Differentiating ictal/subclinical spikes and waves in childhood absence epilepsy by spectral and network analyses: A pilot study

ObjectiveChildhood absence epilepsy (CAE) is a disease with distinct seizure semiology and electroencephalographic (EEG) features. Differentiating ictal and subclinical generalized spikes and waves discharges (GSWDs) in the EEG is challenging, since they appear to be identical upon visual inspection. Here, spectral and functional connectivity (FC) analyses were applied to routine EEG data of CAE patients, to differentiate ictal and subclinical GSWDs.MethodsTwelve CAE patients with both ictal and subclinical GSWDs were retrospectively selected for this study. The selected EEG epochs were subjected to frequency analysis in the range of 1–30 Hz. Further, FC analysis based on the imaginary part of coherency was used to determine sensor level networks.ResultsDelta, alpha and beta band frequencies during ictal GSWDs showed significantly higher power compared to subclinical GSWDs. FC showed significant network differences for all frequency bands, demonstrating weaker connectivity between channels during ictal GSWDs.ConclusionUsing spectral and FC analyses significant differences between ictal and subclinical GSWDs in CAE patients were detected, suggesting that these features could be used for machine learning classification purposes to improve EEG monitoring.SignificanceIdentifying differences between ictal and subclinical GSWDs using routine EEG, may improve understanding of this syndrome and the management of patients with CAE.     

Dynamic functional connectivity of the EEG in relation to outcome of postanoxic coma

ObjectiveEarly EEG contains reliable information for outcome prediction of comatose patients after cardiac arrest. We introduce dynamic functional connectivity measures and estimate additional predictive values.MethodsWe performed a prospective multicenter cohort study on continuous EEG for outcome prediction of comatose patients after cardiac arrest. We calculated Link Rates (LR) and Link Durations (LD) in the α, δ, and θ band, based on similarity of instantaneous frequencies in five-minute EEG epochs, hourly, during 3 days after cardiac arrest. We studied associations of LR and LD with good (Cerebral Performance Category (CPC) 1–2) or poor outcome (CPC 3–5) with univariate analyses. With random forest classification, we established EEG-based predictive models. We used receiver operating characteristics to estimate additional values of dynamic connectivity measures for outcome prediction.ResultsOf 683 patients, 369 (54%) had poor outcome. Patients with poor outcome had significantly lower LR and longer LD, with largest differences 12 h after cardiac arrest (LR_θ 1.87 vs. 1.95 Hz and LD_α 91 vs. 82 ms). Adding these measures to a model with classical EEG features increased sensitivity for reliable prediction of poor outcome from 34% to 38% at 12 h after cardiac arrest.ConclusionPoor outcome is associated with lower dynamics of connectivity after cardiac arrest.SignificanceDynamic functional connectivity analysis may improve EEG based outcome prediction.     

EEG functional connectivity contributes to outcome prediction of postanoxic coma

ObjectiveTo investigate the additional value of EEG functional connectivity features, in addition to non-coupling EEG features, for outcome prediction of comatose patients after cardiac arrest.MethodsProspective, multicenter cohort study. Coherence, phase locking value, and mutual information were calculated in 19-channel EEGs at 12 h, 24 h and 48 h after cardiac arrest. Three sets of machine learning classification models were trained and validated with functional connectivity, EEG non-coupling features, and a combination of these. Neurological outcome was assessed at six months and categorized as “good” (Cerebral Performance Category [CPC] 1–2) or “poor” (CPC 3–5).ResultsWe included 594 patients (46% good outcome). A sensitivity of 51% (95% CI: 34–56%) at 100% specificity in predicting poor outcome was achieved by the best functional connectivity-based classifier at 12 h after cardiac arrest, while the best non-coupling-based model reached a sensitivity of 32% (0–54%) at 100% specificity using data at 12 h and 48 h. Combination of both sets of features achieved a sensitivity of 73% (50–77%) at 100% specificity.ConclusionFunctional connectivity measures improve EEG based prediction models for poor outcome of postanoxic coma.SignificanceFunctional connectivity features derived from early EEG hold potential to improve outcome prediction of coma after cardiac arrest.     

Is watch and wait a safe and effective way to treat rectal cancer in older patients?

IntroductionThe aim was assess the oncological and functional outcome of the watch-and-wait (W&W) approach in older patients with a clinical (near)complete response after neoadjuvant treatment for rectal cancer.Material and methodsPatients were included in a W&W-approach (2004–2019) when digital rectal examination, endoscopy and MRI showed a (near)clinical complete response. Patients underwent endoscopy and MRI every 3 months during the first year, and 6-monthly thereafter. Patients aged ≥75 and ≥ 2 years of follow-up (FU) were selected. Oncological outcomes were assessed with Kaplan-Meier curves. Functional outcome was assessed with colostomy-free rate, Vaizey incontinence score, low anterior resection syndrome-score and International Prostate Syndrome Score.Results43/304 (14%) of patients in a W&W-approach met the inclusion criteria. Median FU was 37 (24–109) months. 5/43(12%) developed a local regrowth. All were treated surgically, with one patient experiencing a pelvic failure. Distant metastases occurred in 3/43 patients and 4 patients died, 3 of whom not related to rectal cancer. The 3-year local regrowth-free rate was 88%, 3-year non-regrowth disease-free survival 91%, overall survival 97% and 3-year colostomy-free rate 93%. Overall, the bowel- and urinary dysfunction scores at 3, 12 and 24 months indicated good continence, no or minor LARS and moderate urinary problems.ConclusionW&W for older patients with a clinical (near) complete response appears to be a safe alternative to a total mesorectal excision (TME), with a very high pelvic control rate, and few rectal cancer related deaths. Most patients can avoid major surgery and a definitive colostomy, and have a reasonable anorectal and urinary function.     

静息态功能磁共振成像功能连接特异性指数模型在评估健康老年人认知分数中的应用

与传统量表法和任务态功能磁共振成像(fMRI)相比,静息态功能磁共振(rfMRI)在认知功能检测上有很大优势(特别是针对老年人),但脑老化功能影像学标记尚在探索中。提出功能连接特异性指数模型,试图与健康壮年人对照,分析健康老年人脑功能特异性,寻求区分认知分数的功能影像学指标,探索其分类认知分数优差的可能性,为替代提供研究基础。实验数据来自98名健康老年人和90名健康壮年人,前者来源于葡萄牙健康老年人认知功能的队列研究,在rfMRI扫描前,在认知量表测试分数最优和最差中,分别选出55名和43名作为实验组;后者数据来自哈佛医学院GSP影像组学,年龄在18～35岁之间,在rfMRI扫描前的认知功能评价分数居中,作为对照组。首先,对rfMRI预处理后,计算每人全脑功能连接,构建以脑区为单位的功能连接特异性指数模型,分析老年人脑功能连接与壮年人的偏移程度,统计、对比获得对优、差分数敏感的标志性脑区;然后,以其特异性指数值形成特征向量;最后,应用概率神经网络(PNN)模型对优、差分数组进行分类和N折交叉验证以检验所建指数模型的分类能力。健康老年人脑功能连接特异性指数模型可定位于健康老年人认知分数敏感的标志性脑区,分别处于额叶、颞叶、顶叶中的5个脑区;以这些脑区的指数为特征向量,可有效地区分优、差认知分数,准确度可达81.7%。通过对评价指数的建模并联合机器学习方法,可为rfMRI评估健康老年人认知分数提供有效的评价指标和新方法。     

Depletion of microglia in developing cortical circuits reveals its critical role in glutamatergic synapse development,functional connectivity,and critical period plasticity

Microglia populate the early developing brain and mediate pruning of the central synapses. Yet, little is known on their functional significance in shaping the developing cortical circuits. We hypothesize that the developing cortical circuits require microglia for proper circuit maturation and connectivity, and as such, ablation of microglia during the cortical critical period may result in a long-lasting circuit abnormality. We administered PLX3397, a colony-stimulating factor 1 receptor inhibitor, to mice starting at postnatal day 14 and through P28, which depletes >75% of microglia in the visual cortex (VC). This treatment largely covers the critical period (P19-32) of VC maturation and plasticity. Patch clamp recording in VC layer 2/3 (L2/3) and L5 neurons revealed increased mEPSC frequency and reduced amplitude, and decreased AMPA/NMDA current ratio, indicative of altered synapse maturation. Increased spine density was observed in these neurons, potentially reflecting impaired synapse pruning. In addition, VC intracortical circuit functional connectivity, assessed by laser scanning photostimulation combined with glutamate uncaging, was dramatically altered. Using two photon longitudinal dendritic spine imaging, we confirmed that spine elimination/pruning was diminished during VC critical period when microglia were depleted. Reduced spine pruning thus may account for increased spine density and disrupted connectivity of VC circuits. Lastly, using single-unit recording combined with monocular deprivation, we found that ocular dominance plasticity in the VC was obliterated during the critical period as a result of microglia depletion. These data establish a critical role of microglia in developmental cortical synapse pruning, maturation, functional connectivity, and critical period plasticity.     

Resting-state connectivity and network parameter analysis in alcohol-dependent males. A simultaneous EEG-MEG study

There is supporting evidence of alcohol negative effects on the brain: neuroimaging and psychophysiological studies finding anatomical and functional connectivity (FC) changes associated with the dependence process. Thus, the aim of this work was to evaluate brain FC and network characteristics of alcohol-dependent individuals in resting state. For this study, we included males diagnosed with alcohol dependence (N = 25) and a group of healthy individuals (N = 23). Simultaneous EEG-MEG (electroencephalographic and magnetoencephalographic) activity was recorded in 5 min of eyes-closed resting state. EEG-MEG activity was preprocessed and FC was computed through the leakage-corrected version of phase locking value (ciPLV). Additionally, local (degree, efficiency, clustering) and global (efficiency, characteristic path length) network parameters were computed. Connectivity analysis showed an increase in phase-lagged synchronization, mainly between frontal and frontotemporal regions, in high beta band, and a decrease in interhemispheric gamma, for alcohol-dependent individuals. Network analysis revealed intergroup differences at the local level for high beta, indicating higher degree, clustering, and efficiency, mostly at frontal nodes, together with a decrease in these measures at more posterior sites for patients’ group. The hyper-synchronization in beta, next to the hypo-synchronization in gamma, could indicate an alteration in communication between hemispheres, but also a possible functional compensation mechanism in neural circuits. This could be also supported by network characteristic data, where local alterations in communication are observed.