Fast computation of voxel-level brain connectivity maps from resting-state functional MRI using l1-norm as approximation of Pearson's temporal correlation: Proof-of-concept and example vector hardware implementation

An outstanding issue in graph-based analysis of resting-state functional MRI is choice of network nodes. Individual consideration of entire brain voxels may represent a less biased approach than parcellating the cortex according to pre-determined atlases, but entails establishing connectedness for 1⁹–1¹¹ links, with often prohibitive computational cost. Using a representative Human Connectome Project dataset, we show that, following appropriate time-series normalization, it may be possible to accelerate connectivity determination replacing Pearson correlation with l₁-norm. Even though the adjacency matrices derived from correlation coefficients and l₁-norms are not identical, their similarity is high. Further, we describe and provide in full an example vector hardware implementation of l₁-norm on an array of 4096 zero instruction-set processors. Calculation times <1000 s are attainable, removing the major deterrent to voxel-based resting-sate network mapping and revealing fine-grained node degree heterogeneity. L₁-norm should be given consideration as a substitute for correlation in very high-density resting-state functional connectivity analyses.     

Combining spatial and temporal information to explore resting-state networks changes in abstinent heroin-dependent individuals

Majority of previous heroin fMRI studies focused on abnormal brain function in heroin-dependent individuals. However, few fMRI studies focused on the resting-state abnormalities in heroin-dependent individuals and assessed the relationship between the resting-state functional connectivity changes and duration of heroin use. In the present study, discrete cosine transform (DCT) was employed to explore spatial distribution of low frequency BOLD oscillations in heroin-dependent individuals and healthy subjects during resting-state; meanwhile resting-state functional connectivity analysis was used to investigate the temporal signatures of overlapping brain regions obtained in DCT analysis among these two groups. Main finding of the present study is that the default mode network (DMN) and rostral anterior cingulate cortex (rACC) network of heroin-dependent individuals were changed compared with healthy subjects. More importantly, these changes negatively correlated with duration of heroin use. These resting-state functional abnormalites in heroin-dependent individuals provided evidence for abnormal functional organization in heroin-dependent individuals, such as functional impairments in decision-making and inhibitory control.     

Intrinsic functional relations between human cerebral cortex and thalamus

The brain is active even in the absence of explicit stimuli or overt responses. This activity is highly correlated within specific networks of the cerebral cortex when assessed with resting-state functional magnetic resonance imaging (fMRI) blood oxygen level–dependent (BOLD) imaging. The role of the thalamus in this intrinsic activity is unknown despite its critical role in the function of the cerebral cortex. Here we mapped correlations in resting-state activity between the human thalamus and the cerebral cortex in adult humans using fMRI BOLD imaging. Based on this functional measure of intrinsic brain activity we partitioned the thalamus into nuclear groups that correspond well with postmortem human histology and connectional anatomy inferred from nonhuman primates. This structure/function correspondence in resting-state activity was strongest between each cerebral hemisphere and its ipsilateral thalamus. However, each hemisphere was also strongly correlated with the contralateral thalamus, a pattern that is not attributable to known thalamocortical monosynaptic connections. These results extend our understanding of the intrinsic network organization of the human brain to the thalamus and highlight the potential of resting-state fMRI BOLD imaging to elucidate thalamocortical relationships.     

Low-Dimensional Dynamics of Resting-State Cortical Activity

Endogenous brain activity supports spontaneous human thought and shapes perception and behavior. Connectivity-based analyses of endogenous, or resting-state, functional magnetic resonance imaging (fMRI) data have revealed the existence of a small number of robust networks which have a rich spatial structure. Yet the temporal information within fMRI data is limited, motivating the complementary analysis of electrophysiological recordings such as electroencephalography (EEG). Here we provide a novel method based on multivariate time–frequency interdependence to reconstruct the principal resting-state network dynamics in human EEG data. The stability of network expression across subjects is assessed using resampling techniques. We report the presence of seven robust networks, with distinct topographic organizations and high frequency (～5–45 Hz) fingerprints, nested within slow temporal sequences that build up and decay over several orders of magnitude. Interestingly, all seven networks are expressed concurrently during these slow dynamics, although there is a temporal asymmetry in the pattern of their formation and dissolution. These analyses uncover the complex temporal character of endogenous cortical fluctuations and, in particular, offer an opportunity to reconstruct the low dimensional linear subspace in which they unfold.     

Brain activity at rest: a multiscale hierarchical functional organization

Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems.     

Assessing the mean strength and variations of the time-to-time fluctuations of resting-state brain activity

The time-to-time fluctuations (TTFs) of resting-state brain activity as captured by resting-state fMRI (rsfMRI) have been repeatedly shown to be informative of functional brain structures and disease-related alterations. TTFs can be characterized by the mean and the range of successive difference. The former can be measured with the mean squared successive difference (MSSD), which is mathematically similar to standard deviation; the latter can be calculated by the variability of the successive difference (VSD). The purpose of this study was to evaluate both the resting state-MSSD and VSD of rsfMRI regarding their test–retest stability, sensitivity to brain state change, as well as their biological meanings. We hypothesized that MSSD and VSD are reliable in resting brain; both measures are sensitive to brain state changes such as eyes-open compared to eyes-closed condition; both are predictive of age. These hypotheses were tested with three rsfMRI datasets and proven true, suggesting both MSSD and VSD as reliable and useful tools for resting-state studies.     

Modulation of limbic-cerebellar functional connectivity enables alcoholics to recognize who is who

Chronic alcoholism is known to disrupt functions served by distributed brain systems, including limbic and frontocerebellar circuits involved in resting-state and task-activated networks subserving component processes of memory often affected in alcoholics. Using an fMRI paradigm, we investigated whether memory performance by alcoholics on a face–name association test previously observed to be problematic for alcoholics could be explained by desynchronous activity between nodes of these specific networks. While in the scanner, 18 alcoholics and 15 controls performed a face–name associative learning task with different levels of processing at encoding. This task was designed to activate the hippocampus, cerebellum, and frontal cortex. Alcoholics and controls were also scanned at rest. Twelve alcoholics and 12 controls were selected to be matched on face–name recognition performance. Task-related fMRI analysis indicated that alcoholics had preserved limbic activation but lower cerebellar activation (Crus II) than the controls in the face–name learning task. Crus II was, therefore, chosen as a seed for functional connectivity MRI analysis. At rest, the left hippocampus and left Crus II had positively synchronized activity in controls, while hippocampal and cerebellar activities were negatively synchronized in alcoholics. Task engagement resulted in hippocampal-cerebellar desynchronization in both groups. We speculate that atypical cerebello-hippocampal activity synchronization during rest in alcoholics was reset to the normal pattern of asynchrony by task engagement. Aberrations from the normal pattern of resting-state default mode synchrony could be interpreted as enabling preserved face–name associative memory in alcoholism.     

抑郁症的静息态脑功能磁共振研究

本研究的目的是研究抑郁症患者与健康人静息态脑功能的差别。对符合DSM-IV诊断标准的53例抑郁症患者和38例正常对照进行静息态功能磁共振扫描,采用局部一致性(regional homogeneity,ReHo)的方法分析数据,然后进行基于体素的组间比较,分析其静息态脑功能的差异。结果显示与正常组相比,抑郁组在双侧前扣带皮质(anterior cingulate cortex,ACC)、左侧内侧前额叶皮质、左侧颞中回均有ReHo值降低。ACC位置ReHo值显著降低提示抑郁症患者在前扣带皮质及其相邻部位自发神经活动异常。     

慢性失眠患者大脑蓝斑的异常静息态功能连接

目的:利用功能连接方法观察慢性失眠患者静息态下蓝斑的异常功能连接。方法:采集49例慢性失眠患者以及47例性别年龄和受教育程度相匹配的健康对照组的功能磁共振图像,以蓝斑为感兴趣区域,与全脑其他体素进行功能连接分析,得到两组之间功能连接的差异脑区,再对异常连接脑区的功能连接值与临床量表分数做相关分析。结果:与对照组相比,慢性失眠患者蓝斑与右楔前叶皮质、右后扣带回皮质、左颞中回皮质、左距状沟周围皮质、右眶部额上回皮质之间的功能连接增强（P<0.05, FDR校正）,并且蓝斑与左颞中回皮质之间功能连接值与抑郁自评量表呈正相关（P=0.021）。结论:慢性失眠患者蓝斑与多个脑区（主要是默认模式网络）出现的异常功能连接,可能有助于更好地理解慢性失眠的神经生物学机制,可能为失眠的高度唤醒假说提供新的影像学证据。     

Functional topography of the thalamocortical system in human

Various studies have indicated that the thalamus is involved in controlling both cortico-cortical information flow and cortical communication with the rest of the brain. Detailed anatomy and functional connectivity patterns of the thalamocortical system are essential to understanding the cortical organization and pathophysiology of a wide range of thalamus-related neurological and neuropsychiatric diseases. The current study used resting-state fMRI to investigate the topography of the human thalamocortical system from a functional perspective. The thalamus-related cortical networks were identified by performing independent component analysis on voxel-based thalamic functional connectivity maps across a large group of subjects. The resulting functional brain networks were very similar to well-established resting-state network maps. Using these brain network components in a spatial regression model with each thalamic voxel’s functional connectivity map, we localized the thalamic subdivisions related to each brain network. For instance, the medial dorsal nucleus was shown to be associated with the default mode, the bilateral executive, the medial visual networks; and the pulvinar nucleus was involved in both the dorsal attention and the visual networks. These results revealed that a single nucleus may have functional connections with multiple cortical regions or even multiple functional networks, and may be potentially related to the function of mediation or modulation of multiple cortical networks. This observed organization of thalamocortical system provided a reference for studying the functions of thalamic sub-regions. The importance of intrinsic connectivity-based mapping of the thalamocortical relationship is discussed, as well as the applicability of the approach for future studies.     

The potential of functional MRI as a biomarker in early Alzheimer's disease

Functional magnetic resonance imaging (fMRI) is a relative newcomer in the field of biomarkers for Alzheimer's disease (AD). fMRI has several potential advantages, particularly for clinical trials, as it is a noninvasive imaging technique that does not require the injection of contrast agent or radiation exposure and thus can be repeated many times during a longitudinal study. fMRI has relatively high spatial and reasonable temporal resolution, and can be acquired in the same session as structural magnetic resonance imaging. Perhaps most importantly, fMRI may provide useful information about the functional integrity of brain networks supporting memory and other cognitive domains, including the neural correlates of specific behavioral events, such as successful versus failed memory formation.     

原发性失眠患者大脑背外侧前额叶的异常静息态功能连接

目的:利用功能连接方法观察原发性失眠患者静息态下的背外侧前额叶的异常功能连接。方法:采集33 例原 发性失眠患者以及33 例年龄、性别和受教育程度相匹配的健康对照的功能磁共振图像,以背外侧前额叶为感兴趣区 域,与全脑其他体素进行功能连接分析,得到两组之间功能连接的差异脑区,再对异常功能连接脑区与临床的量表分 数做相关分析。结果:与对照组相比,发现失眠患者左侧背外侧前额叶与左侧枕下回、右侧枕下回、右侧枕中回、右侧 颞叶、左侧额中回,左侧额下回以及右侧梭状回之间的功能连接增强（P<0.05,体素簇个数≥100,FDR校正）,与左侧前 扣带皮层、右侧海马旁回、右侧脑岛、右侧背外侧额上回、右侧顶上回、右侧中央后回以及右侧中央前回之间的功能连 接减弱（P<0.05,体素簇个数≥100,FDR校正）。并且左侧背外侧前额叶与左侧枕叶下回的功能连接值与睡眠状况自评 量表分数成正相关（P=0.035）。结论:原发性失眠患者背外侧前额叶与大脑多个脑区出现异常的功能连接,可能为理 解原发性失眠患者的神经机制提供一些新的影像学依据。     

Towards a functional connectome in Drosophila

Abstract

The full functionality of the brain is determined by its molecular, cellular and circuit structure. Modern neuroscience now prioritizes the mapping of whole brain connectomes by detecting all direct neuron to neuron synaptic connections, a feat first accomplished for C. elegans, a full reconstruction of a 302-neuron nervous system. Efforts at Janelia Research Campus will soon reconstruct the whole brain connectomes of a larval and an adult Drosophila. These connectomes will provide a framework for incorporating detailed neural circuit information that Drosophila neuroscientists have gathered over decades. But when viewed in the context of a whole brain, it becomes difficult to isolate the contributions of distinct circuits, whether sensory systems or higher brain regions. The complete wiring diagram tells us that sensory information is not only processed in separate channels, but that even the earliest sensory layers are strongly synaptically interconnected. In the higher brain, long-range projections densely interconnect major brain regions and convergence centers that integrate input from different sensory systems. Furthermore, we also need to understand the impact of neuronal communication beyond direct synaptic modulation. Nevertheless, all of this can be pursued with Drosophila, combining connectomics with a diverse array of genetic tools and behavioral paradigms that provide effective approaches to entire brain function.     

Decoupling of the Occipitotemporal Cortex and the Brain’s Default-Mode Network in Dyslexia and a Role for the Cingulate Cortex in Good Readers: A Brain Imaging Study of Brazilian Children

The goal of the present study was to investigate intrinsic and reading-related brain function associated with dyslexia and typical readers in monolingual Brazilian children. Two fMRI studies were carried out: a resting-state and a word-reading study. The results show (a) underconnectivity between the occipitotemporal region (visual word form area) and the brain’s default-mode network in dyslexic readers and (b) more activation of the anterior cingulate cortex for typical readers relative to dyslexic readers. The findings provide evidence for brain connectivity and function differences in an underrepresented population in fMRI studies of dyslexia; the results suggest atypical intrinsic function, and differences in directed attention processes in dyslexia.     

Transcranial magnetic stimulation--a new tool for functional imaging of the brain

Recent progress in the theory and technology of transcranial magnetic stimulation (TMS) is leading to novel approaches in brain mapping. TMS becomes a powerful functional brain mapping tool when other imaging methods are used to record TMS-evoked activity or when peripheral effects are observed as a function of stimulus location. TMS-evoked activity currently can be recorded by EEG, PET, and fMRI. In addition to providing indices of cortical excitability, these methods allow one to study brain connectivity directly, without the need for behavioral activations. When the coordinate systems in the different imaging modalities are combined, anatomical structures seen in MRI and activation sites determined by PET, fMRI, or MEG/EEG can be used for the selection of target areas in the brain. PET and fMRI can be used to map the spatial distribution of TMS-evoked activity. On the other hand, the combination of TMS and high-resolution EEG may often be the method of choice for basic neuroscience and for clinical diagnosis, for example, in the assessment of brain connectivity in patients suffering from neurodegenerative diseases or head injuries.     

Brain mapping and detection of functional patterns in fMRI using wavelet transform; application in detection of dyslexia

Background

Functional Magnetic Resonance Imaging (fMRI) has been proven to be useful for studying brain functions. However, due to the existence of noise and distortion, mapping between the fMRI signal and the actual neural activity is difficult. Because of the difficulty, differential pattern analysis of fMRI brain images for healthy and diseased cases is regarded as an important research topic. From fMRI scans, increased blood ows can be identified as activated brain regions. Also, based on the multi-sliced images of the volume data, fMRI provides the functional information for detecting and analyzing different parts of the brain.

Methods

In this paper, the capability of a hierarchical method that performed an optimization algorithm based on modified maximum model (MCM) in our previous study is evaluated. The optimization algorithm is designed by adopting modified maximum correlation model (MCM) to detect active regions that contain significant responses. Specifically, in the study, the optimization algorithm is examined based on two groups of datasets, dyslexia and healthy subjects to verify the ability of the algorithm that enhances the quality of signal activities in the interested regions of the brain. After verifying the algorithm, discrete wavelet transform (DWT) is applied to identify the difference between healthy and dyslexia subjects.

Results

We successfully showed that our optimization algorithm improves the fMRI signal activity for both healthy and dyslexia subjects. In addition, we found that DWT based features can identify the difference between healthy and dyslexia subjects.

Conclusion

The results of this study provide insights of associations of functional abnormalities in dyslexic subjects that may be helpful for neurobiological identification from healthy subject.

     

Effect of scanner acoustic background noise on strict resting-state fMRI

Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a ‘resting-state’ fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced “silent” pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.     

基于功能连接的屈光参差性弱视视觉网络损伤研究

目的基于功能连接算法分析屈光参差性弱视和正常对照组的功能性磁共振成像(functional magnetic resonance imaging,fMRI)数据,通过对比弱视患者脑部自发活动的视觉网络功能连接异常,揭示其视觉损伤机制。方法在闭眼静息条件下采集21名弱视成年人和21名正常对照组的fMRI数据,进行去噪、校正等预处理后,计算初级视觉网络、高级视觉网络和视觉空间网络3个典型的视觉网络内和网络间的功能连接系数,并采用双样本t检验进行统计分析。结果屈光参差性弱视与正常对照组在初级视觉网络中差异无统计学意义,在高级视觉网络和视觉空间网络中差异具有统计学意义,并且它们网络之间的功能连接差异也无统计学意义。结论基于功能连接的静息态功能磁共振分析是有效的非侵入式脑区功能性连接异常研究方法,能够反映屈光参差性弱视不同视觉网络的自发脑部活动脑区异常表现,对于弱视致病机制模型研究和提出新的治疗方法都有重要启发。     

Current status of functional MRI on small animals: application to physiology, pathophysiology, and cognition

This review aims to make the reader aware of the potential of functional MRI (fMRI) in brain activation studies in small animal models. As small animals generally require anaesthesia for immobilization during MRI protocols, this is believed to be a serious limitation to the type of question that can be addressed with fMRI. We intend to introduce a fresh view with an in-depth overview of the surprising number of fMRI applications in a wide range of important research domains in neuroscience. These include the pathophysiology of brain functioning, the basic science of activity, and functional connectivity of different sensory circuits, including sensory brain mapping, the challenges when studying the hypothalamus as the major control centre in the central nervous system, and the limbic system as neural substrate for emotions and reward. Finally the contribution of small animal fMRI research to cognitive neuroscience is outlined. This review avoids focusing exclusively on traditional small laboratory animals such as rodents, but rather aims to broaden the scope by introducing alternative lissencephalic animal models such as songbirds and fish, as these are not yet well recognized as neuroimaging study subjects. These models are well established in many other neuroscience disciplines, and this review will show that their investigation with in vivo imaging tools will open new doors to cognitive neuroscience and the study of the autonomous nervous system in experimental animals.     

Visual imagery and functional connectivity in blindness: a single-case study

We present a case report on visual brain plasticity after total blindness acquired in adulthood. SH lost her sight when she was 27. Despite having been totally blind for 43 years, she reported to strongly rely on her vivid visual imagery. Three-Tesla magnetic resonance imaging (MRI) of SH and age-matched controls was performed. The MRI sequence included anatomical MRI, resting-state functional MRI, and task-related functional MRI where SH was instructed to imagine colours, faces, and motion. Compared to controls, voxel-based analysis revealed white matter loss along SH’s visual pathway as well as grey matter atrophy in the calcarine sulci. Yet we demonstrated activation in visual areas, including V1, using functional MRI. Of the four identified visual resting-state networks, none showed alterations in spatial extent; hence, SH’s preserved visual imagery seems to be mediated by intrinsic brain networks of normal extent. Time courses of two of these networks showed increased correlation with that of the inferior posterior default mode network, which may reflect adaptive changes supporting SH’s strong internal visual representations. Overall, our findings demonstrate that conscious visual experience is possible even after years of absence of extrinsic input.