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.     

Functional imaging of memory processes in humans: positron emission tomography and functional magnetic resonance imaging

Human memory is not a unitary function; it consists of multiple memory systems, with different characteristics and specialisations that are implemented in the brain. The cognitive neuroscience of human memory tries to comprehend how we encode, store, and retrieve memory items within and across those systems. The emergence of functional neuroimaging techniques offered the unprecedented opportunity to directly observe the brain regions engaged in memory functions. Brain imaging techniques can roughly be divided into those measuring the electric or magnetic fields generated by neuronal activity (EEG, magnetencephalography [MEG]) and those measuring the haemodynamic or metabolic sequelae of neuronal activity (positron emission tomography [PET], functional magnetic resonance imaging [fMRI]). Out of these techniques, the following two will be discussed in detail: fMRI and PET. Although functional neuroimaging is able to acquire images of the brain engaged in consolidating or retrieving memories, these processes are not clearly visible in the data. Statistical techniques are needed to reduce the complexity of the data and to extract the processes of interest. This article outlines the experimental and analytical procedures of neuroimaging studies with PET and fMRI. We will use a PET-study on episodic memory in human volunteers to illustrate design, analysis, and interpretation of functional imaging studies on memory.     

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.     

Brain Signature of Chronic Orofacial Pain: A Systematic Review and Meta-Analysis on Neuroimaging Research of Trigeminal Neuropathic Pain and Temporomandibular Joint Disorders

Brain neuroimaging has been widely used to investigate the bran signature of chronic orofacial pain, including trigeminal neuropathic pain (TNP) and pain related to temporomandibular joint disorders (TMD). We here systematically reviewed the neuroimaging literature regarding the functional and structural changes in the brain of TNP and TMD pain patients, using a computerized search of journal articles via PubMed. Ten TNP studies and 14 TMD studies were reviewed. Study quality and risk of bias were assessed based on the criteria of patient selection, the history of medication, the use of standardized pain/psychological assessments, and the model and statistics of imaging analyses. Qualitative meta-analysis was performed by examining the brain regions which showed significant changes in either brain functions (including the blood-oxygen-level dependent signal, cerebral blood flow and the magnetic resonance spectroscopy signal) or brain structure (including gray matter and white matter anatomy). We hypothesized that the neuroimaging findings would display a common pattern as well as distinct patterns of brain signature in the disorders. This major hypothesis was supported by the following findings: (1) TNP and TMD patients showed consistent functional/structural changes in the thalamus and the primary somatosensory cortex, indicating the thalamocortical pathway as the major site of plasticity. (2) The TNP patients showed more alterations at the thalamocortical pathway, and the two disorders showed distinct patterns of thalamic and insular connectivity. Additionally, functional and structural changes were frequently reported in the prefrontal cortex and the basal ganglia, suggesting the role of cognitive modulation and reward processing in chronic orofacial pain. The findings highlight the potential for brain neuroimaging as an investigating tool for understanding chronic orofacial pain.     

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia.     

What has functional connectivity and chemical neuroimaging in fibromyalgia taught us about the mechanisms and management of ‘centralized’ pain?

Research suggests that fibromyalgia is a central, widespread pain syndrome supported by a generalized disturbance in central nervous system pain processing. Over the past decades, multiple lines of research have identified the locus for many functional, chronic pain disorders to the central nervous system, and the brain. In recent years, brain neuroimaging techniques have heralded a revolution in our understanding of chronic pain, as they have allowed researchers to non-invasively (or minimally invasively) evaluate human patients suffering from various pain disorders. While many neuroimaging techniques have been developed, growing interest in two specific imaging modalities has led to significant contributions to chronic pain research. For instance, resting functional connectivity magnetic resonance imaging (fcMRI) is a recent adaptation of fMRI that examines intrinsic brain connectivity - defined as synchronous oscillations of the fMRI signal that occurs in the resting basal state. Proton magnetic resonance spectroscopy (¹H-MRS) is a non-invasive magnetic resonance imaging technique that can quantify the concentration of multiple metabolites within the human brain. This review will outline recent applications of the complementary imaging techniques - fcMRI and ¹H-MRS - to improve our understanding of fibromyalgia pathophysiology and how pharmacological and non-pharmacological therapies contribute to analgesia in these patients. A better understanding of the brain in chronic pain, with specific linkage as to which neural processes relate to spontaneous pain perception and hyperalgesia, will greatly improve our ability to develop novel therapeutics. Neuroimaging will play a growing role in the translational research approaches needed to make this a reality.     

Learning related interactions among neuronal systems involved in memory processes

Functional neuroimaging techniques using positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) have provided new insights in our understanding of brain function from the molecular to the systems level. While subtraction strategy based data analyses have revealed the involvement of distributed brain regions in memory processes, covariance analysis based data analysis strategies allow functional interactions between brain regions of a neuronal network to be assessed. The focus of this chapter is to (1) establish the functional topography of episodic and working memory processes in young and old normal volunteers, (2) to assess functional interactions between modules of networks of brain regions by means of covariance based analyses and systems level modelling and (3) to relate neuroimaging data to the underpinning neural networks. Male normal young and old volunteers without neurological or psychiatric illness participated in neuroimaging studies (PET, fMRI) on working and episodic memory. Distributed brain areas are involved in memory processes (episodic and working memory) in young volunteers and show much of an overlap with respect to the network components. Systems level modelling analyses support the hypothesis of bihemispheric, asymmetric networks subserving memory processes and revealed both similarities in general and differences in the interactions between brain regions during episodic encoding and retrieval as well as working memory. Changes in memory function with ageing are evident from studies in old volunteers activating more brain regions compared to young volunteers and revealing more and stronger influences of prefrontal regions. We finally discuss the way in which the systems level models based on PET and fMRI results have implications for the understanding of the underlying neural network functioning of the brain.     

Linking variability in brain chemistry and circuit function through multimodal human neuroimaging

Identifying neurobiological mechanisms mediating the emergence of individual differences in behavior is critical for advancing our understanding of relative risk for psychopathology. Neuroreceptor positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) can be used to assay in vivo regional brain chemistry and function, respectively. Typically, these neuroimaging modalities are implemented independently despite the capacity for integrated data sets to offer unique insight into molecular mechanisms associated with brain function. Through examples from the serotonin and dopamine system and its effects on threat- and reward-related brain function, we review evidence for how such a multimodal neuroimaging strategy can be successfully implemented. Furthermore, we discuss how multimodal PET-fMRI can be integrated with techniques such as imaging genetics, pharmacological challenge paradigms and gene-environment interaction models to more completely map biological pathways mediating individual differences in behavior and related risk for psychopathology and inform the development of novel therapeutic targets.     

Pathophysiology and functional consequences of human partial epilepsy: lessons from positron emission tomography studies

Positron emission tomography (PET) is a powerful clinical and research tool that, in the past two decades, has provided a great amount of novel data on the pathophysiology and functional consequences of human epilepsy. PET studies revealed cortical and subcortical brain dysfunction of a widespread brain circuitry, providing an unprecedented insight in the complex functional abnormalities of the epileptic brain. Correlation of metabolic and neuroreceptor PET abnormalities with electroclinical variables helped identify parts of this circuitry, some of which are directly related to primary epileptogenesis, while others, adjacent to or remote from the primary epileptic focus, may be secondary to longstanding epilepsy. PET studies have also provided detailed data on the functional anatomy of cognitive and behavioral abnormalities associated with epilepsy. PET, along with other neuroimaging modalities, can measure longitudinal changes in brain function attributed to chronic seizures as well as therapeutic interventions. This review demonstrates how development of more specific PET tracers and application of multimodality imaging by combining structural and functional neuroimaging with electrophysiological data can further improve our understanding of human partial epilepsy, and helps more effective application of PET in presurgical evaluation of patients with intractable seizures.     

Mouse models in neurological disorders: Applications of non-invasive imaging

Neuroimaging techniques represent powerful tools to assess disease-specific cellular, biochemical and molecular processes non-invasively in vivo. Besides providing precise anatomical localisation and quantification, the most exciting advantage of non-invasive imaging techniques is the opportunity to investigate the spatial and temporal dynamics of disease-specific functional and molecular events longitudinally in intact living organisms, so called molecular imaging (MI). Combining neuroimaging technologies with in vivo models of neurological disorders provides unique opportunities to understand the aetiology and pathophysiology of human neurological disorders. In this way, neuroimaging in mouse models of neurological disorders not only can be used for phenotyping specific diseases and monitoring disease progression but also plays an essential role in the development and evaluation of disease-specific treatment approaches. In this way MI is a key technology in translational research, helping to design improved disease models as well as experimental treatment protocols that may afterwards be implemented into clinical routine. The most widely used imaging modalities in animal models to assess in vivo anatomical, functional and molecular events are positron emission tomography (PET), magnetic resonance imaging (MRI) and optical imaging (OI). Here, we review the application of neuroimaging in mouse models of neurodegeneration (Parkinson's disease, PD, and Alzheimer's disease, AD) and brain cancer (glioma).     

Pathogenesis and brain functional imaging in nocturnal enuresis: A review

Nocturnal enuresis is a common and distressing developmental disease, which may cause various degrees of psychosocial stress and impairment to self-esteem in affected children as well as agitation to their parents or caregivers. Nevertheless, the etiology and pathogenesis of nocturnal enuresis are not understood. Currently, nocturnal enuresis is generally considered a multifactorial disease associated with a complex interaction of somatic, psychosocial, and environmental factors. A variety of postulations have been proposed to explain the occurrence and progression of nocturnal enuresis, including hereditary aberration, abnormal circadian rhythm of antidiuretic hormone secretion during sleep, bladder dysfunction, abnormal sleep, difficulties in arousal, neuropsychological disorders, and maturational delays of the brain. In recent decades, the introduction of functional neuroimaging technologies has provided new approaches for uncovering the mechanisms underlying nocturnal enuresis. The main neuroimaging modalities have included brain morphometry based on structural magnetic resonance imaging (MRI), task-based and event-related functional MRI (fMRI), and resting-state fMRI. The relevant studies have indicated that nocturnal enuresis is associated with functional and structural alterations of the brain. In this review, we briefly summarized the popular hypotheses regarding the pathogenesis of nocturnal enuresis and the current progress of functional neuroimaging studies in examining the underlying mechanisms thereof.     

人脑功能连通性研究进展

对人脑结构和功能的深入研究,已经要求脑成像技术不能仅仅局限于研究简单的脑功能定位问题,即寻找和定位与特定认知任务相关的某一块或者一组大脑皮层功能区,而必须研究分析各功能区间的动态功能连通和整合问题,即描述特定脑功能区域间的交互作用以及这些交互作用如何受认知任务的影响.已有几种非常规的脑成像技术和数据分析方法,包括时间相关性分析、心理生理交互作用(PPI)、结构方程模型(SEM)、动态因果模型(DCM)、弥散张量成像(DTI)等等,被成功用于人脑功能连通性和有效连通性的研究.脑功能连通性研究的发展,有利于深入理解人脑在系统水平上的动态运作方式,是今后认知神经科学发展的一个重要方向.     

Structural and Functional Brain Connectivity of People with Obesity and Prediction of Body Mass Index Using Connectivity

Obesity is a medical condition affecting billions of people. Various neuroimaging methods including magnetic resonance imaging (MRI) have been used to obtain information about obesity. We adopted a multi-modal approach combining diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) to incorporate complementary information and thus better investigate the brains of non-healthy weight subjects. The objective of this study was to explore multi-modal neuroimaging and use it to predict a practical clinical score, body mass index (BMI). Connectivity analysis was applied to DTI and rs-fMRI. Significant regions and associated imaging features were identified based on group-wise differences between healthy weight and non-healthy weight subjects. Six DTI-driven connections and 10 rs-fMRI-driven connectivities were identified. DTI-driven connections better reflected group-wise differences than did rs-fMRI-driven connectivity. We predicted BMI values using multi-modal imaging features in a partial least-square regression framework (percent error 15.0%). Our study identified brain regions and imaging features that can adequately explain BMI. We identified potentially good imaging biomarker candidates for obesity-related diseases.     

Reproducibility of Structural,Resting-State BOLD and DTI Data between Identical Scanners

Increasingly, clinical trials based on brain imaging are adopting multiple sites/centers to increase their subject pool and to expedite the studies, and more longitudinal studies are using multiple imaging methods to assess structural and functional changes. Careful investigation of the test-retest reliability and image quality of inter- or intra- scanner neuroimaging measurements are critical in the design, statistical analysis and interpretation of results. We propose a framework and specific metrics to quantify the reproducibility and image quality for neuroimaging studies (structural, BOLD and Diffusion Tensor Imaging) collected across identical scanners and following a major hardware repair (gradient coil replacement). We achieved consistent measures for the proposed metrics: structural (mean volume in specific regions and stretch factor), functional (temporal Signal-to-Noise ratio), diffusion (mean Fractional Anisotropy and Mean Diffusivity in multiple regions). The proposed frame work of imaging metrics should be used to perform daily quality assurance testing and incorporated into multi-center studies.     

Pattern classification of large-scale functional brain networks: identification of informative neuroimaging markers for epilepsy

The accurate prediction of general neuropsychiatric disorders, on an individual basis, using resting-state functional magnetic resonance imaging (fMRI) is a challenging task of great clinical significance. Despite the progress to chart the differences between the healthy controls and patients at the group level, the pattern classification of functional brain networks across individuals is still less developed. In this paper we identify two novel neuroimaging measures that prove to be strongly predictive neuroimaging markers in pattern classification between healthy controls and general epileptic patients. These measures characterize two important aspects of the functional brain network in a quantitative manner: (i) coordinated operation among spatially distributed brain regions, and (ii) the asymmetry of bilaterally homologous brain regions, in terms of their global patterns of functional connectivity. This second measure offers a unique understanding of brain asymmetry at the network level, and, to the best of our knowledge, has not been previously used in pattern classification of functional brain networks. Using modern pattern-recognition approaches like sparse regression and support vector machine, we have achieved a cross-validated classification accuracy of 83.9% (specificity: 82.5%; sensitivity: 85%) across individuals from a large dataset consisting of 180 healthy controls and epileptic patients. We identified significantly changed functional pathways and subnetworks in epileptic patients that underlie the pathophysiological mechanism of the impaired cognitive functions. Specifically, we find that the asymmetry of brain operation for epileptic patients is markedly enhanced in temporal lobe and limbic system, in comparison with healthy individuals. The present study indicates that with specifically designed informative neuroimaging markers, resting-state fMRI can serve as a most promising tool for clinical diagnosis, and also shed light onto the physiology behind complex neuropsychiatric disorders. The systematic approaches we present here are expected to have wider applications in general neuropsychiatric disorders.     

Revealing Topological Organization of Human Brain Functional Networks with Resting-State Functional near Infrared Spectroscopy

Background

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics.

Results

We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques.

Conclusions

Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.     

Integrating across neuroimaging modalities boosts prediction accuracy of cognitive ability

Variation in cognitive ability arises from subtle differences in underlying neural architecture. Understanding and predicting individual variability in cognition from the differences in brain networks requires harnessing the unique variance captured by different neuroimaging modalities. Here we adopted a multi-level machine learning approach that combines diffusion, functional, and structural MRI data from the Human Connectome Project (N = 1050) to provide unitary prediction models of various cognitive abilities: global cognitive function, fluid intelligence, crystallized intelligence, impulsivity, spatial orientation, verbal episodic memory and sustained attention. Out-of-sample predictions of each cognitive score were first generated using a sparsity-constrained principal component regression on individual neuroimaging modalities. These individual predictions were then aggregated and submitted to a LASSO estimator that removed redundant variability across channels. This stacked prediction led to a significant improvement in accuracy, relative to the best single modality predictions (approximately 1% to more than 3% boost in variance explained), across a majority of the cognitive abilities tested. Further analysis found that diffusion and brain surface properties contribute the most to the predictive power. Our findings establish a lower bound to predict individual differences in cognition using multiple neuroimaging measures of brain architecture, both structural and functional, quantify the relative predictive power of the different imaging modalities, and reveal how each modality provides unique and complementary information about individual differences in cognitive function.     

Non-invasive NIR spectroscopy of human brain function during exercise

The assessment of physiological changes associated with brain activity has become possible by optical methods, such as near-infrared spectroscopy (NIRS). NIRS is a useful neuroimaging technique based on haemodynamic principles for the non-invasive investigation of brain in motion. Due to its properties, the near-infrared light can penetrate biological tissue reasonably well to assess brain activity and two types of measurements are possible according to the number of channels used: dynamic changes in a localized brain region or functional brain imaging. The theoretical and technological advances of the past 10–15 years have opened the door to a range of applications in the human movement sciences, including some that involve imaging of the adult brain during motor and cognitive tasks, which for many years had been inaccessible to NIRS. This article examines the perturbation methods for measuring cerebral haemodynamic responses within resting and exercise conditions in humans and how NIRS can be used to image the moving brain. Methodological challenges of NIRS technique are presented, while the advantages and pitfalls of NIRS compared to other neuroimaging methods are discussed. Actual and future uses for NIRS in the field of sport sciences are outlined for a better understanding of brain processes during movement.     

Reading vascular changes in brain imaging: is dendritic calcium the key?

A key goal in functional neuroimaging is to use signals that are related to local changes in metabolism and blood flow to track the neuronal correlates of mental activity. Recent findings indicate that the dendritic processing of excitatory synaptic inputs correlates more closely than the generation of spikes with brain imaging signals. The correlation is often nonlinear and context-sensitive, and cannot be generalized for every condition or brain region. The vascular signals are mainly produced by increases in intracellular calcium in neurons and possibly astrocytes, which activate important enzymes that produce vasodilators to generate increments in flow and the positive blood oxygen level dependent signal. Our understanding of the cellular mechanisms of functional imaging signals places constraints on the interpretation of the data.     

The constructive nature of affective vision: seeing fearful scenes activates extrastriate body area

It is part of basic emotions like fear or anger that they prepare the brain to act adaptively. Hence scenes representing emotional events are normally associated with characteristic adaptive behavior. Normally, face and body representation areas in the brain are modulated by these emotions when presented in the face or body. Here, we provide neuroimaging evidence (using functional magnetic resonance imaging) that the extrastriate body area (EBA) is highly responsive when subjects observe isolated faces presented in emotional scenes. This response of EBA to threatening scenes in which no body is present gives rise to speculation about its function. We discuss the possibility that the brain reacts proactively to the emotional meaning of the scene.