Improving control effects of absence seizures using single-pulse alternately resetting stimulation (SARS) of corticothalamic circuit

Fan, Denggui; Zheng, Yanhong; Yang, Zecheng; Wang, Qingyun

doi:10.1007/s10483-020-2644-8

Cited by 33 publications

(14 citation statements)

References 48 publications

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“…Besides, they also explored the possible sources of abnormal oscillations in the CTBG, and found that oscillations around 5 Hz and 20 Hz can be generated through a strong indirect way, which will also lead to increase the synchronization of the entire BG. In addition to exploring PD, the mean-field model of CTBG has also been widely used to explore neurological diseases such as epilepsy [38][39] . Subsequently, based on the mean-field model of CTBG, a new network model for the pedunculopontine nucleus (PPN) was established to investigate how PPN controls the PD through the projections from the PPN to several key nuclei of BG and thalamus [40] .…”

Section: Neural Field Modelsmentioning

confidence: 99%

A review of computational modeling and deep brain stimulation: applications to Parkinson’s disease

Wang

2020

Appl. Math. Mech.-Engl. Ed.

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Biophysical computational models are complementary to experiments and theories, providing powerful tools for the study of neurological diseases. The focus of this review is the dynamic modeling and control strategies of Parkinson’s disease (PD). In previous studies, the development of parkinsonian network dynamics modeling has made great progress. Modeling mainly focuses on the cortex-thalamus-basal ganglia (CTBG) circuit and its sub-circuits, which helps to explore the dynamic behavior of the parkinsonian network, such as synchronization. Deep brain stimulation (DBS) is an effective strategy for the treatment of PD. At present, many studies are based on the side effects of the DBS. However, the translation from modeling results to clinical disease mitigation therapy still faces huge challenges. Here, we introduce the progress of DBS improvement. Its specific purpose is to develop novel DBS treatment methods, optimize the treatment effect of DBS for each patient, and focus on the study in closed-loop DBS. Our goal is to review the inspiration and insights gained by combining the system theory with these computational models to analyze neurodynamics and optimize DBS treatment.

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Section: Neural Field Modelsmentioning

confidence: 99%

A review of computational modeling and deep brain stimulation: applications to Parkinson’s disease

Wang

2020

Appl. Math. Mech.-Engl. Ed.

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“…Introduction. Nonlinear dynamics has played very important roles in identifying dynamics of neural electrical activities [10,29,32], which are involved in the information processing, locomotion control, cognitive functions, and brain disease [8,19,31]. These activities mainly include the steady state such as the resting state and the firing behavior composed of action potentials or spikes, for example, the spiking and bursting, which has been widely investigated with the conceptions of bifurcations and chaos [6,16,18,23,33].…”

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confidence: 99%

Big homoclinic orbit bifurcation underlying post-inhibitory rebound spike and a novel threshold curve of a neuron

Wang

2021

era

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Post-inhibitory rebound (PIR) spike induced by the negative stimulation, which plays important roles and presents counterintuitive nonlinear phenomenon in the nervous system, is mainly related to the Hopf bifurcation and hyperpolarization-active caution (I h) current. In the present paper, the emerging condition for the PIR spike is extended to the bifurcation of the big homoclinic (BHom) orbit in a model without I h current. The threshold curve for a spike evoked from a mono-stable or coexisting steady state surrounds the steady state from left, to below, and to right, because the BHom orbit is big enough to surround the steady state. The right part of the threshold curve coincides with the stable manifold of the saddle and acts the threshold for the spike induced by the positive stimulation, resembling that of the saddle-node bifurcation on an invariant cycle, and the left part acts the threshold for the PIR spike, resembling that of the Hopf bifurcation. The bifurcation curve and a codimension-2 bifurcation point related to the BHom orbit are acquired in the two-parameter plane. The results present a comprehensive viewpoint to the dynamics near the BHom orbit bifurcation, which presents a novel threshold curve and extends the conditions for the PIR spike.

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“…Identification of nonlinear dynamics of neuronal electrical behavior is very important for understanding the functions of nervous system [1][2][3][4][5][6]. Neuronal bursting is a complex nonlinear electrical behavior related to fast and slow variables, which participates many kinds of physiological functions, pathological functions, and even brain diseases [7][8][9]. For example, bifurcations of bursting have been identified to participate information coding [10][11][12][13][14] in blood pressure and pathological pain.…”

Section: Introductionmentioning

confidence: 99%

Fast-slow Variable Dissection with Two Slow Variables Related to Calcium Concentrations: A Case Study to Bursting in a Neural Pacemaker Model

Jia

et al. 2021

Preprint

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Neuronal bursting is an electrophysiological behavior participating in physiological or pathological functions and a complex nonlinear alternating between burst and quiescent state modulated by slow variables. Identification of dynamics of bursting modulated by two slow variables is still an open problem. In the present paper, a novel fast-slow variable dissection method with two slow variables is proposed to analyze the complex bursting in a 4-dimensional neuronal model to describe bursting associated with pathological pain. The lumenal (Clum) and intracellular (Cin) calcium concentrations are the slowest variables respectively in the quiescent state and burst duration. Questions encountered when the traditional method with one low variable is used. When Clum is taken as slow variable, the burst is successfully identified to terminate near the saddle-homoclinic bifurcation point of the fast subsystem and begin not from the saddle-node bifurcation. With Cin chosen as slow variable, Clum value of initiation point is far from the saddle-node bifurcation point, due to Clum not contained in the equation of membrane potential. To overcome this problem, both Cin and Clum are regarded as slow variables, the two-dimensional fast subsystem exhibits a saddle-node bifurcation point, which is extended to a saddle-node bifurcation curve by introducing Clum dimension. Then, the initial point of burst is successfully identified to be near the saddle-node bifurcation curve. The results present a feasible method for fast-slow variable dissection and deep understanding to the complex bursting behavior with two slow variables, which is helpful for the modulation to pathological pain.

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Improving control effects of absence seizures using single-pulse alternately resetting stimulation (SARS) of corticothalamic circuit

Cited by 33 publications

References 48 publications

A review of computational modeling and deep brain stimulation: applications to Parkinson’s disease

A review of computational modeling and deep brain stimulation: applications to Parkinson’s disease

Big homoclinic orbit bifurcation underlying post-inhibitory rebound spike and a novel threshold curve of a neuron

Fast-slow Variable Dissection with Two Slow Variables Related to Calcium Concentrations: A Case Study to Bursting in a Neural Pacemaker Model

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