Diverse synchrony of firing reflects diverse cell-assembly coding in the prefrontal cortex

In the present paper, we focus on the coding by cell assemblies in the prefrontal cortex (PFC) and discuss the diversity of the coding, which results in stable and dynamic representations and the processing of various information in that higher brain region. The key activity that reflects cell-assembly coding is the synchrony of the firing of multiple neurons when animals are performing cognitive and memory tasks. First, we introduce some studies that have shown task-related synchrony of neuronal firing in the monkey PFC. These studies have reported fixed and several types of dynamic synchronous firing during working memory, long-term visual memory, and goal selection. The results of these studies have indicated that cell assemblies in the PFC can contribute to both the stability and the dynamics of various types of information. Second, we refer to rat studies and introduce the findings of cellular interactions that contribute to synchrony in working memory, learning-induced changes in synchrony in spatial tasks, and interactions of the PFC and hippocampus in dynamic synchrony. These studies have proposed neuronal mechanisms of cell-assembly coding in the PFC and its critical role in the learning of task demands in problematic situations. Based on the monkey and rat studies, we conclude that cell-assembly coding in the PFC is diverse and has various facets, which allow multipotentiality in the higher brain region. Finally, we discuss the problem of the sizes of cell assembly, how diverse the sizes are in the PFC, and the technical problems in their investigation. We introduce a unique spike-sorting method that can detect small and local cell assemblies that consist of closely neighboring neurons. Then, we describe the findings of our study that showed that the monkey PFC has both small and large cell assemblies, which have different roles in information coding in the working brain.     

一种新的视觉皮层简单细胞工作机制的模型

提出了一种基于独立元分析（ICA）的视觉皮层简单细胞工作机制的模型。用Gabor函数逼近对自然图像进行ICA而获得的基函数,揭示了ICA基函数与视觉皮层简单细胞感受野反应间存在内在的关系。并对水平条纹的图像进行ICA,模拟在特殊视觉环境下生长的幼年动物的视觉皮层发育过程,证实了1970年Blakemore和Cooper在幼猫上的实验结果。从而说明ICA可以模拟动物的视觉皮层简单细胞工作过程。     

Inhibition of Rho kinase by hydroxyfasudil attenuates brain edema after subarachnoid hemorrhage in rats

The blood-brain barrier (BBB) disruption and brain edema are important pathophysiologies of early brain injury after subarachnoid hemorrhage (SAH). This study is to evaluate whether Rho kinase (Rock) enhances BBB permeability via disruption of tight junction proteins during early brain injury. Adult male rats were assigned to five groups; Sham-operated, SAH treated with saline, a Rock inhibitor hydroxyfasudil (HF) (10 mg/kg) treatment at 0.5 h after SAH, HF treatment at 0.5 and 6 h (10 mg/kg, each) after SAH, and another Rock inhibitor Y27632 (10 mg/kg) treatment at 0.5 h after SAH. The perforation model of SAH was performed and neurological score and brain water content were evaluated 24 and 72 h after surgery. Evans blue extravasation, Rock activity assay, and western blotting analyses were evaluated 24 h after surgery. Treatment of HF significantly improved neurological scores 24 h after SAH. Single treatment with HF and Y27632, and two treatments with HF reduced brain water content in the ipsilateral hemisphere. HF reduced Evans blue extravasation in the ipsilateral hemisphere after SAH. Rock activity increased 24 h after SAH, and HF reversed the activity. SAH significantly decreased the levels of tight junction proteins, occludin and zonula occludens-1 (ZO-1), and HF preserved the levels of occluding and ZO-1 in ipsilateral hemisphere. In conclusion, HF attenuated BBB permeability after SAH, possibly by protection of tight junction proteins.     

基于Flexible ICA的睡眠EEG及EOG中心电伪差的消除

提出了一种采用自适应非线性函数的ICA学习算法,Flexible ICA算法,并将其应用于睡眠EEG自动分期的前期预处理中,用于消除采集到的各通道信号中的心电伪差.实验结果证明,Flexible ICA算法能够快速有效的消除各通道的心电伪差,为后期的睡眠EEG自动分期打下了良好的基础.     

Simultaneous production of citric acid and invertase by Yarrowia lipolytica SUC+ transformants

Simultaneous production of citric acid (CA) and invertase by Yarrowia lipolytica A-101-B56-5 (SUC⁺ clone) growing from sucrose, mixture of glucose and fructose, glucose or glycerol was investigated. Among the tested substrates the highest concentration of CA was reached from glycerol (57.15 g/L) with high yield (Y_CA/S = 0.6 g/g). When sucrose was used, comparable amount of CA was secreted (45 g/L) with slightly higher yield (Y_CA/S = 0.643 g/g). In all cultures amount of isocitrate (ICA) was below 2% of total citrates. Considering invertase production, the best carbon source appeared to be sucrose (72 380 U/L). The highest yield of CA and invertase biosynthesis calculated for 1 g of biomass was obtained for cells growing from glycerol (9.9 g/g and 4325 U/g, respectively). Concentrates of extra- and intracellular invertase of the highest activity were obtained from sucrose as substrate (0.5 and 1.8 × 10⁶ U/L, respectively).     

基于空间ICA和时间相关方法的人脑视觉皮层V5区的功能连通性研究

利用功能磁共振成像技术,将空间ICA和时间相关方法相结合来研究不同活动状态下人脑视觉皮层V5区的功能连通性。首先利用空间ICA处理组块视觉运动刺激的数据,定位V5区;然后分别计算静息和连续视觉运动刺激两种稳态下V5区与其它脑区低频振荡的时间相关,检测出该区的功能连通网络。实验结果表明,静息时V5区的功能连通网络更广泛,且与已知的解剖连通一致;当被试接受连续视觉运动刺激时,与V5区连通的脑区网络局限在视觉皮层,此时的网络特定于处理视觉运动这一任务。     

影像诊断在颅内动脉瘤中的研究进展

颅内动脉瘤(intracranial aneurysms,ICA)是由于脑血管局部异常改变而产生的血管瘤样突起,世界2%的人口患有颅内动脉瘤。颅内动脉瘤是引起脑卒中的第三大病因,仅次于脑血栓形成和高血压脑出血,脑卒中病死率、致残率极高,总病死率约为40~50%,早期诊断ICA对预防脑卒中意义重大。颅内动脉瘤的早期诊断主要依赖于影像学检查,近年多层螺旋CT、MRI及DSA技术的迅猛发展对颅内动脉瘤的早期诊断有很大帮助,本文就CT以及MRI功能成像在颅内动脉瘤的应用研究进展进行综述。     

IAA、ICA及GADA联合检测对糖尿病分型的诊断价值

目的:探讨胰岛素自身抗体(IAA)、胰岛细胞抗体(ICA)及谷氨酸脱羧酶抗体(GADA)联合检测对糖尿病分型的诊断价值。方法:选择2015年6月~2016年6月在我院进行诊治的1型糖尿病患者30例为A组,2型糖尿病患者60例为B组,同期在我院进行体检健康者50例为C组,采用酶联免疫吸附法(ELISA)检测三组的IAA、ICA及GADA,比较三组的阳性检出率。结果:A组空腹血糖为(10.12±3.68)mmol/L,B组空腹血糖为(11.23±3.26)mmol/L,A组和B组的空腹血糖均明显高于C组(4.35±1.42mmol/L)(P0.05),但A组和B组的空腹血糖相比无明显差异(P0.05);A组和B组的IAA、ICA及GADA单独和联合检测的阳性率均明显高于C组(P0.05),且A组的IAA、ICA及GADA单独和联合检测的阳性率明显高于B组(P0.05);IAA、ICA及GADA联合检测对1型和2型糖尿病的敏感性和特异性均明显高于单独检测(P0.05)。结论:IAA、ICA及GADA联合检测对糖尿病分型具有较高的临床诊断价值。     

多通道脑电信号的盲分离

提出一种新的多通道脑电信号盲分离的方法,将小波变换和独立分量分析(independent component analysis,ICA)相结合,利用小波变换的滤噪作用,将混合在原始脑电的部分高频噪声滤除后,再重构原始脑电作为ICA的输入信号,有效地克服了现有ICA算法不能区分噪声的缺陷。实验结果表明,该方法对多通道脑电的盲分离是很有效的。