编者按: 脑成像与脑网络

揭示脑的奥秘是人类面临的最大挑战之一。神经元是构成神经系统结构与功能的基本单位。神经元与神经元之间通过突触实现信息交互,并构成神经环路或神经网络。神经环路有局部的,也有跨脑区或长程的,甚至全脑尺度的。神经环路则是脑实现神经信息处理的基本单元。若干神经环路构成脑网络。脑网络研究已经成为脑功能与脑疾病研究领域的热点。 在国家自然科学基金委员会和科技部“973计划”等项目的支持下,我国科学家在这一领域已经开展了卓有成效的工作。2011年第393次香山科学会议“脑网络组及其临床应用的前沿科学问题”曾对此进行过比较深入的研讨。为促进对该领域现状及发展的了解,本期汇集了2篇述评和2篇研究论文,作为脑成像与脑网络专题发表,以飨读者。 利用9.4T功能磁共振成像(fMRI)获得轻度麻醉状态下大鼠静息状态及刺激激活的数据,通过互相关分析构建节点之间的相关系数矩阵并计算相应的网络参数,赖永秀等人报道了大鼠感觉运动系统静息态脑网络的研究成果,发现感觉运动系统在静息态时的脑网络具有小世界属性。 扩散磁共振成像(dMRI)的出现为大脑结构与功能研究提供了全新的检测手段,雷皓等报道了小动物高分辨扩散磁共振成像数据分析方法,为小动物脑dMRI研究提供了统一图像模板与完善的计算方法,对于检测神经纤维微观结构的变化,以及临床诊断,将具有极其重要的意义。 神经环路功能变化的实时在体监测是研究脑网络不可或缺的手段,曾绍群等评述了基于声光偏转器的快速无惯性随机扫描双光子显微成像技术的研究进展及发展趋势,指出该技术的进一步发展将为神经活动观测提供一种全新的方法,从而极大地推动脑科学研究的发展。 针对哺乳动物全脑的神经元网络成像,龚辉等从空间分辨率、探测范围、数据配准和成像速度等方面评述了光学显微水平全脑成像方法的研究进展,并讨论所面临的挑战。他们指出,要在全脑尺度获取突起水平分辨率的结构与功能数据,光学成像方法最为成熟。华中科技大学研制的MOST系统,率先获得了一系列高分辨率的完整大脑解剖数据集,该成果将在神经元网络的构建和脑功能与疾病研究中发挥重要作用。 我们期待更多、更好的有关脑成像与脑网络的论文发表,以更广泛和深入地促进我国脑科学研究领域的学术交流。     

高时空分辨的脑功能光学成像研究进展

脑功能成像技术对深入分析脑的信息加工过程,揭示脑的高级功能至关重要,是目前国际研究热点,已经在神经科学研究和神经系统疾病的临床诊断方面取得了很大的进展.已有脑功能成像技术如:功能磁共振成像(fMRI)、正电子断层成像(PET)、脑电图(EEG)、脑磁图(MEG)等等,虽然已被成功用于脑功能研究,但是目前这些方法也存在着时间或空间分辨率不够的局限.比较而言,光学成像方法表现出其独特魅力.激光散斑衬比成像和内源信号光学成像由于能提供空间取样、时间分辨率及空间分辨率三者的最佳组合和不需加入外源性标记物等特点,与其他脑功能成像技术相比其优势可能更为突出.具有较高的时间和空间分辨率的这两种脑功能光学成像技术及其应用都取得了重大发展,成为研究脑皮层功能构筑和脑病理生理的有力工具.但是目前这两种成像方法也面临着一些挑战.     

功能磁共振和脑电神经成像技术与大脑刺激相结合的研究进展

随着对神经机制问题阐述水平的迅速提高,所应用的神经成像技术、方法及各种工具的复杂程度也在不断提高．一方面是神经成像技术本身的不断发展,另一方面则是大脑直接刺激与神经成像技术同步记录方法的发展．经颅磁刺激-功能磁共振成像同步技术(TMS-fMRI)和经颅磁刺激-脑电技术(TMS-EEG)能为研究大脑网络的功能和有效连通性提供技术手段,该技术在多种认知领域的发展和应用,为神经科学、认知心理学、神经信息学等学科的研究者对人脑的研究开启了多条通道,更加有利于深入地理解人类大脑的工作机制．     

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。     

功能性脑成像的多维模式分析方法

利用非侵入式的功能性脑成像记录大脑活动极大地提升了我们对人类认知功能的理解.与此同时,分析成像数据的手段也逐渐从传统的一元方式向更加有效的多元分析转变.在本综述中,特别针对在认知神经科学领域占主导地位的功能性磁共振成像技术,介绍其多元数据分析方法的发展以及这种分析方法的生理学基础和未来发展方向.     

静息态fMRI在神经、精神类疾病中的研究进展

静息态功能磁共振(resting-state functional MRI,rs-fMRI)是近年出现的一种新的fMRI技术,它通过研究大脑静息状态的自发活动来反映复杂的人脑活动状态,可为我们探索大脑活动的内部机制提供新的途径。由于它无需复杂的任务实验,近年来被广泛用于神经、精神类疾病的基础与临床研究。本文就近年来国内外对静息态脑功能磁共振在神经、精神类疾病中的研究做一综述。     

神经功能成像及其在重大脑疾病中的应用

根据第101期双清论坛"神经功能成像及其在重大脑疾病中的应用"的报告内容,简述了功能神经成像技术与方法的现状与发展趋势,介绍了近年来基于成像技术的重要脑科学研究成果和临床转化研究面临的挑战,并提出了神经功能成像及其在重大脑疾病应用中的主要研究方向和科学问题的设想.     

脊髓磁共振成像技术：方法与应用

脊髓磁共振成像是将磁共振成像应用于脊髓部分(主要是颈髓)的先进研究技术,在人体感觉、运动等基础科学研究,以及脊髓损伤、脊髓炎、慢性疼痛等疾病的临床应用中均已逐渐得到使用。脊髓磁共振成像的发展相比脑成像而言仍处于起步阶段,这主要受限于目前的磁共振成像技术和数据分析方法。本文以认知神经科学和医学领域的基础研究为主,聚焦于脊髓磁共振成像技术的方法与应用。首先介绍了常用多模态脊髓磁共振成像技术的成像原理、成像方法、测量指标及其应用现状,具体包括脊髓定量磁共振成像(结构成像、弥散成像、波谱成像、髓磷脂水分数成像、磁化转移成像和化学交换饱和转移成像等)和脊髓功能磁共振成像等;其次从噪声控制、数据处理流程优化以及可重复性与可信度三个维度介绍了脊髓磁共振成像在数据分析上所面临的技术挑战以及应对策略;最后对脊髓磁共振成像的应用现状和发展前景进行了总结与展望。     

脑机接口：现状，问题与展望

本文综述现有脑机接口技术的最新发展，并讨论这些脑机接口技术的局限和存在的问题，如高估人类个体大脑的功能、对大脑信息存储方式缺乏了解等. 基于大脑信息存储的“二维码”模型，我们认为目前的脑机接口技术方案仅适用于一些简单的应用场景，如了解受测者的情绪变化、生命活动的状态，以及控制体外器械等，而无法通过脑机接口技术获取脑内诸如记忆与思考等信息的精准细节. 我们也提出，向大脑输入信息的脑机接口技术有较大的发展空间，比如发展具有多种调控效果、物理和生化技术结合的深脑刺激装置，有可能广泛应用于抑郁症、癫痫等脑疾病的治疗，以及应用于短期脑力的增强. 本文对于目前的脑机接口研究领域具有一定的警示和启发意义.     

脑科学和脑功能MR成像

目的：在对大脑认知功能进行脑功能成像研究之中,随着磁共振成像技术的发展,人们现在可以对脑的认知功能,如视觉、运动、语言和记忆等功能中枢进行成像。本文首先介绍了脑科学的发展历程,并从脑功能MR成像的方法出发,分析了其成像机理,探讨了用脑功能MR成像为手段对脑科学—认知科学进行的方法研究,最后对脑功能MR成像应用于脑科学的研究作了展望。     

Predicting consumer behavior: using novel mind-reading approaches

Advances in machine learning as applied to functional magnetic resonance imaging (fMRI) data offer the possibility of pretesting and classifying marketing communications using unbiased pattern recognition algorithms. By using these algorithms to analyze brain responses to brands, products, or existing marketing communications that either failed or succeeded in the marketplace and identifying the patterns of brain activity that characterize success or failure, future planned campaigns or new products can now be pretested to determine how well the resulting brain responses match the desired (successful) pattern of brain activity without the need for verbal feedback. This major advance in signal processing is poised to revolutionize the application of these brain-imaging techniques in the marketing sector by offering greater accuracy of prediction in terms of consumer acceptance of new brands, products, and campaigns at a speed that makes them accessible as routine pretesting tools that will clearly demonstrate return on investment.     

The role of fMRI in cognitive neuroscience: where do we stand?

Functional magnetic resonance imaging (fMRI) has quickly become the most prominent tool in cognitive neuroscience. In this article, I outline some of the limits on the kinds of inferences that can be supported by fMRI, focusing particularly on reverse inference, in which the engagement of specific mental processes is inferred from patterns of brain activation. Although this form of inference is weak, newly developed methods from the field of machine learning offer the potential to formalize and strengthen reverse inferences. I conclude by discussing the increasing presence of fMRI results in the popular media and the ethical implications of the increasing predictive power of fMRI.     

Fusing EEG and fMRI based on a bottom-up model: inferring activation and effective connectivity in neural masses

The elucidation of the complex machinery used by the human brain to segregate and integrate information while performing high cognitive functions is a subject of imminent future consequences. The most significant contributions to date in this field, known as cognitive neuroscience, have been achieved by using innovative neuroimaging techniques, such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), which measure variations in both the time and the space of some interpretable physical magnitudes. Extraordinary maps of cerebral activation involving function-restricted brain areas, as well as graphs of the functional connectivity between them, have been obtained from EEG and fMRI data by solving some spatio-temporal inverse problems, which constitutes a top-down approach. However, in many cases, a natural bridge between these maps/graphs and the causal physiological processes is lacking, leading to some misunderstandings in their interpretation. Recent advances in the comprehension of the underlying physiological mechanisms associated with different cerebral scales have provided researchers with an excellent scenario to develop sophisticated biophysical models that permit an integration of these neuroimage modalities, which must share a common aetiology. This paper proposes a bottom-up approach, involving physiological parameters in a specific mesoscopic dynamic equations system. Further observation equations encapsulating the relationship between the mesostates and the EEG/fMRI data are obtained on the basis of the physical foundations of these techniques. A methodology for the estimation of parameters from fused EEG/fMRI data is also presented. In this context, the concepts of activation and effective connectivity are carefully revised. This new approach permits us to examine and discuss some future prospects for the integration of multimodal neuroimages.     

Spatiotemporal dynamics of single-letter reading: a combined ERP-FMRI study

This work investigates the neural correlates of single-letter reading by combining event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI), thus exploiting their complementary spatiotemporal resolutions. Three externally-paced reading tasks were administered with an event-related design: passive observation of letters and symbols and active reading aloud of letters. ERP and fMRI data were separately recorded from 8 healthy adults during the same experimental conditions. Due to the presence of artifacts in the EEG signals, two subjects were discarded from further analysis. Independent Component Analysis was applied to ERPs, after dimensionality reduction by Principal Component Analysis: some independent components were clearly related to specific reading functions and the associated current density distributions in the brain were estimated with Low Resolution Electromagnetic Tomography Analysis method (LORETA). The impulse hemodynamic response function was modeled as a linear combination of linear B-spline functions and fMRI statistical analysis was performed by multiple linear regression. fMRI and LORETA maps were superimposed in order to identify the overlapping activations and the activated regions specifically revealed by each modality. The results showed the existence of neuronal networks functionally specific for letter processing and for explicit verbal-motor articulation, including the temporo-parietal and frontal regions. Overlap between fMRI and LORETA results was observed in the inferior temporal-middle occipital gyrus, suggesting that this area has a crucial and multifunctional role for linguistic and reading processes, likely because its spatial location and strong interconnection with the main visual and auditory sensory systems may have favored its specialization in grapheme-phoneme matching.     

Differences in brain function and changes with intervention in children with poor spelling and reading abilities

Previous fMRI studies in English-speaking samples suggested that specific interventions may alter brain function in language-relevant networks in children with reading and spelling difficulties, but this research strongly focused on reading impaired individuals. Only few studies so far investigated characteristics of brain activation associated with poor spelling ability and whether a specific spelling intervention may also be associated with distinct changes in brain activity patterns. We here investigated such effects of a morpheme-based spelling intervention on brain function in 20 children with comparatively poor spelling and reading abilities using repeated fMRI. Relative to 10 matched controls, children with comparatively poor spelling and reading abilities showed increased activation in frontal medial and right hemispheric regions and decreased activation in left occipito-temporal regions prior to the intervention, during processing of a lexical decision task. After five weeks of intervention, spelling and reading comprehension significantly improved in the training group, along with increased activation in the left temporal, parahippocampal and hippocampal regions. Conversely, the waiting group showed increases in right posterior regions. Our findings could indicate an increased left temporal activation associated with the recollection of the new learnt morpheme-based strategy related to successful training.     

脑网络：从脑结构到脑功能

人脑是自然界中最复杂的系统之一,不同的功能区域相互作用、互相协调,共同构成一个网络来发挥其功能。人脑是一个复杂的网络,具有高效的“小世界”拓扑属性。本文从脑结构到脑功能方面介绍了从不同模态影像学数据构造脑网络的主要进展,并探讨不同的脑疾病患者脑网络拓扑结构是否发生了异常,以及这些异常特征能否用来进行疾病分类,最后对本领域未来的研究做了简单的展望。     

The neural basis of hyperlexic reading: an FMRI case study

Children with autism spectrum disorders in very rare cases display surprisingly advanced "hyperlexic" reading skills. Using functional magnetic resonance imaging (fMRI), we studied the neural basis of this precocious reading ability in a 9-year-old hyperlexic boy who reads 6 years in advance of his age. During covert reading, he demonstrated greater activity in the left inferior frontal and superior temporal cortices than both chronological age- and reading age-matched controls. Activity in the right inferior temporal sulcus was greater when compared to reading age-matched controls. These findings suggest that precocious reading is brought about by simultaneously drawing on both left hemisphere phonological and right hemisphere visual systems, reconciling the two prevailing, but seemingly contradictory, single hemisphere theories of hyperlexia. Hyperlexic reading is therefore associated with hyperactivation of the left superior temporal cortex, much in the same way as developmental dyslexia is associated with hypoactivation of this area.     

Towards a physiology-based measure of pain: patterns of human brain activity distinguish painful from non-painful thermal stimulation

Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessment has long been self-report. Because the inability to verbally communicate can prevent effective pain management, research efforts have focused on the development of a tool that accurately assesses pain without depending on self-report. Those previous efforts have not proven successful at substituting self-report with a clinically valid, physiology-based measure of pain. Recent neuroimaging data suggest that functional magnetic resonance imaging (fMRI) and support vector machine (SVM) learning can be jointly used to accurately assess cognitive states. Therefore, we hypothesized that an SVM trained on fMRI data can assess pain in the absence of self-report. In fMRI experiments, 24 individuals were presented painful and nonpainful thermal stimuli. Using eight individuals, we trained a linear SVM to distinguish these stimuli using whole-brain patterns of activity. We assessed the performance of this trained SVM model by testing it on 16 individuals whose data were not used for training. The whole-brain SVM was 81% accurate at distinguishing painful from non-painful stimuli (p<0.0000001). Using distance from the SVM hyperplane as a confidence measure, accuracy was further increased to 84%, albeit at the expense of excluding 15% of the stimuli that were the most difficult to classify. Overall performance of the SVM was primarily affected by activity in pain-processing regions of the brain including the primary somatosensory cortex, secondary somatosensory cortex, insular cortex, primary motor cortex, and cingulate cortex. Region of interest (ROI) analyses revealed that whole-brain patterns of activity led to more accurate classification than localized activity from individual brain regions. Our findings demonstrate that fMRI with SVM learning can assess pain without requiring any communication from the person being tested. We outline tasks that should be completed to advance this approach toward use in clinical settings.     

Direct intracranial, FMRI, and lesion evidence for the causal role of left inferotemporal cortex in reading

Models of the "visual word form system" postulate that a left occipitotemporal region implements the automatic visual word recognition required for efficient reading. This theory was assessed in a patient in whom reading was explored with behavioral measures, fMRI, and intracranial local field potentials. Prior to surgery, when reading was normal, fMRI revealed a normal mosaic of ventral visual selectivity for words, faces, houses, and tools. Intracranial recordings demonstrated that the left occipitotemporal cortex responded with a short latency to conscious but also to subliminal words. Surgery removed a small portion of word-responsive occipitotemporal cortex overlapping with the word-specific fMRI activation. The patient developed a marked reading deficit, while recognition of other visual categories remained intact. Furthermore, in the post-surgery fMRI map of visual cortex, only word-specific activations disappeared. Altogether, these results provide direct evidence for the causal role of the left occipitotemporal cortex in the recognition of visual words.