High expression of GLT-1 in hippocampal CA3 and dentate gyrus subfields contributes to their inherent resistance to ischemia in rats

It is well known that neurons in the CA3 and dentate gyrus (DG) subfields of the hippocampus are resistant to short period of ischemia which is usually lethal to pyramidal neurons in hippocampal CA1 subfield. The present study was undertaken to clarify whether the inherent higher resistance of neurons in CA3 and DG to ischemia is associated with glial glutamate transporter-1 (GLT-1) in rats. Western blot analysis and immunohistochemistry assay showed that the basal expressions of GLT-1 in both CA3 and DG were much higher than that in CA1 subfield. Mild global brain ischemia for 8 min induced delayed death of almost all CA1 pyramidal neurons and marked GLT-1 down-regulation in the CA1 subfield, but it was not lethal to the neurons in either CA3 or DG and induced GLT-1 up-regulation and astrocyte activation showed normal soma and aplenty slender processes in the both areas. When the global brain ischemia was prolonged to 25 min, neuronal death was clearly observed in CA3 and DG accompanied with down-regulation of GLT-1 expression and abnormal astrocytes represented with hypertrophic somas, but shortened processes. After down-regulating of GLT-1 expression and function by its antisense oligodeoxynucleotides or inhibiting GLT-1 function by dihydrokainate, an inhibitor of GLT-1, the mild global brain ischemia for 8 min, which usually was not lethal to CA3 and DG neurons, induced the neuronal death in CA3 and DG subfields. Taken together, the higher expression of GLT-1 in the CA3 and DG contributes to their inherent resistance to ischemia.     

脑电信号的高阶奇异谱分析

奇异谱分析是脑电信号分析的一种新方法,脑电信号的奇异谱可以反映脑电的特征,它有助于研究大脑的动力学行为。奇异谱分析方法是基于二阶统计的方法,反映的是信号时间上和空间上的一种线性相关关系。而脑电信号属于非线性信号,其内在的非线性关系很难通过奇异谱得到真实的反映,从而会丢失某些有用的信息。提出一种新的基于高阶统计的脑电奇异谱分析方法,并将其运用于正常脑电和癫痫患者的脑电分析中。大量的实测信号样本仿真实验结果表明,正常脑电和癫痫脑电的奇异谱有明显的不同。此外,基于高阶统计的奇异谱和基于二阶统计的奇异谱相比更能反映出信号的细节。     

Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.     

多方式认知功能成像研究进展

对大脑结构和功能的深入研究要求认知功能成像技术同时具有高时间分辨率和高空间分辨率.多方式认知功能成像通过不同成像技术fMRI/PET和EEG/MEG的结合,能够同时在空间定位和时间过程上研究大脑认知活动的动态过程.多方式认知功能成像已经被成功地应用于选择性注意、视觉通路、随意运动和语义加工等的研究,并揭示了相关大脑活动的空间和时间特征.今后的研究将进一步提高多方式认知功能成像的时空分辨率和准确性,以更深入地探索认知功能的神经机制.