scholarly journals Data-driven analysis of motor activity implicates 5-HT2A neurons in backward locomotion of larval Drosophila

2018 ◽  
Author(s):  
Jeonghyuk Park ◽  
Shu Kondo ◽  
Hiromu Tanimoto ◽  
Hiroshi Kohsaka ◽  
Akinao Nose
Keyword(s):  
Neural Circuits ◽  
Central Pattern Generators ◽  
Data Driven ◽  
Neural Dynamics ◽  
Neural Population ◽  
Fictive Locomotion ◽  
Motor Patterns ◽  
Light Stimuli ◽  
Pattern Generators ◽  
Imaging Conditions

ABSTRACTRhythmic animal behaviors are regulated in part by neural circuits called the central pattern generators (CPGs). Classifying neural population activities correlated with body movements and identifying the associated component neurons are critical steps in understanding CPGs. Previous methods that classify neural dynamics obtained by dimension reduction algorithms often require manual optimization which could be laborious and preparation-specific. Here, we present a simpler and more flexible method that is based on the pre-trained convolutional neural network model VGG-16 and unsupervised learning, and successfully classifies the fictive motor patterns in Drosophila larvae under various imaging conditions. We also used voxel-wise correlation mapping to identify neurons associated with motor patterns. By applying these methods to neurons targeted by 5-HT2A-GAL4, which we generated by the CRISPR/Cas9-system, we identified two classes of interneurons, termed Seta and Leta, which are specifically active during backward but not forward fictive locomotion. Optogenetic activation of Seta and Leta neurons increased backward locomotion. Conversely, thermogenetic inhibition of 5-HT2A-GAL4 neurons or application of a 5-HT2 antagonist decreased backward locomotion induced by noxious light stimuli. This study establishes an accelerated pipeline for activity profiling and cell identification in larval Drosophila and implicates the serotonergic system in the modulation of backward locomotion.

scholarly journals Augmenting Flexibility: Mutual Inhibition Between Inhibitory Neurons Expands Functional Diversity

2020 ◽  
Author(s):  
Belle Liu ◽  
Alexander James White ◽  
Chung-Chuan Lo
Keyword(s):  
Dynamical Systems ◽  
Bifurcation Theory ◽  
Neural Circuits ◽  
Feedback Inhibition ◽  
Central Pattern Generators ◽  
Recurrent Network ◽  
Inhibitory Neurons ◽  
Mutual Inhibition ◽  
Input Type ◽  
Pattern Generators

AbstractOne of the most intriguing observations of recurrent neural circuits is their flexibility. Seemingly, this flexibility extends far beyond the ability to learn, but includes the ability to use learned procedures to respond to novel situations. Here, we report that this flexibility arises from the synergistic interplay between recurrent mutual excitation and recurrent mutual inhibition. Specifically, we show that mutual inhibition is critical in expanding the functionality of the circuit, far beyond what feedback inhibition alone can accomplish. By taking advantage of dynamical systems theory and bifurcation analysis, we show mutual inhibition doubles the number of cusp bifurcations in the system in small neural circuits. As a concrete example, we build a simulation model of a class of functional motifs we call Coupled Recurrent inhibitory and Recurrent excitatory Loops (CRIRELs). These CRIRELs have the advantage of being multi-functional, performing a plethora of functions, including decisions, switches, toggles, central pattern generators, depending solely on the input type. We then use bifurcation theory to show how mutual inhibition gives rise to this broad repertoire of possible functions. Finally, we demonstrate how this trend also holds for larger networks, and how mutual inhibition greatly expands the amount of information a recurrent network can hold.

scholarly journals Central pattern generators in the turtle spinal cord: selection among the forms of motor behaviors

2018 ◽  
Vol 119 (2) ◽  
pp. 422-440 ◽  
Author(s):  
Paul S. G. Stein
Keyword(s):  
Spinal Cord ◽  
Motor Pattern ◽  
Central Pattern Generators ◽  
Knee Extensor ◽  
Motor Patterns ◽  
Motor Behaviors ◽  
Multiple Behaviors ◽  
Pattern Generators ◽  
Electrical Stimuli

Neuronal networks in the turtle spinal cord have considerable computational complexity even in the absence of connections with supraspinal structures. These networks contain central pattern generators (CPGs) for each of several behaviors, including three forms of scratch, two forms of swim, and one form of flexion reflex. Each behavior is activated by a specific set of cutaneous or electrical stimuli. The process of selection among behaviors within the spinal cord has multisecond memories of specific motor patterns. Some spinal cord interneurons are partially shared among several CPGs, whereas other interneurons are active during only one type of behavior. Partial sharing is a proposed mechanism that contributes to the ability of the spinal cord to generate motor pattern blends with characteristics of multiple behaviors. Variations of motor patterns, termed deletions, assist in characterization of the organization of the pattern-generating components of CPGs. Single-neuron recordings during both normal and deletion motor patterns provide support for a CPG organizational structure with unit burst generators (UBGs) whose members serve a direction of a specific degree of freedom of the hindlimb, e.g., the hip-flexor UBG, the hip-extensor UBG, the knee-flexor UBG, the knee-extensor UBG, etc. The classic half-center hypothesis that includes all the hindlimb flexors in a single flexor half-center and all the hindlimb extensors in a single extensor half-center lacks the organizational complexity to account for the motor patterns produced by turtle spinal CPGs. Thus the turtle spinal cord is a valuable model system for studies of mechanisms responsible for selection and generation of motor behaviors. NEW & NOTEWORTHY The concept of the central pattern generator (CPG) is a major tenet in motor neuroethology that has influenced the design and interpretations of experiments for over a half century. This review concentrates on the turtle spinal cord and describes studies from the 1970s to the present responsible for key developments in understanding the CPG mechanisms responsible for the selection and production of coordinated motor patterns during turtle hindlimb motor behaviors.

Intrinsic and Extrinsic Modulation of a Single Central Pattern Generating Circuit

2000 ◽  
Vol 84 (3) ◽  
pp. 1186-1193 ◽  
Author(s):  
Peter T. Morgan ◽  
Ray Perrins ◽  
Philip E. Lloyd ◽  
Klaudiusz R. Weiss
Keyword(s):  
Neural Circuits ◽  
Central Pattern Generators ◽  
Motor Program ◽  
Pattern Generator ◽  
Motor Programs ◽  
Appetitive Behavior ◽  
Protraction Phase ◽  
Pattern Generators ◽  
Rhythmic Behaviors ◽  
Appetitive Behaviors

Intrinsic and extrinsic neuromodulation are both thought to be responsible for the flexibility of the neural circuits (central pattern generators) that control rhythmic behaviors. Because the two forms of modulation have been studied in different circuits, it has been difficult to compare them directly. We find that the central pattern generator for biting in Aplysia is modulated both extrinsically and intrinsically. Both forms of modulation increase the frequency of motor programs and shorten the duration of the protraction phase. Extrinsic modulation is mediated by the serotonergic metacerebral cell (MCC) neurons and is mimicked by application of serotonin. Intrinsic modulation is mediated by the cerebral peptide-2 (CP-2) containing CBI-2 interneurons and is mimicked by application of CP-2. Since the effects of CBI-2 and CP-2 occlude each other, the modulatory actions of CBI-2 may be mediated by CP-2 release. Although the effects of intrinsic and extrinsic modulation are similar, the neurons that mediate them are active predominantly at different times, suggesting a specialized role for each system. Metacerebral cell (MCC) activity predominates in the preparatory (appetitive) phase and thus precedes the activation of CBI-2 and biting motor programs. Once the CBI-2s are activated and the biting motor program is initiated, MCC activity declines precipitously. Hence extrinsic modulation prefacilitates biting, whereas intrinsic modulation occurs during biting. Since biting inhibits appetitive behavior, intrinsic modulation cannot be used to prefacilitate biting in the appetitive phase. Thus the sequential use of extrinsic and intrinsic modulation may provide a means for premodulation of biting without the concomitant disruption of appetitive behaviors.

scholarly journals Evolution of central pattern generators and rhythmic behaviours

2016 ◽  
Vol 371 (1685) ◽  
pp. 20150057 ◽  
Author(s):  
Paul S. Katz
Keyword(s):  
Large Scale ◽  
Neural Circuits ◽  
Motor Pattern ◽  
Parallel Evolution ◽  
Central Pattern Generators ◽  
Neural Mechanism ◽  
Rhythmic Movements ◽  
Biological Organization ◽  
Gradual Evolution ◽  
Pattern Generators

Comparisons of rhythmic movements and the central pattern generators (CPGs) that control them uncover principles about the evolution of behaviour and neural circuits. Over the course of evolutionary history, gradual evolution of behaviours and their neural circuitry within any lineage of animals has been a predominant occurrence. Small changes in gene regulation can lead to divergence of circuit organization and corresponding changes in behaviour. However, some behavioural divergence has resulted from large-scale rewiring of the neural network. Divergence of CPG circuits has also occurred without a corresponding change in behaviour. When analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also evolved independently in separate lineages. The evolution of CPGs and rhythmic behaviours shows that although most behaviours and neural circuits are highly conserved, the nature of the behaviour does not dictate the neural mechanism and that the presence of homologous neural components does not determine the behaviour. This suggests that although behaviour is generated by neural circuits, natural selection can act separately on these two levels of biological organization.

Endogenous Motor Neuron Properties Contribute to a Program-Specific Phase of Activity in the Multifunctional Feeding Central Pattern Generator of Aplysia

2007 ◽  
Vol 98 (1) ◽  
pp. 29-42 ◽  
Author(s):  
Geidy E. Serrano ◽  
Clarissa Martínez-Rubio ◽  
Mark W. Miller
Keyword(s):  
Motor Neuron ◽  
Motor Neurons ◽  
Central Pattern Generators ◽  
Ingestive Behavior ◽  
Membrane Properties ◽  
Motor Patterns ◽  
Effector System ◽  
Bilateral Pair ◽  
Pattern Generators ◽  
Specific Phase

Multifunctional central pattern generators (CPGs) are circuits of neurons that can generate manifold actions from a single effector system. This study examined a bilateral pair of pharyngeal motor neurons, designated B67, that participate in the multifunctional feeding network of Aplysia californica. Fictive buccal motor programs (BMPs) were elicited with four distinct stimulus paradigms to assess the activity of B67 during ingestive versus egestive patterns. In both classes of programs, B67 fired during the phase of radula protraction and received a potent inhibitory postsynaptic potential (IPSP) during fictive radula retraction. When programs were ingestive, the retraction phase IPSP exhibited a depolarizing sag and was followed by a postinhibitory rebound (PIR) that could generate a postretraction phase of impulse activity. When programs were egestive, the depolarizing sag potential and PIR were both diminished or were not present. Examination of the membrane properties of B67 disclosed a cesium-sensitive depolarizing sag, a corresponding Ih-like current, and PIR in its responses to hyperpolarizing pulses. Direct IPSPs originating from the influential CPG retraction phase interneuron B64 were also found to activate the sag potential and PIR of B67. Dopamine, a modulator that can promote ingestive behavior in this system, enhanced the sag potential, Ih-like current, and PIR of B67. Finally, a pharyngeal muscle contraction followed the radula retraction phase of ingestive, but not egestive motor patterns. It is proposed that regulation of the intrinsic properties of this motor neuron can contribute to generating a program-specific phase of motor activity.

scholarly journals Behavioral evidence for nested central pattern generator control of Drosophila grooming

2020 ◽  
Author(s):  
Primoz Ravbar ◽  
Neil Zhang ◽  
Julie H. Simpson
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Neural Circuits ◽  
Central Pattern Generators ◽  
Repetitive Behaviors ◽  
Short Time Scale ◽  
Behavioral Experiments ◽  
Behavioral Evidence ◽  
Pattern Generators ◽  
Short Time

AbstractCentral pattern generators (CPGs) are neurons or neural circuits that produce periodic output without requiring patterned input. More complex behaviors can be assembled from simpler subroutines, and nested CPGs have been proposed to coordinate their repetitive elements, simplifying control over different time-scales. Here, we use behavioral experiments to establish that Drosophila grooming may be controlled by nested CPGs. On the short time-scale (5-7 Hz), flies execute periodic leg sweeps and rubs. More surprisingly, transitions between bouts of head cleaning and leg rubbing are also periodic on a longer time-scale (0.3 - 0.6 Hz). We examine grooming at a range of temperatures to show that the frequencies of both oscillations increase – a hallmark of CPG control – and also that the two time-scales increase at the same rate, indicating that the nested CPGs may be linked. This relationship also holds when sensory drive is held constant using optogenetic activation, but the rhythms decouple in spontaneously grooming flies, showing that alternative control modes are possible. Nested CPGs simplify generation of complex but repetitive behaviors, and identifying them in Drosophila grooming presents an opportunity to map the neural circuits that constitute them.

On peripheral control mechanisms acting on the central pattern generators for swimming in the dogfish

1982 ◽  
Vol 98 (1) ◽  
pp. 1-22 ◽  
Author(s):  
S. Grillner ◽  
P. Wallen
Keyword(s):  
Vertebral Column ◽  
Central Pattern Generators ◽  
Control Mechanisms ◽  
Fictive Locomotion ◽  
Tail Region ◽  
Stretch Receptors ◽  
Burst Pattern ◽  
Ventral Roots ◽  
Pattern Generators ◽  
Low Amplitude

When sinusoidal movements were artificially imposed on the tail region of the curarized spinal dogfish during “fictive locomotion' the coordinated burst pattern recorded in the ventral roots was effectively entrained to follow movement frequencies above as well as below the resting rate. The entrainment was characterized by: (1) a broad range of effective movement frequencies and amplitudes (down to a few degrees); (2) frequency-dependent timing of entrained bursts to the movement; (3) constant burst durations at low and moderate frequencies; (4) incomplete entrainment in response to high or low movement frequencies combined with a low amplitude; (5) entrainment was still present when mean position of movement was displaced laterally; (6) effects persisted when the tail region was devoid of skin and muscle tissue. Entrainment effects may be explained by the activation of stretch receptors on either side of the vertebral column-spinal cord, exciting the presumed central pattern generators (CPGs) in the hemisegments ipsilateral to the stretch, while inhibiting the contralateral CPGs.

scholarly journals An optimality principle for locomotor central pattern generators

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hansol X. Ryu ◽  
Arthur D. Kuo
Keyword(s):  
Internal Model ◽  
Sensory Feedback ◽  
Motor Pattern ◽  
Central Pattern Generators ◽  
Optimal Estimation ◽  
Legged Locomotion ◽  
Energetic Cost ◽  
Fictive Locomotion ◽  
Cost Of Transport ◽  
Pattern Generators

AbstractTwo types of neural circuits contribute to legged locomotion: central pattern generators (CPGs) that produce rhythmic motor commands (even in the absence of feedback, termed “fictive locomotion”), and reflex circuits driven by sensory feedback. Each circuit alone serves a clear purpose, and the two together are understood to cooperate during normal locomotion. The difficulty is in explaining their relative balance objectively within a control model, as there are infinite combinations that could produce the same nominal motor pattern. Here we propose that optimization in the presence of uncertainty can explain how the circuits should best be combined for locomotion. The key is to re-interpret the CPG in the context of state estimator-based control: an internal model of the limbs that predicts their state, using sensory feedback to optimally balance competing effects of environmental and sensory uncertainties. We demonstrate use of optimally predicted state to drive a simple model of bipedal, dynamic walking, which thus yields minimal energetic cost of transport and best stability. The internal model may be implemented with neural circuitry compatible with classic CPG models, except with neural parameters determined by optimal estimation principles. Fictive locomotion also emerges, but as a side effect of estimator dynamics rather than an explicit internal rhythm. Uncertainty could be key to shaping CPG behavior and governing optimal use of feedback.

scholarly journals An optimality principle for locomotor central pattern generators

2019 ◽  
Author(s):  
Hansol X. Ryu ◽  
Arthur D. Kuo
Keyword(s):  
Internal Model ◽  
Sensory Feedback ◽  
Motor Pattern ◽  
Central Pattern Generators ◽  
Optimal Estimation ◽  
Legged Locomotion ◽  
Energetic Cost ◽  
Fictive Locomotion ◽  
Cost Of Transport ◽  
Pattern Generators

AbstractTwo types of neural circuits contribute to legged locomotion: central pattern generators (CPGs) that produce rhythmic motor commands (even in the absence of feedback, termed “fictive locomotion”), and reflex circuits driven by sensory feedback. Each circuit alone serves a clear purpose, and the two together are understood to cooperate during normal locomotion. The difficulty is in explaining their relative balance objectively within a control model, as there are infinite combinations that could produce the same nominal motor pattern. Here we propose that optimization in the presence of uncertainty can explain how the circuits should best be combined for locomotion. The key is to re- interpret the CPG in the context of state estimator-based control: an internal model of the limbs that predicts their state, using sensory feedback to optimally balance competing effects of environmental and sensory uncertainties. We demonstrate use of optimally predicted state to drive a simple model of bipedal, dynamic walking, which thus yields minimal energetic cost of transport and best stability. The internal model may be implemented with classic neural half-center circuitry, except with neural parameters determined by optimal estimation principles. Fictive locomotion also emerges, but as a side effect of estimator dynamics rather than an explicit internal rhythm. Uncertainty could be key to shaping CPG behavior and governing optimal use of feedback.New and NoteworthySensory feedback modulates the central pattern generator (CPG) rhythm in locomotion, but there lacks an explanation for how much feedback is appropriate. We propose destabilizing noise as a determinant, where an uncertain environment demands more feedback, but noisy sensors demand less. We reinterpret the CPG as an internal model for predicting body state despite noise. Optimizing its feedback yields robust and economical gait in a walking model, and explains the advantages of feedback-driven CPG control.

scholarly journals Localization of Motor Neurons and Central Pattern Generators for Motor Patterns Underlying Feeding Behavior in Drosophila Larvae

PLoS ONE ◽  
2015 ◽  
Vol 10 (8) ◽  
pp. e0135011 ◽  
Author(s):  
Sebastian Hückesfeld ◽  
Andreas Schoofs ◽  
Philipp Schlegel ◽  
Anton Miroschnikow ◽  
Michael J. Pankratz
Keyword(s):  
Feeding Behavior ◽  
Motor Neurons ◽  
Central Pattern Generators ◽  
Motor Patterns ◽  
Drosophila Larvae ◽  
Pattern Generators
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