人类脑计划与神经信息学

了解脑及其功能是21世纪科学的重大挑战之一。神经信息学是神经科学与信息科学相结合的交叉学科。目前的“人类脑计划”旨在加强脑功能的基础研究,并开发用于分析、整合、合成、建模、模拟与提供各种数据的工具。中国应参与人类脑计划,为发展神经信息学作出贡献。     

日韩两国神经信息学的研究

第八届国际神经信息加工大会 (ＩＣＯＮＩＰ２００１)于２００１年１１月１４日 -１８日在上海举行［１］,这次会议由复旦大学主办 ,会议收到三百余篇论文 ,选出２９５篇作为会议发言和大字报展出 ,来自３１个国家和地区的代表出席会议 ,其中日本代表９５名。Ｉ ＣＯＮＩＰ２００１会后 ,在杭州召开中、日、韩三国神经生物学和神经信息学卫星会［２］ ,中日韩各有１０位代表(５位来自神经生物学 ,５位来自神经信息学 )在会上发言。作者有幸出席这二次会议 ,并代表中方就神经信息学的一个方面作发言。作者在会上遇到不少日韩两国的老朋友 ,据…     

神经丝的结构与功能

神经丝是神经细胞的中间丝,由L、M和H三种蛋白组成,三种蛋白由三个基因编码。神经丝蛋白在神经元胞体合成后,运输到神经突起中,与微丝和微管共同组成神经细胞的骨架网络。磷酸化对神经丝的性质有重要影响。神经丝蛋白在体内能与内源性中间丝共组装,在体外,只有L能自组装成10nm的纤维,M和H可与L共同组装成纤维。在发育过程中,L和M在动物出生前数天开始表达,H则是在出生后才出现。神经丝的数量决定轴突直径,而其过量表达会导致疾病。     

基因编码神经调质荧光探针的研究进展与展望

随着神经科学研究的深入,基因编码神经调质荧光探针因其高灵敏度和选择性、高时空分辨率、高细胞特异性及低侵入性,成为实时监测神经调质动态变化的重要工具.本文总结了近年来基因编码神经调质荧光探针的设计原理、优化策略及取得的显著进展,并展望了未来探针的发展方向,为神经调质荧光探针技术的发展提供新的思路.     

串联质谱数据从头解析与蛋白质的数据库搜索鉴定

蛋白质的鉴定是蛋白质组学研究中必不可少的一步。用串联质谱（ｔａｎｄｅｍ ｍａｓｓ ｓｐｅｃｔｒｏｍｅｔｒｙ,ＭＳ／ＭＳ）可以进行多肽的从头测序（ｄｅ ｎｏｖｏ ｓｅｑｕｅｎｃｉｎｇ）,并搜索数据库以鉴定蛋白质。用图论以及真实谱－理论谱联配（ａｌｉｎｇｍｅｎｔ）的方法对串联质谱得到的多肽图谱进行从头解析,得到了可靠的多肽序列,并应用到数据库搜索中鉴定了相应的蛋白质。同时,还用统计的方法对ＳｗｉｓｓＰ     

人类神经Tau蛋白结构与功能研究进展

Ｔａｕ属微管结合蛋白,对神经细胞的生长发育,物质运输及信息传导起着重要作用。该分子不具有明显的二级结构,其生物学功能的调节功能主要是通过磷酸化和去磷酸化来实现。目前的研究表明,早老性痴呆等疾病与Ｔａｕ分子高级结构的异常改变和功能丧失有关。     

使用非侵入的神经影像方法解码人类思维

随着神经影像技术的发展,“读脑机器”在不久的将来可能会变成现实。在众多实现“读脑机器”的技术中,使用基于血氧水平依赖的脑功能磁共振技术的神经解码方法则是非常有希望的一种技术。在本报告中,我们结合我们实验室最近开展的两个研究工作,说明了使用功能磁共振技术进行神经解码的一般方法及其应用。本领域的发展很快,所有的这些工作让我们对发明“读脑机器”充满了期待。但是,与此同时,我们也应该看到目前还存在着很多技术的局限和挑战。本报告的最后,我们也对这些局限和挑战进行了一些讨论。     

串联质谱数据的从头解析与蛋白质的数据库搜索鉴定

蛋白质的鉴定是蛋白质组学研究中必不可少的一步。用串联质谱 (tandemmassspectrometry ,MS/MS)可以进行多肽的从头测序 (denovosequencing) ,并搜索数据库以鉴定蛋白质。用图论以及真实谱 理论谱联配 (alignment)的方法对串联质谱得到的多肽图谱进行从头解析 ,得到了可靠的多肽序列 ,并应用到数据库搜索中鉴定了相应的蛋白质。同时 ,还用统计的方法对SwissProt以及TrEMBL蛋白质数据库进行了详细的分析。结果表明 ,3个四肽或者 2个五肽或者 1个八肽一般可以唯一地确定一个蛋白质     

从基因组学到功能蛋白质组学的研究

人类基因组草图绘制的完成,标志着生命科学已实质性地跨入了后基因组时代,研究重心已从揭示生命的所有遗传信息转移到在分子整体水平对功能的研究[1]。这种转向表明目前已进入功能基因组学(functional genom ics)以及随之产生的功能蛋白质组学(functional proteomics)等新学科领域的研究。     

内源性神经干细胞与脑老化的治疗

近十几年研究发现成年人脑神经元可以再生,使人们重新认识老年脑神经细胞的可塑性,它为脑损伤的修复带来新的希望。最新研究表明,神经再生可被调控,是一种新的修复机制。这使得利用内源性神经干细胞治疗老龄相关的神经退行性疾病成为可能。     

A link between neuroscience and informatics: large-scale modeling of memory processes

Utilizing advances in functional neuroimaging and computational neural modeling, neuroscientists have increasingly sought to investigate how distributed networks, composed of functionally defined subregions, combine to produce cognition. Large-scale, biologically realistic neural models, which integrate data from cellular, regional, whole brain, and behavioral sources, delineate specific hypotheses about how these interacting neural populations might carry out high-level cognitive tasks. In this review, we discuss neuroimaging, neural modeling, and the utility of large-scale biologically realistic models using modeling of short-term memory as an example. We present a sketch of the data regarding the neural basis of short-term memory from non-human electrophysiological, computational and neuroimaging perspectives, highlighting the multiple interacting brain regions believed to be involved. Through a review of several efforts, including our own, to combine neural modeling and neuroimaging data, we argue that large scale neural models provide specific advantages in understanding the distributed networks underlying cognition and behavior.     

The functional anatomy of cerebral reorganisation after focal brain injury

Stroke is a major cause of disability in all age groups. Although the value of specific rehabilitative therapies is now acknowledged, the mechanisms of impairment and recovery are not well understood. There is growing interest in the role that central nervous system reorganisation might play in the recovery process, and in particular whether this reorganisation can be manipulated to provide clinical benefits for patients. The careful use of non-invasive techniques such as functional magnetic resonance imaging and transcranial magnetic stimulation allows the study of the working human brain, and studies in humans suggest that functionally relevant adaptive changes occur in cerebral networks following stroke. An understanding of how these changes influence the recovery process will facilitate the development of novel therapeutic techniques that are based on neurobiological principles and will allow the delivery of specific therapies to appropriately targeted patients suffering from stroke.     

Great mood in proteomics: Beijing and the HUPO Human Brain Proteome Project

More than 1200 attendees came together at the 3(rd) HUPO World Congess in Beijing, October 25-27, 2004. In numerous different sessions the wide range of proteomic areas became visible. The HUPO Brain Proteome Project (HUPO BPP) organized an evening session on October 23, presenting the first results of two pilot studies as well as the newest, very positive international development in this field. The rising importance became even more apparent in the plenary presentation of all HUPO initiatives and the following congress activities.     

人巨细胞病毒感染新生乳鼠原代培养脑神经细胞研究

为了研究确定人巨细胞病毒（ＨＣＭＶ）体外感染Ｂａｌｂ／ｃ新生乳鼠原代培养脑神经细胞及其感染特征,制备了培养了新生乳鼠脑神经细胞并进行病毒感染。感染后每隔２￣３天在倒置显微镜下观察活细胞培养物并摄影记录。在感染后第１￣４周,取样进行苏木素－伊红（ＨＥ）染色及尼氏（Ｎｉｓｓｌ）染色。同时,用已知抗ＨＣＭＶ外膜蛋白的单克隆抗体进行免疫细胞化学染色,和地高辛标记的ＨＣＭＶ寡核苷酸特异性探针进行原位杂交,检     

神经元簇的层次性联合编码假设

提出一个新的神经信息编码假设,称为神经元簇的层次性联合编码假设。它不同于祖母细胞假设和Hebb经典细胞群编码模型,但融合了它们的优点,因而可以解释更多的神经生物学实验。     

SenseLab: new developments in disseminating neuroscience information

This article presents the latest developments in neuroscience information dissemination through the SenseLab suite of databases: NeuronDB, CellPropDB, ORDB, OdorDB, OdorMapDB, ModelDB and BrainPharm. These databases include information related to: (i) neuronal membrane properties and neuronal models, and (ii) genetics, genomics, proteomics and imaging studies of the olfactory system. We describe here: the new features for each database, the evolution of SenseLab's unifying database architecture and instances of SenseLab database interoperation with other neuroscience online resources.     

HUPO Brain Proteome Project Pilot Studies: bioinformatics at work

The data acquisition phase of initial pilot studies (human and mouse brain samples) of the Human Proteome Organisation (HUPO) Brain Proteome Project (BPP) is now complete and the data generated by the participating laboratories has been submitted to the central Data Collection Center. The BPP Bioinformatics Group met on 8th April 2005 at the European Bioinformatics Institute (Hinxton, UK) to discuss strategies for the reanalysis of the pooled data from all the participating laboratories. A summary of the results of the data reprocessing will be presented at the 4th HUPO World Congress that will be held in August/September 2005.     

A high-yield route to synthesize the P-glycoprotein radioligand [11C]N-desmethyl-loperamide and its parent radioligand [11C]loperamide

N-Desmethyl-loperamide and loperamide were synthesized from α,α-diphenyl-γ-butyrolactone and 4-(4-chlorophenyl)-4-hydroxypiperidine in five and four steps with 8% and 16% overall yield, respectively. The amide precursor was synthesized from 4-bromo-2,2-diphenylbutyronitrile and 4-(4-chlorophenyl)-4-hydroxypiperidine in 2 steps with 21–57% overall yield. [¹¹C]N-Desmethyl-loperamide and [¹¹C]loperamide were prepared from their corresponding amide precursor and N-desmethyl-loperamide with [¹¹C]CH₃OTf through N-[¹¹C]methylation and isolated by HPLC combined with solid-phase extraction (SPE) in 20–30% and 10–15% radiochemical yields, respectively, based on [¹¹C]CO₂ and decay corrected to end of bombardment (EOB), with 370–740 GBq/μmol specific activity at EOB.     

Dynamical correlation patterns and corresponding community structure in neural spontaneous activity at criticality

It has been considered that the state in the vicinity of a critical point, which is the point between ordered and disordered states, can underlie and facilitate information processing of the brain in various aspects. In this research, we numerically study the influence of criticality on one aspect of brain information processing, i.e., the community structure, which is an important characteristic of complex networks. We examine community structure of the functional connectivity in simulated brain spontaneous activity, which is based on dynamical correlations between neural activity patterns at different positions. The brain spontaneous activity is simulated by a neural field model whose parameter covers subcritical, critical, and supercritical regions. Then, the corresponding dynamical correlation patterns and community structure are compared. In the critical region, we found some distinctive properties, namely high correlation and correlation switching, high modularity and a low number of modules, high stability of the dynamical functional connectivity, and moderate flexibility of the community structure across temporal scales. We also discuss how these characteristics might improve information processing of the brain.