Research On The Variability Of The Rhythm Of The Respiratory Central Pattern Generator

Central pattern generators(CPGs)are biological neural circuits that produce rhythmic outputs in the absence of rhythmic input.The respiratory central pattern generator that produces the respiratory rhythm has been experimentally shown to consist of four representative neuron population.A deterministic network model for respiratory CPG has been used to reproduce the respiratory rhythm pattern and to analyze the functional state of the respiratory CPG and the inherent corresponding oscillations mechanism.However,the shortcoming of this respiratory CPG model is the lack of many factors in the real neural network environment,such as ion channel noise,time-delay feedback,synaptic plasticity,and so on.Therefore,in this paper,the model is extended to introduce noise,synaptic plasticity and time-delay feedback,and then to study the effects of these factors on the variability of the respiratory CPG output rhytm.In order to simulate the noise environment of real neuron networks,ion channel noise is introduced in this paper.Noise of different intensities is generated by changing the neuron ion channels number N and the influence of noise intensity on respiratory CPG output is studied.Studies have found that weakened noise intensity(increased channel numbers)reduces expiration period,increases the inspiration period,which leads to respiratory abnormalities,and increases the output irregularities.There is a channel number N that can minimize output variability.Meanwhile it is found that the output amplitude of Early-I in the four types of neurons is most sensitive to changes in noise intensity.Synaptic plasticity is an intrinsic property of neural networks.To study the effect of synaptic plasticity on respiratory CPG output rhythm,the weight of neuronal synaptic input is changed from a constant to a variable that changes with each discharge of presynaptic neurons(short-term synaptic plasticity STP),in order to get research on the effects that inhibitory / excitatory STP of different strength on deterministic and stochastic model output rhythm.The excitatory STP is found to increase the CPG output cycle and increase variability,and the inhibitory STP will reduce the CPG output cycle and increase variability.Feedback is the basic characteristics of neural networks.In order to study the effect of feedback on respiratory CPG output rhythmThis paper simplifies the vagus nerve feedback in the closed-loop respiratory system model,constructs a time-delayed feedback sourced from the Pre-I neuron,and studies the effect of different types(inhibitory/excitatory)and different strengths of the feedback on the CPG output rhythm.It's found to be that the delay feedback can change the variability of the output period and period,which proves delayed feedback alters output period and period variability,and also,the feedbacks with certain delayed time makes the stochastic network output most regular(optimal).This paper extends and investigates the respiratory CPG model,which is completed to a deeper level by this conclusion,and inspires the characteristic study on respiratory rhythm in some certain level.