Central pattern generators and the control of rhythmic movements

Recent advances on the influence of fipronil on insect behavior

Fipronil, a pesticide widely used to control agricultural and household insect pests, blocks insect GABAA and glutamate (GluCl) ionotropic receptors, resulting in uncontrolled hyperexcitation and paralysis that eventually leads to death. The use of fipronil is controversial because unintentional exposure to this compound may contribute to the ongoing global decline of insect pollinator populations. Although the sublethal effects of fipronil have been linked to aberrant behavior and impaired olfactory learning in insects, the precise mechanisms involved in these responses remain unclear. In this article, we highlight recent studies that have investigated the interaction among different pathways involved in the ability of fipronil to modulate insect behavior, with particular emphasis on the role of GABAergic neurotransmission in fine-tuning the integration of sensorial responses and insect behavior. Recent findings suggest that fipronil can also cause functional alterations that affect synaptic organization and the availability of metal ions in the brain.

Recall tempo of Hebbian sequences depends on the interplay of Hebbian kernel with tutor signal timing

Understanding how neural circuits generate sequential activity is a longstanding challenge. While foundational theoretical models have shown how sequences can be stored as memories in neural networks with Hebbian plasticity rules, these models considered only a narrow range of Hebbian rules. Here, we introduce a model for arbitrary Hebbian plasticity rules, capturing the diversity of spike-timing-dependent synaptic plasticity seen in experiments, and show how the choice of these rules and of neural activity patterns influences sequence memory formation and retrieval. In particular, we derive a general theory that predicts the tempo of sequence replay. This theory lays a foundation for explaining how cortical tutor signals might give rise to motor actions that eventually become "automatic." Our theory also captures the impact of changing the tempo of the tutor signal. Beyond shedding light on biological circuits, this theory has relevance in artificial intelligence by laying a foundation for frameworks whereby slow and computationally expensive deliberation can be stored as memories and eventually replaced by inexpensive recall.

Beadex, the Drosophila LIM only protein, is required for the growth of the larval neuromuscular junction

The appropriate growth of the neurons, accurate organization of their synapses, and successful neurotransmission are indispensable for sensorimotor activities. These processes are highly dynamic and tightly regulated. Extensive genetic, molecular, physiological, and behavioral studies have identified many molecular candidates and investigated their roles in various neuromuscular processes. In this article, we show that Beadex (Bx), the Drosophila LIM only (LMO) protein, is required for motor activities and neuromuscular growth of Drosophila. The larvae bearing Bx7, a null allele of Bx, and the RNAi-mediated neuronal-specific knockdown of Bx show drastically reduced crawling behavior, a diminished synaptic span of the neuromuscular junctions (NMJs) and an increased spontaneous neuronal firing with altered motor patterns in the central pattern generators (CPGs). Microarray studies identified multiple targets of Beadex that are involved in different cellular and molecular pathways, including those associated with the cytoskeleton and mitochondria that could be responsible for the observed neuromuscular defects. With genetic interaction studies, we further show that Highwire (Hiw), a negative regulator of synaptic growth at the NMJs, negatively regulates Bx, as the latter's deficiency was able to rescue the phenotype of the Hiw null mutant, HiwDN. Thus, our data indicate that Beadex functions downstream of Hiw to regulate the larval synaptic growth and physiology.NEW & NOTEWORTHY A novel role for Beadex (Bx) regulates the larval neuromuscular junction (NMJ) structure and function in a tissue-specific manner. Bx is expressed in a subset of Toll-6-expressing neurons and is involved in regulating synaptic span and physiology, possibly through its negative interaction with Highwire (Hiw). The findings of this study provide insights into the molecular mechanisms underlying NMJ development and function and warrant further investigation to understand the role of Bx in these processes fully.

Neural underpinnings of fine motor skills under stress and anxiety: A review

This review offers a comprehensive examination of how stress and anxiety affect motor behavior, particularly focusing on fine motor skills and gait adaptability. We explore the role of several neurochemicals, including brain-derived neurotrophic factor (BDNF) and dopamine, in modulating neural plasticity and motor control under these affective states. The review highlights the importance of developing therapeutic strategies that enhance motor performance by leveraging the interactions between key neurochemicals. Additionally, we investigate the complex interplay between emotional-cognitive states and sensorimotor behaviors, showing how stress and anxiety disrupt neural integration, leading to impairments in skilled movements and negatively impacting quality of life. Synthesizing evidence from human and rodent studies, we provide a detailed understanding of the relationships among stress, anxiety, and motor behavior. Our findings reveal neurophysiological pathways, behavioral outcomes, and potential therapeutic targets, emphasizing the intricate connections between neurobiological mechanisms, environmental factors, and motor performance.

A model-free method to learn multiple skills in parallel on modular robots

Legged robots are well-suited for deployment in unstructured environments but require a unique control scheme specific for their design. As controllers optimised in simulation do not transfer well to the real world (the infamous sim-to-real gap), methods enabling quick learning in the real world, without any assumptions on the specific robot model and its dynamics, are necessary. In this paper, we present a generic method based on Central Pattern Generators, that enables the acquisition of basic locomotion skills in parallel, through very few trials. The novelty of our approach, underpinned by a mathematical analysis of the controller model, is to search for good initial states, instead of optimising connection weights. Empirical validation in six different robot morphologies demonstrates that our method enables robots to learn primary locomotion skills in less than 15 minutes in the real world. In the end, we showcase our skills in a targeted locomotion experiment.

Sulfonylurea receptor coupled conductances alter the performace of two central pattern generating circuits in Cancer borealis

Neuronal activity and energy supply must maintain a fine balance for neuronal fitness. Various channels of communication between the two could impact network output in different ways. Sulfonylurea receptors (SURs) are a modification of ATP-binding cassette proteins (ABCs) that confer ATP-dependent gating on their associated ion channels. They are widely expressed and link metabolic states directly to neuronal activity. The role they play varies in different circuits, both enabling bursting and inhibiting activity in pathological conditions. The crab, Cancer borealis, has central patterns generators (CPGs) that fire in rhythmic bursts nearly constantly and it is unknown how energy availability influences these networks. The pyloric network of the stomatogastric ganglion (STG) and cardiac ganglion (GC) control rhythmic contractions of the foregut and heart respectively. Pharmacological manipulation of SURs results in opposite effects in the two CPGs. Neuronal firing completely stops in the STG when SUR-associated channels are open, and firing increases when the channels are closed. This results from a decrease in the excitability of pyloric dilator (PD) neurons, which are a part of the pacemaker kernel. The neurons of the CG, paradoxically, increase firing within bursts when SUR-associated channels are opened, and bursting slows when SUR-associated channels are closed. The channel permeability and sensitivities analyses present novel SUR-conductance biophysics, which nevertheless change activity in ways reminiscent of the predominantly studied mammalian receptor/channels. We suggest that SUR-associated conductances allow different neurons to respond to energy states in different ways through a common mechanism.

The breath shape controls intonation of mouse vocalizations

Intonation in speech is the control of vocal pitch to layer expressive meaning to communication, like increasing pitch to indicate a question. Also, stereotyped patterns of pitch are used to create distinct sounds with different denotations, like in tonal languages and, perhaps, the 10 sounds in the murine lexicon. A basic tone is created by exhalation through a constricted laryngeal voice box, and it is thought that more complex utterances are produced solely by dynamic changes in laryngeal tension. But perhaps, the shifting pitch also results from altering the swiftness of exhalation. Consistent with the latter model, we describe that intonation in most vocalization types follows deviations in exhalation that appear to be generated by the re-activation of the cardinal breathing muscle for inspiration. We also show that the brainstem vocalization central pattern generator, the iRO, can create this breath pattern. Consequently, ectopic activation of the iRO not only induces phonation, but also the pitch patterns that compose most of the vocalizations in the murine lexicon. These results reveal a novel brainstem mechanism for intonation.

Spontaneous rates exhibit high intra-individual stability across movements involving different biomechanical systems and cognitive demands

Spontaneous rhythmic movements are part of everyday life, e.g., in walking, clapping or music making. Humans perform such spontaneous motor actions at different rates that reflect specific biomechanical constraints of the effector system in use. However, there is some evidence for intra-individual consistency of specific spontaneous rates arguably resulting from common underlying processes. Additionally, individual and contextual factors such as musicianship and circadian rhythms have been suggested to influence spontaneous rates. This study investigated the relative contributions of these factors and provides a comprehensive picture of rates among different spontaneous motor behaviors, i.e., melody production, walking, clapping, tapping with and without sound production, the latter measured online before and in the lab. Participants (n = 60) exhibited high intra-individual stability across tasks. Task-related influences included faster tempi for spontaneous production rates of music and wider ranges of spontaneous motor tempi (SMT) and clapping rates compared to walking and music making rates. Moreover, musicians exhibited slower spontaneous rates across tasks, yet we found no influence of time of day on SMT as measured online in pre-lab sessions. Tapping behavior was similar in pre-lab and in-lab sessions, validating the use of online SMT assessments. Together, the prominent role of individual factors and high stability across domains support the idea that different spontaneous motor behaviors are influenced by common underlying processes.

STEERING FROM THE REAR: COORDINATION OF CENTRAL PATTERN GENERATORS UNDERLYING NAVIGATION BY ASCENDING INTERNEURONS

Understanding how animals coordinate movements to achieve goals is a fundamental pursuit in neuroscience. Here we explore how neurons that reside in posterior lower-order regions of a locomotor system project to anterior higher-order regions to influence steering and navigation. We characterized the anatomy and functional role of a population of ascending interneurons in the ventral nerve cord of Drosophila larvae. Through electron microscopy reconstructions and light microscopy, we determined that the cholinergic 19f cells receive input primarily from premotor interneurons and synapse upon a diverse array of postsynaptic targets within the anterior segments including other 19f cells. Calcium imaging of 19f activity in isolated central nervous system (CNS) preparations in relation to motor neurons revealed that 19f neurons are recruited into most larval motor programmes. 19f activity lags behind motor neuron activity and as a population, the cells encode spatio-temporal patterns of locomotor activity in the larval CNS. Optogenetic manipulations of 19f cell activity in isolated CNS preparations revealed that they coordinate the activity of central pattern generators underlying exploratory headsweeps and forward locomotion in a context and location specific manner. In behaving animals, activating 19f cells suppressed exploratory headsweeps and slowed forward locomotion, while inhibition of 19f activity potentiated headsweeps, slowing forward movement. Inhibiting activity in 19f cells ultimately affected the ability of larvae to remain in the vicinity of an odor source during an olfactory navigation task. Overall, our findings provide insights into how ascending interneurons monitor motor activity and shape interactions amongst rhythm generators underlying complex navigational tasks.

Workspace trajectory generation with smooth gait transition using CPG-based locomotion control for hexapod robot

-This paper presents a new control methodology for achieving smooth gait transitions for a hexapod robot using Central Pattern Generators (CPGs). The approach involves modifying the Phase Oscillator within the CPG network to enable smooth transitions between different gaits in order to improve the adaptability to changing environmental conditions. The foot trajectory generator is designed based on the CPG output, allowing the possibility of online adjustment of foot trajectory parameters, such as step height and size, as well as the robot's speed and direction. Our simulation demonstrates the effectiveness of the modified oscillator in achieving smoother gait transitions with a transition time falls close to the output period of the CPG oscillators, and experiments on a real hexapod robot validate the feasibility and efficiency of our approach in considering online adjustability of trajectory parameters, confirming the potential of this methodology to enhance the locomotion capabilities of legged robots for navigating complex terrains.

Cell-type-specific origins of locomotor rhythmicity at different speeds in larval zebrafish

Different speeds of locomotion require heterogeneous spinal populations, but a common mode of rhythm generation is presumed to exist. Here, we explore the cellular versus synaptic origins of spinal rhythmicity at different speeds by performing electrophysiological recordings from premotor excitatory interneurons in larval zebrafish. Chx10-labeled V2a neurons are divided into at least two morphological subtypes proposed to play distinct roles in timing and intensity control. Consistent with distinct rhythm generating and output patterning functions within the spinal V2a population, we find that descending subtypes are recruited exclusively at slow or fast speeds and exhibit intrinsic cellular properties suitable for rhythmogenesis at those speeds, while bifurcating subtypes are recruited more reliably at all speeds and lack appropriate rhythmogenic cellular properties. Unexpectedly, however, phasic firing patterns during locomotion in rhythmogenic and non-rhythmogenic V2a neurons alike are best explained by distinct modes of synaptic inhibition linked to cell-type and speed. At fast speeds reciprocal inhibition in descending V2a neurons supports phasic firing, while recurrent inhibition in bifurcating V2a neurons helps pattern motor output. In contrast, at slow speeds recurrent inhibition in descending V2a neurons supports phasic firing, while bifurcating V2a neurons rely on reciprocal inhibition alone to pattern output. Our findings suggest cell-type-specific, not common, modes of rhythmogenesis generate and coordinate different speeds of locomotion.

Altered Grooming Cycles in Transgenic Drosophila

Head grooming in Drosophila consists of repeated sweeps of the legs across the head, comprising regular cycles. We used the GAL4-UAS system to study the effects of overexpressing shibirets1 and of Adar knockdown via RNA interference, on the period of head-grooming cycles in Drosophila. Overexpressing shibirets1 interferes with synaptic vesicle recycling and thus with cell communication, while Adar knockdown reduces RNA editing of neuronal transcripts for a large number of genes. All transgenic flies and their controls were tested at 22° to avoid temperature effects; in wild type, cycle frequency varied with temperature with a Q10 of 1.3. Two experiments were performed with transgenic shibirets1: (1) each fly was heat-shocked for 10 min at 30° immediately before testing at 22° and (2) flies were not heat shocked. In both experiments, cycle period was increased when shibirets1 was overexpressed in all neurons, but was not increased when shibirets1 was overexpressed in motoneurons alone. We hypothesize that grooming cycles in flies overexpressing shibirets1 are lengthened because of synaptic impairment in neural circuits that control head-grooming cycles. In flies with constitutive, pan-neuronal Adar knockdown, cycle period was more variable within individuals, but mean cycle period was not significantly altered. We conclude that RNA editing is essential for the maintenance of within-individual stereotypy of head-grooming cycles.

The breath shape controls intonation of mouse vocalizations

Intonation in speech is the control of vocal pitch to layer expressive meaning to communication, like increasing pitch to indicate a question. Also, stereotyped patterns of pitch are used to create distinct sounds with different denotations, like in tonal languages and, perhaps, the ten sounds in the murine lexicon. A basic tone is created by exhalation through a constricted laryngeal voice box, and it is thought that more complex utterances are produced solely by dynamic changes in laryngeal tension. But perhaps, the shifting pitch also results from altering the swiftness of exhalation. Consistent with the latter model, we describe that intonation in most vocalization types follows deviations in exhalation that appear to be generated by the re-activation of the cardinal breathing muscle for inspiration. We also show that the brainstem vocalization central pattern generator, the iRO, can create this breath pattern. Consequently, ectopic activation of the iRO not only induces phonation, but also the pitch patterns that compose most of the vocalizations in the murine lexicon. These results reveal a novel brainstem mechanism for intonation.

Are circadian amplitudes and periods correlated? A new twist in the story

Three parameters are important to characterize a circadian and in general any biological clock: period, phase and amplitude. While circadian periods have been shown to correlate with entrainment phases, and clock amplitude influences the phase response of an oscillator to pulse-like zeitgeber signals, the co-modulations of amplitude and periods, which we term twist, have not been studied in detail. In this paper we define two concepts: parametric twist refers to amplitude-period correlations arising in ensembles of self-sustained, limit cycle clocks in the absence of external inputs, and phase space twist refers to the co-modulation of an individual clock's amplitude and period in response to external zeitgebers. Our findings show that twist influences the interaction of oscillators with the environment, facilitating entrainment, speeding upfastening recovery to pulse-like perturbations or modifying the response of an individual clock to coupling. This theoretical framework might be applied to understand the emerging properties of other oscillating systems.

Sparse Firing in a Hybrid Central Pattern Generator for Spinal Motor Circuits

Central pattern generators are circuits generating rhythmic movements, such as walking. The majority of existing computational models of these circuits produce antagonistic output where all neurons within a population spike with a broad burst at about the same neuronal phase with respect to network output. However, experimental recordings reveal that many neurons within these circuits fire sparsely, sometimes as rarely as once within a cycle. Here we address the sparse neuronal firing and develop a model to replicate the behavior of individual neurons within rhythm-generating populations to increase biological plausibility and facilitate new insights into the underlying mechanisms of rhythm generation. The developed network architecture is able to produce sparse firing of individual neurons, creating a novel implementation for exploring the contribution of network architecture on rhythmic output. Furthermore, the introduction of sparse firing of individual neurons within the rhythm-generating circuits is one of the factors that allows for a broad neuronal phase representation of firing at the population level. This moves the model toward recent experimental findings of evenly distributed neuronal firing across phases among individual spinal neurons. The network is tested by methodically iterating select parameters to gain an understanding of how connectivity and the interplay of excitation and inhibition influence the output. This knowledge can be applied in future studies to implement a biologically plausible rhythm-generating circuit for testing biological hypotheses.

A deep learning-based approach for unbiased kinematic analysis in CNS injury

Traumatic spinal cord injury (SCI) is a devastating condition that impacts over 300,000 individuals in the US alone. Depending on the severity of the injury, SCI can lead to varying degrees of sensorimotor deficits and paralysis. Despite advances in our understanding of the underlying pathological mechanisms of SCI and the identification of promising molecular targets for repair and functional restoration, few therapies have made it into clinical use. To improve the success rate of clinical translation, more robust, sensitive, and reproducible means of functional assessment are required. The gold standards for the evaluation of locomotion in rodents with SCI are the Basso Beattie Bresnahan (BBB) and Basso Mouse Scale (BMS) tests. To overcome the shortcomings of current methods, we developed two separate marker-less kinematic analysis paradigms in mice, MotorBox and MotoRater, based on deep-learning algorithms generated with the DeepLabCut open-source toolbox. The MotorBox system uses an originally designed, custom-made chamber, and the MotoRater system was implemented on a commercially available MotoRater device. We validated the MotorBox and MotoRater systems by comparing them with the traditional BMS test and extracted metrics of movement and gait that can provide an accurate and sensitive representation of mouse locomotor function post-injury, while eliminating investigator bias and variability. The integration of MotorBox and/or MotoRater assessments with BMS scoring will provide a much wider range of information on specific aspects of locomotion, ensuring the accuracy, rigor, and reproducibility of behavioral outcomes after SCI.

Highlights

MotorBox and MotoRater systems are two novel marker-less kinematic analysis paradigms in mice, based on deep-learning algorithms generated with DeepLabCut.MotorBox and MotoRater systems are highly sensitive, accurate and unbiased in analyzing locomotor behavior in mice.MotorBox and MotoRater systems allow for sensitive detection of SCI-induced changes in movement metrics, including range of motion, gait, coordination, and speed.MotorBox and MotoRater systems allow for detection of movement metrics not measurable with the BMS.

Neuronal mechanisms regulating locomotion in adult Drosophila

The coordinated action of multiple leg joints and muscles is required even for the simplest movements. Understanding the neuronal circuits and mechanisms that generate precise movements is essential for comprehending the neuronal basis of the locomotion and to infer the neuronal mechanisms underlying several locomotor-related diseases. Drosophila melanogaster provides an excellent model system for investigating the neuronal circuits underlying motor behaviors due to its simple nervous system and genetic accessibility. This review discusses current genetic methods for studying locomotor circuits and their function in adult Drosophila. We highlight recently identified neuronal pathways that modulate distinct forward and backward locomotion and describe the underlying neuronal control of leg swing and stance phases in freely moving flies. We also report various automated leg tracking methods to measure leg motion parameters and define inter-leg coordination, gait and locomotor speed of freely moving adult flies. Finally, we emphasize the role of leg proprioceptive signals to central motor circuits in leg coordination. Together, this review highlights the utility of adult Drosophila as a model to uncover underlying motor circuitry and the functional organization of the leg motor system that governs correct movement.

Dimensionality of locomotor behaviors in developing C. elegans

Adult animals display robust locomotion, yet the timeline and mechanisms of how juvenile animals acquire coordinated movements and how these movements evolve during development are not well understood. Recent advances in quantitative behavioral analyses have paved the way for investigating complex natural behaviors like locomotion. In this study, we tracked the swimming and crawling behaviors of the nematode Caenorhabditis elegans from postembryonic development through to adulthood. Our principal component analyses revealed that adult C. elegans swimming is low dimensional, suggesting that a small number of distinct postures, or eigenworms, account for most of the variance in the body shapes that constitute swimming behavior. Additionally, we found that crawling behavior in adult C. elegans is similarly low dimensional, corroborating previous studies. Further, our analysis revealed that swimming and crawling are distinguishable within the eigenworm space. Remarkably, young L1 larvae are capable of producing the postural shapes for swimming and crawling seen in adults, despite frequent instances of uncoordinated body movements. In contrast, late L1 larvae exhibit robust coordination of locomotion, while many neurons crucial for adult locomotion are still under development. In conclusion, this study establishes a comprehensive quantitative behavioral framework for understanding the neural basis of locomotor development, including distinct gaits such as swimming and crawling in C. elegans.

How neuronal morphology impacts the synchronisation state of neuronal networks

The biophysical properties of neurons not only affect how information is processed within cells, they can also impact the dynamical states of the network. Specifically, the cellular dynamics of action-potential generation have shown relevance for setting the (de)synchronisation state of the network. The dynamics of tonically spiking neurons typically fall into one of three qualitatively distinct types that arise from distinct mathematical bifurcations of voltage dynamics at the onset of spiking. Accordingly, changes in ion channel composition or even external factors, like temperature, have been demonstrated to switch network behaviour via changes in the spike onset bifurcation and hence its associated dynamical type. A thus far less addressed modulator of neuronal dynamics is cellular morphology. Based on simplified and anatomically realistic mathematical neuron models, we show here that the extent of dendritic arborisation has an influence on the neuronal dynamical spiking type and therefore on the (de)synchronisation state of the network. Specifically, larger dendritic trees prime neuronal dynamics for in-phase-synchronised or splayed-out activity in weakly coupled networks, in contrast to cells with otherwise identical properties yet smaller dendrites. Our biophysical insights hold for generic multicompartmental classes of spiking neuron models (from ball-and-stick-type to anatomically reconstructed models) and establish a connection between neuronal morphology and the susceptibility of neural tissue to synchronisation in health and disease.

The synaptic drive of central pattern-generating networks to leg motor neurons of a walking insect is motor neuron pool specific

Rhythmic locomotor activity, such as flying, swimming, or walking, results from an interplay between higher-order centers in the central nervous system, which initiate, maintain, and modify task-specific motor activity, downstream central pattern-generating neural circuits (CPGs) that can generate a default rhythmic motor output, and, finally, feedback from sense organs that modify basic motor activity toward functionality.1,2,3 In this context, CPGs provide phasic synaptic drive to motor neurons (MNs) and thereby support the generation of rhythmic activity for locomotion. We analyzed the synaptic drive that the leg MNs supplying the three main leg joints receive from CPGs in pharmacologically activated and deafferented preparations of the stick insect (Carausius morosus). We show that premotor CPGs pattern the tonic activity of five of the six leg MN pools by phasic inhibitory synaptic drive. These are the antagonistic MN pools supplying the thoraco-coxal joint and the femur-tibial joint4,5 and the levator MN pool supplying the coxa-trochanteral (CTr) joint. In contrast, rhythmic activity of the depressor MN pool supplying the CTr joint was found to be primarily based on a phasic excitatory drive. This difference is likely related to the pivotal role of the depressor muscle in generating leg stance during any walking situation. Thus, our results provide evidence for qualitatively differing mechanisms to generate rhythmic activity between MN pools in the same locomotor system.

Bioelectric control of locomotor gaits in the walking ciliate Euplotes

Diverse animal species exhibit highly stereotyped behavioral actions and locomotor sequences as they explore their natural environments. In many such cases, the neural basis of behavior is well established, where dedicated neural circuitry contributes to the initiation and regulation of certain response sequences. At the microscopic scale, single-celled eukaryotes (protists) also exhibit remarkably complex behaviors and yet are completely devoid of nervous systems. Here, to address the question of how single cells control behavior, we study locomotor patterning in the exemplary hypotrich ciliate Euplotes, a highly polarized cell, which actuates a large number of leg-like appendages called cirri (each a bundle of ∼25-50 cilia) to swim in fluids or walk on surfaces. As it navigates its surroundings, a walking Euplotes cell is routinely observed to perform side-stepping reactions, one of the most sophisticated maneuvers ever observed in a single-celled organism. These are spontaneous and stereotyped reorientation events involving a transient and fast backward motion followed by a turn. Combining high-speed imaging with simultaneous time-resolved electrophysiological recordings, we show that this complex coordinated motion sequence is tightly regulated by rapid membrane depolarization events, which orchestrate the activity of different cirri on the cell. Using machine learning and computer vision methods, we map detailed measurements of cirri dynamics to the cell's membrane bioelectrical activity, revealing a differential response in the front and back cirri. We integrate these measurements with a minimal model to understand how Euplotes-a unicellular organism-manipulates its membrane potential to achieve real-time control over its motor apparatus.

Dynamics of antiphase bursting modulated by the inhibitory synaptic and hyperpolarization-activated cation currents

Antiphase bursting related to the rhythmic motor behavior exhibits complex dynamics modulated by the inhibitory synaptic current (Isyn), especially in the presence of the hyperpolarization-activated cation current (Ih). In the present paper, the dynamics of antiphase bursting modulated by the Ih and Isyn is studied in three aspects with a theoretical model. Firstly, the Isyn and the slow Ih with strong strength are the identified to be the necessary conditions for the antiphase bursting. The dependence of the antiphase bursting on the two currents is different for low (escape mode) and high (release mode) threshold voltages (Vth) of the inhibitory synapse. Secondly, more detailed co-regulations of the two currents to induce opposite changes of the bursting period are obtained. For the escape mode, increase of the Ih induces elevated membrane potential of the silence inhibited by a strong Isyn and shortened silence duration to go beyond Vth, resulting in reduced bursting period. For the release mode, increase of the Ih induces elevated tough value of the former part of the burst modulated by a nearly zero Isyn and lengthen burst duration to fall below Vth, resulting in prolonged bursting period. Finally, the fast-slow dynamics of the antiphase bursting are acquired. Using one-and two-parameter bifurcations of the fast subsystem of a single neuron, the burst of the antiphase bursting is related to the stable limit cycle, and the silence modulated by a strong Isyn to the stable equilibrium to a certain extent. The Ih mainly modulates the dynamics within the burst and quiescent state. Furthermore, with the fast subsystem of the coupled neurons, the silence is associated with the unstable equilibrium point. The results present theoretical explanations to the changes in the bursting period and fast-slow dynamics of the antiphase bursting modulated by the Isyn and Ih, which is helpful for understanding the antiphase bursting and modulating rhythmic motor patterns.

Combined effect of trifluoperazine and sodium cromoglycate on reducing acute edema and limiting lasting functional impairments after spinal cord injury in rats

Edema formation is one of the very first events to occur after spinal cord injury (SCI) leading to an increase of the intrathecal pressure and consequently to serious spinal tissue and functional impairments. Current edema treatments are still symptomatic and/or non-specific. Since edema formation mechanisms are mainly described as vasogenic and cytotoxic, it becomes crucial to understand the interplay between these two subtypes. Acting on key targets to inhibit edema formation may reduce secondary damage and related functional impairments. In this study, we characterize the edema kinetic after T9-10 spinal contusion. We use trifluoperazine (TFP) to block the expression and the functional subcellular localization of aquaporin-4 supposed to be implicated in the cytotoxic edema formation. We also use sodium cromoglycate (SCG) to deactivate mast cell degranulation known to be implicated in the vasogenic edema formation. Our results show a significant reduction of edema after TFP treatment and after TFP-SCG combined treatment compared to control. This reduction is correlated with limited onset of initial sensorimotor impairments particularly after combined treatment. Our results highlight the importance of potential synergetic targets in early edema therapy after SCI as part of tissue sparing strategies.

Switching neuron contributions to second network activity

Network flexibility is important for adaptable behaviors. This includes neuronal switching, where neurons alter their network participation, including changing from single- to dual-network activity. Understanding the implications of neuronal switching requires determining how a switching neuron interacts with each of its networks. Here, we tested 1) whether "home" and second networks, operating via divergent rhythm generation mechanisms, regulate a switching neuron and 2) if a switching neuron, recruited via modulation of intrinsic properties, contributes to rhythm or pattern generation in a new network. Small, well-characterized feeding-related networks (pyloric, ∼1 Hz; gastric mill, ∼0.1 Hz) and identified modulatory inputs make the isolated crab (Cancer borealis) stomatogastric nervous system (STNS) a useful model to study neuronal switching. In particular, the neuropeptide Gly1-SIFamide switches the lateral posterior gastric (LPG) neuron (2 copies) from pyloric-only to dual-frequency pyloric/gastric mill (fast/slow) activity via modulation of LPG-intrinsic properties. Using current injections to manipulate neuronal activity, we found that gastric mill, but not pyloric, network neurons regulated the intrinsically generated LPG slow bursting. Conversely, selective elimination of LPG from both networks using photoinactivation revealed that LPG regulated gastric mill neuron-firing frequencies but was not necessary for gastric mill rhythm generation or coordination. However, LPG alone was sufficient to produce a distinct pattern of network coordination. Thus, modulated intrinsic properties underlying dual-network participation may constrain which networks can regulate switching neuron activity. Furthermore, recruitment via intrinsic properties may occur in modulatory states where it is important for the switching neuron to actively contribute to network output.NEW & NOTEWORTHY We used small, well-characterized networks to investigate interactions between rhythmic networks and neurons that switch their network participation. For a neuron switching into dual-network activity, only the second network regulated its activity in that network. In addition, the switching neuron was sufficient but not necessary to coordinate second network neurons and regulated their activity levels. Thus, regulation of switching neurons may be selective, and a switching neuron is not necessarily simply a follower in additional networks.

Role of the basal ganglia in innate and learned behavioural sequences

Integrating individual actions into coherent, organised behavioural units, a process called chunking, is a fundamental, evolutionarily conserved process that renders actions automatic. In vertebrates, evidence points to the basal ganglia - a complex network believed to be involved in action selection - as a key component of action sequence encoding, although the underlying mechanisms are only just beginning to be understood. Central pattern generators control many innate automatic behavioural sequences that form some of the most basic behaviours in an animal's repertoire, and in vertebrates, brainstem and spinal pattern generators are under the control of higher order structures such as the basal ganglia. Evidence suggests that the basal ganglia play a crucial role in the concatenation of simpler behaviours into more complex chunks, in the context of innate behavioural sequences such as chain grooming in rats, as well as sequences in which innate capabilities and learning interact such as birdsong, and sequences that are learned from scratch, such as lever press sequences in operant behaviour. It has been proposed that the role of the striatum, the largest input structure of the basal ganglia, might lie in selecting and allowing the relevant central pattern generators to gain access to the motor system in the correct order, while inhibiting other behaviours. As behaviours become more complex and flexible, the pattern generators seem to become more dependent on descending signals. Indeed, during learning, the striatum itself may adopt the functional characteristics of a higher order pattern generator, facilitated at the microcircuit level by striatal neuropeptides.

Powered single hip joint exoskeletons for gait rehabilitation: a systematic review and Meta-analysis

BACKGROUND

Gait disorders and as a consequence, robotic rehabilitation techniques are becoming increasingly prevalent as the population ages. In the area of rehabilitation robotics, using lightweight single hip joint exoskeletons are of significance. Considering no prior systematic review article on clinical outcomes, we aim to systematically review powered hip exoskeletons in terms of gait parameters and metabolic expenditure effects.

METHODS

Three databases of PubMed, Scopus, and Web of science were searched for clinical articles comparing outcomes of gait rehabilitation using hip motorized exoskeleton with conventional methods, on patients with gait disorder or healthy individuals. Of total number of 37 reviewed articles, 14 trials were quantitatively analyzed. Analyses performed in terms of gait spatiotemporal parameters like speed (self-speed and maximum speed), step length, stride length, cadence, and oxygen consumption.

RESULTS

Improved clinical outcomes of gait spatiotemporal parameters with hip joint exoskeletons are what our review's findings show. In terms of gait values, meta-analysis indicates that rehabilitation with single hip joint exoskeleton enhanced parameters of maximum speed by 0.13 m/s (0.10-0.17) and step length by 0.06 m (0.05-0.07). For the remaining investigated gait parameters, no statistically significant difference was observed. Regarding metabolic parameters, oxygen consumption was lower in individuals treated with hip exoskeleton (- 1.23 ml/min/kg; range - 2.13 to - 0.32).

CONCLUSION

Although the analysis demonstrated improvement with just specific gait measures utilizing powered hip exoskeletons, the lack of improvement in all parameters is likely caused by the high patient condition heterogeneity among the evaluated articles. We also noted in patients who rehabilitated with the hip exoskeleton, the oxygen cost was lower. More randomized controlled trials are needed to verify both the short- and long-term clinical outcomes, including patient-reported measures.

LEVEL OF EVIDENCE

Level I (systematic review and meta-analysis).

Dual electrical stimulation at spinal-muscular interface reconstructs spinal sensorimotor circuits after spinal cord injury

The neural signals produced by varying electrical stimulation parameters lead to characteristic neural circuit responses. However, the characteristics of neural circuits reconstructed by electrical signals remain poorly understood, which greatly limits the application of such electrical neuromodulation techniques for the treatment of spinal cord injury. Here, we develop a dual electrical stimulation system that combines epidural electrical and muscle stimulation to mimic feedforward and feedback electrical signals in spinal sensorimotor circuits. We demonstrate that a stimulus frequency of 10-20 Hz under dual stimulation conditions is required for structural and functional reconstruction of spinal sensorimotor circuits, which not only activates genes associated with axonal regeneration of motoneurons, but also improves the excitability of spinal neurons. Overall, the results provide insights into neural signal decoding during spinal sensorimotor circuit reconstruction, suggesting that the combination of epidural electrical and muscle stimulation is a promising method for the treatment of spinal cord injury.

Contribution of membrane-associated oscillators to biological timing at different timescales

Environmental rhythms such as the daily light-dark cycle selected for endogenous clocks. These clocks predict regular environmental changes and provide the basis for well-timed adaptive homeostasis in physiology and behavior of organisms. Endogenous clocks are oscillators that are based on positive feedforward and negative feedback loops. They generate stable rhythms even under constant conditions. Since even weak interactions between oscillators allow for autonomous synchronization, coupling/synchronization of oscillators provides the basis of self-organized physiological timing. Amongst the most thoroughly researched clocks are the endogenous circadian clock neurons in mammals and insects. They comprise nuclear clockworks of transcriptional/translational feedback loops (TTFL) that generate ∼24 h rhythms in clock gene expression entrained to the environmental day-night cycle. It is generally assumed that this TTFL clockwork drives all circadian oscillations within and between clock cells, being the basis of any circadian rhythm in physiology and behavior of organisms. Instead of the current gene-based hierarchical clock model we provide here a systems view of timing. We suggest that a coupled system of autonomous TTFL and posttranslational feedback loop (PTFL) oscillators/clocks that run at multiple timescales governs adaptive, dynamic homeostasis of physiology and behavior. We focus on mammalian and insect neurons as endogenous oscillators at multiple timescales. We suggest that neuronal plasma membrane-associated signalosomes constitute specific autonomous PTFL clocks that generate localized but interlinked oscillations of membrane potential and intracellular messengers with specific endogenous frequencies. In each clock neuron multiscale interactions of TTFL and PTFL oscillators/clocks form a temporally structured oscillatory network with a common complex frequency-band comprising superimposed multiscale oscillations. Coupling between oscillator/clock neurons provides the next level of complexity of an oscillatory network. This systemic dynamic network of molecular and cellular oscillators/clocks is suggested to form the basis of any physiological homeostasis that cycles through dynamic homeostatic setpoints with a characteristic frequency-band as hallmark. We propose that mechanisms of homeostatic plasticity maintain the stability of these dynamic setpoints, whereas Hebbian plasticity enables switching between setpoints via coupling factors, like biogenic amines and/or neuropeptides. They reprogram the network to a new common frequency, a new dynamic setpoint. Our novel hypothesis is up for experimental challenge.

Pose analysis in free-swimming adult zebrafish, Danio rerio : "fishy" origins of movement design

Movement requires maneuvers that generate thrust to either make turns or move the body forward in physical space. The computational space for perpetually controlling the relative position of every point on the body surface can be vast. We hypothesize the evolution of efficient design for movement that minimizes active (neural) control by leveraging the passive (reactive) forces between the body and the surrounding medium at play. To test our hypothesis, we investigate the presence of stereotypical postures during free-swimming in adult zebrafish, Danio rerio . We perform markerless tracking using DeepLabCut, a deep learning pose estimation toolkit, to track geometric relationships between body parts. To identify putative clusters of postural configurations obtained from twelve freely behaving zebrafish, we use unsupervised multivariate time-series analysis (B-SOiD machine learning software). When applied to single individuals, this method reveals a best-fit for 36 to 50 clusters in contrast 86 clusters for data pooled from all 12 animals. The centroids of each cluster obtained over 14,000 sequential frames recorded for a single fish represent an apriori classification into relatively stable "target body postures" and inter-pose "transitional postures" that lead to and away from a target pose. We use multidimensional scaling of mean parameter values for each cluster to map cluster-centroids within two dimensions of postural space. From a post-priori visual analysis, we condense neighboring postural variants into 15 superclusters or core body configurations. We develop a nomenclature specifying the anteroposterior level/s (upper, mid and lower) and degree of bending. Our results suggest that constraining bends to mainly three levels in adult zebrafish preempts the neck, fore- and hindlimb design for maneuverability in land vertebrates.

Optimization strategies to obtain smooth gait transitions through biologically plausible central pattern generators

Central pattern generators are small networks that contribute to generating animal locomotion. The models used to study gait generation and gait transition mechanisms often require biologically accurate neuron and synapse models, with high dimensionality and complex dynamics. Tuning the parameters of these models to elicit network dynamics compatible with gait features is not a trivial task, due to the impossibility of inferring a priori the effects of each parameter on the nonlinear system's emergent dynamics. In this paper we explore the use of global optimization strategies for parameter optimization in multigait central pattern generator (CPG) models with complex cell dynamics and minimal topology. We first consider an existing quadruped CPG model as a test bed for the objective function formulation, then proceed to optimize the parameters of a newly proposed multigait, interlimb hexapod CPG model. We successfully obtain hexapod gaits and prompt gait transitions by varying only control currents, while all CPG parameters, once optimized, are kept fixed. This mechanism of gait transitions is compatible with short-term synaptic plasticity.

Generation of locomotor‑like activity using monopolar intraspinal electrical microstimulation in rats

Severe spinal cord injury (SCI) affects the ability of functional standing and walking. As the locomotor central pattern generator (CPG) in the lumbosacral spinal cord can generate a regulatory signal for movement, it is feasible to activate CPG neural network using intra-spinal micro-stimulation (ISMS) to induce alternating patterns. The present study identified two special sites with the ability to activate the CPG neural network that are symmetrical about the posterior median sulcus in the lumbosacral spinal cord by ISMS in adult rats. A reversal of flexion and extension can occur in an attempt to generate a stepping movement of the bilateral hindlimb by either reversing the pulse polarity of the stimulus or changing the special site. Therefore, locomotor-like activity can be restored with monopolar intraspinal electrical stimulation on either special site. To verify the motor function regeneration of the paralyzed hindlimbs, a four-week locomotor training with ISMS applied to the special site in the SCI + ISMS group (n=12) was performed. Evaluations of motor function recovery using behavior, kinematics and physiological analyses, were used to assess hindlimb function and the results showed the stimulation at one special site can promote significant functional recovery of the bilateral hindlimbs (P<0.05). The present study suggested that motor function of paralyzed bilateral hindlimbs can be restored with monopolar ISMS.

Interdependence of cellular and network properties in respiratory rhythmogenesis

How breathing is generated by the preBötzinger Complex (preBötC) remains divided between two ideological frameworks, and the persistent sodium current (INaP) lies at the heart of this debate. Although INaP is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or "pacemaker" activity. In contrast, burstlet theory considers INaP dispensable because rhythm emerges from "pre-inspiratory" spiking activity driven by feed-forward network interactions. Using computational modeling, we discover that changes in spike shape can dissociate INaP from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and pre-inspiratory spiking without altering the role of INaP. Our results support a unifying hypothesis where INaP and excitatory network interactions, but not intrinsic bursting or pre-inspiratory spiking, are critical interdependent features of preBötC rhythmogenesis.

Reconstructing computational system dynamics from neural data with recurrent neural networks

Computational models in neuroscience usually take the form of systems of differential equations. The behaviour of such systems is the subject of dynamical systems theory. Dynamical systems theory provides a powerful mathematical toolbox for analysing neurobiological processes and has been a mainstay of computational neuroscience for decades. Recently, recurrent neural networks (RNNs) have become a popular machine learning tool for studying the non-linear dynamics of neural and behavioural processes by emulating an underlying system of differential equations. RNNs have been routinely trained on similar behavioural tasks to those used for animal subjects to generate hypotheses about the underlying computational mechanisms. By contrast, RNNs can also be trained on the measured physiological and behavioural data, thereby directly inheriting their temporal and geometrical properties. In this way they become a formal surrogate for the experimentally probed system that can be further analysed, perturbed and simulated. This powerful approach is called dynamical system reconstruction. In this Perspective, we focus on recent trends in artificial intelligence and machine learning in this exciting and rapidly expanding field, which may be less well known in neuroscience. We discuss formal prerequisites, different model architectures and training approaches for RNN-based dynamical system reconstructions, ways to evaluate and validate model performance, how to interpret trained models in a neuroscience context, and current challenges.

Active oscillations in microscale navigation

Living organisms routinely navigate their surroundings in search of better conditions, more food, or to avoid predators. Typically, animals do so by integrating sensory cues from the environment with their locomotor apparatuses. For single cells or small organisms that possess motility, fundamental physical constraints imposed by their small size have led to alternative navigation strategies that are specific to the microscopic world. Intriguingly, underlying these myriad exploratory behaviours or sensory functions is the onset of periodic activity at multiple scales, such as the undulations of cilia and flagella, the vibrations of hair cells, or the oscillatory shape modes of migrating neutrophils. Here, I explore oscillatory dynamics in basal microeukaryotes and hypothesize that these active oscillations play a critical role in enhancing the fidelity of adaptive sensorimotor integration.

Frontal cortex activity during the production of diverse social communication calls in marmoset monkeys

Vocal communication is essential for social behaviors in humans and non-human primates. While the frontal cortex is crucial to human speech production, its role in vocal production in non-human primates has long been questioned. It is unclear whether activities in the frontal cortex represent diverse vocal signals used in non-human primate communication. Here we studied single neuron activities and local field potentials (LFP) in the frontal cortex of male marmoset monkeys while the animal engaged in vocal exchanges with conspecifics in a social environment. We found that both single neuron activities and LFP were modulated by the production of each of the four major call types. Moreover, neural activities showed distinct patterns for different call types and theta-band LFP oscillations showed phase-locking to the phrases of twitter calls, suggesting a neural representation of vocalization features. Our results suggest important functions of the marmoset frontal cortex in supporting the production of diverse vocalizations in communication.

Coordinating upper limbs for octave playing on the piano via neuro-musculoskeletal modeling

Understanding the coordination of multiple biomechanical degrees of freedom in biological organisms is crucial for unraveling the neurophysiological control of sophisticated motor tasks. This study focuses on the cooperative behavior of upper-limb motor movements in the context of octave playing on the piano. While the vertebrate locomotor system has been extensively investigated, the coherence and precision timing of rhythmic movements in the upper-limb system remain incompletely understood. Inspired by the spinal cord neuronal circuits (central pattern generator, CPG), a computational neuro-musculoskeletal model is proposed to explore the coordination of upper-limb motor movements during octave playing across varying tempos and volumes. The proposed model incorporates a CPG-based nervous system, a physiologically-informed mechanical body, and a piano environment to mimic human joint coordination and expressiveness. The model integrates neural rhythm generation, spinal reflex circuits, and biomechanical muscle dynamics while considering piano playing quality and energy expenditure. Based on real-world human subject experiments, the model has been refined to study tempo transitions and volume control during piano playing. This computational approach offers insights into the neurophysiological basis of upper-limb motor coordination in piano playing and its relation to expressive features.

Nipple properties affect sensorimotor integration during bottle feeding in an infant pig model

Infant feeding is a critical neurological milestone in development defined by the coordination of muscles, peripheral nerves, and brainstem nuclei. In infants, milk flow rate is often limited to improve feeding performance without treating the underlying deficiencies in the sucking and swallowing processes. Modification of the neuromotor response via sensory information from the nipple during bottle feeding is an unexplored avenue for physiology-based interventions. In this study, we assessed how differences in nipple hole size and nipple stiffness affect sucking muscle activation and subsequent movement. We fabricated four bottle nipples of varying hole size and stiffness to determine how variation in nipple properties affects the sucking behavior of infant pigs. Our results demonstrate that sensory information from the nipple affects sucking motor output. Nipple hole sizes and stiffnesses with a larger milk flow rate resulted in greater muscle activity and kinematic movement. Additionally, our results suggest that sensorimotor interventions are better directed toward modulating tongue function rather than the mandible movements due to a greater response to sensory information. Understanding how sensory information influences infant feeding is instrumental in promoting effective infant feeding.

Motor neurons within a network use cell-type specific feedback mechanisms to constrain relationships among ion channel mRNAs

Recently, activity has been proposed as a primary feedback mechanism used by continuously bursting neurons to coordinate ion channel mRNA relationships that underlie stable output. However, some neuron types only have intermittent periods of activity and so may require alternative mechanisms that induce and constrain the appropriate ion channel profile in different states of activity. To address this, we used the pyloric dilator (PD; constitutively active) and the lateral gastric (LG; periodically active) neurons of the stomatogastric ganglion (STG) of the crustacean Cancer borealis. We experimentally stimulated descending inputs to the STG to cause release of neuromodulators known to elicit the active state of LG neurons and quantified the mRNA abundances and pairwise relationships of 11 voltage-gated ion channels in active and silent LG neurons. The same stimulus does not significantly alter PD activity. Activation of LG upregulated ion channel mRNAs and lead to a greater number of positively correlated pairwise channel mRNA relationships. Conversely, this stimulus did not induce major changes in ion channel mRNA abundances and relationships of PD cells, suggesting their ongoing activity is sufficient to maintain channel mRNA relationships even under changing modulatory conditions. In addition, we found that ion channel mRNA correlations induced by the active state of LG are influenced by a combination of activity- and neuromodulator-dependent feedback mechanisms. Interestingly, some of these same correlations are maintained by distinct mechanisms in PD, suggesting that these motor networks use distinct feedback mechanisms to coordinate the same mRNA relationships across neuron types.NEW & NOTEWORTHY Neurons use various feedback mechanisms to adjust and maintain their output. Here, we demonstrate that different neurons within the same network can use distinct signaling mechanisms to regulate the same ion channel mRNA relationships.

Mechanosensory Feedback in Lamprey Swimming Models and Applications in the Field of Spinal Cord Regeneration

The central pattern generator (CPG) in anguilliform swimming has served as a model for examining the neural basis of locomotion. This system has been particularly valuable for the development of mathematical models. As our biological understanding of the neural basis of locomotion has expanded, so too have these models. Recently, there have been significant advancements in our understanding of the critical role that mechanosensory feedback plays in robust locomotion. This work has led to a push in the field of mathematical modeling to incorporate mechanosensory feedback into CPG models. In this perspective piece, we review advances in the development of these models and discuss how newer complex models can support biological investigation. We highlight lamprey spinal cord regeneration as an area that can both inform these models and benefit from them.

Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion

The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.

Synchronous multi-segmental activity between metachronal waves controls locomotion speed in Drosophila larvae

The ability to adjust the speed of locomotion is essential for survival. In limbed animals, the frequency of locomotion is modulated primarily by changing the duration of the stance phase. The underlying neural mechanisms of this selective modulation remain an open question. Here, we report a neural circuit controlling a similarly selective adjustment of locomotion frequency in Drosophila larvae. Drosophila larvae crawl using peristaltic waves of muscle contractions. We find that larvae adjust the frequency of locomotion mostly by varying the time between consecutive contraction waves, reminiscent of limbed locomotion. A specific set of muscles, the lateral transverse (LT) muscles, co-contract in all segments during this phase, the duration of which sets the duration of the interwave phase. We identify two types of GABAergic interneurons in the LT neural network, premotor neuron A26f and its presynaptic partner A31c, which exhibit segmentally synchronized activity and control locomotor frequency by setting the amplitude and duration of LT muscle contractions. Altogether, our results reveal an inhibitory central circuit that sets the frequency of locomotion by controlling the duration of the period in between peristaltic waves. Further analysis of the descending inputs onto this circuit will help understand the higher control of this selective modulation.

Hebbian learning with elasticity explains how the spontaneous motor tempo affects music performance synchronization

A musician's spontaneous rate of movement, called spontaneous motor tempo (SMT), can be measured while spontaneously playing a simple melody. Data shows that the SMT influences the musician's tempo and synchronization. In this study we present a model that captures these phenomena. We review the results from three previously-published studies: solo musical performance with a pacing metronome tempo that is different from the SMT, solo musical performance without a metronome at a tempo that is faster or slower than the SMT, and duet musical performance between musicians with matching or mismatching SMTs. These studies showed, respectively, that the asynchrony between the pacing metronome and the musician's tempo grew as a function of the difference between the metronome tempo and the musician's SMT, musicians drifted away from the initial tempo toward the SMT, and the absolute asynchronies were smaller if musicians had matching SMTs. We hypothesize that the SMT constantly acts as a pulling force affecting musical actions at a tempo different from a musician's SMT. To test our hypothesis, we developed a model consisting of a non-linear oscillator with Hebbian tempo learning and a pulling force to the model's spontaneous frequency. While the model's spontaneous frequency emulates the SMT, elastic Hebbian learning allows for frequency learning to match a stimulus' frequency. To test our hypothesis, we first fit model parameters to match the data in the first of the three studies and asked whether this same model would explain the data the remaining two studies without further tuning. Results showed that the model's dynamics allowed it to explain all three experiments with the same set of parameters. Our theory offers a dynamical-systems explanation of how an individual's SMT affects synchronization in realistic music performance settings, and the model also enables predictions about performance settings not yet tested.

A Quantitative Analysis of Locomotor Patterns in Developing C. elegans

Adult animals display robust locomotion, yet the timeline and mechanisms of how juvenile animals acquire coordinated movements and how these movements evolve during development are not well understood. Recent advances in quantitative behavioral analyses have paved the way for investigating complex natural behaviors like locomotion. In this study, we tracked the swimming and crawling behaviors of the nematode Caenorhabditis elegans from postembryonic development through to adulthood. Our principal component analyses revealed that adult C. elegans swimming is low dimensional, suggesting that a small number of distinct postures, or eigenworms, account for most of the variance in the body shapes that constitute swimming behavior. Additionally, we found that crawling behavior in adult C. elegans is similarly low dimensional, corroborating previous studies. However, our analysis revealed that swimming and crawling are distinct gaits in adult animals, clearly distinguishable within the eigenworm space. Remarkably, young L1 larvae are capable of producing the postural shapes for swimming and crawling seen in adults, despite frequent instances of uncoordinated body movements. In contrast, late L1 larvae exhibit robust coordination of locomotion, while many neurons crucial for adult locomotion are still under development. In conclusion, this study establishes a comprehensive quantitative behavioral framework for understanding the neural basis of locomotor development, including distinct gaits such as swimming and crawling in C. elegans.

Gait quality after robot therapy compared with physiotherapy in the patient with incomplete spinal cord injured: A systematic review

Background

Spinal cord injury results in the interruption of neuronal conduction in the spinal cord, a condition that occurs in 0.1% of the world's population. This results in severe limitations in autonomy including locomotor function. Its recovery can be pursued through conventional isolated physiotherapeutic rehabilitation (overground walking training - OGT) or associated with Robot-assisted gait training - RAGT (e.g.: Lokomat ®).

Aim

The aim of this review is to compare the effectiveness of RAGT combined with conventional physiotherapy.

Methods

The databases consulted, from March 2022 to November 2022, were PubMed, PEDro, Cochrane Central Register of Controlled Trials (Cochrane Library) and CINAHL. RCT studies of people with incomplete spinal cord injuries treated with RAGT and/or OGT with the aim of improving walking were analysed.

Results

Among the 84 RCTs identified, 4 were included in the synthesis, with a total of 258 participants. The outcomes analysed concerned both locomotor function through lower limb muscle strength and the need for assistance in walking, using the WISCI-II scale and the LEMS. Robotic treatment stimulated the greatest improvements in the four studies; however, they were not always statistically significant.

Conclusion

A rehabilitation protocol combining RAGT with conventional physiotherapy is more effective than isolated OGT in improving ambulation in the subacute phase.

Dynamic models for musical rhythm perception and coordination

Rhythmicity permeates large parts of human experience. Humans generate various motor and brain rhythms spanning a range of frequencies. We also experience and synchronize to externally imposed rhythmicity, for example from music and song or from the 24-h light-dark cycles of the sun. In the context of music, humans have the ability to perceive, generate, and anticipate rhythmic structures, for example, "the beat." Experimental and behavioral studies offer clues about the biophysical and neural mechanisms that underlie our rhythmic abilities, and about different brain areas that are involved but many open questions remain. In this paper, we review several theoretical and computational approaches, each centered at different levels of description, that address specific aspects of musical rhythmic generation, perception, attention, perception-action coordination, and learning. We survey methods and results from applications of dynamical systems theory, neuro-mechanistic modeling, and Bayesian inference. Some frameworks rely on synchronization of intrinsic brain rhythms that span the relevant frequency range; some formulations involve real-time adaptation schemes for error-correction to align the phase and frequency of a dedicated circuit; others involve learning and dynamically adjusting expectations to make rhythm tracking predictions. Each of the approaches, while initially designed to answer specific questions, offers the possibility of being integrated into a larger framework that provides insights into our ability to perceive and generate rhythmic patterns.

A CPG-Based Versatile Control Framework for Metameric Earthworm-Like Robotic Locomotion

Annelids such as earthworms are considered to have central pattern generators (CPGs) that generate rhythms in neural circuits to coordinate the deformation of body segments for effective locomotion. At present, the states of earthworm-like robot segments are often assigned holistically and artificially by mimicking the earthworms' retrograde peristalsis wave, which is unable to adapt their gaits for variable environments and tasks. This motivates the authors to extend the bioinspired research from morphology to neurobiology by mimicking the CPG to build a versatile framework for spontaneous motion control. Here, the spatiotemporal dynamics is exploited from the coupled Hopf oscillators to not only unify the two existing gait generators for restoring temporal-symmetric phase-coordinated gaits and discrete gaits but also generate novel temporal-asymmetric phase-coordinated gaits. Theoretical and experimental tests consistently confirm that the introduction of temporal asymmetry improves the robot's locomotion performance. The CPG-based controller also enables seamless online switching of locomotion gaits to avoid abrupt changes, sharp stops, and starts, thus improving the robot's adaptability in variable working scenarios.

Scanning behaviour in ants: an interplay between random-rate processes and oscillators

At the start of a journey home or to a foraging site, ants often stop, interrupting their forward movement, turn on the spot a number of times, and fixate in different directions. These scanning bouts are thought to provide visual information for choosing a path to travel. The temporal organization of such scanning bouts has implications about the neural organisation of navigational behaviour. We examined (1) the temporal distribution of the start of such scanning bouts and (2) the dynamics of saccadic body turns and fixations that compose a scanning bout in Australian desert ants, Melophorus bagoti, as they came out of a walled channel onto open field at the start of their homeward journey. Ants were caught when they neared their nest and displaced to different locations to start their journey home again. The observed parameters were mostly similar across familiar and unfamiliar locations. The turning angles of saccadic body turning to the right or left showed some stereotypy, with a peak just under 45°. The direction of such saccades appears to be determined by a slow oscillatory process as described in other insect species. In timing, however, both the distribution of inter-scanning-bout intervals and individual fixation durations showed exponential characteristics, the signature for a random-rate or Poisson process. Neurobiologically, therefore, there must be some process that switches behaviour (starting a scanning bout or ending a fixation) with equal probability at every moment in time. We discuss how chance events in the ant brain that occasionally reach a threshold for triggering such behaviours can generate the results.

Neuroscience: Moving thoughts control insulin release

Insulin release has mostly been studied in the context of metabolic signals. An electrophysiology approach in Drosophila now reveals regulation of insulin-producing cell activity by neuronal circuits controlling locomotion. Even without actual movement, activating these circuits is sufficient to inhibit neuropeptide release.

The Expression of Affective Temperaments in Cystic Fibrosis Patients: Psychopathological Associations and Possible Neurobiological Mechanisms

The aim of this study was to investigate the association between Cystic Fibrosis (CF) and affective temperaments, considering the relevance of ionic balances in neural excitability, as a possible neurobiological basis for temperamental expression. A cross-sectional study involving 55 adult CF patients was conducted. Sociodemographic, clinical and therapeutic characteristics, temperamental and personality dispositions and depressive and anxiety symptoms were evaluated through standardized semi-structured and structured interviews. The majority of the enrolled CF patients were receiving Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) therapy (72.7%), and most of them had hyperthymic temperament predominance (29.1%). Different TEMPS-A (Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire) dimensions were not associated with the type of CF phenotype-related mutation or with the use of CFTR-modulator therapy. However, a tendency towards irritability was noted in patients not undergoing CFTR modulator therapy (6.7 ± 4.72 vs. 4.7 ± 4.33; p = 0.13). In light of the limitations imposed by the cross-sectional nature of the study, a hyperthymic temperament was found to be protective against current or lifetime psychopathologic events, whereas the other temperaments were associated with positive psychopathological anamnesis. Based on the measurement of temperament profiles and the study of their associations with clinically relevant variables, we argue that subjecting CF patients to such a temperament assessment could prove beneficial in the transition towards integrated and personalized care.