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.

Azimuthal invariance to looming stimuli in the Drosophila giant fiber escape circuit.

Spatially invariant feature detection is a property of many visual systems that rely on visual information provided by two eyes. However, how information across both eyes is integrated for invariant feature detection is not fully understood. Here, we investigated spatial invariance of looming responses in descending neurons (DNs) of Drosophila melanogaster. We found that multiple looming responsive DNs integrate looming information across both eyes, even though their dendrites are restricted to a single visual hemisphere. One DN, the giant fiber (GF), responds invariantly to looming stimuli across tested azimuthal locations. We confirmed visual information propagates to the GF from the contralateral eye, through an unidentified pathway, and demonstrated that the absence of this pathway alters GF responses to looming stimuli presented to the ipsilateral eye. Our data highlight a role for bilateral visual integration in generating consistent, looming-evoked escape responses that are robust across different stimulus locations and parameters.

Computational Modeling of Spinal Locomotor Circuitry in the Age of Molecular Genetics.

Neuronal circuits in the spinal cord are essential for the control of locomotion. They integrate supraspinal commands and afferent feedback signals to produce coordinated rhythmic muscle activations necessary for stable locomotion. For several decades, computational modeling has complemented experimental studies by providing a mechanistic rationale for experimental observations and by deriving experimentally testable predictions. This symbiotic relationship between experimental and computational approaches has resulted in numerous fundamental insights. With recent advances in molecular and genetic methods, it has become possible to manipulate specific constituent elements of the spinal circuitry and relate them to locomotor behavior. This has led to computational modeling studies investigating mechanisms at the level of genetically defined neuronal populations and their interactions. We review literature on the spinal locomotor circuitry from a computational perspective. By reviewing examples leading up to and in the age of molecular genetics, we demonstrate the importance of computational modeling and its interactions with experiments. Moving forward, neuromechanical models with neuronal circuitry modeled at the level of genetically defined neuronal populations will be required to further unravel the mechanisms by which neuronal interactions lead to locomotor behavior.

Organization of the core respiratory network: Insights from optogenetic and modeling studies.

The circuit organization within the mammalian brainstem respiratory network, specifically within and between the pre-Bötzinger (pre-BötC) and Bötzinger (BötC) complexes, and the roles of these circuits in respiratory pattern generation are continuously debated. We address these issues with a combination of optogenetic experiments and modeling studies. We used transgenic mice expressing channelrhodopsin-2 under the VGAT-promoter to investigate perturbations of respiratory circuit activity by site-specific photostimulation of inhibitory neurons within the pre-BötC or BötC. The stimulation effects were dependent on the intensity and phase of the photostimulation. Specifically: (1) Low intensity (≤ 1.0 mW) pulses delivered to the pre-BötC during inspiration did not terminate activity, whereas stronger stimulations (≥ 2.0 mW) terminated inspiration. (2) When the pre-BötC stimulation ended in or was applied during expiration, rebound activation of inspiration occurred after a fixed latency. (3) Relatively weak sustained stimulation (20 Hz, 0.5-2.0 mW) of pre-BötC inhibitory neurons increased respiratory frequency, while a further increase of stimulus intensity (> 3.0 mW) reduced frequency and finally (≥ 5.0 mW) terminated respiratory oscillations. (4) Single pulses (0.2-5.0 s) applied to the BötC inhibited rhythmic activity for the duration of the stimulation. (5) Sustained stimulation (20 Hz, 0.5-3.0 mW) of the BötC reduced respiratory frequency and finally led to apnea. We have revised our computational model of pre-BötC and BötC microcircuits by incorporating an additional population of post-inspiratory inhibitory neurons in the pre-BötC that interacts with other neurons in the network. This model was able to reproduce the above experimental findings as well as previously published results of optogenetic activation of pre-BötC or BötC neurons obtained by other laboratories. The proposed organization of pre-BötC and BötC circuits leads to testable predictions about their specific roles in respiratory pattern generation and provides important insights into key circuit interactions operating within brainstem respiratory networks.

State-dependent rhythmogenesis and frequency control in a half-center locomotor CPG.

The spinal locomotor central pattern generator (CPG) generates rhythmic activity with alternating flexion and extension phases. This rhythmic pattern is likely to result from inhibitory interactions between neural populations representing flexor and extensor half-centers. However, it is unclear whether the flexor-extensor CPG has a quasi-symmetric organization with both half-centers critically involved in rhythm generation, features an asymmetric organization with flexor-driven rhythmogenesis, or comprises a pair of intrinsically rhythmic half-centers. There are experimental data that support each of the above concepts but appear to be inconsistent with the others. In this theoretical/modeling study, we present and analyze a CPG model architecture that can operate in different regimes consistent with the above three concepts depending on conditions, which are defined by external excitatory drives to CPG half-centers. We show that control of frequency and phase durations within each regime depends on network dynamics, defined by the regime-dependent expression of the half-centers' intrinsic rhythmic capabilities and the operating phase transition mechanisms (escape vs. release). Our study suggests state dependency in locomotor CPG operation and proposes explanations for seemingly contradictory experimental data. NEW & NOTEWORTHY Our theoretical/modeling study focuses on the analysis of locomotor central pattern generators (CPGs) composed of conditionally bursting half-centers coupled with reciprocal inhibition and receiving independent external drives. We show that this CPG framework can operate in several regimes consistent with seemingly contradictory experimental data. In each regime, we study how intrinsic dynamics and phase-switching mechanisms control oscillation frequency and phase durations. Our results provide insights into the organization of spinal circuits controlling locomotion.

Optogenetic activation of excitatory premotor interneurons is sufficient to generate coordinated locomotor activity in larval zebrafish.

Neural networks in the spinal cord can generate locomotion in the absence of rhythmic input from higher brain structures or sensory feedback because they contain an intrinsic source of excitation. However, the molecular identity of the spinal interneurons underlying the excitatory drive within the locomotor circuit has remained unclear. Using optogenetics, we show that activation of a molecularly defined class of ipsilateral premotor interneurons elicits locomotion. These interneurons represent the excitatory module of the locomotor networks and are sufficient to produce a coordinated swimming pattern in zebrafish. They correspond to the V2a interneuron class and express the transcription factor Chx10. They produce sufficient excitatory drive within the spinal networks to generate coordinated locomotor activity. Therefore, our results define the V2a interneurons as the excitatory module within the spinal locomotor networks that is sufficient to initiate and maintain locomotor activity.

Decoding the rules of recruitment of excitatory interneurons in the adult zebrafish locomotor network.

Neural networks in the spinal cord transform signals from the brain into coordinated locomotor movements. An optimal adjustment of the speed of locomotion entails a precise order of recruitment of interneurons underlying excitation within these networks. However, the mechanisms encoding the recruitment threshold of excitatory interneurons have remained unclear. Here we show, using a juvenile/adult zebrafish preparation, that excitatory V2a interneurons are incrementally recruited with increased swimming frequency. The order of recruitment is not imprinted by the topography or the input resistance of the V2a interneurons. Rather, it is determined by scaling the effect of excitatory synaptic currents by the input resistance. We also show that the locomotor networks are composed of multiple microcircuits encompassing subsets of V2a interneurons and motoneurons that are recruited in a continuum with increased swimming speeds. Thus, our results provide insights into the organization and mechanisms determining the recruitment of spinal microcircuits to ensure optimal execution of locomotor movements.

Origin of excitation underlying locomotion in the spinal circuit of zebrafish.

Neural circuits in the spinal cord transform instructive signals from the brain into well-coordinated locomotor movements by virtue of rhythm-generating components. Although evidence suggests that excitatory interneurons are the essence of locomotor rhythm generation, their molecular identity and the assessment of their necessity have remained unclear. Here we show, using larval zebrafish, that V2a interneurons represent an intrinsic source of excitation necessary for the normal expression of the locomotor rhythm. Acute and selective ablation of these interneurons increases the threshold of induction of swimming activity, decreases the burst frequency, and alters the coordination of the rostro-caudal propagation of activity. Thus, our results argue that V2a interneurons represent a source of excitation that endows the spinal circuit with the capacity to generate locomotion.

Pattern of innervation and recruitment of different classes of motoneurons in adult zebrafish.

In vertebrates, spinal circuits drive rhythmic firing in motoneurons in the appropriate sequence to produce locomotor movements. These circuits become active early during development and mature gradually to acquire the flexibility necessary to accommodate the increased behavioral repertoire of adult animals. The focus here is to elucidate how different pools of motoneurons are organized and recruited and how membrane properties contribute to their mode of operation. For this purpose, we have used the in vitro preparation of adult zebrafish. We show that different motoneuron pools are organized in a somatotopic fashion in the motor column related to the type of muscle fibers (slow, intermediate, fast) they innervate. During swimming, the different motoneuron pools are recruited in a stepwise manner from slow, to intermediate, to fast to cover the full range of locomotor frequencies seen in intact animals. The spike threshold, filtering properties, and firing patterns of the different motoneuron pools are graded in a manner that relates to their order of recruitment. Our results thus show that motoneurons in adult zebrafish are organized into distinct modules, each with defined locations, properties, and recruitment patterns tuned to precisely match the muscle properties and hence produce swimming of different speeds and modalities.

Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons.

Synapses are often precisely organized on dendritic arbors, yet the role of synaptic topography in dendritic integration remains poorly understood. Utilizing electron microscopy (EM) connectomics we investigate synaptic topography in Drosophila melanogaster looming circuits, focusing on retinotopically tuned visual projection neurons (VPNs) that synapse onto descending neurons (DNs). Synapses of a given VPN type project to non-overlapping regions on DN dendrites. Within these spatially constrained clusters, synapses are not retinotopically organized, but instead adopt near random distributions. To investigate how this organization strategy impacts DN integration, we developed multicompartment models of DNs fitted to experimental data and using precise EM morphologies and synapse locations. We find that DN dendrite morphologies normalize EPSP amplitudes of individual synaptic inputs and that near random distributions of synapses ensure linear encoding of synapse numbers from individual VPNs. These findings illuminate how synaptic topography influences dendritic integration and suggest that linear encoding of synapse numbers may be a default strategy established through connectivity and passive neuron properties, upon which active properties and plasticity can then tune as needed.

Neuronal identity control at the resolution of a single transcription factor isoform.

The brain exhibits remarkable neuronal diversity which is critical for its functional integrity. From the sheer number of cell types emerging from extensive transcriptional, morphological, and connectome datasets, the question arises of how the brain is capable of generating so many unique identities. 'Terminal selectors' are transcription factors hypothesized to determine the final identity characteristics in post-mitotic cells. Which transcription factors function as terminal selectors and the level of control they exert over different terminal characteristics are not well defined. Here, we establish a novel role for the transcription factor broad as a terminal selector in Drosophila melanogaster. We capitalize on existing large sequencing and connectomics datasets and employ a comprehensive characterization of terminal characteristics including Perturb-seq and whole-cell electrophysiology. We find a single isoform broad-z4 serves as the switch between the identity of two visual projection neurons LPLC1 and LPLC2. Broad-z4 is natively expressed in LPLC1, and is capable of transforming the transcriptome, morphology, and functional connectivity of LPLC2 cells into LPLC1 cells when perturbed. Our comprehensive work establishes a single isoform as the smallest unit underlying an identity switch, which may serve as a conserved strategy replicated across developmental programs.

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model.

Objective.Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locomotor circuits. Past neuromechanical models proposed control of locomotion either driven by central pattern generators (CPGs) with simple sensory commands or by a purely reflex-based network regulated by state-machine mechanisms, which activate and deactivate reflexes depending on the detected gait cycle phases. However, the physiological interpretation of these state machines remains unclear. Here, we present a physiologically plausible model to investigate spinal control and modulation of human locomotion.Approach.We propose a bio-inspired controller composed of two coupled CPGs that produce the rhythm and pattern, and a reflex-based network simulating low-level reflex pathways and Renshaw cells. This reflex network is based on leaky-integration neurons, and the whole system does not rely on changing reflex gains according to the gait cycle state. The musculoskeletal model is composed of a skeletal structure and nine muscles per leg generating movement in sagittal plane.Main results.Optimizing the open parameters for effort minimization and stability, human kinematics and muscle activation naturally emerged. Furthermore, when CPGs were not activated, periodic motion could not be achieved through optimization, suggesting the necessity of this component to generate rhythmic behavior without a state machine mechanism regulating reflex activation. The controller could reproduce ranges of speeds from 0.3 to 1.9 m s-1. The results showed that the net influence of feedback on motoneurons (MNs) during perturbed locomotion is predominantly inhibitory and that the CPGs provide the timing of MNs' activation by exciting or inhibiting muscles in specific gait phases.Significance.The proposed bio-inspired controller could contribute to our understanding of locomotor circuits of the intact spinal cord and could be used to study neuromotor disorders.

Sensory Feedback and Central Neuronal Interactions in Mouse Locomotion.

Locomotion is a complex process involving specific interactions between the central neural controller and the mechanical components of the system. The basic rhythmic activity generated by locomotor circuits in the spinal cord defines rhythmic limb movements and their central coordination. The operation of these circuits is modulated by sensory feedback from the limbs providing information about the state of the limbs and the body. However, the specific role and contribution of central interactions and sensory feedback in the control of locomotor gait and posture remain poorly understood. We use biomechanical data on quadrupedal locomotion in mice and recent findings on the organization of neural interactions within the spinal locomotor circuitry to create and analyze a tractable mathematical model of mouse locomotion. The model includes a simplified mechanical model of the mouse body with four limbs and a central controller composed of four rhythm generators, each operating as a state machine controlling the state of one limb. Feedback signals characterize the load and extension of each limb as well as postural stability (balance). We systematically investigate and compare several model versions and compare their behavior to existing experimental data on mouse locomotion. Our results highlight the specific roles of sensory feedback and some central propriospinal interactions between circuits controlling fore and hind limbs for speed-dependent gait expression. Our models suggest that postural imbalance feedback may be critically involved in the control of swing-to-stance transitions in each limb and the stabilization of walking direction.

Initiation of locomotion in adult zebrafish.

Motor behavior is generated by specific neural circuits. Those producing locomotion are located in the spinal cord, and their activation depends on descending inputs from the brain or on sensory inputs. In this study, we have used an in vitro brainstem-spinal cord preparation from adult zebrafish to localize a region where stimulation of descending inputs can induce sustained locomotor activity. We show that a brief stimulation of descending inputs at the junction between the brainstem and spinal cord induces long-lasting swimming activity. The swimming frequencies induced are remarkably similar to those observed in freely moving adult fish, arguing that the induced locomotor episode is highly physiological. The motor pattern is mediated by activation of ionotropic glutamate and glycine receptors in the spinal cord and is not the result of synaptic interactions between neurons at the site of the stimulation in the brainstem. We also compared the activity of motoneurons during locomotor activity induced by electrical stimulation of descending inputs and by exogenously applied NMDA. Prolonged NMDA application changes the shape of the synaptic drive and action potentials in motoneurons. When escape activity occurs, the swimming activity in the intact zebrafish was interrupted and some of the motoneurons involved became inhibited in vitro. Thus, the descending inputs seem to act as a switch to turn on the activity of the spinal locomotor network in the caudal spinal cord. We propose that recurrent synaptic activity within the spinal locomotor circuits can transform a brief input into a well coordinated and long-lasting swimming pattern.

Contribution of Afferent Feedback to Adaptive Hindlimb Walking in Cats: A Neuromusculoskeletal Modeling Study.

Mammalian locomotion is generated by central pattern generators (CPGs) in the spinal cord, which produce alternating flexor and extensor activities controlling the locomotor movements of each limb. Afferent feedback signals from the limbs are integrated by the CPGs to provide adaptive control of locomotion. Responses of CPG-generated neural activity to afferent feedback stimulation have been previously studied during fictive locomotion in immobilized cats. Yet, locomotion in awake, behaving animals involves dynamic interactions between central neuronal circuits, afferent feedback, musculoskeletal system, and environment. To study these complex interactions, we developed a model simulating interactions between a half-center CPG and the musculoskeletal system of a cat hindlimb. Then, we analyzed the role of afferent feedback in the locomotor adaptation from a dynamic viewpoint using the methods of dynamical systems theory and nullcline analysis. Our model reproduced limb movements during regular cat walking as well as adaptive changes of these movements when the foot steps into a hole. The model generates important insights into the mechanism for adaptive locomotion resulting from dynamic interactions between the CPG-based neural circuits, the musculoskeletal system, and the environment.

Multiple Rhythm-Generating Circuits Act in Tandem with Pacemaker Properties to Control the Start and Speed of Locomotion.

In vertebrates, specific command centers in the brain can selectively drive slow-explorative or fast-speed locomotion. However, it remains unclear how the locomotor central pattern generator (CPG) processes descending drive into coordinated locomotion. Here, we reveal, in adult zebrafish, a logic of the V2a interneuron rhythm-generating circuits involving recurrent and hierarchical connectivity that acts in tandem with pacemaker properties to provide an ignition and gear-shift mechanism to start locomotion and change speed. A comprehensive mapping of synaptic connections reveals three recurrent circuit modules engaged sequentially to increase locomotor speed. The connectivity between V2a interneurons of different modules displayed a clear asymmetry in favor of connections from faster to slower modules. The interplay between V2a interneuron pacemaker properties and their organized connectivity provides a mechanism for locomotor initiation and speed control. Thus, our results provide mechanistic insights into how the spinal CPG transforms descending drive into locomotion and align its speed with the initial intention.

The interaction of positive and negative sensory feedback loops in dynamic regulation of a motor pattern.

In many rhythmic behaviors, phasic sensory feedback modifies the motor pattern. This modification is assumed to depend on feedback sign (positive vs. negative). While on a phenomenological level feedback sign is well defined, many sensory pathways also process antagonistic, and possibly contradictory, sensory information. We here model the locust flight pattern generator and proprioceptive feedback provided by the tegula wing receptor to test the functional significance of sensory pathways processing antagonistic information. We demonstrate that the tegula provides delayed positive feedback via interneuron 301, while all other pathways provide negative feedback. Contradictory to previous assumptions, the increase of wing beat frequency when the tegula is activated during flight is due to the positive feedback. By use of an abstract model we reveal that the regulation of motor pattern frequency by sensory feedback critically depends on the interaction of positive and negative feedback, and thus on the weighting of antagonistic pathways.

Computational modeling of brainstem circuits controlling locomotor frequency and gait.

A series of recent studies identified key structures in the mesencephalic locomotor region and the caudal brainstem of mice involved in the initiation and control of slow (exploratory) and fast (escape-type) locomotion and gait. However, the interactions of these brainstem centers with each other and with the spinal locomotor circuits are poorly understood. Previously we suggested that commissural and long propriospinal interneurons are the main targets for brainstem inputs adjusting gait (Danner et al., 2017). Here, by extending our previous model, we propose a connectome of the brainstem-spinal circuitry and suggest a mechanistic explanation of the operation of brainstem structures and their roles in controlling speed and gait. We suggest that brainstem control of locomotion is mediated by two pathways, one controlling locomotor speed via connections to rhythm generating circuits in the spinal cord and the other providing gait control by targeting commissural and long propriospinal interneurons.

Frequency control of motor patterning by negative sensory feedback.

The sensory system plays a key role in the generation of behavior by providing the nervous system with information about the environment and feedback about body movements such that motor output can continuously be adapted to changing circumstances. Although the effects of sensory organs on nervous system function have been demonstrated in many systems, the impact of sensory activity has rarely been studied in conditions in which motor output and sensory activity can interact as they do in behaving animals. In such situations, emergent properties may surface and govern the characteristics of the motor system. We studied the dynamics of sensorimotor interaction with a combination of electrophysiological experiments and computational modeling in the locust flight pattern generator, including its sensory components. The locust flight motor output is produced by a central pattern generator that interacts with phasic sensory feedback from the tegula, a proprioceptor that signals downstroke movement of the wing. We modeled the flight control system, and we tested the model predictions by replacing tegula feedback in the animal with artificial feedback through computer-controlled electric stimulation of the appropriate sensory nerves. With reference to the cycle frequency in the locust flight rhythm, our results show that motor patterns can be regulated via the variation of sensory feedback loops. In closed-loop conditions, tegula feedback strength determines cycle frequency in the model and the biological preparation such that stronger feedback results in lower frequencies. This regulatory mechanism appears to be a general emergent property of negative feedback systems.

Motor pattern selection by combinatorial code of interneuronal pathways.

We use a modeling approach to examine ideas derived from physiological network analyses, pertaining to the switch of a motor control network between two opposite control modes. We studied the femur-tibia joint control system of the insect leg, and its switch between resistance reflex in posture control and "active reaction" in walking, both elicited by the same sensory input. The femur-tibia network was modeled by fitting the responses of model neurons to those obtained in animals. The strengths of 16 interneuronal pathways that integrate sensory input were then assigned three different values and varied independently, generating a database of more than 43 million network variants. We demonstrate that the same neural network can produce the two different behaviors, depending on the combinatorial code of interneuronal pathways. That is, a switch between behaviors, such as standing to walking, can be brought about by altering the strengths of selected sensory integration pathways.