The important role of glial transmitters released by astrocytes in Alzheimer's disease: A perspective from dynamical modeling.

This paper aims to establish a coupling model of neuronal populations and astrocytes and, on this basis, explore the possible mechanism of electroencephalography (EEG) slowing in Alzheimer's disease (AD) from the viewpoint of dynamical modeling. First and foremost, excitatory and inhibitory time constants are shown to induce the early symptoms of AD. The corresponding dynamic nature is mainly due to changes in the amplitude and frequency of the oscillatory behavior. However, there are also a few cases that can be attributed to the change of the oscillation mode caused by the limit cycle bifurcation and birhythmicity. Then, an improved neural mass model influenced by astrocytes is proposed, considering the important effects of glutamate and adenosine triphosphate (ATP) released by astrocytes on the synaptic transmission process reported in experiments. The results show that a dysfunctional astrocyte disrupts the physiological state, causing three typical EEG slowing phenomena reported clinically: the decreased dominant frequency, the decreased rhythmic activity in the α band, and the increased rhythmic activity in the δ+θ band. In addition, astrocytes may control AD when the effect of ATP on synaptic connections is greater than that of glutamate. The control rate depends on the ratio of the effect of glutamate on excitatory and inhibitory synaptic connections. These modeling results can not only reproduce some experimental and clinical results, but, more importantly, may offer a prediction of some underlying phenomena, helping to inspire the disease mechanisms and therapeutic methods of targeting astrocytes.

Dynamical Mechanism Analysis of Three Neuroregulatory Strategies on the Modulation of Seizures.

This paper attempts to explore and compare the regulatory mechanisms of optogenetic stimulation (OS), deep brain stimulation (DBS) and electromagnetic induction on epilepsy. Based on the Wilson-Cowan model, we first demonstrate that the external input received by excitatory and inhibitory neural populations can induce rich dynamic bifurcation behaviors such as Hopf bifurcation, and make the system exhibit epileptic and normal states. Then, both OS and DBS are shown to be effective in controlling the epileptic state to a normal low-level state, and the stimulus parameters have a broad effective range. However, electromagnetic induction cannot directly control epilepsy to this desired state, even if it can significantly reduce the oscillation frequency of neural populations. One main difference worth noting is that the high spatiotemporal specificity of OS allows it to target inhibitory neuronal populations, whereas DBS and electromagnetic induction can only stimulate excitatory as well as inhibitory neuronal populations together. Next, the propagation behavior of epilepsy is explored under a typical three-node feedback loop structure. An increase in coupling strength accelerates and exacerbates epileptic activity in other brain regions. Finally, OS and DBS applied to the epileptic focus play similar positive roles in controlling the behavior of the area of seizure propagation, while electromagnetic induction still only achieves unsatisfactory effects. It is hoped that these dynamical results can provide insights into the treatment of epilepsy as well as other neurological disorders.

Transition dynamics and optogenetic controls of generalized periodic epileptiform discharges.

This paper aims to analyze possible mechanisms underlying the generation of generalized periodic epileptiform discharges (GPEDs), especially to design targeted optogenetic regulation strategies. First and foremost, inspired by existing physiological experiments, we propose a new computational framework by introducing a second inhibitory neuronal population and related synaptic connections into the classic Liley mean field model. The improved model can simulate the basic normal and abnormal brain activities mentioned in previous studies, but much to our relief, it perfectly reproduces some types of GPEDs that match the clinical records. Specifically, results show that disinhibitory synaptic connections between inhibitory interneuronal populations are closely related to the occurrence, transition and termination of GPEDs, including delaying the occurrence of GPEDs caused by the excitatory AMPAergic autapses and regulating the transition process of GPEDs bidirectionally, which support the conjecture that selective changes of synaptic connections can trigger GPEDs. Additionally, we creatively offer six optogenetic strategies with dual targets. They can all control GPEDs well, just as experiments reveal that optogenetic stimulation of inhibitory interneurons can suppress abnormal activities in epilepsy or other brain diseases. More importantly, 1:1 coordinated reset stimulation with one period rest is concluded as the optimal strategy after taking into account the energy consumption and control effect. Hope these results provide feasible references for pathophysiological mechanisms of GPEDs.

Adaptive Event-Triggered Synchronization of Uncertain Fractional Order Neural Networks with Double Deception Attacks and Time-Varying Delay.

This paper investigates the problem of adaptive event-triggered synchronization for uncertain FNNs subject to double deception attacks and time-varying delay. During network transmission, a practical deception attack phenomenon in FNNs should be considered; that is, we investigated the situation in which the attack occurs via both communication channels, from S-C and from C-A simultaneously, rather than considering only one, as in many papers; and the double attacks are described by high-level Markov processes rather than simple random variables. To further reduce network load, an advanced AETS with an adaptive threshold coefficient was first used in FNNs to deal with deception attacks. Moreover, given the engineering background, uncertain parameters and time-varying delay were also considered, and a feedback control scheme was adopted. Based on the above, a unique closed-loop synchronization error system was constructed. Sufficient conditions that guarantee the stability of the closed-loop system are ensured by the Lyapunov-Krasovskii functional method. Finally, a numerical example is presented to verify the effectiveness of the proposed method.

Dynamic Transitions of Epilepsy Waveforms Induced by Astrocyte Dysfunction and Electrical Stimulation.

Experimental studies have shown that astrocytes participate in epilepsy through inducing the release of glutamate. Meanwhile, considering the disinhibition circuit among inhibitory neuronal populations with different time scales and the feedforward inhibition connection from thalamic relay nucleus to cortical inhibitory neuronal population, here, we propose a modified thalamocortical field model to systematically investigate the mechanism of epilepsy. Firstly, our results show that rich firing activities can be induced by astrocyte dysfunction, including high or low saturated state, high- or low-frequency clonic, spike-wave discharge (SWD), and tonic. More importantly, with the enhancement of feedforward inhibition connection, SWD and tonic oscillations will disappear. In other words, all these pathological waveforms can be suppressed or eliminated. Then, we explore the control effects after different external stimulations applying to thalamic neuronal population. We find that single-pulse stimulation can not only suppress but also induce pathological firing patterns, such as SWD, tonic, and clonic oscillations. And we further verify that deep brain stimulation can control absence epilepsy by regulating the amplitude and pulse width of stimulation. In addition, based on our modified model, 3 : 2 coordinated reset stimulation strategies with different intensities are compared and a more effective and safer stimulation mode is proposed. Our conclusions are expected to give more theoretical insights into the treatment of epilepsy.

Control analysis of electrical stimulation for epilepsy waveforms in a thalamocortical network.

Physiological experiments and computational models both show that the thalamic reticular nucleus (RE) participates in inducing various firing patterns of cortex. Absence seizure, featured by 2-4 Hz spike-wave discharges (SWD) oscillation, is a high incidence of disease in children. Lots of electrophysiological experiments have verified the correlation between absence seizures and RE, however, the dynamical mechanisms are not well understood. Based on previous Taylor model, we firstly study the effects of external input and self-inhibition of RE on epilepsy transition. We show that increasing external input and self-inhibition of RE can lead the system from epileptic state to normal state, and vice versa. Next, we explore two stimulus strategies added in RE and various transition behaviors can be induced, such as high saturated state to clonic. Meanwhile, as the intensity of stimulation increasing, they can not only suppress the SWD, but also produce tonic-clonic oscillation. Finally, the control of DBS on single neuron cluster and two neuron clusters are compared and we find stimulating RE and TC simultaneously is a superior mode to stimulate anyone of RE or TC. It is hoped that the results we obtained will have an enlightenment on clinical treatment.