Comment: Gating effects and constraints on the central pattern generators for rhythmic movements

1981 ◽  
Vol 59 (7) ◽  
pp. 727-732 ◽  
Author(s):  
Larry M. Jordan
Keyword(s):  
Central Pattern Generators ◽  
Rhythmic Activity ◽  
Inhibitory Interneurons ◽  
Inhibitory Mechanism ◽  
Rhythmic Movements ◽  
Locomotor Pattern ◽  
Renshaw Cell ◽  
Proprioceptive Input ◽  
Pattern Generators

Respiration, mastication, and locomotion are compared in terms of the contributions of events occurring at the motoneuron membrane and at premotoneuronal levels for the production of phasic gain changes of afferent effects. Data are presented which suggest that an inhibitory mechanism operating on limb motoneurons can prevent disruption of the locomotor pattern by proprioceptive input and that Ia inhibitory interneurons contribute to this rhythmic inhibition of both flexor and extensor motoneurons. Renshaw cell rhythmic activity during locomotion is described and discussed in terms of its possible role in gating of inputs to motoneurons.

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.

Altered Gravity Highlights Central Pattern Generator Mechanisms

2008 ◽  
Vol 100 (5) ◽  
pp. 2819-2824 ◽  
Author(s):  
Olivier White ◽  
Yannick Bleyenheuft ◽  
Renaud Ronsse ◽  
Allan M. Smith ◽  
Jean-Louis Thonnard ◽  
...  
Keyword(s):  
Neural Networks ◽  
Resonant Frequency ◽  
Parabolic Flight ◽  
Central Pattern Generators ◽  
Arm Movement ◽  
Rhythmic Movements ◽  
Earth Environment ◽  
Major Interest ◽  
Microgravity Conditions ◽  
Pattern Generators

In many nonprimate species, rhythmic patterns of activity such as locomotion or respiration are generated by neural networks at the spinal level. These neural networks are called central pattern generators (CPGs). Under normal gravitational conditions, the energy efficiency and the robustness of human rhythmic movements are due to the ability of CPGs to drive the system at a pace close to its resonant frequency. This property can be compared with oscillators running at resonant frequency, for which the energy is optimally exchanged with the environment. However, the ability of the CPG to adapt the frequency of rhythmic movements to new gravitational conditions has never been studied. We show here that the frequency of a rhythmic movement of the upper limb is systematically influenced by the different gravitational conditions created in parabolic flight. The period of the arm movement is shortened with increasing gravity levels. In weightlessness, however, the period is more dependent on instructions given to the participants, suggesting a decreased influence of resonant frequency. Our results are in agreement with a computational model of a CPG coupled to a simple pendulum under the control of gravity. We demonstrate that the innate modulation of rhythmic movements by CPGs is highly flexible across gravitational contexts. This further supports the involvement of CPG mechanisms in the achievement of efficient rhythmic arm movements. Our contribution is of major interest for the study of human rhythmic activities, both in a normal Earth environment and during microgravity conditions in space.

scholarly journals Asymmetric and transient properties of reciprocal activity of antagonists during the paw-shake response in the cat

2021 ◽  
Vol 17 (12) ◽  
pp. e1009677
Author(s):  
Jessica R. Parker ◽  
Alexander N. Klishko ◽  
Boris I. Prilutsky ◽  
Gennady S. Cymbalyuk
Keyword(s):  
Activity Patterns ◽  
Central Pattern Generators ◽  
Emg Activity ◽  
Rhythmic Movements ◽  
Related Activity ◽  
Fast Transient Response ◽  
Hindlimb Muscles ◽  
Pattern Generators ◽  
A Current

Mutually inhibitory populations of neurons, half-center oscillators (HCOs), are commonly involved in the dynamics of the central pattern generators (CPGs) driving various rhythmic movements. Previously, we developed a multifunctional, multistable symmetric HCO model which produced slow locomotor-like and fast paw-shake-like activity patterns. Here, we describe asymmetric features of paw-shake responses in a symmetric HCO model and test these predictions experimentally. We considered bursting properties of the two model half-centers during transient paw-shake-like responses to short perturbations during locomotor-like activity. We found that when a current pulse was applied during the spiking phase of one half-center, let’s call it #1, the consecutive burst durations (BDs) of that half-center increased throughout the paw-shake response, while BDs of the other half-center, let’s call it #2, only changed slightly. In contrast, the consecutive interburst intervals (IBIs) of half-center #1 changed little, while IBIs of half-center #2 increased. We demonstrated that this asymmetry between the half-centers depends on the phase of the locomotor-like rhythm at which the perturbation was applied. We suggest that the fast transient response reflects functional asymmetries of slow processes that underly the locomotor-like pattern; e.g., asymmetric levels of inactivation across the two half-centers for a slowly inactivating inward current. We compared model results with those of in-vivo paw-shake responses evoked in locomoting cats and found similar asymmetries. Electromyographic (EMG) BDs of anterior hindlimb muscles with flexor-related activity increased in consecutive paw-shake cycles, while BD of posterior muscles with extensor-related activity did not change, and vice versa for IBIs of anterior flexors and posterior extensors. We conclude that EMG activity patterns during paw-shaking are consistent with the proposed mechanism producing transient paw-shake-like bursting patterns found in our multistable HCO model. We suggest that the described asymmetry of paw-shaking responses could implicate a multifunctional CPG controlling both locomotion and paw-shaking.

scholarly journals Inhibition and Recurrent Excitation in a Computational Model of Sparse Bursting in Song Nucleus HVC

2009 ◽  
Vol 102 (3) ◽  
pp. 1748-1762 ◽  
Author(s):  
Leif Gibb ◽  
Timothy Q. Gentner ◽  
Henry D. I. Abarbanel
Keyword(s):  
Computational Model ◽  
Critical Point ◽  
Central Pattern Generators ◽  
Projection Neurons ◽  
Inhibitory Interneurons ◽  
Sustained Activity ◽  
Recurrent Excitation ◽  
Pattern Generators ◽  
Propagation Of Waves ◽  
Bursting Activity

The telencephalic premotor nucleus HVC is situated at a critical point in the pattern-generating premotor circuitry of oscine songbirds. A striking feature of HVC's premotor activity is that its projection neurons burst extremely sparsely. Here we present a computational model of HVC embodying several central hypotheses: 1) sparse bursting is generated in bistable groups of recurrently connected robust nucleus of the arcopallium (RA)–projecting (HVCRA) neurons; 2) inhibitory interneurons terminate bursts in the HVCRA groups; and 3) sparse sequences of bursts are generated by the propagation of waves of bursting activity along networks of HVCRA neurons. Our model of sparse bursting places HVC in the context of central pattern generators and cortical networks using inhibition, recurrent excitation, and bistability. Importantly, the unintuitive result that inhibitory interneurons can precisely terminate the bursts of HVCRA groups while showing relatively sustained activity throughout the song is made possible by a specific constraint on their connectivity. We use the model to make novel predictions that can be tested experimentally.

scholarly journals Central Pattern Generation of Locomotion: A Review of the Evidence

2002 ◽  
Vol 82 (1) ◽  
pp. 69-83 ◽  
Author(s):  
Marilyn MacKay-Lyons
Keyword(s):  
Final Section ◽  
Central Pattern Generators ◽  
Pattern Generation ◽  
Stable Phase ◽  
Rhythmic Movements ◽  
Sensory Afferents ◽  
Future Directions ◽  
Pattern Generators ◽  
Regulatory Functions ◽  
The Brain

Abstract Neural networks in the spinal cord, referred to as “central pattern generators” (CPGs), are capable of producing rhythmic movements, such as swimming, walking, and hopping, even when isolated from the brain and sensory inputs. This article reviews the evidence for CPGs governing locomotion and addresses other factors, including supraspinal, sensory, and neuromodulatory influences, that interact with CPGs to shape the final motor output. Supraspinal inputs play a major role not only in initiating locomotion but also in adapting the locomotor pattern to environmental and motivational conditions. Sensory afferents involved in muscle and cutaneous reflexes have important regulatory functions in preserving balance and ensuring stable phase transitions in the locomotor cycle. Neuromodulators evoke changes in cellular and synaptic properties of CPG neurons, conferring flexibility to CPG circuits. Briefly addressed is the interaction of CPG networks to produce intersegmental coordination for locomotion. Evidence for CPGs in humans is reviewed, and although a comprehensive clinical review is not an objective, examples are provided of animal and human studies that apply knowledge of CPG mechanisms to improve locomotion. The final section deals with future directions in CPG research.

scholarly journals A Computational Model for Rhythmic and Discrete Movements in Uni- and Bimanual Coordination

2009 ◽  
Vol 21 (5) ◽  
pp. 1335-1370 ◽  
Author(s):  
Renaud Ronsse ◽  
Dagmar Sternad ◽  
Philippe Lefèvre
Keyword(s):  
Computational Model ◽  
Bimanual Coordination ◽  
Central Pattern Generators ◽  
Unified Model ◽  
Model Complexity ◽  
Rhythmic Movements ◽  
Discrete Movements ◽  
Oscillatory Systems ◽  
Small Set ◽  
Pattern Generators

Current research on discrete and rhythmic movements differs in both experimental procedures and theory, despite the ubiquitous overlap between discrete and rhythmic components in everyday behaviors. Models of rhythmic movements usually use oscillatory systems mimicking central pattern generators (CPGs). In contrast, models of discrete movements often employ optimization principles, thereby reflecting the higher-level cortical resources involved in the generation of such movements. This letter proposes a unified model for the generation of both rhythmic and discrete movements. We show that a physiologically motivated model of a CPG can not only generate simple rhythmic movements with only a small set of parameters, but can also produce discrete movements if the CPG is fed with an exponentially decaying phasic input. We further show that a particular coupling between two of these units can reproduce main findings on in-phase and antiphase stability. Finally, we propose an integrated model of combined rhythmic and discrete movements for the two hands. These movement classes are sequentially addressed in this letter with increasing model complexity. The model variations are discussed in relation to the degree of recruitment of the higher-level cortical resources, necessary for such movements.

scholarly journals Why Firing Rate Distributions Are Important for Understanding Spinal Central Pattern Generators

2021 ◽  
Vol 15 ◽  
Author(s):  
Henrik Lindén ◽  
Rune W. Berg
Keyword(s):  
Firing Rate ◽  
Normal Distribution ◽  
Population Distribution ◽  
Central Pattern Generators ◽  
Recurrent Inhibition ◽  
Rhythmic Movements ◽  
Firing Rates ◽  
Motor Circuits ◽  
Pattern Generators ◽  
The Impact

Networks in the spinal cord, which are responsible for the generation of rhythmic movements, commonly known as central pattern generators (CPGs), have remained elusive for decades. Although it is well-known that many spinal neurons are rhythmically active, little attention has been given to the distribution of firing rates across the population. Here, we argue that firing rate distributions can provide an important clue to the organization of the CPGs. The data that can be gleaned from the sparse literature indicate a firing rate distribution, which is skewed toward zero with a long tail, akin to a normal distribution on a log-scale, i.e., a “log-normal” distribution. Importantly, such a shape is difficult to unite with the widespread assumption of modules composed of recurrently connected excitatory neurons. Spinal modules with recurrent excitation has the propensity to quickly escalate their firing rate and reach the maximum, hence equalizing the spiking activity across the population. The population distribution of firing rates hence would consist of a narrow peak near the maximum. This is incompatible with experiments, that show wide distributions and a peak close to zero. A way to resolve this puzzle is to include recurrent inhibition internally in each CPG modules. Hence, we investigate the impact of recurrent inhibition in a model and find that the firing rate distributions are closer to the experimentally observed. We therefore propose that recurrent inhibition is a crucial element in motor circuits, and suggest that future models of motor circuits should include recurrent inhibition as a mandatory element.

Control of Central Pattern Generators by an Identified Neurone in Crustacea: Activation of the Gastric Mill Motor Pattern by a Neurone Known to Modulate the Pyloric Network

1988 ◽  
Vol 136 (1) ◽  
pp. 53-87
Author(s):  
PATSY S. DICKINSON ◽  
FRÉDÉRIC NAGY ◽  
MAURICE MOULINS
Keyword(s):  
Central Pattern Generator ◽  
Motor Pattern ◽  
Central Pattern Generators ◽  
Rhythmic Activity ◽  
Pattern Generator ◽  
Gastric Mill ◽  
Pyloric Network ◽  
Single Burst ◽  
Pattern Generators ◽  
Synaptic Drive

In the red lobster (Palinurus vulgaris), an identified neurone, the anterior pyloric modulator neurone (APM), which has previously been shown to modulate the output of the pyloric central pattern generator, was shown to modulate the output of the gastric mill central pattern generator. APM activity induced a rhythm when the network was silent and increased rhythmic activity when the network was already active. Rhythmic activity was induced whether APM fired in single bursts, tonically or in repetitive bursts. A single burst in APM induced a rhythm which considerably outlasted the burst, whereas repetitive bursts effectively entrained the gastric oscillator. These modulations involved two major mechanisms. (1) APM induced or enhanced plateau properties in some of the gastric mill neurones. (2) APM activated the extrinsic inputs to the network, thus increasing the excitatory synaptic drive to most of the neurones of the network. As a result, when APM was active, all the neurones of the pattern generator actively participated in the rhythmic activity. By its actions on two separate but behaviourally related neural networks, the APM neurone may be able to control an entire concert of related types of behaviour.

Connection Topology Selection in Central Pattern Generators by Maximizing the Gain of Information

2007 ◽  
Vol 19 (4) ◽  
pp. 974-993 ◽  
Author(s):  
Gregory R. Stiesberg ◽  
Marcelo Bussotti Reyes ◽  
Pablo Varona ◽  
Reynaldo D. Pinto ◽  
Ramón Huerta
Keyword(s):  
Theoretical Analysis ◽  
Computer Simulations ◽  
Central Pattern Generators ◽  
Rhythmic Activity ◽  
Pattern Generator ◽  
Spatiotemporal Patterns ◽  
Small Subset ◽  
Electronic Circuits ◽  
Invaluable Tool ◽  
Pattern Generators

A study of a general central pattern generator (CPG) is carried out by means of a measure of the gain of information between the number of available topology configurations and the output rhythmic activity. The neurons of the CPG are chaotic Hindmarsh-Rose models that cooperate dynamically to generate either chaotic or regular spatiotemporal patterns. These model neurons are implemented by computer simulations and electronic circuits. Out of a random pool of input configurations, a small subset of them maximizes the gain of information. Two important characteristics of this subset are emphasized: (1) the most regular output activities are chosen, and (2) none of the selected input configurations are networks with open topology. These two principles are observed in living CPGs as well as in model CPGs that are the most efficient in controlling mechanical tasks, and they are evidence that the information-theoretical analysis can be an invaluable tool in searching for general properties of CPGs.

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