Central Pattern Generator for Escape Swimming in the Notaspid Sea Slug Pleurobranchaea californica

1999 ◽  
Vol 81 (2) ◽  
pp. 654-667 ◽  
Author(s):  
Jian Jing ◽  
Rhanor Gillette
Keyword(s):  
Central Pattern Generator ◽  
Electrical Coupling ◽  
Reciprocal Inhibition ◽  
Pattern Generator ◽  
Cycle Number ◽  
Sea Slug ◽  
Pleurobranchaea Californica ◽  
Normal Behavior ◽  
Persistent Firing ◽  
Dorsal Flexion

Central pattern generator for escape swimming in the notaspid sea slug Pleurobranchaea californica. Escape swimming in the notaspid opisthobranch Pleurobranchaea is an episode of alternating dorsal and ventral body flexions that overrides all other behaviors. We have explored the structure of the central pattern generator (CPG) in the cerebropleural ganglion as part of a study of neural network interactions underlying decision making in normal behavior. The CPG comprises at least eight bilaterally paired interneurons, each of which contributes and is phase-locked to the swim rhythm. Dorsal flexion is mediated by hemiganglion ensembles of four serotonin-immunoreactive neurons, the As1, As2, As3, and As4, and an electrically coupled pair, the A1 and A10 cells. When stimulated, A10 commands fictive swimming in the isolated CNS and actual swimming behavior in whole animals. As1–4 provide prolonged, neuromodulatory excitation enhancing dorsal flexion bursts and swim cycle number. Ventral flexion is mediated by the A3 cell and a ventral swim interneuron, IVS, the soma of which is yet unlocated. Initiation of a swim episode begins with persistent firing in A10, followed by recruitment of As1–4 and A1 into dorsal flexion. Recurrent excitation within the As1–4 ensemble and with A1/A10 may reinforce coactivity. Synchrony among swim interneuron partners and bilateral coordination is promoted by electrical coupling among the A1/A10 and As4 pairs, and among unilateral As2–4, and reciprocal chemical excitation between contralateral As1–4 groups. The switch from dorsal to ventral flexion coincides with delayed recruitment of A3, which is coupled electrically to A1, and with recurrent inhibition from A3/IVS to A1/A10. The alternating phase relation may be reinforced by reciprocal inhibition between As1–4 and IVS. Pleurobranchaea’s swim resembles that of the nudibranch Tritonia; we find that the CPGs are similar in many details, suggesting that the behavior and network are primitive characters derived from a common pleurobranchid ancestor.

scholarly journals Phase-Locked Coordination Between Two Rhythmically Active Feeding Structures in the Mollusk Clione limacina. I. Motor Neurons

2002 ◽  
Vol 87 (6) ◽  
pp. 2996-3005 ◽  
Author(s):  
Aleksey Y. Malyshev ◽  
Tigran P. Norekian
Keyword(s):  
Central Pattern Generator ◽  
Motor Neurons ◽  
Electrical Coupling ◽  
Pattern Generator ◽  
Dependent Manner ◽  
Synaptic Connections ◽  
Buccal Ganglia ◽  
Active Feeding ◽  
Clione Limacina ◽  
Specific Phase

Coordination between different motor centers is essential for the orderly production of all complex behaviors, in both vertebrates and invertebrates. The current study revealed that rhythmic activities of two feeding structures of the pteropod mollusk Clione limacina, radula and hooks, which are used to extract the prey from its shell, are highly coordinated in a phase-dependent manner. Hook protraction always coincided with radula retraction, while hook retraction coincided with radula protraction. Thus hooks and radula were always moving in the opposite phases, taking turns grabbing and pulling the prey tissue out of the shell. Identified buccal ganglia motor neurons controlling radula and hooks protraction and retraction were rhythmically active in the same phase-dependent manner. Hook protractor motor neurons were active in the same phase with radula retractor motor neurons, while hook retractor motor neurons burst in phase with radula protractor motor neurons. One of the main mechanisms underlying the phase-locked coordination was electrical coupling between hook protractor and radula retractor motor neurons. In addition, reciprocal inhibitory synaptic connections were found between hook protractor and radula protractor motor neurons. These electrical and inhibitory synaptic connections ensure that rhythmically active hooks and radula controlling motor neurons are coordinated in the specific phase-dependent manner described above. The possible existence of a single multifunctional central pattern generator for both radula and hook motor centers is discussed.

scholarly journals Using a Model to Assess the Role of the Spatiotemporal Pattern of Inhibitory Input and Intrasegmental Electrical Coupling in the Intersegmental and Side-to-Side Coordination of Motor Neurons by the Leech Heartbeat Central Pattern Generator

2008 ◽  
Vol 100 (3) ◽  
pp. 1354-1371 ◽  
Author(s):  
Paul S. García ◽  
Terrence M. Wright ◽  
Ian R. Cunningham ◽  
Ronald L. Calabrese
Keyword(s):  
Motor Neuron ◽  
Central Pattern Generator ◽  
Motor Neurons ◽  
Electrical Coupling ◽  
Pattern Generator ◽  
Living System ◽  
Phase Relations ◽  
Spatiotemporal Pattern ◽  
Intrinsic Properties ◽  
Synaptic Inputs

Previously we presented a quantitative description of the spatiotemporal pattern of inhibitory synaptic input from the heartbeat central pattern generator (CPG) to segmental motor neurons that drive heartbeat in the medicinal leech and the resultant coordination of CPG interneurons and motor neurons. To begin elucidating the mechanisms of coordination, we explore intersegmental and side-to-side coordination in an ensemble model of all heart motor neurons and their known synaptic inputs and electrical coupling. Model motor neuron intrinsic properties were kept simple, enabling us to determine the extent to which input and electrical coupling acting together can account for observed coordination in the living system in the absence of a substantive contribution from the motor neurons themselves. The living system produces an asymmetric motor pattern: motor neurons on one side fire nearly in synchrony (synchronous), whereas on the other they fire in a rear-to-front progression (peristaltic). The model reproduces the general trends of intersegmental and side-to-side phase relations among motor neurons, but the match with the living system is not quantitatively accurate. Thus realistic (experimentally determined) inputs do not produce similarly realistic output in our model, suggesting that motor neuron intrinsic properties may contribute to their coordination. By varying parameters that determine electrical coupling, conduction delays, intraburst synaptic plasticity, and motor neuron excitability, we show that the most important determinant of intersegmental and side-to-side phase relations in the model was the spatiotemporal pattern of synaptic inputs, although phasing was influenced significantly by electrical coupling.

Modeling the gastric mill central pattern generator of the lobster with a relaxation-oscillator network

1993 ◽  
Vol 70 (3) ◽  
pp. 1030-1053 ◽  
Author(s):  
P. F. Rowat ◽  
A. I. Selverston
Keyword(s):  
Central Pattern Generator ◽  
Model Neuron ◽  
Relaxation Oscillator ◽  
Reciprocal Inhibition ◽  
Pattern Generator ◽  
Pattern Generation ◽  
Gastric Mill ◽  
Plateau Potentials ◽  
Isolated Cells ◽  
Current Parameter

1. The gastric mill central pattern generator (CPG) controls the chewing movements of teeth in the gastric mill of the lobster. This CPG has been extensively studied, but the precise mechanism underlying pattern generation is not well understood. The goal of this research was to develop a simplified model that captures the principle, biologically significant features of this CPG. We introduce a simplified neuron model that embodies approximations of well-known membrane currents, and is able to reproduce several global characteristics of gastric mill neurons. A network built with these neurons, using graded synaptic transmission and having the synaptic connections of the biological circuit, is sufficient to explain much of the network's behavior. 2. The cell model is a generalization and extension of the Van der Pol relaxation oscillator equations. It is described by two differential equations, one for current conservation and one for slow current activation. The model has a fast current that may, by adjusting one parameter, have a region of negative resistance in its current-voltage (I-V) curve. It also has a slow current with a single gain parameter that can be regarded as the combination of slow inward and outward currents. 3. For suitable values of the fast current parameter and the slow current parameter, the isolated model neuron exhibits several different behaviors: plateau potentials, postinhibitory rebound, postburst hyperpolarization, and endogenous oscillations. When the slow current is separated into inward and outward fractions with separately adjustable gain parameters, the model neuron can fire tonically, be quiescent, or generate spontaneous voltage oscillations with varying amounts of depolarization or hyperpolarization. 4. The most common form of synaptic interaction in the gastric CPG is reciprocal inhibition. A pair of identical model cells, connected with reciprocal inhibition, oscillates in antiphase if either the isolated cells are endogenous oscillators, or they are quiescent without plateau potentials, or they have plateau potentials but the synaptic strengths are below a critical level. If the isolated cells have widely differing frequencies (or would have if the cells were made to oscillate by adjusting the fast currents), reciprocal inhibition entrains the cells to oscillate with the same frequency but with phases that are advanced or retarded relative to the phases seen when the cells have the same frequency. The frequency of the entrained pair of cells lies between the frequencies of the original cells. The relative phases can also be modified by using very unequal synaptic strengths.(ABSTRACT TRUNCATED AT 400 WORDS)

The Tritonia Swim Central Pattern Generator

2017 ◽  
pp. 561-568
Author(s):  
Paul S. Katz
Keyword(s):  
Central Pattern Generator ◽  
Sensory Feedback ◽  
Pattern Generator ◽  
Emergent Property ◽  
The Other ◽  
Entire Body ◽  
Neural Basis ◽  
Sea Slug ◽  
Tritonia Diomedea ◽  
State Dependent

Tritonia diomedea is a sea slug that escapes from predatory starfish by rhythmically flexing its entire body in the dorsal and ventral directions. This escape swim behavior is produced by a central pattern generator (CPG), without needing sensory feedback. There are several features of the neural basis for this response that make it of particular interest for neuroscientists. One is that the CPG is a network oscillator; bursting arises as an emergent property of the neurons and their connectivity. Another interesting feature is that the CPG contains state-dependent, intrinsic neuromodulation: one of the CPG neurons uses the neurotransmitter serotonin (5-HT) to modulate the strength of synapses made by the other CPG neurons under certain conditions. This CPG seems to have evolved from a nonoscillatory network. Finally, there are novel mechanisms for plasticity during learning and in response to injury.

scholarly journals Making a Swim Central Pattern Generator Out of Latent Parabolic Bursters

2015 ◽  
Vol 25 (07) ◽  
pp. 1540003 ◽  
Author(s):  
Deniz Alaçam ◽  
Andrey Shilnikov
Keyword(s):  
Central Pattern Generator ◽  
Building Blocks ◽  
Pattern Generator ◽  
Nerve Cells ◽  
Spiking Neurons ◽  
Network Motifs ◽  
Plant Model ◽  
Sea Slug

We study the rhythmogenesis of oscillatory patterns emerging in network motifs composed of inhibitory coupled tonic spiking neurons represented by the Plant model of R15 nerve cells. Such motifs are argued to be used as building blocks for a larger central pattern generator network controlling swim locomotion of sea slug Melibe leonina.

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