulties or lack of features specifically suited for C. elegans. Track-A-Worm 2.0 addresses these challenges with three key components: WormTracker, SleepTracker, and Action Potential (AP) Analyzer. WormTracker accurately quantifies a comprehensive set of locomotor and body bending metrics, reliably distinguish between the ventral and dorsal sides, continuously tracks the animal using a motorized stage, and seamlessly integrates external devices, such as a light source for optogenetic stimulation. SleepTracker detects and quantifies sleep-like behavior in freely moving animals. AP Analyzer assesses the resting membrane potential, afterhyperpolarization level, and various AP properties, including threshold, amplitude, mid-peak width, rise and decay times, and maximum and minimum slopes. Importantly, it addresses the challenge of AP threshold quantification posed by the absence of a pre-upstroke inflection point. Track-A-Worm 2.0 is potentially a valuable tool for many C. elegans research labs due to its powerful functionality and ease of implementation.

Symmetries and synchronization from whole-neural activity in C. elegans connectome: Integration of functional and structural networks

Understanding the dynamical behavior of complex systems from their underlying network architectures is a long-standing question in complexity theory. Therefore, many metrics have been devised to extract network features like motifs, centrality, and modularity measures. It has previously been proposed that network symmetries are of particular importance since they are expected to underly the synchronization of a system's units, which is ubiquitously observed in nervous system activity patterns. However, perfectly symmetrical structures are difficult to assess in noisy measurements of biological systems, like neuronal connectomes. Here, we devise a principled method to infer network symmetries from combined connectome and neuronal activity data. Using nervous system-wide population activity recordings of the C.elegans backward locomotor system, we infer structures in the connectome called fibration symmetries, which can explain which group of neurons synchronize their activity. Our analysis suggests functional building blocks in the animal's motor periphery, providing new testable hypotheses on how descending interneuron circuits communicate with the motor periphery to control behavior. Our approach opens a new door to exploring the structure-function relations in other complex systems, like the nervous systems of larger animals.

Segmentation-free measurement of locomotor frequency in Caenorhabditis elegans using image invariants

An animal's locomotor rate is an important indicator of its motility. In studies of the nematode C. elegans, assays of the frequency of body bending waves have often been used to discern the effects of mutations, drugs, or aging. Traditional manual methods for measuring locomotor frequency are low in throughput and subject to human error. Most current automated methods depend on image segmentation, which requires high image quality and is prone to errors. Here, we describe an algorithm for automated estimation of C. elegans locomotor frequency using image invariants, i.e., shape-based parameters that are independent of object translation, rotation, and scaling. For each video frame, the method calculates a combination of 8 Hu's moment invariants and a set of Maximally Stable Extremal Regions (MSER) invariants. The algorithm then calculates the locomotor frequency by computing the autocorrelation of the time sequence of the invariant ensemble. Results of our method show excellent agreement with manual or segmentation-based results over a wide range of frequencies. We show that compared to a segmentation-based method that analyzes a worm's shape and a method based on video covariance, our technique is more robust to low image quality and background noise. We demonstrate the system's capabilities by testing the effects of serotonin and serotonin pathway mutations on C. elegans locomotor frequency.

C. elegans foraging as a model for understanding the neuronal basis of decision-making

Animals have evolved to seek, select, and exploit food sources in their environment. Collectively termed foraging, these ubiquitous behaviors are necessary for animal survival. As a foundation for understanding foraging, behavioral ecologists established early theoretical and mathematical frameworks which have been subsequently refined and supported by field and laboratory studies of foraging animals. These simple models sought to explain how animals decide which strategies to employ when locating food, what food items to consume, and when to explore the environment for new food sources. These foraging decisions involve integration of prior experience with multimodal sensory information about the animal's current environment and internal state. We suggest that the nematode Caenorhabditis elegans is well-suited for a high-resolution analysis of complex goal-oriented behaviors such as foraging. We focus our discussion on behavioral studies highlighting C. elegans foraging on bacteria and summarize what is known about the underlying neuronal and molecular pathways. Broadly, we suggest that this simple model system can provide a mechanistic understanding of decision-making and present additional avenues for advancing our understanding of complex behavioral processes.

Can repetitive mechanical motion cause structural damage to axons?

Biological structures have evolved to very efficiently generate, transmit, and withstand mechanical forces. These biological examples have inspired mechanical engineers for centuries and led to the development of critical insights and concepts. However, progress in mechanical engineering also raises new questions about biological structures. The past decades have seen the increasing study of failure of engineered structures due to repetitive loading, and its origin in processes such as materials fatigue. Repetitive loading is also experienced by some neurons, for example in the peripheral nervous system. This perspective, after briefly introducing the engineering concept of mechanical fatigue, aims to discuss the potential effects based on our knowledge of cellular responses to mechanical stresses. A particular focus of our discussion are the effects of mechanical stress on axons and their cytoskeletal structures. Furthermore, we highlight the difficulty of imaging these structures and the promise of new microscopy techniques. The identification of repair mechanisms and paradigms underlying long-term stability is an exciting and emerging topic in biology as well as a potential source of inspiration for engineers.

Innate Orientating Behavior of a Multi-Legged Robot Driven by the Neural Circuits of C. elegans

The objective of this research is to achieve biologically autonomous control by utilizing a whole-brain network model, drawing inspiration from biological neural networks to enhance the development of bionic intelligence. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of the cellular synapses. The neural network simulation integrates computational programming and the visualization of the neurons and synapse connections of C. elegans, containing the specific controllable circuits and their dynamic characteristics. To illustrate the biological neural network (BNN)'s particular intelligent control capability, we introduced an innovative methodology for applying the BNN model to a 12-legged robot's movement control. Two methods were designed, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of the BNN. Both the simulation and experimental results indicate that the robot exhibits more autonomy and a more intelligent movement performance under BNN control. The systematic approach of employing the whole-brain BNN for robot control provides biomimetic research with a framework that has been substantiated by innovative methodologies and validated through the observed positive outcomes. This method is established as follows: (1) two integrated dynamic models of the C. elegans' whole-brain network and the robot moving dynamics are built, and all of the controllable circuits are discovered and verified; (2) real-time communication is achieved between the BNN model and the robot's dynamical model, both in the simulation and the experiments, including applicable encoding and decoding algorithms, facilitating their collaborative operation; (3) the designed mechanisms using the BNN model to control the robot are shown to be effective through numerical and experimental tests, focusing on 'foraging' behavior control and locomotion control.

Synaptic architecture of leg and wing premotor control networks in Drosophila

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles. MN activity is coordinated by complex premotor networks that allow individual muscles to contribute to many different behaviors. Here, we use connectomics to analyze the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. In contrast, wing premotor networks lack proportional synaptic connectivity, which may allow wing steering muscles to be recruited with different relative timing. By comparing the architecture of distinct limb motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

FUNCTIONS OF C. ELEGANS NEURONS FROM SYNAPTIC CONNECTIVITY

Despite decades of research on the C. elegans nervous system based on an anatomical description of synaptic connectivity, the circuits underlying behavior remain incompletely described and the functions of many neurons are still unknown. Updated and more complete chemical and gap junction connectomes of both adult sexes covering the entire animal including the muscle end organ have become available recently. Here these are analyzed to gain insight into the overall structure of the connectivity network and to suggest functions of individual neuron classes. Modularity analysis divides the connectome graph into ten communities that can be correlated with broad categories of behavior. A significant role of the body wall musculature end organ is emphasized as both a site of significant information convergence and as a source of sensory input in a feedback loop. Convergence of pathways for multisensory integration occurs throughout the network - most interneurons have similar indegrees and outdegrees and hence disperse information as much as they aggregate it. New insights include description of a set of high degree interneurons connected by many gap junctions running through the ventral cord that may represent a previously unrecognized locus of information processing. There is an apparent mechanosensory and proprioceptive field covering the entire body formed by connectivity of the many mechanosensory neurons of multiple types to two interneurons with output connections across the nervous system. Several additional significant, previously unrecognized circuits and pathways are uncovered, some involving unstudied neurons. The insights are valuable for guiding theoretical investigation of network properties as well as experimental studies of the functions of individual neurons, groups of neurons, and circuits.

Biophysical modeling of the whole-cell dynamics of C. elegans motor and interneurons families

The nematode Caenorhabditis elegans is a widely used model organism for neuroscience. Although its nervous system has been fully reconstructed, the physiological bases of single-neuron functioning are still poorly explored. Recently, many efforts have been dedicated to measuring signals from C. elegans neurons, revealing a rich repertoire of dynamics, including bistable responses, graded responses, and action potentials. Still, biophysical models able to reproduce such a broad range of electrical responses lack. Realistic electrophysiological descriptions started to be developed only recently, merging gene expression data with electrophysiological recordings, but with a large variety of cells yet to be modeled. In this work, we contribute to filling this gap by providing biophysically accurate models of six classes of C. elegans neurons, the AIY, RIM, and AVA interneurons, and the VA, VB, and VD motor neurons. We test our models by comparing computational and experimental time series and simulate knockout neurons, to identify the biophysical mechanisms at the basis of inter and motor neuron functioning. Our models represent a step forward toward the modeling of C. elegans neuronal networks and virtual experiments on the nematode nervous system.

A molecular atlas of adult C. elegans motor neurons reveals ancient diversity delineated by conserved transcription factor codes

Motor neurons (MNs) constitute an ancient cell type targeted by multiple adult-onset diseases. It is therefore important to define the molecular makeup of adult MNs in animal models and extract organizing principles. Here, we generate a comprehensive molecular atlas of adult Caenorhabditis elegans MNs and a searchable database. Single-cell RNA sequencing of 13,200 cells reveals that ventral nerve cord MNs cluster into 29 molecularly distinct subclasses. Extending C. elegans Neuronal Gene Expression Map and Network (CeNGEN) findings, all MN subclasses are delineated by distinct expression codes of either neuropeptide or transcription factor gene families. Strikingly, combinatorial codes of homeodomain transcription factor genes succinctly delineate adult MN diversity in both C. elegans and mice. Further, molecularly defined MN subclasses in C. elegans display distinct patterns of connectivity. Hence, our study couples the connectivity map of the C. elegans motor circuit with a molecular atlas of its constituent MNs and uncovers organizing principles and conserved molecular codes of adult MN diversity.

The neuropeptidergic connectome of C. elegans

Efforts are ongoing to map synaptic wiring diagrams, or connectomes, to understand the neural basis of brain function. However, chemical synapses represent only one type of functionally important neuronal connection; in particular, extrasynaptic, "wireless" signaling by neuropeptides is widespread and plays essential roles in all nervous systems. By integrating single-cell anatomical and gene-expression datasets with biochemical analysis of receptor-ligand interactions, we have generated a draft connectome of neuropeptide signaling in the C. elegans nervous system. This network is characterized by high connection density, extended signaling cascades, autocrine foci, and a decentralized topology, with a large, highly interconnected core containing three constituent communities sharing similar patterns of input connectivity. Intriguingly, several key network hubs are little-studied neurons that appear specialized for peptidergic neuromodulation. We anticipate that the C. elegans neuropeptidergic connectome will serve as a prototype to understand how networks of neuromodulatory signaling are organized.

A molecular atlas of adult C. elegans motor neurons reveals ancient diversity delineated by conserved transcription factor codes

Motor neurons (MNs) constitute an ancient cell type targeted by multiple adult-onset diseases. It is therefore important to define the molecular makeup of adult MNs in animal models and extract organizing principles. Here, we generated a comprehensive molecular atlas of adult Caenorhabditis elegans MNs and a searchable database (http://celegans.spinalcordatlas.org). Single-cell RNA-sequencing of 13,200 cells revealed that ventral nerve cord MNs cluster into 29 molecularly distinct subclasses. All subclasses are delineated by unique expression codes of either neuropeptide or transcription factor gene families. Strikingly, we found that combinatorial codes of homeodomain transcription factor genes define adult MN diversity both in C. elegans and mice. Further, molecularly defined MN subclasses in C. elegans display distinct patterns of connectivity. Hence, our study couples the connectivity map of the C. elegans motor circuit with a molecular atlas of its constituent MNs, and uncovers organizing principles and conserved molecular codes of adult MN diversity.

Locomotion modulates olfactory learning through proprioception in C. elegans

Locomotor activities can enhance learning, but the underlying circuit and synaptic mechanisms are largely unknown. Here we show that locomotion facilitates aversive olfactory learning in C. elegans by activating mechanoreceptors in motor neurons, and transmitting the proprioceptive information thus generated to locomotion interneurons through antidromic-rectifying gap junctions. The proprioceptive information serves to regulate experience-dependent activities and functional coupling of interneurons that process olfactory sensory information to produce the learning behavior. Genetic destruction of either the mechanoreceptors in motor neurons, the rectifying gap junctions between the motor neurons and locomotion interneurons, or specific inhibitory synapses among the interneurons impairs the aversive olfactory learning. We have thus uncovered an unexpected role of proprioception in a specific learning behavior as well as the circuit, synaptic, and gene bases for this function.

The Conscious Nematode: Exploring Hallmarks of Minimal Phenomenal Consciousness in Caenorhabditis Elegans

While subcellular components of cognition and affectivity that involve the interaction between experience, environment, and physiology -such as learning, trauma, or emotion- are being identified, the physical mechanisms of phenomenal consciousness remain more elusive. We are interested in exploring whether ancient, simpler organisms such as nematodes have minimal consciousness. Is there something that feels like to be a worm? Or are worms blind machines? 'Simpler' models allow us to simultaneously extract data from multiple levels such as slow and fast neural dynamics, structural connectivity, molecular dynamics, behavior, decision making, etc., and thus, to test predictions of the current frameworks in dispute. In the present critical review, we summarize the current models of consciousness in order to reassess in light of the new evidence whether Caenorhabditis elegans, a nematode with a nervous system composed of 302 neurons, has minimal consciousness. We also suggest empirical paths to further advance consciousness research using C. elegans.

SAMPL is a high-throughput solution to study unconstrained vertical behavior in small animals

Balance and movement are impaired in many neurological disorders. Recent advances in behavioral monitoring provide unprecedented access to posture and locomotor kinematics but without the throughput and scalability necessary to screen candidate genes/potential therapeutics. Here, we present a scalable apparatus to measure posture and locomotion (SAMPL). SAMPL includes extensible hardware and open-source software with real-time processing and can acquire data from D. melanogaster, C. elegans, and D. rerio as they move vertically. Using SAMPL, we define how zebrafish balance as they navigate vertically and discover small but systematic variations among kinematic parameters between genetic backgrounds. We demonstrate SAMPL's ability to resolve differences in posture and navigation as a function of effect size and data gathered, providing key data for screens. SAMPL is therefore both a tool to model balance and locomotor disorders and an exemplar of how to scale apparatus to support screens.

A proprioceptive feedback circuit drives Caenorhabditis elegans locomotor adaptation through dopamine signaling

An animal adapts its motor behavior to navigate the external environment. This adaptation depends on proprioception, which provides feedback on an animal's body postures. How proprioception mechanisms interact with motor circuits and contribute to locomotor adaptation remains unclear. Here, we describe and characterize proprioception-mediated homeostatic control of undulatory movement in the roundworm Caenorhabditis elegans. We found that the worm responds to optogenetically or mechanically induced decreases in midbody bending amplitude by increasing its anterior amplitude. Conversely, it responds to increased midbody amplitude by decreasing the anterior amplitude. Using genetics, microfluidic and optogenetic perturbation response analyses, and optical neurophysiology, we elucidated the neural circuit underlying this compensatory postural response. The dopaminergic PDE neurons proprioceptively sense midbody bending and signal to AVK interneurons via the D2-like dopamine receptor DOP-3. The FMRFamide-like neuropeptide FLP-1, released by AVK, regulates SMB head motor neurons to modulate anterior bending. We propose that this homeostatic behavioral control optimizes locomotor efficiency. Our findings demonstrate a mechanism in which proprioception works with dopamine and neuropeptide signaling to mediate motor control, a motif that may be conserved in other animals.

Automated recognition and analysis of body bending behavior in C. elegans

BACKGROUND

Locomotion behaviors of Caenorhabditis elegans play an important role in drug activity screening, anti-aging research, and toxicological assessment. Previous studies have provided important insights into drug activity screening, anti-aging, and toxicological research by manually counting the number of body bends. However, manual counting is often low-throughput and takes a lot of time and manpower. And it is easy to cause artificial bias and error in counting results.

RESULTS

In this paper, an algorithm is proposed for automatic counting and analysis of the body bending behavior of nematodes. First of all, the numerical coordinate regression method with convolutional neural network is used to obtain the head and tail coordinates. Next, curvature-based feature point extraction algorithm is used to calculate the feature points of the nematode centerline. Then the maximum distance between the peak point and the straight line between the pharynx and the tail is calculated. The number of body bends is counted according to the change in the maximum distance per frame.

CONCLUSION

Experiments are performed to prove the effectiveness of the proposed algorithm. The accuracy of head coordinate prediction is 0.993, and the accuracy of tail coordinate prediction is 0.990. The Pearson correlation coefficient between the results of the automatic count and manual count of the number of body bends is 0.998 and the mean absolute error is 1.931. Different strains of nematodes are selected to analyze differences in body bending behavior, demonstrating a relationship between nematode vitality and lifespan. The code is freely available at https://github.com/hthana/Body-Bend-Count .

Scalable Apparatus to Measure Posture and Locomotion (SAMPL): a high-throughput solution to study unconstrained vertical behavior in small animals

Balance and movement are impaired in a wide variety of neurological disorders. Recent advances in behavioral monitoring provide unprecedented access to posture and locomotor kinematics, but without the throughput and scalability necessary to screen candidate genes / potential therapeutics. We present a powerful solution: a Scalable Apparatus to Measure Posture and Locomotion (SAMPL). SAMPL includes extensible imaging hardware and low-cost open-source acquisition software with real-time processing. We first demonstrate that SAMPL's hardware and acquisition software can acquire data from from D. melanogaster, C. elegans, and D. rerio as they move vertically. Next, we leverage SAMPL's throughput to rapidly (two weeks) gather a new zebrafish dataset. We use SAMPL's analysis and visualization tools to replicate and extend our current understanding of how zebrafish balance as they navigate through a vertical environment. Next, we discover (1) that key kinematic parameters vary systematically with genetic background, and (2) that such background variation is small relative to the changes that accompany early development. Finally, we simulate SAMPL's ability to resolve differences in posture or vertical navigation as a function of affect size and data gathered -- key data for screens. Taken together, our apparatus, data, and analysis provide a powerful solution for labs using small animals to investigate balance and locomotor disorders at scale. More broadly, SAMPL is both an adaptable resource for labs looking process videographic measures of behavior in real-time, and an exemplar of how to scale hardware to enable the throughput necessary for screening.

Visualizing Neurons Under Tension In Vivo with Optogenetic Molecular Force Sensors

The visualization of mechanical stress distribution in specific molecular networks within a living and physiologically active cell or animal remains a formidable challenge in mechanobiology. The advent of fluorescence-resonance energy transfer (FRET)-based molecular tension sensors overcame a significant hurdle that now enables us to address previously technically limited questions. Here, we describe a method that uses genetically encoded FRET tension sensors to visualize the mechanics of cytoskeletal networks in neurons of living animals with sensitized emission FRET and confocal scanning light microscopy. This method uses noninvasive immobilization of living animals to image neuronal β-spectrin cytoskeleton at the diffraction limit, and leverages multiple imaging controls to verify and underline the quality of the measurements. In combination with a semiautomated machine-vision algorithm to identify and trace individual neurites, our analysis performs simultaneous calculation of FRET efficiencies and visualizes statistical uncertainty on a pixel by pixel basis. Our approach is not limited to genetically encoded spectrin tension sensors, but can also be used for any kind of ratiometric imaging in neuronal cells both in vivo and in vitro.

Axonal plasticity in response to active forces generated through magnetic nano-pulling

Mechanical force is crucial in guiding axon outgrowth before and after synapse formation. This process is referred to as "stretch growth." However, how neurons transduce mechanical input into signaling pathways remains poorly understood. Another open question is how stretch growth is coupled in time with the intercalated addition of new mass along the entire axon. Here, we demonstrate that active mechanical force generated by magnetic nano-pulling induces remodeling of the axonal cytoskeleton. Specifically, the increase in the axonal density of microtubules induced by nano-pulling leads to an accumulation of organelles and signaling vesicles, which, in turn, promotes local translation by increasing the probability of assembly of the "translation factories." Modulation of axonal transport and local translation sustains enhanced axon outgrowth and synapse maturation.

Fluid circulation driven by collectively organized metachronal waves in swimming T. aceti nematodes

Recent experiments have shown that the nematode T. aceti can assemble into collectively undulating groups at the edge of fluid drops. This coordinated state consists of metachronal waves and drives fluid circulation inside the drop. We find that the circulation velocity is about 2 mm/s and nearly half the speed of the metachronal wave. We develop a quasi-two-dimensional hydrodynamics model using the Stokes flow approximation. The periodic motion of the nematodes constitute our moving boundary condition that drives the flow. Our model suggests that large-amplitude excursions of the nematode tails produce the fluid circulation. We discuss the constraints on containers that would enhance fluid motion, which could be used in the future design of on demand flow generating systems.

BAM15 Relieves Neurodegeneration in Aged Caenorhabditis elegans and Extends Lifespan

BAM15 was recently screened as a protonophore uncoupler specifically for the mitochondrial membrane but not the plasma membrane. It is equally as potent as FCCP, but less toxic. Previously, mitochondrial uncoupling via DNP alleviates neurodegeneration in the nematode Caenorhabditis elegans during aging. Therefore, we investigated whether BAM15 uncouplers could phenotypically and functionally reduce neuronal defects in aged nematodes. We observed green fluorescence protein-tagged mechanosensory neurons and performed touch and chemotaxis assays during aging. Wild-type animals treated with both 50 µM BAM15 and 10 µM DNP showed reduced mechanosensory neuronal defects during aging, which correlates with the maintenance of touch responses and short-term memory during aging. Uncoupler mutant ucp-4 also responded the same way as the wild-type, reducing neurodegeneration in 50 µM BAM15 and 10 µM DNP-treated animals compared to the DMSO control. These results suggest that 50 µM BAM15 alleviates neurodegeneration phenotypically and functionally in C. elegans during aging, potentially through mitochondrial uncoupling. In accordance with the preserved neuronal shape and function in aged C. elegans, 50 µM BAM15 extended the mean lifespan of both wild-type and ucp-4 mutants.

Neural Network-Based Autonomous Search Model with Undulatory Locomotion Inspired by Caenorhabditis Elegans

Caenorhabditis elegans (C. elegans) exhibits sophisticated chemotaxis behavior with a unique locomotion pattern using a simple nervous system only and is, therefore, well suited to inspire simple, cost-effective robotic navigation schemes. Chemotaxis in C. elegans involves two complementary strategies: klinokinesis, which allows reorientation by sharp turns when moving away from targets; and klinotaxis, which gradually adjusts the direction of motion toward the preferred side throughout the movement. In this study, we developed an autonomous search model with undulatory locomotion that combines these two C. elegans chemotaxis strategies with its body undulatory locomotion. To search for peaks in environmental variables such as chemical concentrations and radiation in directions close to the steepest gradients, only one sensor is needed. To develop our model, we first evolved a central pattern generator and designed a minimal network unit with proprioceptive feedback to encode and propagate rhythmic signals; hence, we realized realistic undulatory locomotion. We then constructed adaptive sensory neuron models following real electrophysiological characteristics and incorporated a state-dependent gating mechanism, enabling the model to execute the two orientation strategies simultaneously according to information from a single sensor. Simulation results verified the effectiveness, superiority, and realness of the model. Our simply structured model exploits multiple biological mechanisms to search for the shortest-path concentration peak over a wide range of gradients and can serve as a theoretical prototype for worm-like navigation robots.

Extrasynaptic signaling enables an asymmetric juvenile motor circuit to produce symmetric undulation

In many animals, there is a direct correspondence between the motor patterns that drive locomotion and the motor neuron innervation. For example, the adult C. elegans moves with symmetric and alternating dorsal-ventral bending waves arising from symmetric motor neuron input onto the dorsal and ventral muscles. In contrast to the adult, the C. elegans motor circuit at the juvenile larval stage has asymmetric wiring between motor neurons and muscles but still generates adult-like bending waves with dorsal-ventral symmetry. We show that in the juvenile circuit, wiring between excitatory and inhibitory motor neurons coordinates the contraction of dorsal muscles with relaxation of ventral muscles, producing dorsal bends. However, ventral bending is not driven by analogous wiring. Instead, ventral muscles are excited uniformly by premotor interneurons through extrasynaptic signaling. Ventral bends occur in anti-phasic entrainment to activity of the same motor neurons that drive dorsal bends. During maturation, the juvenile motor circuit is replaced by two motor subcircuits that separately drive dorsal and ventral bending. Modeling reveals that the juvenile's immature motor circuit is an adequate solution to generate adult-like dorsal-ventral bending before the animal matures. Developmental rewiring between functionally degenerate circuit solutions, which both generate symmetric bending patterns, minimizes behavioral disruption across maturation.

Multisensory Integration in Caenorhabditis elegans in Comparison to Mammals

Multisensory integration refers to sensory inputs from different sensory modalities being processed simultaneously to produce a unitary output. Surrounded by stimuli from multiple modalities, animals utilize multisensory integration to form a coherent and robust representation of the complex environment. Even though multisensory integration is fundamentally essential for animal life, our understanding of the underlying mechanisms, especially at the molecular, synaptic and circuit levels, remains poorly understood. The study of sensory perception in Caenorhabditis elegans has begun to fill this gap. We have gained a considerable amount of insight into the general principles of sensory neurobiology owing to C. elegans’ highly sensitive perceptions, relatively simple nervous system, ample genetic tools and completely mapped neural connectome. Many interesting paradigms of multisensory integration have been characterized in C. elegans, for which input convergence occurs at the sensory neuron or the interneuron level. In this narrative review, we describe some representative cases of multisensory integration in C. elegans, summarize the underlying mechanisms and compare them with those in mammalian systems. Despite the differences, we believe C. elegans is able to provide unique insights into how processing and integrating multisensory inputs can generate flexible and adaptive behaviors. With the emergence of whole brain imaging, the ability of C. elegans to monitor nearly the entire nervous system may be crucial for understanding the function of the brain as a whole.

A set of hub neurons and non-local connectivity features support global brain dynamics in C. elegans

The wiring architecture of neuronal networks is assumed to be a strong determinant of their dynamical computations. An ongoing effort in neuroscience is therefore to generate comprehensive synapse-resolution connectomes alongside brain-wide activity maps. However, the structure-function relationship, i.e., how the anatomical connectome and neuronal dynamics relate to each other on a global scale, remains unsolved. Systematically, comparing graph features in the C. elegans connectome with correlations in nervous system-wide neuronal dynamics, we found that few local connectivity motifs and mostly other non-local features such as triplet motifs and input similarities can predict functional relationships between neurons. Surprisingly, quantities such as connection strength and amount of common inputs do not improve these predictions, suggesting that the network's topology is sufficient. We demonstrate that hub neurons in the connectome are key to these relevant graph features. Consistently, inhibition of multiple hub neurons specifically disrupts brain-wide correlations. Thus, we propose that a set of hub neurons and non-local connectivity features provide an anatomical substrate for global brain dynamics.

Microfluidics for understanding model organisms

New microfluidic systems for whole organism analysis and experimentation are catalyzing biological breakthroughs across many fields, from human health to fundamental biology principles. This perspective discusses recent microfluidic tools to study intact model organisms to demonstrate the tremendous potential for these integrated approaches now and into the future. We describe these microsystems' technical features and highlight the unique advantages for precise manipulation in areas including immobilization, automated alignment, sorting, sensory, mechanical and chemical stimulation, and genetic and thermal perturbation. Our aim is to familiarize technologically focused researchers with microfluidics applications in biology research, while providing biologists an entrée to advanced microengineering techniques for model organisms.

A Graph Network Model for Neural Connection Prediction and Connection Strength Estimation

Objective. Reconstruction of connectomes at the cellular scale is a prerequisite for understanding the principles of neural circuits. However, due to methodological limits, scientists have reconstructed the connectomes of only a few organisms such as C. elegans, and estimated synaptic strength indirectly according to their size and number. Approach. Here, we propose a graph network model to predict synaptic connections and estimate synaptic strength by using the calcium activity data from C. elegans. Main results. The results show that this model can reliably predict synaptic connections in the neural circuits of C. elegans, and estimate their synaptic strength, which is an intricate and comprehensive reflection of multiple factors such as synaptic type and size, neurotransmitter and receptor type, and even activity dependence. In addition, the excitability or inhibition of synapses can be identified by this model. We also found that chemical synaptic strength is almost linearly positively correlated to electrical synaptic strength, and the influence of one neuron on another is non-linearly correlated with the number between them. This reflects the intrinsic interaction between electrical and chemical synapses. Significance. Our model is expected to provide a more accessible quantitative and data-driven approach for the reconstruction of connectomes in more complex nervous systems, as well as a promising method for accurately estimating synaptic strength.

Stearoyl-CoA desaturases sustain cholinergic excitation and copulatory robustness in metabolically aging C. elegansmales

Regulated metabolism is required for behaviors as adults age. To understand how lipid usage affects motor coordination, we studied male Caenorhabditis elegans copulation as a model of energy-intensive behavior. Copulation performance drops after 48 h of adulthood. We found that 12–24 h before behavioral decline, males prioritize exploring and copulation behavior over feeding, suggesting that catabolizing stored metabolites, such as lipids, occurs during this period. Because fat-6/7-encoded stearoyl-CoA desaturases are essential for converting the ingested fatty acids to lipid storage, we examined the copulation behavior and neural calcium transients of fat-6(lf); fat-7(lf) mutants. In wild-type males, intestinal and epithelial fat-6/7 expression increases during the first 48 h of adulthood. The fat-6(lf); fat-7(lf) behavioral and metabolic defects indicate that in aging wild-type males, the increased expression of stearoyl-CoA desaturases in the epidermis may indirectly modulate the levels of EAG-family K⁺ channels in the reproductive cholinergic neurons and muscles.

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Tissue distribution of fat-6-encoded stearoyl-CoA desaturase changes in adulthood

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Markov modeling shows reduced feeding linked with more exploring in day 2 males

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fat-6(lf); fat-7(lf) disrupted behavior can be rescued by epidermal FAT-6

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fat-6(lf); fat-7(lf) alters neural and muscular ERG and EAG K+ channel expression

Neural model generating klinotaxis behavior accompanied by a random walk based on C. elegans connectome

Klinotaxis is a strategy of chemotaxis behavior in Caenorhabditis elegans (C. elegans), and random walking is evident during its locomotion. As yet, the understanding of the neural mechanisms underlying these behaviors has remained limited. In this study, we present a connectome-based simulation model of C. elegans to concurrently realize realistic klinotaxis and random walk behaviors and explore their neural mechanisms. First, input to the model is derived from an ASE sensory neuron model in which the all-or-none depolarization characteristic of ASEL neuron is incorporated for the first time. Then, the neural network is evolved by an evolutionary algorithm; klinotaxis emerged spontaneously. We identify a plausible mechanism of klinotaxis in this model. Next, we propose the liquid synapse according to the stochastic nature of biological synapses and introduce it into the model. Adopting this, the random walk is generated autonomously by the neural network, providing a new hypothesis as to the neural mechanism underlying the random walk. Finally, simulated ablation results are fairly consistent with the biological conclusion, suggesting the similarity between our model and the biological network. Our study is a useful step forward in behavioral simulation and understanding the neural mechanisms of behaviors in C. elegans.

Reciprocal interactions between transforming growth factor beta signaling and collagens: Insights from Caenorhabditis elegans

Studies in genetically tractable organisms such as the nematode Caenorhabditis elegans have led to pioneering insights into conserved developmental regulatory mechanisms. For example, Smad signal transducers for the transforming growth factor beta (TGF-β) superfamily were first identified in C. elegans and in the fruit fly Drosophila. Recent studies of TGF-β signaling and the extracellular matrix (ECM) in C. elegans have forged unexpected links between signaling and the ECM, yielding novel insights into the reciprocal interactions that occur across tissues and spatial scales, and potentially providing new opportunities for the study of biomechanical regulation of gene expression.

A high-throughput method to deliver targeted optogenetic stimulation to moving C. elegans populations

We present a high-throughput optogenetic illumination system capable of simultaneous closed-loop light delivery to specified targets in populations of moving Caenorhabditis elegans. The instrument addresses three technical challenges: It delivers targeted illumination to specified regions of the animal's body such as its head or tail; it automatically delivers stimuli triggered upon the animal's behavior; and it achieves high throughput by targeting many animals simultaneously. The instrument was used to optogenetically probe the animal's behavioral response to competing mechanosensory stimuli in the the anterior and posterior gentle touch receptor neurons. Responses to more than 43,418 stimulus events from a range of anterior-posterior intensity combinations were measured. The animal's probability of sprinting forward in response to a mechanosensory stimulus depended on both the anterior and posterior stimulation intensity, while the probability of reversing depended primarily on the anterior stimulation intensity. We also probed the animal's response to mechanosensory stimulation during the onset of turning, a relatively rare behavioral event, by delivering stimuli automatically when the animal began to turn. Using this closed-loop approach, over 9,700 stimulus events were delivered during turning onset at a rate of 9.2 events per worm hour, a greater than 25-fold increase in throughput compared to previous investigations. These measurements validate with greater statistical power previous findings that turning acts to gate mechanosensory evoked reversals. Compared to previous approaches, the current system offers targeted optogenetic stimulation to specific body regions or behaviors with many fold increases in throughput to better constrain quantitative models of sensorimotor processing.

cAMP controls a trafficking mechanism that maintains the neuron specificity and subcellular placement of electrical synapses

Electrical synapses are established between specific neurons and within distinct subcellular compartments, but the mechanisms that direct gap junction assembly in the nervous system are largely unknown. Here, we show that a developmental program tunes cAMP signaling to direct the neuron-specific assembly and placement of electrical synapses in the C. elegans motor circuit. We use live-cell imaging to visualize electrical synapses in vivo and an optogenetic assay to confirm that they are functional. In ventral A class (VA) motor neurons, the UNC-4 transcription factor blocks expression of cAMP antagonists that promote gap junction miswiring. In unc-4 mutants, VA electrical synapses are established with an alternative synaptic partner and are repositioned from the VA axon to soma. cAMP counters these effects by driving gap junction trafficking into the VA axon for electrical synapse assembly. Thus, our experiments establish that cAMP regulates gap junction trafficking for the biogenesis of functional electrical synapses.

Carbon Monoxide Modulation of Microglia-Neuron Communication: Anti-Neuroinflammatory and Neurotrophic Role

Microglia, the 'resident immunocompetent cells' of the central nervous system (CNS), are key players in innate immunity, synaptic refinement and homeostasis. Dysfunctional microglia contribute heavily to creating a toxic inflammatory milieu, a driving factor in the pathophysiology of several CNS disorders. Therefore, strategies to modulate the microglial function are required to tackle exacerbated tissue inflammation. Carbon monoxide (CO), an endogenous gaseous molecule produced by the degradation of haem, has anti-inflammatory, anti-apoptotic, and pro-homeostatic and cytoprotective roles, among others. ALF-826A, a novel molybdenum-based CO-releasing molecule, was used for the assessment of neuron-microglia remote communication. Primary cultures of rat microglia and neurons, or the BV-2 microglial and CAD neuronal murine cell lines, were used to study the microglia-neuron interaction. An approach based on microglial-derived conditioned media in neuronal culture was applied. Medium derived from CO-treated microglia provided indirect neuroprotection against inflammation by limiting the lipopolysaccharide (LPS)-induced expression of reactivity markers (CD11b), the production of reactive oxygen species (ROS) and the secretion of inflammatory factors (TNF-α, nitrites). This consequently prevented neuronal cell death and maintained neuronal morphology. In contrast, in the absence of inflammatory stimulus, conditioned media from CO-treated microglia improved neuronal morphological complexity, which is an indirect manner of assessing neuronal function. Likewise, the microglial medium also prevented neuronal cell death induced by pro-oxidant tert-Butyl hydroperoxide (t-BHP). ALF-826 treatment reinforced microglia secretion of Interleukin-10 (IL-10) and adenosine, mediators that may protect against t-BHP stress in this remote communication model. Chemical inhibition of the adenosine receptors A_2A and A₁ reverted the CO-derived neuroprotective effect, further highlighting a role for CO in regulating neuron-microglia communication via purinergic signalling. Our findings indicate that CO has a modulatory role on microglia-to-neuron communication, promoting neuroprotection in a non-cell autonomous manner. CO enhances the microglial release of neurotrophic factors and blocks exacerbated microglial inflammation. CO improvement of microglial neurotrophism under non-inflammatory conditions is here described for the first time.

Alteration of mitochondrial homeostasis is an early event in a C. elegans model of human tauopathy

Tauopathies are a group of progressive neurodegenerative disorders characterized by the presence of insoluble intracellular tau filaments in the brain. Evidence suggests that there is a tight connection between mitochondrial dysfunction and tauopathies, including Alzheimer’s disease. However, whether mitochondrial dysfunction occurs prior to the detection of tau aggregates in tauopathies remains elusive. Here, we utilized transgenic nematodes expressing the full length of wild type tau in neuronal cells and monitored mitochondrial morphology alterations over time. Although tau-expressing nematodes did not accumulate detectable levels of tau aggregates during larval stages, they displayed increased mitochondrial damage and locomotion defects compared to the control worms. Chelating calcium restored mitochondrial activity and improved motility in the tau-expressing larvae suggesting a link between mitochondrial damage, calcium homeostasis and neuronal impairment in these animals. Our findings suggest that defective mitochondrial function is an early pathogenic event of tauopathies, taking place before tau aggregation and undermining neuronal homeostasis and organismal fitness. Understanding the molecular mechanisms causing mitochondrial dysfunction early in tauopathy will be of significant clinical and therapeutic value and merits further investigation.

Microglia at the Centre of Brain Research: Accomplishments and Challenges for the Future

Microglia are the immune guardians of the central nervous system (CNS), with critical functions in development, maintenance of homeostatic tissue balance, injury and repair. For a long time considered a forgotten 'third element' with basic phagocytic functions, a recent surge in interest, accompanied by technological progress, has demonstrated that these distinct myeloid cells have a wide-ranging importance for brain function. This review reports microglial origins, development, and function in the healthy brain. Moreover, it also targets microglia dysfunction and how it contributes to the progression of several neurological disorders, focusing on particular molecular mechanisms and whether these may present themselves as opportunities for novel, microglia-targeted therapeutic approaches, an ever-enticing prospect. Finally, as it has been recently celebrated 100 years of microglia research, the review highlights key landmarks from the past century and looked into the future. Many challenging problems have arisen, thus it points out some of the most pressing questions and experimental challenges for the ensuing century.

Phase response analyses support a relaxation oscillator model of locomotor rhythm generation in Caenorhabditis elegans

Neural circuits coordinate with muscles and sensory feedback to generate motor behaviors appropriate to an animal's environment. In C. elegans, the mechanisms by which the motor circuit generates undulations and modulates them based on the environment are largely unclear. We quantitatively analyzed C. elegans locomotion during free movement and during transient optogenetic muscle inhibition. Undulatory movements were highly asymmetrical with respect to the duration of bending and unbending during each cycle. Phase response curves induced by brief optogenetic inhibition of head muscles showed gradual increases and rapid decreases as a function of phase at which the perturbation was applied. A relaxation oscillator model based on proprioceptive thresholds that switch the active muscle moment was developed and is shown to quantitatively agree with data from free movement, phase responses, and previous results for gait adaptation to mechanical loadings. Our results suggest a neuromuscular mechanism underlying C. elegans motor pattern generation within a compact circuit.

Conformational changes in twitchin kinase in vivo revealed by FRET imaging of freely moving C. elegans

The force-induced unfolding and refolding of proteins is speculated to be a key mechanism in the sensing and transduction of mechanical signals in the living cell. Yet, little evidence has been gathered for its existence in vivo. Prominently, stretch-induced unfolding is postulated to be the activation mechanism of the twitchin/titin family of autoinhibited sarcomeric kinases linked to the mechanical stress response of muscle. To test the occurrence of mechanical kinase activation in living working muscle, we generated transgenic Caenorhabditis elegans expressing twitchin containing FRET moieties flanking the kinase domain and developed a quantitative technique for extracting FRET signals in freely moving C. elegans, using tracking and simultaneous imaging of animals in three channels (donor fluorescence, acceptor fluorescence, and transmitted light). Computer vision algorithms were used to extract fluorescence signals and muscle contraction states in each frame, in order to obtain fluorescence and body curvature measurements with spatial and temporal precision in vivo. The data revealed statistically significant periodic changes in FRET signals during muscle activity, consistent with a periodic change in the conformation of twitchin kinase. We conclude that stretch-unfolding of twitchin kinase occurs in the active muscle, whereby mechanical activity titrates the signaling pathway of this cytoskeletal kinase. We anticipate that the methods we have developed here could be applied to obtaining in vivo evidence for force-induced conformational changes or elastic behavior of other proteins not only in C. elegans but in other animals in which there is optical transparency (e.g., zebrafish).

Generation of Direct-, Retrograde-, and Source-Wave Gaits in Multi-Legged Locomotion in a Decentralized Manner via Embodied Sensorimotor Interaction

Multi-legged animals show several types of ipsilateral interlimb coordination. Millipedes use a direct-wave gait, in which the swing leg movements propagate from posterior to anterior. In contrast, centipedes use a retrograde-wave gait, in which the swing leg movements propagate from anterior to posterior. Interestingly, when millipedes walk in a specific way, both direct and retrograde waves of the swing leg movements appear with the waves' source, which we call the source-wave gait. However, the gait generation mechanism is still unclear because of the complex nature of the interaction between neural control and dynamic body systems. The present study used a simple model to understand the mechanism better, primarily how local sensory feedback affects multi-legged locomotion. The model comprises a multi-legged body and its locomotion control system using biologically inspired oscillators with local sensory feedback, phase resetting. Each oscillator controls each leg independently. Our simulation produced the above three types of animal gaits. These gaits are not predesigned but emerge through the interaction between the neural control and dynamic body systems through sensory feedback (embodied sensorimotor interaction) in a decentralized manner. The analytical description of these gaits' solution and stability clarifies the embodied sensorimotor interaction's functional roles in the interlimb coordination.

An asymmetric mechanical code ciphers curvature-dependent proprioceptor activity

A repetitive gait cycle is an archetypical component within the behavioral repertoire of many animals including humans. It originates from mechanical feedback within proprioceptors to adjust the motor program during locomotion and thus leads to a periodic orbit in a low-dimensional space. Here, we investigate the mechanics, molecules, and neurons responsible for proprioception in Caenorhabditis elegans to gain insight into how mechanosensation shapes the orbital trajectory to a well-defined limit cycle. We used genome editing, force spectroscopy, and multiscale modeling and found that alternating tension and compression with the spectrin network of a single proprioceptor encodes body posture and informs TRP-4/NOMPC and TWK-16/TREK2 homologs of mechanosensitive ion channels during locomotion. In contrast to a widely accepted model of proprioceptive “stretch” reception, we found that proprioceptors activated locally under compressive stresses in-vivo and in-vitro and propose that this property leads to compartmentalized activity within long axons delimited by curvature-dependent mechanical stresses.

Proprioception, the regulator of motor function

In animals, proper locomotion is crucial to find mates and foods and avoid predators or dangers. Multiple sensory systems detect external and internal cues and integrate them to modulate motor outputs. Proprioception is the internal sense of body position, and proprioceptive control of locomotion is essential to generate and maintain precise patterns of movement or gaits. This proprioceptive feedback system is conserved in many animal species and is mediated by stretch-sensitive receptors called proprioceptors. Recent studies have identified multiple proprioceptive neurons and proprioceptors and their roles in the locomotion of various model organisms. In this review we describe molecular and neuronal mechanisms underlying proprioceptive feedback systems in C. elegans, Drosophila, and mice.

Metachronal waves in concentrations of swimming Turbatrix aceti nematodes and an oscillator chain model for their coordinated motions

At high concentration, free swimming nematodes known as vinegar eels (Turbatrix aceti), collectively exhibit metachronal waves near a boundary. We find that the frequency of the collective traveling wave is lower than that of the freely swimming organisms. We explore models based on a chain of oscillators with nearest-neighbor interactions that inhibit oscillator phase velocity. The phase of each oscillator represents the phase of the motion of the eel's head back and forth about its mean position. A strongly interacting directed chain model mimicking steric repulsion between organisms robustly gives traveling wave states and can approximately match the observed wavelength and oscillation frequency of the observed traveling wave. We predict body shapes assuming that waves propagate down the eel body at a constant speed. The phase oscillator model that impedes eel head overlaps also reduces close interactions throughout the eel bodies.