A Modeling Study Of Persistent Inward Currents Regulating The Excitability Of 5-HT Neurons

Locomotion is the most basic form of movement in vertebrates.It is initiated by the mesencephalic locomotor region.Through the neural network distributed in the spinal cord,it controls the periodic excitation and inhibition of spinal motorneurons and then produces the flexion and extension of skeletal muscles to generate shifting of the vertebrates.In this process,the intrinsic membrane properties determined by ion channels,and the coding and processing of neural signals determined by the spinal network play an essential role in generation and control of locomotion.This study focuses on the channel mechanisms underlying neuronal excitability and the approach of acquiring the ventral root recording of the spinal cord.The acquisition and processing of signals from the ventral root of spinal cord are the most basic techniques to study the locomotion.Different animal preparations require different signal processing methods.In this study,a professional software was developed for the acquisition and quantitative analysis of ventral root recordings of rodent spinal cord collected during fictive locomotion.At the same time,this thesis focuses on the persistent inward currents(PICs)expressed in the serotonin(5-HT)neurons of midbrain,which plays an important role in locomotion.The PICs consist of the voltage-gated calcium current(Ca-PIC)and slow-inactivating sodium current(NaPIC).Studies have found that 5-HT neurons in the midbrain express PICs,and PICs play an important role in regulating the excitability of 5-HT neurons.Physiological experiment results show that under bi-ramp of voltage-clamp mode,the PICs in 5-HT neurons exhibit different current patterns.The mechanism producing these different patterns of PICs remains unknown,and their roles in regulation of neuronal excitability is also unclear.In order to solve the above problems,a typical neuron model with the electrophysiological properties of 5-HT neurons was built,based on the biophysical parameters of 5-HT neurons in the midbrain.By modulating the dynamic parameters of PICs,the formation of PIC patterns with regulation of discharge patterns of 5-HT neurons were investigated in this study.The simulation results are summarized as below:(1)Increasing the conductance of Na-PIC and Ca-PIC hyperpolarized(decreased)the onset voltage(Vonset)and offset voltage(Voffset)of 5-HT neurons recorded with the triangular ramp voltage-clamp.And the onset current(Ionset)and offset current(Ioffset)of the continuous discharge of neurons recorded with the triangular ramp current-clamp were reduced.However,no obvious effect on the PIC hysteresis(VonsetVoffset)and the discharge frequency hysteresis(Ionset-Ioffset)were observed.(2)Reduction of the slope of the Na-PIC activation curve,increase of the degree of inactivation,lowering of the slope of the Ca-PIC activation curve,and depolarization of the half activation voltage(shift to the right)could make the Vonset less than Voffset and the Ionset smaller than Ioffset.These reduce the PIC hysteresis and the discharge frequency hysteresis.(3)Extending the length of dendrites depolarized the Vonset and hyperpolarized Voffset.The Ionset was increased linearly while Ioffset was increased first and then decreased nonlinearly,that is,PIC hysteresis and discharge frequency hysteresis were enhanced.(4)The excitatory synaptic input and current injection to soma generated the same discharge frequency hysteresis.(5)The amplitude of the ascending PIC(A-PIC)greater than the amplitude of the descending PIC(D-PIC)is mainly caused by the inactivation gating mechanism of NaPIC.On the contrary,however,the amplitude of A-PIC smaller than that of D-PIC was mainly produced by the activation gating mechanism of the Ca-PIC.Combined with a series of biological simulation methods and data from physiological experiments,for the first time this study investigated the channel mechanisms underlying the multiple PIC patterns.It could provide new clues and basis for future neurophysiological experiments.It could also guide future physiological experiments to verify the validity of the results predicted by this model.In addition,the neural signal processing software developed in this study is an efficient method for study of locomotion and motor control.The results of this study could provide ideas for research and development of intelligent systems for motion control from the aspects of neural signal processing and ionic channel modulation.