Undulatory Locomotion — Simulations with Realistic Segmental Oscillator

Wadden, Tom; Grillner, Sten; Matsushima, Toshiya; Lansner, Anders

doi:10.1007/978-1-4615-3254-5_46

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…4 A1-5). This is in accordance with the earlier simulations of fictive swimming where more detailed neuron models were used (Wallrn et al 1992;Wadden et al 1993). The resulting length of these neural waves is slightly shorter than the length of the spinal cord.…”

Section: Propulsionsupporting

confidence: 68%

“…The "extent" denotes how far these connections reach (in number of segments) in the rostral and caudal direction. The connection weight (w~) used in (1) is the "strength" given here divided by the number of segments it connects to Ex, Excitatory; Inh, inhibitory findings for the isolated spinal cord of the lamprey (Matsushima and Grillner 1992) as well as with simulation results using the detailed neuron model (Wadden et al 1993).…”

Section: The Neural Network Modelmentioning

confidence: 99%

“…Indeed, computer simulations of the lamprey central pattern generator have been successful in explaining most observations during fictive swimming (Wall6n et al 1992;Wadden et al 1993) in terms of realistically simulated neurons Brodin et al 1991) and a synaptic connectivity based on known connections from paired intracellular recordings . However, restricting the use of realistic simulations only to model such isolated preparations is not desirable.…”

Section: Introductionmentioning

confidence: 99%

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A combined neuronal and mechanical model of fish swimming

1993

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Abstract.A simulated neural network has been connected to a simulated mechanical environment. The network is based on a model of the spinal central pattern generator producing rhythmic swimming movements in the lamprey and the model is similar to that used in earlier simulations of fictive swimming. Here, the network has been extended with a model of how motoneuron activity is transformed via the muscles to mechanical forces. Further, these forces are used in a two-dimensional mechanical model including interaction with the surrounding water, giving the movements of the different parts of the body. Finally, these movements are fed back through stretch receptors interacting with the central pattern generator. The combined model provides a platform for various simulation experiments relating the currently known neural properties and connectivity to the behavior of the animal in vivo. By varying a small set of parameters, corresponding to brainstem input to the spinal network, a variety of basic locomotor behaviors, like swimming at different speeds and turning can be produced. This paper describes the combined model and its basic properties.

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Section: Propulsionsupporting

confidence: 68%

Section: The Neural Network Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A combined neuronal and mechanical model of fish swimming

1993

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“…A number of models where neurons are used have been based on the reasonable assumption that the connectivity pattern observed locally is also preserved between segments (Buchanan 1992;Williams 1992;Ekeberg 1993;Wadden et al 1993Wadden et al , 1997. These simulations show that coordinated waves of activity can be generated without any extra mechanisms involved.…”

Section: (B) Intersegmental Coordinationmentioning

confidence: 99%

Simulations of neuromuscular control in lamprey swimming

Ekeberg

Grillner

1999

Phil. Trans. R. Soc. Lond. B

121

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The neuronal generation of vertebrate locomotion has been extensively studied in the lamprey. Models at di¡erent levels of abstraction are being used to describe this system, from abstract nonlinear oscillators to interconnected model neurons comprising multiple compartments and a Hodgkin^Huxley representation of the most relevant ion channels. To study the role of sensory feedback by simulation, it eventually also becomes necessary to incorporate the mechanical movements in the models. By using simplifying models of muscle activation, body mechanics, counteracting water forces, and sensory feedback through stretch receptors and vestibular organs, we have been able to close the feedback loop to enable studies of the interaction between the neuronal and the mechanical systems. The neuromechanical simulations reveal that the currently known network is su¤cient for generating a whole repertoire of swimming patterns. Swimming at di¡erent speeds and with di¡erent wavelengths, together with the performance of lateral turns can all be achieved by simply varying the brainstem input. The neuronal mechanisms behind pitch and roll manoeuvres are less clear. We have put forward a`crossed-oscillators' hypothesis where partly separate dorsal and ventral circuits are postulated. Neuromechanical simulations of this system show that it is also capable of generating realistic pitch turns and rolls, and that vestibular signals can stabilize the posture during swimming.

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“…The present study further develops the model of Wadden et al (1993). It includes the multisegmental connectivity from excitatory and inhibitory interneurons, the latter possessing long descending axons.…”

Section: Introductionmentioning

confidence: 98%

Intersegmental coordination in the lamprey: simulations using a network model without segmental boundaries

Wadden

Hellgren

Lansner

et al. 1997

Biological Cybernetics

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Swimming in vertebrates such as eel and lamprey involves the coordination of alternating left and right activity in each segment. Forward swimming is achieved by a lag between the onset of activity in consecutive segments rostrocaudally along the spinal cord. The intersegmental phase lag is approximately 1% of the cycle duration per segment and is independent of the swimming frequency. Since the lamprey has approximately 100 spinal segments, at any given time one wave of activity is propagated along the body. Most previous simulations of intersegmental coordination in the lamprey have treated the cord as a chain of coupled oscillators or well-defined segments. Here a network model without segmental boundaries is described which can produce coordinated activity with a phase lag. This 'continuous' pattern-generating network is composed of a column of 420 excitatory interneurons (E1 to E420) and 300 inhibitory interneurons (C1 to C300) on each half of the simulated spinal cord. The interneurons are distributed evenly along the simulated spinal cord, and their connectivity is chosen to reflect the behavior of the intact animal and what is known about the length and strength of the synaptic connections. For example, E100 connects to all interneurons between E51 and E149, but at varying synaptic strengths, while E101 connects to all interneurons between E52 and E150. This unsegmented E-C network generates a motor pattern that is sampled by output elements similar to motoneurons (M cells), which are arranged along the cell column so that they receive input from seven E and five C interneurons. The M cells thus represent the summed excitatory and inhibitory input at different points along the simulated spinal cord and can be regarded as representing the ventral root output to the myotomes along the spinal cord. E and C interneurons have five simulated compartments and Hodgkin-Huxley based dynamics. The simulated network produces rhythmic output over a wide range of frequencies (1-11 Hz) with a phase lag constant over most of the length, with the exception of the 'cut' ends due to reduced synaptic input. As the inhibitory C interneurons in the simulation have more extensive caudal than rostral projections, the output of the simulation has positive phase lags, as occurs in forward swimming. However, unlike the biological network, phase lags in the simulation increase significantly with burst frequency, from 0.5% to 2.3% over the range of frequencies of the simulation. Local rostral or caudal increases in excitatory drive in the simulated network are sufficient to produce motor patterns with increased or decreased phase lags, respectively.

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Undulatory Locomotion — Simulations with Realistic Segmental Oscillator

Cited by 5 publications

References 9 publications

A combined neuronal and mechanical model of fish swimming

A combined neuronal and mechanical model of fish swimming

Simulations of neuromuscular control in lamprey swimming

Intersegmental coordination in the lamprey: simulations using a network model without segmental boundaries

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