A General Rhythmic Pattern Generation Architecture for Legged Locomotion

2011 ◽  
pp. 202-230
Author(s):  
Zhijun Yang ◽  
Felipe M.G. França
Keyword(s):  
Critical Role ◽  
Central Pattern Generators ◽  
Legged Locomotion ◽  
Building Blocks ◽  
Pattern Generation ◽  
Rhythmic Pattern ◽  
Motor Information ◽  
Pattern Generators ◽  
Life Phenomena ◽  
Almost All

As an engine of almost all life phenomena, the motor information generated by the central nervous system (CNS) plays a critical role in the activities of all animals. After a brief review of some recent research results on locomotor central pattern generators (CPG), which is a concrete branch of studies on the CNS generating rhythmic patterns, this chapter presents a novel, macroscopic and model-independent approach to the retrieval of different patterns of coupled neural oscillations observed in biological CPGs during the control of legged locomotion. Based on scheduling by multiple edge reversal (SMER), a simple and discrete distributed synchroniser, various types of oscillatory building blocks (OBB) can be reconfigured for the production of complicated rhythmic patterns and a methodology is provided for the construction of a target artificial CPG architecture behaving as a SMER-like asymmetric Hopfield neural networks.

Rhythmic Pattern Generation in Invertebrates

2018 ◽  
pp. 390-400
Author(s):  
Astrid A. Prinz
Keyword(s):  
Central Pattern Generators ◽  
Pattern Generation ◽  
Rhythmic Pattern ◽  
Neuronal Circuit ◽  
Neuronal Circuits ◽  
Timing Circuit ◽  
Core Components ◽  
Pattern Generators

This chapter begins by defining central pattern generators (CPGs) and proceeds to focus on one of their core components, the timing circuit. After arguing why invertebrate CPGs are particularly useful for the study of neuronal circuit operation in general, the bulk of the chapter then describes basic mechanisms of CPG operation at the cellular, synaptic, and network levels, and how different CPGs combine these mechanisms in various ways. Finally, the chapter takes a semihistorical perspective to discuss whether or not the study of invertebrate CPGs has seen its prime and what it has contributed—and may continue to offer—to a wider understanding of neuronal circuits in general.

scholarly journals Evolution of central pattern generators for the control of a five-link bipedal walking mechanism

2012 ◽  
Vol 3 (1) ◽  
Author(s):  
Atılım Güneş Baydin
Keyword(s):  
Robot Control ◽  
Central Pattern Generators ◽  
Legged Locomotion ◽  
Bipedal Walking ◽  
Biologically Inspired ◽  
Neurophysiological Studies ◽  
Real Robot ◽  
Pattern Generators ◽  
And Performance ◽  
Walking Mechanism

AbstractCentral pattern generators (CPGs), with a basis is neurophysiological studies, are a type of neural network for the generation of rhythmic motion. While CPGs are being increasingly used in robot control, most applications are hand-tuned for a specific task and it is acknowledged in the field that generic methods and design principles for creating individual networks for a given task are lacking. This study presents an approach where the connectivity and oscillatory parameters of a CPG network are determined by an evolutionary algorithm with fitness evaluations in a realistic simulation with accurate physics. We apply this technique to a five-link planar walking mechanism to demonstrate its feasibility and performance. In addition, to see whether results from simulation can be acceptably transferred to real robot hardware, the best evolved CPG network is also tested on a real mechanism. Our results also confirm that the biologically inspired CPG model is well suited for legged locomotion, since a diverse manifestation of networks have been observed to succeed in fitness simulations during evolution.

Control of Locomotion in Hexapods

2017 ◽  
pp. 422-438 ◽  
Author(s):  
Roy E. Ritzmann ◽  
Sasha N. Zill
Keyword(s):  
Control Systems ◽  
Local Control ◽  
Sensory Information ◽  
Legged Locomotion ◽  
Pattern Generation ◽  
Central Complex ◽  
Joint Movement ◽  
Control Circuits ◽  
Pattern Generators ◽  
The Brain

This article discusses legged locomotion in insects. It describes the basic patterns of coordinated movement both within each leg and among the various legs. The nervous system controls these actions through groups of joint pattern generators coupled through interneurons and interjoint reflexes in a range of insect species. These local control systems within the thoracic ganglia rely on leg proprioceptors that monitor joint movement and cuticular strain interacting with central pattern generation interneurons. The local control systems can change quantitatively and qualitatively as needed to generate turns or more forceful movements. In dealing with substantial obstacles or changes in navigational movements, more profound changes are required. These rely on sensory information processed in the brain that projects to the multimodal sensorimotor neuropils collectively referred to as the central complex. The central complex affects descending commands that alter local control circuits to accomplish appropriate redirected movements.

scholarly journals From Spinal Central Pattern Generators to Cortical Network: Integrated BCI for Walking Rehabilitation

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
G. Cheron ◽  
M. Duvinage ◽  
C. De Saedeleer ◽  
T. Castermans ◽  
A. Bengoetxea ◽  
...  
Keyword(s):  
Brain Plasticity ◽  
Central Pattern Generators ◽  
Pattern Generation ◽  
Lower Limbs ◽  
Plantar Surface ◽  
Rehabilitation Programs ◽  
Walking Rehabilitation ◽  
Locomotor Patterns ◽  
Pattern Generators ◽  
Clinical Conditions

Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

Correlated and uncorrelated high-frequency oscillations in phrenic and recurrent laryngeal neurograms

1988 ◽  
Vol 59 (4) ◽  
pp. 1188-1203 ◽  
Author(s):  
E. N. Bruce
Keyword(s):  
Central Pattern Generators ◽  
Power Spectra ◽  
Power Spectral Analysis ◽  
Pattern Generation ◽  
Common Source ◽  
Power Spectral ◽  
Left And Right ◽  
Motor Outputs ◽  
Pattern Generators ◽  
40 Hz

1. Power spectral analysis of phrenic and recurrent laryngeal (or efferent vagal) inspiratory discharge activity from anesthetized cats revealed a peak within the 60- to 110-Hz range in all spectra, plus a peak within the 40- to 60-Hz range in the laryngeal (and efferent vagal) spectra, and a peak less than 40 Hz in the phrenic spectra. 2. A 60- to 110-Hz peak was present in coherence spectra between the left and right phrenic neurograms, the left and right recurrent laryngeal (and efferent vagal) neurograms, and all combinations of phrenic-laryngeal (and phrenic-efferent vagal) pairs. It is concluded that the nearly-periodic oscillations represented by these peaks arise from a single source that projects functionally in parallel to many respiratory motor outputs. This source may be part of, or interact with, respiratory central pattern generation. 3. The 40- to 60-Hz oscillations in left and right recurrent laryngeal (and efferent vagal) neurograms were uncorrelated or occasionally were very weakly correlated. Thus it is unlikely that these oscillations arise from a common source such as a second respiratory central pattern generator. 4. The oscillations less than 40 Hz were weakly correlated between left and right phrenic neurograms. This correlation may be due substantially to spinal crossed-phrenic pathways. 5. It is proposed that both the 40- to 60-Hz oscillations in recurrent laryngeal neurograms and the oscillations below 40 Hz in phrenic neurograms originate in neural circuits associated with individual left or right recurrent laryngeal or phrenic motor outputs. 6. Our results do not support the interpretation that multiple peaks in phrenic and recurrent laryngeal power spectra are due to two respiratory central pattern generators whose outputs have parallel pathways to respiratory motoneurons.

scholarly journals Diversity of molecularly defined spinal interneurons engaged in mammalian locomotor pattern generation

2017 ◽  
Vol 118 (6) ◽  
pp. 2956-2974 ◽  
Author(s):  
Lea Ziskind-Conhaim ◽  
Shawn Hochman
Keyword(s):  
Activity Patterns ◽  
Central Pattern Generators ◽  
Pattern Generation ◽  
Model Systems ◽  
Locomotor Rhythm ◽  
Spinal Interneurons ◽  
Adult Mice ◽  
Descending Fibers ◽  
Experimental Model Systems ◽  
Pattern Generators

Mapping the expression of transcription factors in the mouse spinal cord has identified ten progenitor domains, four of which are cardinal classes of molecularly defined, ventrally located interneurons that are integrated in the locomotor circuitry. This review focuses on the properties of these interneuronal populations and their contribution to hindlimb locomotor central pattern generation. Interneuronal populations are categorized based on their excitatory or inhibitory functions and their axonal projections as predictors of their role in locomotor rhythm generation and coordination. The synaptic connectivity and functions of these interneurons in the locomotor central pattern generators (CPGs) have been assessed by correlating their activity patterns with motor output responses to rhythmogenic neurochemicals and sensory and descending fibers stimulations as well as analyzing kinematic gait patterns in adult mice. The observed complex organization of interneurons in the locomotor CPG circuitry, some with seemingly similar physiological functions, reflects the intricate repertoire associated with mammalian motor control and is consistent with high transcriptional heterogeneity arising from cardinal interneuronal classes. This review discusses insights derived from recent studies to describe innovative approaches and limitations in experimental model systems and to identify missing links in current investigational enterprise.

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 The speed–curvature power law in Drosophila larval locomotion

2016 ◽  
Vol 12 (10) ◽  
pp. 20160597 ◽  
Author(s):  
Myrka Zago ◽  
Francesco Lacquaniti ◽  
Alex Gomez-Marin
Keyword(s):  
Power Law ◽  
Scaling Laws ◽  
Central Pattern Generators ◽  
Dynamic Effects ◽  
Muscle Properties ◽  
Wide Range ◽  
Behavioural Tracking ◽  
The Law ◽  
Pattern Generators ◽  
Almost All

We report the discovery that the locomotor trajectories of Drosophila larvae follow the power-law relationship between speed and curvature previously found in the movements of human and non-human primates. Using high-resolution behavioural tracking in controlled but naturalistic sensory environments, we tested the law in maggots tracing different trajectory types, from reaching-like movements to scribbles. For most but not all flies, we found that the law holds robustly, with an exponent close to three-quarters rather than to the usual two-thirds found in almost all human situations, suggesting dynamic effects adding on purely kinematic constraints. There are different hypotheses for the origin of the law in primates, one invoking cortical computations, another viscoelastic muscle properties coupled with central pattern generators. Our findings are consistent with the latter view and demonstrate that the law is possible in animals with nervous systems orders of magnitude simpler than in primates. Scaling laws might exist because natural selection favours processes that remain behaviourally efficient across a wide range of neural and body architectures in distantly related species.

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