Effect of applied electric fields on supralinear dendritic integration of interneuron

Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron.However,it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic inputs.Considering the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations,we suppose that the applied EFs could functionally modulate interneurons’response via regulating dendritic integration.At first,we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials,which characterizes the relationship among EF-induced spatial polarizations,dendritic integration,and somatic output.By performing model-based singular perturbation analysis,it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input–output(sI/O)relationship of dendritic integration.It predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input,and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA spike.Also,the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA synapses.Furthermore,we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.

Parkinsonian oscillations and their suppression by closed-loop deep brain stimulation based on fuzzy concept

This paper provides an adaptive closed-loop strategy for suppressing the pathological oscillations of the basal ganglia based on a variable universe fuzzy algorithm.The pathological basal ganglia oscillations in the theta(4-9 Hz)and beta(12-35 Hz)frequency bands have been demonstrated to be associated with the tremor and rigidity/bradykinesia symptoms in Parkinson’s disease(PD).Although the clinical application of open-loop deep brain stimulation(DBS)is effective,the stimulation waveform with the fixed parameters cannot be self-adjusted as the disease progresses,and thus the stimulation effects go poor.To deal with this difficult problem,a variable universe fuzzy closed-loop strategy is proposed to modulate different PD states.We establish a cortico-basal ganglia-thalamocortical network model to simulate pathological oscillations and test the control effect.The results suggest that the proposed closed-loop control strategy can accommodate the variation of brain states and symptoms,which may become an alternative method to administrate the symptoms in PD.