Computational modelling of a Central Pattern Generator
نویسندگان
چکیده
Central Pattern Generators (CPGs) are small, rhythmically active networks, which control simple repetitive behaviours, in both vertebrates and invertebrates. Research on CPGs aims at understanding how the periodic pattern is generated and modulated, by investigating the intrinsic and synaptic properties of the component neurons. In this study, we present a mathematical, biophysically-realistic model of the feeding CPG of the pond snail Lymnaea stagnalis. This network is composed of three groups of interneurons (N1, N2 and N3), which are sequentially activated and inhibited, thus providing a triphasic pattern of activity, which drives the movements of the feeding muscles (protraction, rasp and swallow). The model gives a successful description of the intrinsic properties of the individual neurons (e.g. plateau potentials and post-inhibitory rebound) and it reflects the topology of the biological network. The core of the model is a twocomponent circuit, composed of the neurons N1 medial and N2 ventral from the first two groups of CPG interneurons, which is capable of producing oscillations at low frequencies, when appropriately stimulated. A neuron from the third group, the N3 tonic, is not necessary for the generation of a rhythmic pattern, but it is included, since it provides a third phase of activity and it has a potentially modulatory role by exerting inhibitory effects of variable strength upon the rest of the CPG. This minimal oscillatory network is utilized in order to determine possible mechanisms by which a modulatory neuron known as Slow Oscillator affects the behaviour of the CPG. An important conclusion is that this neuron may mediate high frequency rhythms by inducing a reduction of both the protraction and swallow phases of the feeding cycle. The predictions of our model are in agreement with all known experimental results
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تاریخ انتشار 2005