Abstract
A biologically realistic neural network model of the tadpole spinal cord has been design. Morris-Lecar model of a single neuron is used to describe the spike generation. A bifurcation analysis of two inhibitory coupled Morris-Lecar elements with post-inhibitory rebound provides a range of parameters where anti-phase oscillations exist. A simple model of axon growth with deterministic and stochastic components allows to generate a complete biologically realistic architecture of neuronal connectivity of the tadpole spinal cord. We use this architecture of interconnected Morris-Lecar elements with randomly distributed parameter values to demonstrate that the neural network can generate a specific pattern of neural activity corresponding to the tadpole swimming.
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