Visualizing columnar architectures using high-field fMRI

Among the many neuroimaging tools available for studying human brain functions, functional magnetic resonance imaging (fMRI) is the most widely used today. One advantage of fMRI over other imaging techniques is its relatively high spatial resolution. High-resolution fMRI, with its superb signal-to-noise ratio and improved tissue-vessel specificity, has strengthened the capability of fMRI and allowed mapping of fine cortical architectures in the human brain. In this review, I will first explain the factors limiting the spatial specificity of the blood oxygenation level-dependent (BOLD) effect, based on which most of fMRI experiments are conducted, and the measures dealing with these factors, and then briefly introduce several high-resolution (sub-millimeter) studies on the functional organization of human primary visual cortex (V1), including mapping of ocular dominance columns, mapping of temporal frequency dependent domains and direct demonstration of tuning to stimulus orientation.     

Visualizing columnar architectures using high-field fMRI

Among the many neuroimaging tools available for studying human brain functions, functional magnetic resonance imaging (fMRI) is the most widely used today. One advantage of fMRI over other imaging techniques is its relatively high spatial resolution. High-resolution fMRI, with its superb signal-to-noise ratio and improved tissue-vessel specificity, has strengthened the capability of fMRI and allowed mapping of fine cortical architectures in the human brain. In this review, I will first explain the factors limiting the spatial specificity of the blood oxygenation level-dependent (BOLD) effect, based on which most of fMRI experiments are conducted, and the measures dealing with these factors, and then briefly introduce several high-resolution (sub-millimeter) studies on the functional organization of human primary visual cortex (V1), including mapping of ocular dominance columns, mapping of temporal frequency dependent domains and direct demonstration of tuning to stimulus orientation.     

Recent advances in the data analysis method of functional magnetic resonance imaging and its applications in neuroimaging

Functional magnetic resonance imaging (fMRI) has opened a new area to explore the human brain. The fMRI can reveal the deep insights of spatial and temporal changes underlying a broad range of brain function, such as motor, vision, memory and emotion, all of which are helpful in the clinical investigation. In this paper, we introduce some recent-developed algorithms for fMRI signal detection such as model-driven method (general linear model, deconvolution model, non-linear model, etc.) and data-driven method (principle component analysis, independent component analysis, self-organization mapping, clustered constrained non-negative matrix factorization, etc.). We also propose several important applications of neuroimaging and point out their shortcomings and future perspectives.     

利用质疑改进教育信息技术标准化活动：更多关注其范围和原理

标准化对于开发“学习、教育和培训”（LET）中使用的“信息通信技术”（ICT）有重要意义,但ICT的利益相关者（stakeholders）却往往质疑标准化活动.本文提出,利用这种质疑形式来分析和改进当前的ICT标准化活动.讨论了由各方参与产生ICT标准过程的模型框架,其中一系列“为什么”的问题（Why questions）起着重要作用.讨论主要围绕两个方面：一是标准及相关事物在发展过程中的管理与核准;二是如何识别LET中的相关问题与可用来解决这些问题的创新技术.给出了两个事例： 一个是对“内容共享对象参考模型”（Sharable Content Object Reference Model, SCORM）的质疑,这能帮助理解该模型;特别是对其适用范围（scope）的质疑而使该模型更完善.另一个是对制定“新工作条款”（New Work Items）必要性的质疑,使人们认识到澄清标准中有关技术原理（rationale）的重要性.     

基于CCA的fMRI时空模型数据处理的方法

在目前大脑认知功能的研究中,人们常常采用功能性磁共振(fMR I)技术.相关分析是常见的用于检测fMR I数据的方法,而其检测的准确度有一定局限性.在典型相关分析(CCA)基础上将时域相关系数与空域相关系数有机结合,并得到新的相关系数进行阈值分割,进而对fMR I数据进行提取.经过仿真数据与实际fMR I数据的应用分析,证明了本算法的有效性.     

Resting state brain activity and functional brain mapping

Functional brain imaging studies commonly use either resting or passive task states as their control conditions, and typically identify the activation brain region associated with a specific task by subtracting the resting from the active task conditions. Numerous studies now suggest, however, that the resting state may not reflect true mental “rest” conditions. The mental activity that occurs during “rest” might therefore greatly influence the functional neuroimaging observations that are collected through the usual subtracting analysis strategies. Exploring the ongoing mental processes that occur during resting conditions is thus of particular importance for deciphering functional brain mapping results and obtaining a more comprehensive understanding of human brain functions. In this review article, we will mainly focus on the discussion of the current research background of functional brain mapping at resting state and the physiological significance of the available neuroimaging data.     

Resting state brain activity and functional brain mapping

Functional brain imaging studies commonly use either resting or passive task states as their control conditions, and typically identify the activation brain region associated with a specific task by subtracting the resting from the active task conditions. Numerous studies now suggest, however, that the resting state may not reflect true mental "rest" conditions. The mental activity that occurs during "rest" might therefore greatly influence the functional neuroimaging observations that are collected through the usual subtracting analysis strategies. Exploring the ongoing mental processes that occur during resting conditions is thus of particular importance for deciphering functional brain mapping results and obtaining a more comprehensive understanding of human brain functions. In this review article, we will mainly focus on the discussion of the current research background of functional brain mapping at resting state and the physiological significance of the available neuroimaging data.     

一种改进的ICA算法及其在fMRI信号上的应用

摘要:给出了独立成分分析(ICA)的一个优化模型,在此基础上,提出了一种牛顿型迭代算法,为加快算法的收敛速度,对牛顿迭代进行了进一步修正,使该算法收敛速度达到三阶.本文从理论上阐明了新方法的合理性和优越性,同时将其应用于实际fMRI数据,经与其他两个ICA算法(Fast ICA算法、infomax算法)比较,该算法能够很好地分离出任务成分,同时大大减少了运算量,提高了运算速度,对处理大数据量的fMRI信号有明显的优势.     

Watching cartoons activates the medial prefrontal cortex in children

The medial prefrontal cortex (MPFC) of human adults is involved in attributing mental states to real human agents but not to virtual artificial characters. This study examined whether such differential MPFC activity can be observed in children who are more fascinated by cartoons than adults. We measured brain activity using functional magnetic resonance imaging (fMRI) while 10-year-old children watched movie and cartoon clips, simulating real and virtual visual worlds, respectively. We showed neuroimaging evidence that, in contrast to adults, the MPFC of children was activated when perceiving both human agents and artificial characters in coherent visual events. Our findings suggest that, around the age of 10 years, the MPFC activity in children is different from that in adults in that it can be spontaneously activated by non-human agents in a virtual visual world.     

Neuroimaging studies of self-reflection

This paper reviews some basic findings and methodological issues in neuroimaging studies of self-referential processing.As a general rule,making judgments about one's self,inclusive of personality trait adjectives or current mental states(person's prefer ences,norms,aesthetic values and feeling)uniformly generates medial prefrontal activations,regardless of stimulus materials(words or pictures)and modality(visual or auditory).Cingulate activations are also observed in association with most self-referential processing.Methodological issues include treating self-referential processing as either representing one's own personality traits or representing one's own current mental states.Finally,self-referential processing could Be considered as implement of "I think therefore I am" approach to neuroimaging the self.     

深反射地震数据采集处理和解释技术现状与展望

深反射地震是了解地球深部结构的关键技术之一,在深部探测领域得到了广泛应用,但由于深反射地震剖面长、穿越构造单元复杂等原因,资料品质较油气地震要低,为更准确的探测地下,需要针对深反射地震数据特点,改进去噪、叠加等处理技术以及解释等方法,以得到地壳精细结构。本文系统总结了当前深反射地震数据采集、处理以及解释的方法,结合实例对这些方法的优缺点进行了对比分析,认为将来深反射地震需要在观测系统的优化改进,人工智能在数据处理、解释等方面开展研究,提高深反射地震剖面的成像质量。     

联合独立成分分析和典型相关分析盲分析fMRI数据

为了自动识别功能信号成分,通过对灰质数据和脑脊液数据独立成分的空间相关性进行典型相关分析,有效地解决了独立成分的排序问题.提出的方法不需要任何先验信息,能够稳健地识别与实验设计相关的功能信号成分,实现了对fMRI数据的盲分析.通过对临床真实fMRI数据的分析,阐明了提出方法的有效性及可靠性.     

fMRI time series analysis based on stationary wavelet and spectrum analysis

The low signal to noise ratio (SNR) of functional MRI (fMRI) prefers more sensitive data analysis methods. Based on stationary wavelet transform and spectrum analysis, a new method with high detective sensitivity was developed for analyzing fMRI time series, which does not require any prior assumption of the characteristics of noises. In the proposed method, every component of fMRI time series in the different time-frequency scales of stationary wavelet transform was discerned by the spectrum analysis, then the components from noises were removed using the stationary wavelet transform, finally the components of real brain activation were detected by cross-correlation analysis. The results obtained from both simulated and in vivo visual experiments illustrated that the proposed method has much higher sensitivity than the traditional cross-correlation method.     

New advances in the neural correlates of insight: A decade in review of the insightful brain

The first neuroimaging study of real-time brain activity during insight problem solving was conducted almost ten years ago. Many subsequent studies have used high-resolution event-related potentials (ERPs) and event-related functional magnetic resonance imaging (fMRI) to investigate the temporal dynamics and neural correlates of insight. Recent results on the neural underpinnings of insight have led researchers to propose a neural framework referred to as the "insightful brain". This putative framework represents the neural basis of the cognitive and affective processes that are involved in insight. The insightful brain may involve numerous brain regions, including the lateral prefrontal cortex, cingulate cortex, hippocampus, superior temporal gyrus, fusiform gyrus, precuneus, cuneus, insula and cerebellum. Functional studies have demonstrated that the lateral prefrontal cortex is responsible for mental set shifting and breaking during insight problem solving. The cingulate cortex is involved in the cognitive conflict between new and old ideas and progress monitoring. The hippocampus, superior temporal gyrus and fusiform gyrus form an integrated functional network that specializes in the formation of novel and effective associations. The effective transformation of problem representations depends on a non-verbal visuospatial information-processing network that comprises the precuneus and cuneus. The insula reflects cognitive flexibility and the emotional experience that is associated with insight. The cortical control of finger movements relies on the cerebellum.     

广西横县土地利用现状遥感调查

在1990年土地详查基础上，以1：5万TM影像为研究的基本信息源，应用遥感解译原理与方法，通过确定上地利用现状分类系统、建立解译标志、进行编图和面积量算及结果分析等工作，对横县上地资源利用现状进行了调查与调整；并就上地利用中存在的问题提出了应采取的对策。     

试论口译教学中合作学习的策略

口译作为国际交流与合作的重要途径。在当今世界起着越来越重要的作用。然而由于教学条件所限，长期以来英语教师都无法通过口译课堂给学生提供更多的语言实践机会。在这种情况下，口译课作为一门语言技能与专业知识相结合的课程，在教学中开展合作学习就显得尤为重要。本文通过对我国口译教学现状的分析，结合口译教学的技巧和训练，提出了如何运用合作学习提高口译教学的策略。     

基于粒子群-支持向量机的时间序列分类诊断模型

构建一种基于粒子群算法-支持向量机(PSO-SVM)的磁共振功能成像(fMRI)时间序列分类诊断模型,通过针对脑区多维时间序列数据的深层次分析实现病症患者和健康者的准确判断与区分,为面向fMRI时间序列数据的病症诊断和预测提供有效科学依据.该方法在以下4个方面不同于其他已有相关研究工作:(1)构建基于自回归模型的脑区多维时间序列数据特征表示;(2)构建基于支持向量机模型的脑区多维时间序列数据分类机制;(3)构建基于粒子群算法的分类学习参数寻优策略;(4)建立融合上述特征表示、优化分类与参数优选模式的fMRI时间序列数据分类诊断模型.通过以精神抑郁症作为实证分析的具体案例,所提出分类诊断模型已取得良好实验效果,展示出其有效性与合理性.     

自传体记忆研究的若干新进展

总结了自传体记忆研究中新近出现的功能研究取向以及自传体记忆脑机制的神经心理学研究和脑成像研究结果。功能取向的研究表明,自传体记忆具有自我、社会和指导这3类主要功能。神经心理学和脑成像研究发现自传体记忆主要定位于颞叶与海马,但这2方面研究的结果之间却存在着很大的不一致：以脑损伤病人进行的神经心理学研究发现自传体记忆主要表现为右侧颞叶与海马的功能,而对正常人的脑成像研究却表明提取自传体记忆事件时主要的激活部位是左侧颞叶与海马。目前尚无关于这种不一致现象的评论与解释,由于自传体记忆的脑成像研究数量较少且结论并不一致,在进行更多的脑成像研究之后再来比较神经心理学与脑成像的研究结果可能更为合适。     

手针和电针足三里穴持续性效应的功能磁共振成像研究

通过采集的静息态脑功能磁共振成像数据和并对其进行分析,分别探索传统手针和电针足三里穴的人脑持续性效应的中枢神经系统活动.选择12例(6男,6女,23～27岁)无针刺经历的、右利手健康成年志愿者,分成手针组(12例)和电针组(12例).手针刺激(2 Hz)和电针刺激(2 Hz,连续方波,电流强度0.5～1.4 mA)实验中,针刺刺激分别以2 Hz的频率对足三里进行2 min的双向捻转,采集针刺刺激前后静息态的数据进行预处理并对其进行统计分析.统计结果显示手针和电针针刺足三里后引起了不同的持续性效应,包括中脑和基底神经节在内的参与与镇痛有关的神经递质释放的脑区结构,在针刺刺激后阶段呈现出了持续性的活动.两种针刺模态下不同的脑区响应模式表明两者可能在经络传输通道和神经递质系统的活动存在差异.     

陇东油田V区Y9储层参数解释模型的建立及应用

在大量文献调研基础上,基于收集到的岩心资料、地质资料、测井资料和生产动态资料等,遵循地质约束测井、岩心刻度测井的建模原则,开展了陇东油田V区Y9储层四性关系研究,建立了储层参数测井解释模型,并将建立的泥质含量、孔隙度、渗透率和含油饱和度测井解释模型加载到专门的测井解释平台上,开展了研究区的测井资料二次解释.研究表明,经过岩心深度归位后的岩心资料和标准化后的测井资料相关性分析可靠,本研究建立的储层参数解释模型实际应用取得了良好的效果.