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  • 1.

    【2hr】Abnormal Coupling Between Default Mode Network and Delta and Beta Band Brain Electric Activity in Psychotic Patients

    包量

    机译 精神病患者默认模式网络与Delta和β波段脑电活动之间的异常耦合
    摘要：Common-phase synchronization of neuronal oscillations is a mechanism by which distributed brain regions can be integrated into transiently stable networks. Based on the hypothesis that schizophrenia is characterized by deficits in functional integration within neuronal networks, this study aimed to explore whether psychotic patients exhibit differences in brain regions involved in integrative mechanisms. We report an electroencephalography (EEG)-informed functional magnetic resonance imaging analysis of eyes-open resting-state data collected from patients and healthy controls at two study sites. Global field synchronization (GFS) was chosen as an EEG measure indicating common-phase synchronization across electrodes. Several brain clusters appeared to be coupled to GFS differently in patients and controls. Activation in brain areas belonging to the default mode network was negatively associated to GFS delta (1–3.5 Hz) and positively to GFS beta (13–30 Hz) bands in patients, whereas controls showed an opposite pattern for both GFS frequency bands in those regions; activation in the extrastriate visual cortex was inversely related to GFS alpha1 (8.5–10.5 Hz) band in healthy controls, while patients had a tendency toward a positive relationship. Taken together, the GFS measure might be useful for detecting additional aspects of deficient functional network integration in psychosis.
  • 2.

    【2hr】Contrasting Effects of Posttraumatic Stress Disorder and Mild Traumatic Brain Injury on the Whole-Brain Resting-State Network: A Magnetoencephalography Study

    包量

    机译 创伤后应激障碍和轻度创伤性脑损伤对全脑静息状态网络的对比影响：磁脑图研究
    摘要：The aim of this study was to evaluate alterations in whole-brain resting-state networks associated with posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI). Networks were constructed from locations of peak statistical power on an individual basis from magnetoencephalography (MEG) source series data by applying the weighted phase lag index and surrogate data thresholding procedures. Networks representing activity in the alpha bandwidth as well as wideband activity (DC-80 Hz) were created. Statistical comparisons were adjusted for age and education level. Alpha network results demonstrate reductions in network structure associated with PTSD, but no differences associated with mTBI. Wideband network results demonstrate a shift in connectivity from the alpha to theta bandwidth in both PTSD and mTBI. Also, contrasting alterations in network structure are noted, with increased randomness associated with PTSD and increased structure associated with mTBI. These results demonstrate the potential of the analysis of MEG resting-state networks to differentiate two highly comorbid conditions. The importance of the alpha bandwidth to resting-state connectivity is also highlighted, while demonstrating the necessity of considering activity in other bandwidths during network construction.
  • 3.

    【2hr】Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

    包量

    机译 评估从人Connectome项目获得的静息状态功能磁共振成像数据中与运动相关的伪影的去噪策略的评估
    摘要：Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR.
  • 4.

    【2hr】Resting-State Functional Connectivity by Independent Component Analysis-Based Markers Corresponds to Areas of Initial Seizure Propagation Established by Prior Modalities from the Hypothalamus

    包量

    机译 通过基于独立成分分析的标记进行的静息状态功能连通性对应于下丘脑以前的形态建立的初始癫痫传播区域。
    摘要：The aims of this study were to evaluate a clinically practical functional connectivity (fc) protocol designed to blindly identify the corresponding areas of initial seizure propagation and also to differentiate these areas from remote secondary areas affected by seizure. The patients in this cohort had intractable epilepsy caused by intrahypothalamic hamartoma, which is the location of the ictal focus. The ictal propagation pathway is homogeneous and established, thus creating the optimum situation for the proposed method validation study. Twelve patients with seizures from hypothalamic hamartoma and six normal control patients underwent resting-state functional MRI, using independent component analysis (ICA) to identify network differences in patients. This was followed by seed-based connectivity measures to determine the extent of fc derangement between hypothalamus and these areas. The areas with significant change in connectivity were compared with the results of prior studies' modalities used to evaluate seizure propagation. The left amygdala-parahippocampal gyrus area, cingulate gyrus, and occipitotemporal gyrus demonstrated the highest derangement in connectivity with the hypothalamus, p < 0.01, corresponding to the initial seizure propagation areas established by prior modalities. Areas of secondary ictal propagation were differentiated from these initial locations by first being identified as an abnormal neuronal signal source through ICA, but did not show significant connectivity directly with the known ictal focus. Noninvasive connectivity measures correspond to areas of initial ictal propagation and differentiate such areas from secondary ictal propagation, which may aid in ictal focus surgical disconnection planning and support the use of this newer modality for adjunctive information in epilepsy surgery evaluation.
  • 5.

    【2hr】Increased Modularity of Resting State Networks Supports Improved Narrative Production in Aphasia Recovery

    包量

    机译 静息状态网络模块化的增加支持失语症恢复中叙事产生的改善。
    摘要：The networks that emerge in the analysis of resting state functional magnetic resonance imaging (rsfMRI) data are believed to reflect the intrinsic organization of the brain. One key property of such complex biological networks is modularity, a measure of community structure. This topological characteristic changes in neurological disease and recovery. Nineteen subjects with language disorders after stroke (aphasia) underwent neuroimaging and behavioral assessment at multiple time points before (baseline) and after an imitation-based therapy. Language was assessed with a narrative production task. Group independent component analysis was performed on the rsfMRI data to identify resting state networks (RSNs). For each participant and each rsfMRI acquisition, we constructed a graph comprising all RSNs. We assigned nodal community based on a region's RSN membership, calculated the modularity score, and then correlated changes in modularity and therapeutic gains on the narrative task. We repeated this comparison controlling for pretherapy performance and using a community structure not based on RSN membership. Increased RSN modularity was positively correlated with improvement on the narrative task immediately post-therapy. This finding remained significant when controlling for pretherapy performance. There were no significant findings for network modularity and behavior when nodal community was assigned without consideration of RSN membership. We interpret these findings as support for the adaptive role of network segregation in behavioral improvement in aphasia therapy. This has important clinical implications for the targeting of noninvasive brain stimulation in poststroke remediation and suggests potential for further insight into the processes underlying such changes through computational modeling.
  • 6.

    【2hr】Implication of the Slow-5 Oscillations in the Disruption of the Default-Mode Network in Healthy Aging and Stroke

    包量

    机译 Slow-5振荡对健康衰老和中风的默认模式网络中断的影响
    摘要：The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the default-mode network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However, no clear stipulation on the underlying mechanisms of the de-synchronization has yet been provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFOs) of the DMN sub-networks in populations of young normals, older subjects, and acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order group independent component analysis with 117 eyes-closed resting-state functional magnetic resonance imaging (rs-fMRI) sessions from volunteers in those population groups, isolating three robust components of the DMN among other resting-state networks. The posterior component of the DMN presented noticeable differences. Measures of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of the network component demonstrated a decrease in resting-state cortical oscillation power in the elderly (normal and patient), specifically in the slow-5 (0.01–0.027 Hz) range of oscillations. Furthermore, the contribution of the slow-5 oscillations during the resting state was diminished for a greater influence of the slow-4 (0.027–0.073 Hz) oscillations in the subacute stroke group, not only suggesting a vulnerability of the slow-5 oscillations to disruption but also indicating a change in the distribution of the oscillations within the resting-state frequencies. The reduction of network slow-5 fALFF in the posterior DMN component was found to present a potential association with behavioral measures, suggesting a brain–behavior relationship to those oscillations, with this change in behavior potentially resulting from an altered network integrity induced by a weakening of the slow-5 oscillations during the resting state. The repeated identification of those frequencies in the disruption of DMN stresses a critical role of the slow-5 oscillations in network disruption, and it accentuates the importance of managing those oscillations in the health of the DMN.
  • 7.

    【2hr】The Whole-Brain “Global” Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism

    包量

    机译 来自静止状态功能磁共振成像的全脑“全局”信号作为葡萄糖代谢状态定量变化的潜在生物标志物
    摘要：The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI “nuisance signals” were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a “nuisance signal,” also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states.
  • 8.

    【2hr】Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder

    包量

    机译 研究自闭症谱系障碍中白色物质的微观结构相关性
    摘要：White matter microstructure forms a complex and dynamical system that is critical for efficient and synchronized brain function. Neuroimaging findings in children with autism spectrum disorder (ASD) suggest this condition is associated with altered white matter microstructure, which may lead to atypical macroscale brain connectivity. In this study, we used diffusion tensor imaging measures to examine the extent that white matter tracts are interrelated within ASD and typical development. We assessed the strength of inter-regional white matter correlations between typically developing and ASD diagnosed individuals. Using hierarchical clustering analysis, clustering patterns of the pairwise white matter correlations were constructed and revealed to be different between the two groups. Additionally, we explored the use of graph theory analysis to examine the characteristics of the patterns formed by inter-regional white matter correlations and compared these properties between ASD and typical development. We demonstrate that the ASD sample has significantly less coherence in white matter microstructure across the brain compared to that in the typical development sample. The ASD group also presented altered topological characteristics, which may implicate less efficient brain networking in ASD. These findings highlight the potential of graph theory based network characteristics to describe the underlying networks as measured by diffusion magnetic resonance imaging and furthermore indicates that ASD may be associated with altered brain network characteristics. Our findings are consistent with those of a growing number of studies and hypotheses that have suggested disrupted brain connectivity in ASD.
  • 9.

    【2hr】Interhemispheric Dorsolateral Prefrontal Cortex Connectivity is Associated with Individual Differences in Pain Sensitivity in Healthy Controls

    包量

    机译 半球间外侧前额叶皮层连通性与健康控件中疼痛敏感性的个体差异相关。
    摘要：The dorsolateral prefrontal cortex (DLPFC) is implicated in pain modulation through multiple psychological processes. Recent noninvasive brain stimulation studies suggest that interhemispheric DLPFC connectivity influences pain tolerance and discomfort by altering interhemispheric inhibition. The structure and role of interhemispheric DLPFC connectivity in pain processing have not been investigated. The present study used dynamic causal modeling (DCM) for fMRI to investigate transcallosal DLPFC connectivity during painful stimulation in healthy volunteers. DCM parameters were used to predict individual differences in sensitivity to noxious heat stimuli. Bayesian model selection results indicated that influences among the right DLPFC (rDLPFC) and left DLPFC (lDLPFC) are modulated during painful stimuli. Regression analyses revealed that greater rDLPFC→lDLPFC couplings were associated with higher suprathreshold pain temperatures. These results highlight the role of interhemispheric connectivity in pain modulation and support the preferential role of the right hemisphere in pain processing. Knowledge of these mechanisms may improve understanding of abnormal pain modulation in chronic pain populations.
  • 10.

    【2hr】A Mapping Between Structural and Functional Brain Networks

    包量

    机译 结构和功能性大脑网络之间的映射
    摘要：The relationship between structural and functional brain networks is still highly debated. Most previous studies have used a single functional imaging modality to analyze this relationship. In this work, we use multimodal data, from functional MRI, magnetoencephalography, and diffusion tensor imaging, and assume that there exists a mapping between the connectivity matrices of the resting-state functional and structural networks. We investigate this mapping employing group averaged as well as individual data. We indeed find a significantly high goodness of fit level for this structure–function mapping. Our analysis suggests that a functional connection is shaped by all walks up to the diameter in the structural network in both modality cases. When analyzing the inverse mapping, from function to structure, longer walks in the functional network also seem to possess minor influence on the structural connection strengths. Even though similar overall properties for the structure–function mapping are found for different functional modalities, our results indicate that the structure–function relationship is modality dependent.
  • 11.

    【2hr】Demonstration of Brain Tumor-Induced Neurovascular Uncoupling in Resting-State fMRI at Ultrahigh Field

    包量

    机译 在超高场静息状态功能磁共振成像中证明脑肿瘤诱导的神经血管解耦
    摘要：To demonstrate in a small case series for the first time the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) at ultrahigh field (7T). Two de novo (i.e., untreated) brain tumor patients underwent both BOLD resting-state fMRI (rsfMRI) on a 7T MRI system and motor task-based BOLD fMRI at 3T. Ipsilesional (i.e., ipsilateral to tumor or IL) and contralesional (i.e., contralateral to tumor or CL) region of interest (ROI) analysis was performed on both 3T motor task-related general linear model-derived activation maps and on 7T rsfMRI independent component analysis (ICA)-derived sensorimotor network maps for each case. Asymmetry scores (ASs) were computed based on numbers of suprathreshold voxels in the IL and CL ROIs. In each patient, ASs derived from ROI analysis of suprathreshold voxels in IL and CL ROIs in task-related activation maps and rsfMRI ICA-derived sensorimotor component maps indicate greater number of suprathreshold voxels in contralesional than ipsilesional sensorimotor cortex in both maps. In patient 1, an AS of 0.2 was obtained from the suprathreshold Z-score spectrum (voxels with Z-scores >5.0) of the task-based activation map and AS of 1.0 was obtained from the suprathreshold Z-score spectrum (Z-scores >5.0) of the ICA-derived sensorimotor component map. Similarly, in patient 2, an AS of 1.0 was obtained from the suprathreshold Z-score spectrum (Z-scores >5.0) of the task-based activation map and an AS of 1.0 was obtained from the suprathreshold Z-score spectrum (Z-scores >5.0) of the ICA-derived sensorimotor component map. Overall, decreased BOLD signal was noted in IL compared with CL ROIs on both task-based activation maps and ultrahigh field resting-state maps, indicating the presence of NVU. We have demonstrated evidence of NVU on ultrahigh field 7T rsfMRI comparable with the findings on standard 3T motor task-based fMRI in both cases.
  • 12.

    【2hr】The Structural Connectome of the Human Central Homeostatic Network

    包量

    机译 人类中央稳态网络的结构连接体
    摘要：Homeostatic adaptations to stress are regulated by interactions between the brainstem and regions of the forebrain, including limbic sites related to respiratory, autonomic, affective, and cognitive processing. Neuroanatomic connections between these homeostatic regions, however, have not been thoroughly identified in the human brain. In this study, we perform diffusion spectrum imaging tractography using the MGH-USC Connectome MRI scanner to visualize structural connections in the human brain linking autonomic and cardiorespiratory nuclei in the midbrain, pons, and medulla oblongata with forebrain sites critical to homeostatic control. Probabilistic tractography analyses in six healthy adults revealed connections between six brainstem nuclei and seven forebrain regions, several over long distances between the caudal medulla and cerebral cortex. The strongest evidence for brainstem-homeostatic forebrain connectivity in this study was between the brainstem midline raphe and the medial temporal lobe. The subiculum and amygdala were the sampled forebrain nodes with the most extensive brainstem connections. Within the human brainstem-homeostatic forebrain connectome, we observed that a lateral forebrain bundle, whose connectivity is distinct from that of rodents and nonhuman primates, is the primary conduit for connections between the brainstem and medial temporal lobe. This study supports the concept that interconnected brainstem and forebrain nodes form an integrated central homeostatic network (CHN) in the human brain. Our findings provide an initial foundation for elucidating the neuroanatomic basis of homeostasis in the normal human brain, as well as for mapping CHN disconnections in patients with disorders of homeostasis, including sudden and unexpected death, and epilepsy.
  • 13.

    【2hr】Disentangling Brain Graphs: A Note on the Conflation of Network and Connectivity Analyses

    包量

    机译 解开脑图：关于网络和连通性分析的融合的注记
    摘要：Understanding the human brain remains the holy grail in biomedical science, and arguably in all of the sciences. Our brains represent the most complex systems in the world (and some contend the universe) comprising nearly 100 billion neurons with septillions of possible connections between them. The structure of these connections engenders an efficient hierarchical system capable of consciousness, as well as complex thoughts, feelings, and behaviors. Brain connectivity and network analyses have exploded over the last decade due to their potential in helping us understand both normal and abnormal brain function. Functional connectivity (FC) analysis examines functional associations between time series pairs in specified brain voxels or regions. Brain network analysis serves as a distinct subfield of connectivity analysis, in which associations are quantified for all time series pairs to create an interconnected representation of the brain (a brain network), which allows studying its systemic properties. While connectivity analyses underlie network analyses, the subtle distinction between the two research areas has generally been overlooked in the literature, with them often being referred to synonymously. However, developing more useful analytic methods and allowing for more precise biological interpretations require distinguishing these two complementary domains.
  • 14.

    【2hr】Data-Driven and Predefined ROI-Based Quantification of Long-Term Resting-State fMRI Reproducibility

    包量

    机译 数据驱动和基于ROI的长期静止状态fMRI重现性的定量分析
    摘要：Resting-state functional magnetic resonance imaging (fMRI) is a promising tool for neuroscience and clinical studies. However, there exist significant variations in strength and spatial extent of resting-state functional connectivity over repeated sessions in a single or multiple subjects with identical experimental conditions. Reproducibility studies have been conducted for resting-state fMRI where the reproducibility was usually evaluated in predefined regions-of-interest (ROIs). It was possible that reproducibility measures strongly depended on the ROI definition. In this work, this issue was investigated by comparing data-driven and predefined ROI-based quantification of reproducibility. In the data-driven analysis, the reproducibility was quantified using functionally connected voxels detected by a support vector machine (SVM)-based technique. In the predefined ROI-based analysis, all voxels in the predefined ROIs were included when estimating the reproducibility. Experimental results show that (1) a moderate to substantial within-subject reproducibility and a reasonable between-subject reproducibility can be obtained using functionally connected voxels identified by the SVM-based technique; (2) in the predefined ROI-based analysis, an increase in ROI size does not always result in higher reproducibility measures; (3) ROI pairs with high connectivity strength have a higher chance to exhibit high reproducibility; (4) ROI pairs with high reproducibility do not necessarily have high connectivity strength; (5) the reproducibility measured from the identified functionally connected voxels is generally higher than that measured from all voxels in predefined ROIs with typical sizes. The findings (2) and (5) suggest that conventional ROI-based analyses would underestimate the resting-state fMRI reproducibility.
  • 15.

    【2hr】Linking Functional Connectivity and Structural Connectivity Quantitatively: A Comparison of Methods

    包量

    机译 定量链接功能连接性和结构连接性：方法的比较
    摘要：Structural connectivity in the brain is the basis of functional connectivity. Quantitatively linking the two, however, remains a challenge. For a pair of regions of interest (ROIs), anatomical connections derived from diffusion-weighted imaging are often quantified by fractional anisotropy (FA) or edge weight, whereas functional connections, derived from resting-state functional magnetic resonance imaging, can be characterized by non-time-series measures such as zero-lag cross correlation and partial correlation, as well as by time-series measures such as coherence and Granger causality. In this study, we addressed the question of linking structural connectivity and functional connectivity quantitatively by considering two pairs of ROIs, one from the default mode network (DMN) and the other from the central executive network (CEN), using two different data sets. Selecting (1) posterior cingulate cortex and medial prefrontal cortex of the DMN as the first pair of ROIs and (2) left dorsal lateral prefrontal cortex and left inferior parietal lobule of the CEN as the second pair of ROIs, we show that (1) zero-lag cross correlation, partial correlation, and pairwise Granger causality were not significantly correlated with either mean FA or edge weight and (2) conditional Granger causality (CGC) was significantly correlated with edge weight but not with mean FA. These results suggest that (1) edge weight may be a more appropriate measure to quantify the strength of the anatomical connection between ROIs and (2) CGC, which statistically removes common input and the indirect influences between a given ROI pair, may be a more appropriate measure to quantify the strength of the functional interaction enabled by the fibers linking the two ROIs.
  • 16.

    【2hr】Partial Correlation-Based Retinotopically Organized Resting-State Functional Connectivity Within and Between Areas of the Visual Cortex Reflects More Than Cortical Distance

    包量

    机译 在视觉皮层区域内和区域之间基于局部相关性的视网膜组织的静息状态功能连接反映了比皮层距离更多。
    摘要：Numerous studies have demonstrated functional magnetic resonance imaging (fMRI)-based resting-state functional connectivity (RSFC) between cortical areas. Recent evidence suggests that synchronous fluctuations in blood oxygenation level-dependent fMRI reflect functional organization at a scale finer than that of visual areas. In this study, we investigated whether RSFCs within and between lower visual areas are retinotopically organized and whether retinotopically organized RSFC merely reflects cortical distance. Subjects underwent retinotopic mapping and separately resting-state fMRI. Visual areas V1, V2, and V3, were subdivided into regions of interest (ROIs) according to quadrants and visual field eccentricity. Functional connectivity (FC) was computed based on Pearson's linear correlation (correlation), and Pearson's linear partial correlation (correlation between two time courses after the time courses from all other regions in the network are regressed out). Within a quadrant, within visual areas, all correlation and nearly all partial correlation FC measures showed statistical significance. Consistently in V1, V2, and to a lesser extent in V3, correlation decreased with increasing eccentricity separation. Consistent with previously reported monkey anatomical connectivity, correlation/partial correlation values between regions from adjacent areas (V1-V2 and V2-V3) were higher than those between nonadjacent areas (V1-V3). Within a quadrant, partial correlation showed consistent significance between regions from two different areas with the same or adjacent eccentricities. Pairs of ROIs with similar eccentricity showed higher correlation/partial correlation than pairs distant in eccentricity. Between dorsal and ventral quadrants, partial correlation between common and adjacent eccentricity regions within a visual area showed statistical significance; this extended to more distant eccentricity regions in V1. Within and between quadrants, correlation decreased approximately linearly with increasing distances separating the tested ROIs. Partial correlation showed a more complex dependence on cortical distance: it decreased exponentially with increasing distance within a quadrant, but was best fit by a quadratic function between quadrants. We conclude that RSFCs within and between lower visual areas are retinotopically organized. Correlation-based FC is nonselectively high across lower visual areas, even between regions that do not share direct anatomical connections. The mechanisms likely involve network effects caused by the dense anatomical connectivity within this network and projections from higher visual areas. FC based on partial correlation, which minimizes network effects, follows expectations based on direct anatomical connections in the monkey visual cortex better than correlation. Last, partial correlation-based retinotopically organized RSFC reflects more than cortical distance effects.
  • 17.

    【2hr】Sexual Dimorphism in White Matter Developmental Trajectories Using Tract-Based Spatial Statistics

    包量

    机译 基于基于道的空间统计的白色物质发展轨迹中的性二态性
    摘要：Increasing evidence is emerging for sexual dimorphism in the trajectory of white matter development in children assessed using volumetric magnetic resonance imaging (MRI) and more recently diffusion MRI. Recent studies using diffusion MRI have examined cohorts with a wide age range (typically between 5 and 30 years) showing focal regions of differential diffusivity and fractional anisotropy (FA) and have implicated puberty as a possible contributory factor. To further investigate possible dimorphic trajectories in a young cohort, presumably closer to the expected onset of puberty, we used tract-based spatial statistics to investigate diffusion metrics. The cohort consisted of 23 males and 30 females between the ages of 8 and 16 years. Differences in diffusion metrics were corrected for age, total brain volume, and full scale IQ. In contrast to previous studies showing focal differences between males and females, widespread sexually dimorphic trajectories in structural white matter development were observed. These differences were characterized by more advanced development in females compared to males indicated by lower mean diffusivity, radial and axial diffusivity, and higher FA in females. This difference appeared to be larger at lower ages (8–9 years) with diffusion measures from males and females tending to converge between 10 and 14 years of age. Males showed a steeper slope for age-diffusion metric correlations compared to females, who either did not correlate with age or correlated in fewer regions. Further studies are now warranted to determine the role of hormones on the observed differences, particularly in 8–9-year-old children.
  • 18.

    【2hr】Abnormal Resting-State Functional Connectivity in Patients with Chronic Fatigue Syndrome: Results of Seed and Data-Driven Analyses

    包量

    机译 慢性疲劳综合征患者的异常休息状态功能连接：种子和数据驱动分析的结果
    摘要：Although altered resting-state functional connectivity (FC) is a characteristic of many chronic pain conditions, it has not yet been evaluated in patients with chronic fatigue. Our objective was to investigate the association between fatigue and altered resting-state FC in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Thirty-six female subjects, 19 ME/CFS and 17 healthy controls, completed a fatigue inventory before undergoing functional magnetic resonance imaging. Two methods, (1) data driven and (2) model based, were used to estimate and compare the intraregional FC between both groups during the resting state (RS). The first approach using independent component analysis was applied to investigate five RS networks: the default mode network, salience network (SN), left frontoparietal networks (LFPN) and right frontoparietal networks, and the sensory motor network (SMN). The second approach used a priori selected seed regions demonstrating abnormal regional cerebral blood flow (rCBF) in ME/CFS patients at rest. In ME/CFS patients, Method-1 identified decreased intrinsic connectivity among regions within the LFPN. Furthermore, the FC of the left anterior midcingulate with the SMN and the connectivity of the left posterior cingulate cortex with the SN were significantly decreased. For Method-2, five distinct clusters within the right parahippocampus and occipital lobes, demonstrating significant rCBF reductions in ME/CFS patients, were used as seeds. The parahippocampal seed and three occipital lobe seeds showed altered FC with other brain regions. The degree of abnormal connectivity correlated with the level of self-reported fatigue. Our results confirm altered RS FC in patients with ME/CFS, which was significantly correlated with the severity of their chronic fatigue.
  • 19.

    【2hr】Characterizing Information Flux Within the Distributed Pediatric Expressive Language Network: A Core Region Mapped Through fMRI-Constrained MEG Effective Connectivity Analyses

    包量

    机译 表征分布式儿科表现语言网络内的信息通量：通过fMRI约束的MEG有效连接分析映射的核心区域
    摘要：Using noninvasive neuroimaging, researchers have shown that young children have bilateral and diffuse language networks, which become increasingly left lateralized and focal with development. Connectivity within the distributed pediatric language network has been minimally studied, and conventional neuroimaging approaches do not distinguish task-related signal changes from those that are task essential. In this study, we propose a novel multimodal method to map core language sites from patterns of information flux. We retrospectively analyze neuroimaging data collected in two groups of children, ages 5–18 years, performing verb generation in functional magnetic resonance imaging (fMRI) (n = 343) and magnetoencephalography (MEG) (n = 21). The fMRI data were conventionally analyzed and the group activation map parcellated to define node locations. Neuronal activity at each node was estimated from MEG data using a linearly constrained minimum variance beamformer, and effective connectivity within canonical frequency bands was computed using the phase slope index metric. We observed significant (p ≤ 0.05) effective connections in all subjects. The number of suprathreshold connections was significantly and linearly correlated with participant's age (r = 0.50, n = 21, p ≤ 0.05), suggesting that core language sites emerge as part of the normal developmental trajectory. Across frequencies, we observed significant effective connectivity among proximal left frontal nodes. Within the low frequency bands, information flux was rostrally directed within a focal, left frontal region, approximating Broca's area. At higher frequencies, we observed increased connectivity involving bilateral perisylvian nodes. Frequency-specific differences in patterns of information flux were resolved through fast (i.e., MEG) neuroimaging.
  • 20.

    【2hr】On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series

    包量

    机译 关于稳定动态功能性大脑连接时间序列的方差
    摘要：Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box–Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.
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