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  • 1.

    【2hr】Effect of Repetitive Transcranial Magnetic Stimulation on fMRI Resting-State Connectivity in Multiple System Atrophy

    包量

    机译 重复经颅磁刺激对多系统萎缩中fMRI静止状态连通性的影响
    摘要：Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique that has been used to treat neurological and psychiatric conditions. Although results of rTMS intervention are promising, so far, little is known about the rTMS effect on brain functional networks in clinical populations. In this study, we used a whole-brain connectivity analysis of resting-state functional magnetic resonance imaging data to uncover changes in functional connectivity following rTMS intervention and their association with motor symptoms in patients with multiple system atrophy (MSA). Patients were randomized to active rTMS or sham rTMS groups and completed a 10-session 5-Hz rTMS treatment over the left primary motor area. The results showed significant rTMS-related changes in motor symptoms and functional connectivity. Specifically, (1) significant improvement of motor symptoms was observed in the active rTMS group, but not in the sham rTMS group; and (2) several functional links involving the default mode, cerebellar, and limbic networks exhibited positive changes in functional connectivity in the active rTMS group. Moreover, the positive changes in functional connectivity were associated with improvement in motor symptoms for the active rTMS group. The present findings suggest that rTMS may improve motor symptoms by modulating functional links connecting to the default mode, cerebellar, and limbic networks, inferring a future therapeutic candidate for patients with MSA.
  • 2.

    【2hr】Functional Connectivity Density and Balance in Young Patients with Traumatic Axonal Injury

    包量

    机译 年轻的创伤性轴索损伤患者的功能连接密度和平衡。
    摘要：Our previous study provided some evidence for the relationship between abnormal structural connectivity and poor balance performance in young traumatic axonal injury (TAI) patients. An enhanced understanding of the functional connectivity following TAI may allow targeted treatments geared toward improving brain function and postural control. Twelve patients with TAI and 28 normally developing children (aged 9–19 years) performed the sensory organization test (SOT) protocol of the EquiTest (Neurocom). All participants were scanned using resting-state functional magnetic resonance imaging series along with anatomical scans. We applied “functional connectivity density mapping” (FCDM), a voxel-wise data-driven method that calculates individual functional connectivity maps to obtain both short-range and long-range FCD. Findings revealed that the TAI group scored generally lower than the control group on the SOT, especially when proprioceptive feedback was compromised. Between-group maps noted significantly decreased long-range FCD in the TAI group in frontal and subcortical regions and significantly increased short-range FCD in frontal regions, left inferior parietal, and cerebellar lobules. Moreover, lower balance levels in TAI patients were associated with a lower long-range FCD in left putamen and cerebellar vermis. These findings suggest that long-range connections may be more vulnerable to TAI than short-range connections. Moreover, higher values of short-range FCD may suggest adaptive mechanisms in the TAI group. Finally, this study supports the view that FCDM is a valuable tool for selectively predicting functional motor deficits in TAI patients.
  • 3.

    【2hr】Detecting Functional Connectivity During Audiovisual Integration with MEG: A Comparison of Connectivity Metrics

    包量

    机译 在与MEG进行视听集成期间检测功能连通性：连通性指标的比较
    摘要：In typical magnetoencephalography and/or electroencephalography functional connectivity analysis, researchers select one of several methods that measure a relationship between regions to determine connectivity, such as coherence, power correlations, and others. However, it is largely unknown if some are more suited than others for various types of investigations. In this study, the authors investigate seven connectivity metrics to evaluate which, if any, are sensitive to audiovisual integration by contrasting connectivity when tracking an audiovisual object versus connectivity when tracking a visual object uncorrelated with the auditory stimulus. The authors are able to assess the metrics' performances at detecting audiovisual integration by investigating connectivity between auditory and visual areas. Critically, the authors perform their investigation on a whole-cortex all-to-all mapping, avoiding confounds introduced in seed selection. The authors find that amplitude-based connectivity measures in the beta band detect strong connections between visual and auditory areas during audiovisual integration, specifically between V4/V5 and auditory cortices in the right hemisphere. Conversely, phase-based connectivity measures in the beta band as well as phase and power measures in alpha, gamma, and theta do not show connectivity between audiovisual areas. The authors postulate that while beta power correlations detect audiovisual integration in the current experimental context, it may not always be the best measure to detect connectivity. Instead, it is likely that the brain utilizes a variety of mechanisms in neuronal communication that may produce differential types of temporal relationships.
  • 4.

    【2hr】Functional Connectivity in Frequency-Tagged Cortical Networks During Active Harm Avoidance

    包量

    机译 主动避障过程中带有频率标签的皮层网络中的功能连接
    摘要：Many behavioral and cognitive processes are grounded in widespread and dynamic communication between brain regions. Thus, the quantification of functional connectivity with high temporal resolution is highly desirable for capturing in vivo brain function. However, many of the commonly used measures of functional connectivity capture only linear signal dependence and are based entirely on relatively simple quantitative measures such as mean and variance. In this study, the authors used a recently developed algorithm, the generalized measure of association (GMA), to quantify dynamic changes in cortical connectivity using steady-state visual evoked potentials (ssVEPs) measured in the context of a conditioned behavioral avoidance task. GMA uses a nonparametric estimator of statistical dependence based on ranks that are efficient and capable of providing temporal precision roughly corresponding to the timing of cognitive acts (∼100–200 msec). Participants viewed simple gratings predicting the presence/absence of an aversive loud noise, co-occurring with peripheral cues indicating whether the loud noise could be avoided by means of a key press (active) or not (passive). For active compared with passive trials, heightened connectivity between visual and central areas was observed in time segments preceding and surrounding the avoidance cue. Viewing of the threat stimuli also led to greater initial connectivity between occipital and central regions, followed by heightened local coupling among visual regions surrounding the motor response. Local neural coupling within extended visual regions was sustained throughout major parts of the viewing epoch. These findings are discussed in a framework of flexible synchronization between cortical networks as a function of experience and active sensorimotor coupling.
  • 5.

    【2hr】Functional Connectivity Changes and Executive and Social Problems in Neurofibromatosis Type I

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    机译 I型神经纤维瘤病的功能连通性变化以及执行和社会问题
    摘要：Neurofibromatosis type 1 (NF1) has regularly been associated with cognitive, social, and behavioral problems. The fact that many different cognitive and behavioral impairments have been observed in NF1 suggests that networks of brain regions are involved rather than specific brain regions. Here, we examined whether functional connectivity was different in NF1 and, if so, whether associations were present with cognitive, social, and behavioral outcomes. Fourteen NF1 patients (8 male, age: M=12.49, SD=2.65) and 30 healthy controls (HC; 23 male, age: M=12.30, SD=2.94; p=0.835) were included. Functional connectivity was assessed using functional resting-state scanning. We analyzed brain regions that have been associated with cognitive and social functions: the bilateral ventral anterior cingulate cortex (vACC), the bilateral amygdala, the bilateral orbitofrontal cortex (OFC), and the posterior cingulate cortex (PCC). For NF1 patients, connection strengths between brain regions showing HC-NF1 differences were correlated with parent reports of cognitive, social, and behavioral functioning. Compared to HC, patients showed differences in functional connectivity between the left vACC and the frontal cortex, insula, and subcortical areas (caudate, putamen), between the left amygdala and the frontal cortex, insula, supramarginal gyrus, and PCC/precuneus, and between the left OFC and frontal and subcortical areas (caudate, pallidum). In patients, indications were found for associations between increased frontofrontal and temporofrontal functional connectivity with cognitive, social, and behavioral deficits (r-range=0.536–0.851). NF1 patients showed differences in functional connectivity between areas associated with cognitive and social functioning when compared to controls. This, plus the fact that connectivity strengths in these networks were associated with worse cognitive, social, and behavioral outcomes, suggests a neuropathological basis for the widespread deficits observed in NF1.
  • 6.

    【2hr】Negative Blood Oxygen Level Dependent Signals During Speech Comprehension

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    机译 语音理解过程中依赖于血氧水平的负信号
    摘要：Speech comprehension studies have generally focused on the isolation and function of regions with positive blood oxygen level dependent (BOLD) signals with respect to a resting baseline. Although regions with negative BOLD signals in comparison to a resting baseline have been reported in language-related tasks, their relationship to regions of positive signals is not fully appreciated. Based on the emerging notion that the negative signals may represent an active function in language tasks, the authors test the hypothesis that negative BOLD signals during receptive language are more associated with comprehension than content-free versions of the same stimuli. Regions associated with comprehension of speech were isolated by comparing responses to passive listening to natural speech to two incomprehensible versions of the same speech: one that was digitally time reversed and one that was muffled by removal of high frequencies. The signal polarity was determined by comparing the BOLD signal during each speech condition to the BOLD signal during a resting baseline. As expected, stimulation-induced positive signals relative to resting baseline were observed in the canonical language areas with varying signal amplitudes for each condition. Negative BOLD responses relative to resting baseline were observed primarily in frontoparietal regions and were specific to the natural speech condition. However, the BOLD signal remained indistinguishable from baseline for the unintelligible speech conditions. Variations in connectivity between brain regions with positive and negative signals were also specifically related to the comprehension of natural speech. These observations of anticorrelated signals related to speech comprehension are consistent with emerging models of cooperative roles represented by BOLD signals of opposite polarity.
  • 7.

    【2hr】Brain Networks Engaged in Audiovisual Integration During Speech Perception Revealed by Persistent Homology-Based Network Filtration

    包量

    机译 基于持久同源性的网络过滤揭示了语音感知过程中参与视听整合的大脑网络
    摘要：The human brain naturally integrates audiovisual information to improve speech perception. However, in noisy environments, understanding speech is difficult and may require much effort. Although the brain network is supposed to be engaged in speech perception, it is unclear how speech-related brain regions are connected during natural bimodal audiovisual or unimodal speech perception with counterpart irrelevant noise. To investigate the topological changes of speech-related brain networks at all possible thresholds, we used a persistent homological framework through hierarchical clustering, such as single linkage distance, to analyze the connected component of the functional network during speech perception using functional magnetic resonance imaging. For speech perception, bimodal (audio-visual speech cue) or unimodal speech cues with counterpart irrelevant noise (auditory white-noise or visual gum-chewing) were delivered to 15 subjects. In terms of positive relationship, similar connected components were observed in bimodal and unimodal speech conditions during filtration. However, during speech perception by congruent audiovisual stimuli, the tighter couplings of left anterior temporal gyrus-anterior insula component and right premotor-visual components were observed than auditory or visual speech cue conditions, respectively. Interestingly, visual speech is perceived under white noise by tight negative coupling in the left inferior frontal region–right anterior cingulate, left anterior insula, and bilateral visual regions, including right middle temporal gyrus, right fusiform components. In conclusion, the speech brain network is tightly positively or negatively connected, and can reflect efficient or effortful processes during natural audiovisual integration or lip-reading, respectively, in speech perception.
  • 8.

    【2hr】Handedness- and Brain Size-Related Efficiency Differences in Small-World Brain Networks: A Resting-State Functional Magnetic Resonance Imaging Study

    包量

    机译 小世界脑网络中与手性和大脑大小有关的效率差异：静止状态功能磁共振成像研究
    摘要：The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical regions. Graph theory-based methods were employed to further analyze their topological properties. As expected, all participants demonstrated small-world topology, suggesting a highly efficient topological structure. Furthermore, we found that smaller brains showed higher local efficiency, whereas larger brains showed higher global efficiency, reflecting a suitable efficiency balance between local specialization and global integration of brain functional activity. Compared with right-handers, significant alterations in nodal efficiency were revealed in left-handers, involving the anterior and median cingulate gyrus, middle temporal gyrus, angular gyrus, and amygdala. Our findings indicated that the functional network organization in the human brain was associated with handedness and brain size.
  • 9.

    【2hr】Transcallosal Connectivity Changes from Infancy to Late Adulthood: An Ex Vivo Diffusion Spectrum Imaging Study of Macaque Brains

    包量

    机译 从婴儿期到成年晚期的跨Callosalal连接性变化：猕猴脑的体外扩散光谱成像研究。
    摘要：Interhemispheric communication plays a critical role to ensure normal brain functions in cognition and behavior. Since non-human primate (NHP) brains resemble most aspects of the human brain, a thorough knowledge of interhemispheric cortical connectivity changes in NHP brains throughout the developmental and aging periods may provide valuable insights for translational and clinical research. In this study, formalin-fixed rhesus monkey brains aged from 1 to 24 years were utilized to examine transcallosal connectivity changes using diffusion spectrum imaging (DSI). It was found that the transcallosal connectivity for most frontal cortical areas, including dorso- and ventro-lateral prefrontal, premotor, and motor cortices, demonstrated pronounced age-related alterations. However, such a pattern was less obvious in temporal, posterior parietal, and visual cortices. The DSI results reveal the age-related evolution pattern of transcallosal connectivity in various cortical areas of macaque brains from infancy to late adulthood, and may have implications for assessing the functional defects or alterations in the associated cortical areas during brain development and aging in humans.
  • 10.

    【2hr】Associations of Resting-State fMRI Functional Connectivity with Flow-BOLD Coupling and Regional Vasculature

    包量

    机译 静息状态fMRI功能连通性与大胆耦合和局部脉管系统的关联。
    摘要：There has been tremendous interest in applying functional magnetic resonance imaging-based resting-state functional connectivity (rs-fcMRI) measurements to the study of brain function. However, a lack of understanding of the physiological mechanisms of rs-fcMRI limits their ability to interpret rs-fcMRI findings. In this work, the authors examine the regional associations between rs-fcMRI estimates and dynamic coupling between the blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF), as well as resting macrovascular volume. Resting-state BOLD and CBF data were simultaneously acquired using a dual-echo pseudocontinuous arterial spin labeling (pCASL) technique, whereas macrovascular volume fraction was estimated using time-of-flight MR angiography. Functional connectivity within well-known functional networks—including the default mode, frontoparietal, and primary sensory-motor networks—was calculated using a conventional seed-based correlation approach. They found the functional connectivity strength to be significantly correlated with the regional increase in CBF-BOLD coupling strength and inversely proportional to macrovascular volume fraction. These relationships were consistently observed within all functional networks considered. Their findings suggest that highly connected networks observed using rs-fcMRI are not likely to be mediated by common vascular drainage linking distal cortical areas. Instead, high BOLD functional connectivity is more likely to reflect tighter neurovascular connections, attributable to neuronal pathways.
  • 11.

    【2hr】Inhibitory Behavioral Control: A Stochastic Dynamic Causal Modeling Study Using Network Discovery Analysis

    包量

    机译 抑制性行为控制：使用网络发现分析的随机动态因果建模研究
    摘要：This study employed functional magnetic resonance imaging (fMRI)-based dynamic causal modeling (DCM) to study the effective (directional) neuronal connectivity underlying inhibitory behavioral control. fMRI data were acquired from 15 healthy subjects while they performed a Go/NoGo task with two levels of NoGo difficulty (Easy and Hard NoGo conditions) in distinguishing spatial patterns of lines. Based on the previous inhibitory control literature and the present fMRI activation results, 10 brain regions were postulated as nodes in the effective connectivity model. Due to the large number of potential interconnections among these nodes, the number of models for final analysis was reduced to a manageable level for the whole group by conducting DCM Network Discovery, which is a recently developed option within the Statistical Parametric Mapping software package. Given the optimum network model, the DCM Network Discovery analysis found that the locations of the driving input into the model from all the experimental stimuli in the Go/NoGo task were the amygdala and the hippocampus. The strengths of several cortico-subcortical connections were modulated (influenced) by the two NoGo conditions. Specifically, connectivity from the middle frontal gyrus (MFG) to hippocampus was enhanced by the Easy condition and further enhanced by the Hard NoGo condition, possibly suggesting that compared with the Easy NoGo condition, stronger control from MFG was needed for the hippocampus to discriminate/learn the spatial pattern in order to respond correctly (inhibit), during the Hard NoGo condition.
  • 12.

    【2hr】Connectomic Profiles for Individualized Resting State Networks and Regions of Interest

    包量

    机译 个性化休息状态网络和感兴趣区域的连接组概况
    摘要：Functional connectivity analysis of human brain resting state functional magnetic resonance imaging (rsfMRI) data and resultant functional networks, or RSNs, have drawn increasing interest in both research and clinical applications. A fundamental yet challenging problem is to identify distinct functional regions or regions of interest (ROIs) that have accurate functional correspondence across subjects. This article presents an algorithmic framework to identify ROIs of common RSNs at the individual level. It first employed a dual-sparsity dictionary learning algorithm to extract group connectomic profiles of ROIs and RSNs from noisy and high-dimensional fMRI data, with special attention to the well-known inter-subject variability in anatomy and then identified the ROIs of a given individual by employing both anatomic and group connectomic profile constraints using an energy minimization approach. Applications of this framework demonstrated that it can identify individualized ROIs of RSNs with superior performance over commonly used registration methods in terms of functional correspondence, and a test–retest study revealed that the framework is robust and consistent across both short-interval and long-interval repeated sessions of the same population. These results indicate that our framework can provide accurate substrates for individualized rsfMRI analysis.
  • 13.

    【2hr】Phonemic Fluency and Brain Connectivity in Age-Related Macular Degeneration: A Pilot Study

    包量

    机译 与年龄相关的黄斑变性的音素流利性和大脑连通性：一项初步研究
    摘要：Age-related macular degeneration (AMD), the leading cause of blindness in developed nations, has been associated with poor performance on tests of phonemic fluency. This pilot study sought to (1) characterize the relationship between phonemic fluency and resting-state functional brain connectivity in AMD patients and (2) determine whether regional connections associated with phonemic fluency in AMD patients were similarly linked to phonemic fluency in healthy participants. Behavior-based connectivity analysis was applied to resting-state, functional magnetic resonance imaging data from seven patients (mean age=79.9±7.5 years) with bilateral AMD who completed fluency tasks prior to imaging. Phonemic fluency was inversely related to the strength of functional connectivity (FC) among six pairs of brain regions, representing eight nodes: left opercular portion of inferior frontal gyrus (which includes Broca's area), left superior temporal gyrus (which includes part of Wernicke's area), inferior parietal lobe (bilaterally), right superior parietal lobe, right supramarginal gyrus, right supplementary motor area, and right precentral gyrus. The FC of these reference links was not related to phonemic fluency among 32 healthy individuals (16 younger adults, mean age=23.5±4.6 years and 16 older adults, mean age=68.3±3.4 years). Compared with healthy individuals, AMD patients exhibited higher mean connectivity within the reference links and within the default mode network, possibly reflecting compensatory changes to support performance in the setting of reduced vision. These findings are consistent with the hypothesis that phonemic fluency deficits in AMD reflect underlying brain changes that develop in the context of AMD.
  • 14.

    【2hr】Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands

    包量

    机译 多个频段出现静止的大脑区域之间的功能整合
    摘要：Studies of resting-state fMRI have shown that blood oxygen level dependent (BOLD) signals giving rise to temporal correlation across voxels (or regions) are dominated by low-frequency fluctuations in the range of ∼0.01–0.1 Hz. These low-frequency fluctuations have been further divided into multiple distinct frequency bands (slow-5 and -4) based on earlier neurophysiological studies, though low sampling frequency of fMRI (∼0.5 Hz) has substantially limited the exploration of other known frequency bands of neurophysiological origins (slow-3, -2, and -1). In this study, we used resting-state fMRI data acquired from 21 healthy subjects at a higher sampling frequency of 1.5 Hz to assess the presence of resting-state functional connectivity (RSFC) across multiple frequency bands: slow-5 to slow-1. The effect of different frequency bands on spatial extent and connectivity strength for known resting-state networks (RSNs) was also evaluated. RSNs were derived using independent component analysis and seed-based correlation. Commonly known RSNs, such as the default mode, the fronto-parietal, the dorsal attention, and the visual networks, were consistently observed at multiple frequency bands. Significant inter-hemispheric connectivity was observed between each seed and its contra lateral brain region across all frequency bands, though overall spatial extent of seed-based correlation maps decreased in slow-2 and slow-1 frequency bands. These results suggest that functional integration between brain regions at rest occurs over multiple frequency bands and RSFC is a multiband phenomenon. These results also suggest that further investigation of BOLD signal in multiple frequency bands for related cognitive processes should be undertaken.
  • 15.

    【2hr】Dynamic Repertoire of Intrinsic Brain States Is Reduced in Propofol-Induced Unconsciousness

    包量

    机译 丙泊酚引起的意识丧失内在脑状态的动态库。
    摘要：The richness of conscious experience is thought to scale with the size of the repertoire of causal brain states, and it may be diminished in anesthesia. We estimated the state repertoire from dynamic analysis of intrinsic functional brain networks in conscious sedated and unconscious anesthetized rats. Functional resonance images were obtained from 30-min whole-brain resting-state blood oxygen level-dependent (BOLD) signals at propofol infusion rates of 20 and 40 mg/kg/h, intravenously. Dynamic brain networks were defined at the voxel level by sliding window analysis of regional homogeneity (ReHo) or coincident threshold crossings (CTC) of the BOLD signal acquired in nine sagittal slices. The state repertoire was characterized by the temporal variance of the number of voxels with significant ReHo or positive CTC. From low to high propofol dose, the temporal variances of ReHo and CTC were reduced by 78%±20% and 76%±20%, respectively. Both baseline and propofol-induced reduction of CTC temporal variance increased from lateral to medial position. Group analysis showed a 20% reduction in the number of unique states at the higher propofol dose. Analysis of temporal variance in 12 anatomically defined regions of interest predicted that the largest changes occurred in visual cortex, parietal cortex, and caudate-putamen. The results suggest that the repertoire of large-scale brain states derived from the spatiotemporal dynamics of intrinsic networks is substantially reduced at an anesthetic dose associated with loss of consciousness.
  • 16.

    【2hr】Dynamic Connectivity at Rest Predicts Attention Task Performance

    包量

    机译 静态动态连接预测注意力任务的表现
    摘要：Consistent spatial patterns of coherent activity, representing large-scale networks, have been reliably identified in multiple populations. Most often, these studies have examined “stationary” connectivity. However, there is a growing recognition that there is a wealth of information in the time-varying dynamics of networks which has neural underpinnings, which changes with age and disease and that supports behavior. Using factor analysis of overlapping sliding windows across 25 participants with Parkinson disease (PD) and 21 controls (ages 41–86), we identify factors describing the covarying correlations of regions (dynamic connectivity) within attention networks and the default mode network, during two baseline resting-state and task runs. Cortical regions that support attention networks are affected early in PD, motivating the potential utility of dynamic connectivity as a sensitive way to characterize physiological disruption to these networks. We show that measures of dynamic connectivity are more reliable than comparable measures of stationary connectivity. Factors in the dorsal attention network (DAN) and fronto-parietal task control network, obtained at rest, are consistently related to the alerting and orienting reaction time effects in the subsequent Attention Network Task. In addition, the same relationship between the same DAN factor and the alerting effect was present during tasks. Although reliable, dynamic connectivity was not invariant, and changes between factor scores across sessions were related to changes in accuracy. In summary, patterns of time-varying correlations among nodes in an intrinsic network have a stability that has functional relevance.
  • 17.

    【2hr】DynamicBC: A MATLAB Toolbox for Dynamic Brain Connectome Analysis

    包量

    机译 DynamicBC：用于动态大脑Connectome分析的MATLAB工具箱
    摘要：The brain connectome collects the complex network architectures, looking at both static and dynamic functional connectivity. The former normally requires stationary signals and connections. However, the human brain activity and connections are most likely time dependent and dynamic, and related to ongoing rhythmic activity. We developed an open-source MATLAB toolbox DynamicBC with user-friendly graphical user interfaces, implementing both dynamic functional and effective connectivity for tracking brain dynamics from functional MRI. We provided two strategies for dynamic analysis: (1) the commonly utilized sliding-window analysis and (2) the flexible least squares based time-varying parameter regression strategy. The toolbox also implements multiple functional measures including seed-to-voxel analysis, region of interest (ROI)-to-ROI analysis, and voxel-to-voxel analysis. We describe the principles of the implemented algorithms, and then present representative results from simulations and empirical data applications. We believe that this toolbox will help neuroscientists and neurologists to easily map dynamic brain connectomics.
  • 18.

    【2hr】The Neural Basis of Time-Varying Resting-State Functional Connectivity

    包量

    机译 时变静止状态功能连通性的神经基础
    摘要：Dynamic network analysis based on resting-state magnetic resonance imaging (rsMRI) is a fairly new and potentially powerful tool for neuroscience and clinical research. Dynamic analysis can be sensitive to changes that occur in psychiatric or neurologic disorders and can detect variations related to performance on individual trials in healthy subjects. However, the appearance of time-varying connectivity can also arise in signals that share no temporal information, complicating the interpretation of dynamic functional connectivity studies. Researchers have begun utilizing simultaneous imaging and electrophysiological recording to elucidate the neural basis of the networks and their variability in animals and in humans. In this article, we review findings that link changes in electrically recorded brain states to changes in the networks obtained with rsMRI and discuss some of the challenges inherent in interpretation of these studies. The literature suggests that multiple brain processes may contribute to the dynamics observed, and we speculate that it may be possible to separate particular aspects of the rsMRI signal to enhance sensitivity to certain types of neural activity, providing new tools for basic neuroscience and clinical research.
  • 19.

    【2hr】Intrinsic Coupling Modes in Source-Reconstructed Electroencephalography

    包量

    机译 源重构脑电图的内在耦合模式。
    摘要：Intrinsic coupling of neuronal assemblies constitutes a key feature of ongoing brain activity, yielding the rich spatiotemporal patterns observed in neuroimaging data and putatively supporting cognitive processes. Intrinsic coupling has been investigated in electrophysiological recordings using two types of functional connectivity measures: amplitude and phase coupling. These two coupling modes differ in their likely causes and functions, and have been proposed to provide complementary insights into intrinsic neuronal interactions. Here, we investigate the relationship between amplitude and phase coupling in source-reconstructed electroencephalography (EEG). Volume conduction is a key obstacle for connectivity analysis in EEG—we therefore also test the envelope correlation of orthogonalized signals and the phase lag index. Functional connectivity between six seed source regions (bilateral visual, sensorimotor, and auditory cortices) and all other cortical voxels was computed. For all four measures, coupling between homologous sensory areas in both hemispheres was significantly higher than with other voxels at the same physical distance. The frequency of significant coupling differed between sensory areas: 10 Hz for visual, 30 Hz for auditory, and 40 Hz for sensorimotor cortices. By contrasting envelope correlations and phase locking values, we observed two distinct clusters of voxels showing a different relationship between amplitude and phase coupling. Large clusters contiguous to the seed regions showed an identity (1:1) relationship between amplitude and phase coupling, whereas a cluster located around the contralateral homologous regions showed higher phase than amplitude coupling. These results show a relationship between intrinsic coupling modes that is distinct from the effect of volume conduction.
  • 20.

    【2hr】Quantification of the Statistical Effects of Spatiotemporal Processing of Nontask fMRI Data

    包量

    机译 非任务fMRI数据的时空处理的统计效果的量化
    摘要：Nontask functional magnetic resonance imaging (fMRI) has become one of the most popular noninvasive areas of brain mapping research for neuroscientists. In nontask fMRI, various sources of “noise” corrupt the measured blood oxygenation level-dependent signal. Many studies have aimed to attenuate the noise in reconstructed voxel measurements through spatial and temporal processing operations. While these solutions make the data more “appealing,” many commonly used processing operations induce artificial correlations in the acquired data. As such, it becomes increasingly more difficult to derive the true underlying covariance structure once the data have been processed. As the goal of nontask fMRI studies is to determine, utilize, and analyze the true covariance structure of acquired data, such processing can lead to inaccurate and misleading conclusions drawn from the data if they are unaccounted for in the final connectivity analysis. In this article, we develop a framework that represents the spatiotemporal processing and reconstruction operations as linear operators, providing a means of precisely quantifying the correlations induced or modified by such processing rather than by performing lengthy Monte Carlo simulations. A framework of this kind allows one to appropriately model the statistical properties of the processed data, optimize the data processing pipeline, characterize excessive processing, and draw more accurate functional connectivity conclusions.
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