Coordinated motor activity in simulated spinal networks emerges from simple biologically plausible rules of connectivity
UNSPECIFIED. (2003) Coordinated motor activity in simulated spinal networks emerges from simple biologically plausible rules of connectivity. JOURNAL OF COMPUTATIONAL NEUROSCIENCE, 14 (1). pp. 55-70. ISSN 0929-5313Full text not available from this repository.
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.) 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.
|Item Type:||Journal Article|
|Subjects:||Q Science > QH Natural history > QH301 Biology
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
|Journal or Publication Title:||JOURNAL OF COMPUTATIONAL NEUROSCIENCE|
|Publisher:||KLUWER ACADEMIC PUBL|
|Number of Pages:||16|
|Page Range:||pp. 55-70|
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