Stability and synchronization of memristor-based fractional-order delayed neural networks

Global asymptotic stability and synchronization of a class of fractional-order memristor-based delayed neural networks are investigated. For such problems in integer-order systems, Lyapunov–Krasovskii functional is usually constructed, whereas similar method has not been well developed for fractional-order nonlinear delayed systems. By employing a comparison theorem for a class of fractional-order linear systems with time delay, sufficient condition for global asymptotic stability of fractional memristor-based delayed neural networks is derived. Then, based on linear error feedback control, the synchronization criterion for such neural networks is also presented. Numerical simulations are given to demonstrate the effectiveness of the theoretical results.     

Epileptogenic modulation index and synchronization in hypsarrhythmia of West syndrome secondary to perinatal arterial ischemic stroke

ObjectivePerinatal arterial ischemic stroke (PAIS) is associated with epileptic spasms of West syndrome (WS) and long term Focal epilepsy (FE). The mechanism of epileptogenic network generation causing hypsarrhythmia of WS is unknown. We hypothesized that Modulation index (MI) [strength of phase-amplitude coupling] and Synchronization likelihood (SL) [degree of connectivity] could interrogate the epileptogenic network in hypsarrhythmia of WS secondary to PAIS.MethodsWe analyzed interictal scalp electroencephalography (EEG) in 10 WS and 11 FE patients with unilateral PAIS. MI between gamma (30–70 Hz) and slow waves (3–4 Hz) was calculated to measure phase-amplitude coupling. SL between electrode pairs was analyzed in 9-frequency bands (5-delta, theta, alpha, beta, gamma) to examine inter- and intra-hemispheric connectivity.ResultsMI was higher in affected hemispheres in WS (p = 0.006); no differences observed in FE. Inter-hemispheric SL of 3-delta, theta, alpha, beta, gamma bands was significantly higher in WS (p < 0.001). In WS, modified Z-Score of intra-hemispheric SL values in 3-delta, theta, alpha, beta and gamma in the affected hemispheres were significantly higher than those in the unaffected hemispheres (p < 0.001) as well as 0.5–4 Hz (p = 0.004).ConclusionsThe significantly higher modulation in affected hemisphere and stronger inter- and intra-hemispheric connectivity generate hypsarrhythmia of WS secondary to PAIS.SignificanceEpileptogenic cortical-subcortical transcallosal networks from affected hemisphere post-PAIS provokes infantile spasms.     

How structural and functional MRI can inform dual-site tACS parameters: A case study in a clinical population and its pragmatic implications

BackgroundAbnormalities in frontoparietal network (FPN) were observed in many neuropsychiatric diseases including substance use disorders. A growing number of studies are using dual-site-tACS with frontoparietal synchronization to engage this network. However, a computational pathway to inform and optimize parameter space for frontoparietal synchronization is still lacking. In this case study, in a group of participants with methamphetamine use disorders, we proposed a computational pathway to extract optimal electrode montage while accounting for stimulation intensity using structural and functional MRI.MethodsSixty methamphetamine users completed an fMRI drug cue-reactivity task. Four main steps were taken to define electrode montage and adjust stimulation intensity using 4x1 high-definition (HD) electrodes for a dual-site-tACS; (1) Frontal seed was defined based on the maximum electric fields (EF) predicted by simulation of HD montage over DLPFC (F3/F4 in EEG 10–10), (2) frontal seed-to-whole brain context-dependent correlation was calculated to determine connected regions to frontal seeds, (3) center of connected cluster in parietal cortex was selected as a location for placing the second set of HD electrodes to shape the informed montage, (4) individualized head models were used to determine optimal stimulation intensity considering underlying brain structure. The informed montage was compared to montages with large electrodes and classic frontoparietal HD montages (F3-P3/F4-P4) in terms of tACS-induced EF and ROI-to-ROI task-based/resting-state connectivity.ResultsCompared to the large electrodes, HD frontoparietal montages allow for a finer control of the spatial peak fields in the main nodes of the FPN at the cost of lower maximum EF (large-pad/HD: max EF[V/m] = 0.37/0.11, number of cortical sub-regions that EF exceeds 50% of the max = 77/13). For defining stimulation targets based on EF patterns, using group-level head models compared to a single standard head model results in comparable but significantly different seed locations (6.43 mm Euclidean distance between the locations of the frontal maximum EF in standard-space). As expected, significant task-based/resting-state connections were only found between frontal-parietal locations in the informed montage. Cue-induced craving score was correlated with frontoparietal connectivity only in the informed montage (r = ?0.24). Stimulation intensity in the informed montage, and not in the classic HD montage, needs 40% reduction in the parietal site to reduce the disparity in EF between stimulation sites.ConclusionThis study provides some empirical insights to montage and dose selection in dual-site-tACS using individual brain structures and functions and proposes a computational pathway to use head models and functional MRI to define (1) optimum electrode montage for targeting FPN in a context of interest (drug-cue-reactivity) and (2) proper transcranial stimulation intensity.     

An EEG-based functional connectivity measure for automatic detection of alcohol use disorder

BackgroundThe abnormal alcohol consumption could cause toxicity and could alter the human brain’s structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and manual. Hence, to perform automatic screening of AUD patients, objective methods are needed. The electroencephalographic (EEG) data have been utilized to study the differences of brain signals between alcoholics and healthy controls that could further developed as an automatic screening tool for alcoholics.MethodIn this work, resting-state EEG-derived features were utilized as input data to the proposed feature selection and classification method. The aim was to perform automatic classification of AUD patients and healthy controls. The validation of the proposed method involved real-EEG data acquired from 30 AUD patients and 30 age-matched healthy controls. The resting-state EEG-derived features such as synchronization likelihood (SL) were computed involving 19 scalp locations resulted into 513 features. Furthermore, the features were rank-ordered to select the most discriminant features involving a rank-based feature selection method according to a criterion, i.e., receiver operating characteristics (ROC). Consequently, a reduced set of most discriminant features was identified and utilized further during classification of AUD patients and healthy controls. In this study, three different classification models such as Support Vector Machine (SVM), Naïve Bayesian (NB), and Logistic Regression (LR) were used.ResultsThe study resulted into SVM classification accuracy = 98%, sensitivity = 99.9%, specificity = 95%, and f-measure = 0.97; LR classification accuracy = 91.7%, sensitivity = 86.66%, specificity = 96.6%, and f-measure = 0.90; NB classification accuracy = 93.6%, sensitivity = 100%, specificity = 87.9%, and f-measure = 0.95.ConclusionThe SL features could be utilized as objective markers to screen the AUD patients and healthy controls.     

Dysfunction of sensory oscillations in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a highly prevalent developmental disability characterized by deficits in social communication and interaction, restricted interests, and repetitive behaviors. Recently, anomalous sensory and perceptual function has gained an increased level of recognition as an important feature of ASD. A specific impairment in the ability to integrate information across brain networks has been proposed to contribute to these disruptions. A crucial mechanism for these integrative processes is the rhythmic synchronization of neuronal excitability across neural populations; collectively known as oscillations. In ASD there is believed to be a deficit in the ability to efficiently couple functional neural networks using these oscillations. This review discusses evidence for disruptions in oscillatory synchronization in ASD, and how disturbance of this neural mechanism contributes to alterations in sensory and perceptual function. The review also frames oscillatory data from the perspective of prevailing neurobiologically-inspired theories of ASD.     

实时三维超声评价冠状动脉性心脏病患者左室收缩功能及同步性研究

目的探讨实时三维超声(RT-3DE)评价冠状动脉性心脏病(以下简称冠心病)患者左室收缩功能及同步性的应用价值。方法 61例健康志愿者(正常组)及67例冠心病患者(冠心病组)分别进行实时三维超声和常规超声检查,分析比较各种方法所测左室整体、局部收缩功能参数及同步性参数。结果 RT-3DE与双平面Simpson’s法的相关性高于其与M型超声的相关性。RT-3DE估测左室容积低于常规超声。RT-3DE测量从基底段至心尖段容积呈递减趋势,射血分数呈递增趋势;冠心病组的梗死节段左室整体舒张末期容积和整体收缩末期容积均高于正常组相应节段,各节段射血分数均低于正常组相应节段(均P0.05)。冠心病组左室16节段从QRS波起点到最小收缩容积时间的标准差和最大差值(Tmsv 16-SD、Tmsv 16-Dif),以及用R-R间期校正后的Tmsv 16-SD%、Tmsv 16-Dif%均显著高于正常组,且多支病变患者均高于单支病变(均P0.05)。结论 RT-3DE能更加精准、客观地评价冠心病患者左室收缩功能及同步性。     

林麝泌香期和发情期血清性激素含量的变化

目的:检测林麝泌香期与发情期血清性激素(睾酮、雌二醇和孕酮)水平的变化,研究其变化规律与泌香的关系。方法:采用磁微粒分离酶联免疫法测定林麝泌香期和发情期血中3种性激素含量。结果:林麝在泌香期3种血清性激素含量变化具有明显规律性,三者同步出现波峰,泌香前期睾酮、雌二醇和孕酮含量均处于较低水平,泌香盛期均升到各自最高峰,泌香末期又均迅速降低到与其泌香前期接近的水平。发情期血清睾酮含量升高,出现峰值较低的波峰,雌二醇维持在较低水平,孕酮含量接近零。泌香盛期的血清睾酮含量是发情期的114.4~190.5倍。在泌香期,3种血清性激素含量的相关性属中等、强正直线相关;产香量与血清睾酮含量呈正相关,与血清雌二醇、孕酮含量和年龄均呈负相关。结论:泌香盛期林麝血清睾酮含量上升到最高,可作为人工诱导麝泌香的参考。     

Phase synchronization of coupled bursting neurons and the generalized Kuramoto model

Bursting neurons fire rapid sequences of action potential spikes followed by a quiescent period. The basic dynamical mechanism of bursting is the slow currents that modulate a fast spiking activity caused by rapid ionic currents. Minimal models of bursting neurons must include both effects. We considered one of these models and its relation with a generalized Kuramoto model, thanks to the definition of a geometrical phase for bursting and a corresponding frequency. We considered neuronal networks with different connection topologies and investigated the transition from a non-synchronized to a partially phase-synchronized state as the coupling strength is varied. The numerically determined critical coupling strength value for this transition to occur is compared with theoretical results valid for the generalized Kuramoto model.