ArticleJournal of computational neuroscience
Coordinated motor activity in simulated spinal networks emerges from simple biologically plausible rules of connectivity.
Article in Journal of computational neuroscience. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Spatial and network principles behind neural generation of locomotion.Nature communications · 2026Article
- Spinal Interneurons: Diversity and Connectivity in Motor Control.Annual review of neuroscience · 2023Review
- Spinal V1 neurons inhibit motor targets locally and sensory targets distally.Current biology : CB · 2021Article
- Computational Modeling of Spinal Locomotor Circuitry in the Age of Molecular Genetics.International journal of molecular sciences · 2021Review
- Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity.PLoS computational biology · 2016Article
- Modelling the Effects of Electrical Coupling between Unmyelinated Axons of Brainstem Neurons Controlling Rhythmic Activity.PLoS computational biology · 2015Article
- How neurons generate behavior in a hatchling amphibian tadpole: an outline.Frontiers in behavioral neuroscience · 2010Article
- Longitudinal neuronal organization and coordination in a simple vertebrate: a continuous, semi-quantitative computer model of the central pattern generator for swimming in young frog tadpoles.Journal of computational neuroscience · 2009Article
- Roles for inhibition: studies on networks controlling swimming in young frog tadpoles.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2008Review
- Role of type-specific neuron properties in a spinal cord motor network.Journal of computational neuroscience · 2007Article
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Abstract
The spinal motor circuits of the Xenopus embryo have been simulated in a 400-neuron network. To explore the consequences of differing patterns of synaptic connectivity within the network for the generation of the motor rhythm, a system of biologically plausible rules was devised to control synapse formation by three parameters. Each neuron had an intrinsic probability of synapse formation (P(soma), specified by a space constant lambda) that was a monotonically decreasing function of its soma location in the rostro-caudal axis of the simulated network. The neurons had rostral and caudal going axons of specified length (L(axon)) associated with a probability of synapse formation (P(axon)). The final probability of synapse formation was the product of P(soma) and P(axon). Realistic coordinated activity only occurred when L(axon) and the probabilities of interconnection were sufficiently high. Increasing the values of the three network parameters reduced the burst duration, cycle period, and rostro-caudal delay and increased the reliability with which the network functioned as measured by the coefficient of variance of these parameters. Whereas both L(axon) and P(axon) had powerful and consistent effects on network output, the effects of lambda on burst duration and rostro-caudal delay were more variable and depended on the values of the other two parameters. This network model can reproduce the rostro-caudal coordination of swimming without using coupled oscillator theory. The changes in network connectivity and resulting changes in activity explored by the model mimic the development of the motor pattern for swimming in the real embryo.
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