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.     

脑疲劳状态下脑功能网络研究与分析

旨在研究连续长时间脑力活动引发的脑疲劳对大脑连接性的影响,探索大脑疲劳评价的客观指标.通过持续认知任务实验诱发脑疲劳,选用互相关方法对采集到的脑电信号进行了不同导联间时域关联特性分析,构建并比较分析了正常态和脑疲劳态的脑功能网络.最后基于复杂网络理论对脑功能网络的特征参数进行了统计分析.结果表明,持续认知任务后,主观感觉疲劳程度显著增加,脑功能网络的平均度、平均聚类系数和网络密度与正常态相比均显著降低,而平均路径长度显著增大.脑功能网络参数可以很好地反映脑疲劳后大脑的连接性变化情况.     

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.     

任务背景下腹侧注意功能网络的fMRI研究

基于静息状态的功能磁共振成像(functional MRI,fMRI)已经成为当前人脑功能研究的重要手段之一,本研究采用任务背景来获取一种更为"纯净"的静息状态,其中脑区的"任务背景"被定义为那些不会激活感兴趣脑区的任务.由于到目前为止还不清楚在"任务背景"下人脑除默认网络外的其他"高级"功能网络内部是否被中断,本文研究了人脑听觉背景下腹侧注意网络内部的功能连接.结果表明在听觉背景下该网络内部存在显著的功能连接,这一结果说明简单的感觉任务不会中断人脑的腹侧注意网络.本研究首次证明在任务背景下,除默认网络之外,人脑还有一些高级功能网络内部存在显著功能连接.     

Mapping human visual cortex with positron emission tomography

Positron-emission tomography (PET) can localize functions of the human brain by imaging regional cerebral blood flow (CBF) during voluntary behaviour. Functional brain mapping with PET, however, has been hindered by PET's poor spatial resolution (typically greater than 1 cm). We have developed an image-analysis strategy that can map functional zones not resolved by conventional PET images. Brain areas selectively activated by a behavioural task can be isolated by subtracting a paired control-state image from the task-state image, thereby removing areas not recruited by the task. When imaged in isolation the centre of an activated area can be located very precisely. This allows subtle shifts in response locale due to changes in task to be detected readily despite poor spatial resolution. As an initial application of this strategy we mapped the retinal projection topography of human primary visual cortex. Functional zones separated by less than 3 mm (centre-to-centre) were differentiated using PET CBF images with a spatial resolution of 18 mm. This technique is not limited to a particular brain area or type of behaviour but does require that the increase in CBF produced by the task be both intense and focal.     

Detection of dynamic brain networks modulated by acupuncture using a graph theory model

Neuroimaging studies involving acute acupuncture manipulation have already demonstrated significant modulatory effects on wide limbic/paralimbic nuclei, subcortical gray structures and the neocortical system of the brain. Due to the sustained effect of acupuncture, however, knowledge on the organization of such large-scale cortical networks behind the active needle stimulation phase is lacking. In this study, we originally adopted a network model analysis from graph theory to evaluate the functional connectivity among multiple brain regions during the post-stimulus phase. Evidence from our findings clearly supported the existence of a large organized functional connectivity network related to acupuncture function in the resting brain. More importantly, acupuncture can change such a network into a functional state underlying both pain perception and modulation, which is exhibited by significant changes in the functional connectivity of some brain regions. This analysis may help us to better understand the long-lasting effects of acupuncture on brain function, as well as the potential benefits of clinical treatments.     

静息态人脑功能网络的小世界特性

研究了静息态下健康人脑的功能连接模式有助于理解人脑在正常或疾病状态下的功能活动规律.利用小波变换从健康志愿者静息态的功能磁共振成像中提取时间序列,计算90个脑区的相关性,设定阈值建立脑功能网络的无向简单图,然后计算特征路径长度和聚类系数,并对度分布进行拟合.结果显示:脑功能网络具有规则网络的大聚集系数又具有随机网络的小特征路径长度,度的拟合显示具有指数截断幂律分布,即脑功能网络具有小世界特性.     

Interactive memory systems in the human brain.

Learning and memory in humans rely upon several memory systems, which appear to have dissociable brain substrates. A fundamental question concerns whether, and how, these memory systems interact. Here we show using functional magnetic resonance imaging (FMRI) that these memory systems may compete with each other during classification learning in humans. The medial temporal lobe and basal ganglia were differently engaged across subjects during classification learning depending upon whether the task emphasized declarative or nondeclarative memory, even when the to-be-learned material and the level of performance did not differ. Consistent with competition between memory systems suggested by animal studies and neuroimaging, activity in these regions was negatively correlated across individuals. Further examination of classification learning using event-related FMRI showed rapid modulation of activity in these regions at the beginning of learning, suggesting that subjects relied upon the medial temporal lobe early in learning. However, this dependence rapidly declined with training, as predicted by previous computational models of associative learning.     

心算任务下脑电信息传输

通过计算多导脑电的互信息传输时间序列的复杂度,研究了心算任务和安静状态下不同认知水平的对象脑电特异表现.结果表明,不同的实验状态、不同认知能力的被试者以及大脑的不同部位均可对互信息复杂度产生显著影响.抑郁症在心算任务下的互信息传输复杂度显著低于（P<0.001）安静闭目状态下的复杂度,而正常对照组虽然在心算任务下的脑电互信息传输复杂度也较安静闭目状态时有所下降,但不具有统计意义.据此推测,完成认知作业时的脑电互信息复杂度在一定程度上反映了认知水平的不同.     

Deactivations during the numerical processing

Deactivation has been encountered frequently in functional brain imaging researches. However, the deactivations during the numerical processing have not been reported yet. In this study, the functional magnetic resonance imaging (fMRI) was employed to investigate the pattern of the deactivation in the brain of 15 healthy subjects during the numerical addition task. Analyses revealed significant deactivations in several brain regions, including the posterior cingulate, precuneus, anterior cingulate and prefrontal cortex. Especially, we found notable deactivation in bilateral insula. Accounting for the cognitive functions of these regions participating in a combinated way, we discuss their contributions in sustaining the brain activity during conscious resting state, and indicate that the insula is an important area of gathering auditory information from the external world.     

Functional brain laterality for sequential movements： Impact of transient practice

The impact of learning on brain functional laterality has not been systematically investigated. We employed an event-related functional magnetic resonance imaging combined with a delayed sequential movement task to investigate brain activation pattern and laterality during a transient practice in 12 subjects. Both hemispheres, involving motor areas and posterior parietal cortex, were engaged during motor preparation and execution, with larger activation volume in the left hemisphere than in the right. Activation volume in these regions significantly decreased after a transient practice, with more reduction in the right hemisphere resulting increase in left lateralization. The theoretical implications of these findings are discussed in relation to the physiological significance of brain functional laterality.     

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.     

Finer discrimination of brain activation with local multivariate distance

The organization of human brain function is diverse on different spatial scales. Various cognitive states are always represented as distinct activity patterns across the specific brain region on fine scales. Conventional univariate analysis of functional MRI data seeks to determine how a particular cognitive state is encoded in brain activity by analyzing each voxel separately without considering the fine-scale patterns information contained in the local brain regions. In this paper, a local multivariate distance mapping (LMDM) technique is proposed to detect the brain activation and to map the fine-scale brain activity patterns. LMDM directly represents the local brain activity with the patterns across multiple voxels rather than individual voxels, and it employs the multivariate distance between different patterns to discriminate the brain state on fine scales. Experiments with simulated and real fMRI data demonstrate that LMDM technique can dramatically increase the sensitivity of the detection for the fine-scale brain activity patterns which contain the subtle information of the experimental conditions.     

基于脑电的磁刺激神门穴脑功能网络研究

研究磁刺激神门穴状态下与静息状态下9名健康被试的脑电信号样本,分别构建两种状态下的脑功能网络,并对不同的网络测度进行分析.首次从复杂网络角度探索神门穴的治病机理,期望为穴位磁刺激疗法提供实验参考.分析结果表明磁刺激神门穴时脑电信号之间的关联系数值相比静息状态下降低,平均聚类系数、平均最短特征路径长度以及平均度在阈值区间均发生显著变化,小世界属性指标增强,并存在显著性差异(P<0.01).磁刺激神门穴状态下各节点通道间的紧密程度降低、连接情况较为松散、网络中各节点同步能力减弱、效率降低、网络规模减小,这时的大脑很可能处于一种比较镇静的状态而有利于睡眠的产生.     

Finer discrimination of brain activation with local multivariate distance

The organization of human brain function is diverse on different spatial scales. Various cognitive states are always represented as distinct activity patterns across the specific brain region on fine scales. Conventional univariate analysis of functional MRI data seeks to determine how a particular cognitive state is encoded in brain activity by analyzing each voxel separately without considering the fine-scale patterns information contained in the local brain regions. In this paper, a local multivariate distance mapping (LMDM) technique is proposed to detect the brain activation and to map the fine-scale brain activity patterns. LMDM directly represents the local brain activity with the patterns across multiple voxels rather than individual voxels, and it employs the multivariate distance between different patterns to discriminate the brain state on fine scales. Experiments with simulated and real fMRI data demonstrate that LMDM technique can dramatically increase the sensitivity of the detection for the fine-scale brain activity patterns which contain the subtle information of the experimental conditions.     

Early consolidation in human primary motor cortex.

Behavioural studies indicate that a newly acquired motor skill is rapidly consolidated from an initially unstable state to a more stable state, whereas neuroimaging studies demonstrate that the brain engages new regions for performance of the task as a result of this consolidation. However, it is not known where a new skill is retained and processed before it is firmly consolidated. Some early aspects of motor skill acquisition involve the primary motor cortex (M1), but the nature of that involvement is unclear. We tested the possibility that the human M1 is essential to early motor consolidation. We monitored changes in elementary motor behaviour while subjects practised fast finger movements that rapidly improved in movement acceleration and muscle force generation. Here we show that low-frequency, repetitive transcranial magnetic stimulation of M1 but not other brain areas specifically disrupted the retention of the behavioural improvement, but did not affect basal motor behaviour, task performance, motor learning by subsequent practice, or recall of the newly acquired motor skill. These findings indicate that the human M1 is specifically engaged during the early stage of motor consolidation.     

基于对称导联脑电信号分析方法的脑损伤区域的判别

为研究采用脑电信号判别脑损伤的部位,提出了基于对称导联的信号分析方法。首先,获取安静状态和唤名刺激下脑电数据,提取脑电信号的近似熵和频谱特征;然后,分别计算对称导联的EEG特征,并对损伤区和非损伤区两组的特征值进行单因素方差分析;最后,选取一个病例,分析不同部位的特征参数比值进行损伤部位的判别,并同CT图像诊断结果进行匹配对比。结果表明,严重意识障碍患者的脑损伤和未损伤部位对称电极之间脑电特征参数比值具有显著性的差异(P0.05)。单一病例的分析结果表明,采用本文提出的方法所得出的判断结果是正确的。因此,该方法能够简便可靠地实现脑损伤部位的判别,在临床辅助诊断中有一定的应用推广价值。     

静息态亚健康失眠脑功能网络分析

针对亚健康失眠者根据匹兹堡睡眠质量指数筛选被试参与实验,利用128导脑电（EEG）分析仪,提取静息态64导脑电信号,通过多通道脑电信号同步性分析,脑功能网络的构建和分析,研究亚健康失眠者与健康人脑电信号的特异性差异,同时进一步比较分析亚健康失眠者与健康人脑电的负相关特性.分析结果表明亚健康失眠者与健康人相比,脑电信号同步性降低,脑功能网络的连接减弱,大脑的活跃度降低,并且这种差异性在脑电负相关特性中表现更为明显.     

监测缺血性脑水肿的新方法--脑电阻抗地形图法

脑电阻抗的变化与脑水肿、脑梗塞有极大的关系,文中提出了脑电阻抗地形图应用在脑水肿检测的新方法.介绍了脑电阻抗地形图的硬件结构、脑阻抗网络拓扑结构,以网络中的三角形单元为基础,详细讨论地形图的绘制处理算法.对脑水肿病人,进行了数据测取,并通过计算机形成阻抗地形图.从对病情变化病例的比较分析和稳定病人数据的重复性已经验证了这种方法的可行性.     

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.