Small-world organization is known to be a robust and consistent network architecture, and is a hallmark of the structurally and functionally connected human brain. However, it remains unknown if the same organization is present in directed influence brain networks whose connectivity is inferred by the transfer of information from one node to another. Here, we aimed to reveal the network architecture of the directed influence brain network using multivariate Granger causality analysis and graph theory on resting-state fMRI recordings. We found that some regions acted as pivotal hubs, either being influenced by or influencing other regions, and thus could be considered as information convergence regions. In addition, we observed that an exponentially truncated power law fits the topological distribution for the degree of total incoming and outgoing connectivity. Furthermore, we also found that this directed network has a modular structure. More importantly, according to our data, we suggest that the human brain directed influence network could have a prominent small-world topological property.

Brain activation during motor imagery has been studied extensively for years, but only a few of these studies focused on investigating the effective connectivity in the brain. The existence of interactions or closed loop circuits between the SMA and other brain regions during motor imagery still remains unclear. In the present study, selecting the SMA as the region of interest, we used the Granger causality mapping (GCM) method to explore the effective connectivity in the brain during motor imagery. Our results demonstrated that more brain regions showed effective connections to the SMA during the right-hand motor imagery than during the left-hand motor imagery, but the strength of the casual influence during the left-hand motor imagery was stronger than that of the right-hand motor imagery. We further found forward and backward effective connectivity between the SMA and three regions, including the bilateral dorsal premotor area (PMd), the contralateral primary and secondary somatosensory cortex (S1), and the primary motor cortex (M1). these results might indicate how the brain regions were inter-activated during motor imagery.

The basal ganglia often show abnormal metabolism and intracranial hemodynamics in cirrhotic patients with hepatic encephalopathy (HE). Little is known about how the basal ganglia affect other brain system and is affected by other brain regions in HE. The purpose of this study was to investigate whether the effective connectivity network associated with the basal ganglia is disturbed in HE patients by using resting-state functional magnetic resonance imaging (rs-fMRI).

A network approach to brain and dynamics opens new perspectives towards understanding of its function. The functional connectivity from functional MRI recordings in humans is widely explored at large scale, and recently also at the voxel level. The networks of dynamical directed connections are far less investigated, in particular at the voxel level. To reconstruct full brain effective connectivity network and study its topological organization, we present a novel approach to multivariate Granger causality which integrates information theory and the architecture of the dynamical network to efficiently select a limited number of variables. The proposed method aggregates conditional information sets according to community organization, allowing to perform Granger causality analysis avoiding redundancy and overfitting even for high-dimensional and short datasets, such as time series from individual voxels in fMRI. We for the first time depicted the voxel-wise hubs of incoming and outgoing information, called Granger causality density (GCD), as a complement to previous repertoire of functional and anatomical connectomes. Analogies with these networks have been presented in most part of default mode network; while differences suggested differences in the specific measure of centrality. Our findings could open the way to a new description of global organization and information influence of brain function. With this approach is thus feasible to study the architecture of directed networks at the voxel level and individuating hubs by investigation of degree, betweenness and clustering coefficient.

Resting-state functional magnetic resonance imaging (RS-fMRI) has been widely used to investigate temporally correlated fluctuations between distributed brain areas, as well as to characterize local synchronization of low frequency (<0.1 Hz) spontaneous fMRI signal. Regional homogeneity (ReHo) was proposed as a voxel-wise measure of the synchronization of the timecourses of neighboring voxels and has been used in many studies of brain disorders. However, the interpretation of ReHo remains challenging because the effect of high frequency task on ReHo is still not clear. In order to investigate the effect of a high-frequency task on the modulation of local synchronization of resting-state activity, we employed three right-finger movement scanning sessions: slow-event related ('Slow'), fast-event related ('Fast'), and continuous finger pressure ('Tonic'), from 21 healthy participants and compared the ReHo of the three task states with that of resting-state ('Rest'). In the contralateral sensorimotor cortex, 'Slow' task state showed greater ReHo than 'Rest' in low frequency band (0-0.08Hz) fMRI signal, but lower ReHo in high frequency band (0.08-1.67 Hz); 'Fast' task state showed lower ReHo than 'Rest' in both the low and high frequency band; 'Tonic' state did not show any significant difference compared to 'Rest'. The results in the contralateral sensorimotor cortex suggest that local synchronization of BOLD signal varies with different finger tapping speed. In the ipsilateral sensorimotor cortex, all the three task states had lower ReHo than the 'Rest' state both in the low and high frequency, suggesting a similar effect of fast and slow finger tapping frequencies on local synchronization of BOLD signal in the ipsilateral motor cortex.

Children with rolandic epilepsy (RE) are often associated with cognitive deficits and behavioral problems. Findings from neurophysiological and neuroimaging studies in RE have now demonstrated dysfunction not only in rolandic focus, but also in distant neuronal circuits. Little is known, however, about whether there is distributed abnormal spontaneous brain activity in RE. Using resting-state functional magnetic resonance imaging (RS-fMRI), the present study aimed to determine whether children with RE show abnormal local synchronization during resting state and, if so, whether these changes could be associated with the behavioral/clinical characteristics of RE. Regional homogeneity (ReHo) in children with RE (n = 30) and healthy children (n = 20) was computed on resting-state functional MRI data. In comparison with healthy children, children with RE showed increased ReHo in the central, premotor, and prefrontal regions, while they showed decreased ReHo in bilateral orbitofrontal cortex and temporal pole. In addition, the ReHo value in the left orbitofrontal cortex negatively was corrected with performance intelligence quotient in the children with RE. The aberrant local synchronization, not strictly related to primary site of the typical rolandic focus, indicates the neuropathophysiological mechanism of RE. The study findings may shed new light on the understanding of neural correlation of neuropsychological deficiencies in the children with RE.

We aimed to elucidate the dACC laterality in typically developing children and their sex/age-related differences with a sample of 84 right-handed children (6-16 years, 42 boys). We first replicated the previous finding observed in adults that gray matter density asymmetry in the dACC was region-specific: leftward (left > right) in its superior part, rightward (left < right) in its inferior part. Intrinsic connectivity analysis of these regions further revealed region-specific asymmetric connectivity profiles in dACC as well as their sex and age differences. Specifically, the superior dACC connectivity with frontoparietal network and the inferior dACC connectivity with visual network are rightward. The superior dACC connectivity with the default network (lateral temporal cortex) was more involved in the left hemisphere. In contrast, the inferior dACC connectivity with the default network (anterior medial prefrontal cortex) was more lateralized towards the right hemisphere. The superior dACC connectivity with lateral visual cortex was more distinct across two hemispheres in girls than that in boys. This connection in boys changed with age from right-prominent to left-prominent asymmetry whereas girls developed the connection from left-prominent to no asymmetry. These findings not only highlight the complexity and laterality of the dACC but also provided insights into dynamical structure-function relationships during the development.

Little is known about how spontaneous brain activity progresses from non-hepatic encephalopathy (non-HE) to minimal HE (MHE). The purpose of this study was to evaluate the evolution pattern of spontaneous brain activities in cirrhotic patients using resting-state fMRI with a regional homogeneity (ReHo) method.

Although mesial temporal lobe epilepsy (mTLE) is characterized by the pathological changes in mesial temporal lobe, function alteration was also found in extratemporal regions. Our aim is to investigate the information flow between the epileptogenic zone (EZ) and other brain regions. Resting-state functional magnetic resonance imaging (RS-fMRI) data were recorded from 23 patients with left mTLE and matched controls. We first identified the potential EZ using the amplitude of low-frequency fluctuation (ALFF) of RS-fMRI signal, then performed voxel-wise Granger causality analysis between EZ and the whole brain. Relative to controls, patients demonstrated decreased driving effect from EZ to thalamus and basal ganglia, and increased feedback. Additionally, we found an altered causal relation between EZ and cortical networks (default mode network, limbic system, visual network and executive control network). The influence from EZ to right precuneus and brainstem negatively correlated with disease duration, whereas that from the right hippocampus, fusiform cortex, and lentiform nucleus to EZ showed positive correlation. These findings demonstrate widespread brain regions showing abnormal functional interaction with EZ. In addition, increased ALFF in EZ was positively correlated with the increased driving effect on EZ in patients, but not in controls. This finding suggests that the initiation of epileptic activity depends not only on EZ itself, but also on the activity emerging in large-scale macroscopic brain networks. Overall, this study suggests that the causal topological organization is disrupted in mTLE, providing valuable information to understand the pathophysiology of this disorder.

Neuroimaging studies have uncovered the neural roots of individual differences in human general fluid intelligence (Gf). Gf is characterized by the function of specific neural circuits in brain gray-matter; however, the association between Gf and neural function in brain white-matter (WM) remains unclear. Given reliable detection of blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals in WM, we used a functional, rather than an anatomical, neuromarker in WM to identify individual Gf. We collected longitudinal BOLD-fMRI data (in total three times, ~11 months between time 1 and time 2, and ~29 months between time 1 and time 3) in normal volunteers at rest, and identified WM functional connectomes that predicted the individual Gf at time 1 (n = 326). From internal validation analyses, we demonstrated that the constructed predictive model at time 1 predicted an individual's Gf from WM functional connectomes at time 2 (time 1 ∩ time 2: n = 105) and further at time 3 (time 1 ∩ time 3: n = 83). From external validation analyses, we demonstrated that the predictive model from time 1 was generalized to unseen individuals from another center (n = 53). From anatomical aspects, WM functional connectivity showing high predictive power predominantly included the superior longitudinal fasciculus system, deep frontal WM, and ventral frontoparietal tracts. These results thus demonstrated that WM functional connectomes offer a novel applicable neuromarker of Gf and supplement the gray-matter connectomes to explore brain-behavior relationships.

Recent studies employing rapid sampling techniques have demonstrated that the resting state fMRI (rs-fMRI) signal exhibits synchronized activities at frequencies much higher than the conventional frequency range (<0.1 Hz). However, little work has investigated the changes in the high-frequency fluctuations between different resting states. Here, we acquired rs-fMRI data at a high sampling rate (TR = 400 ms) from subjects with both eyes open (EO) and eyes closed (EC), and compared the amplitude of fluctuation (AF) between EO and EC for both the low- and high-frequency components. In addition to robust AF differences in the conventional low frequency band (<0.1 Hz) in visual cortex, primary auditory cortex and primary sensorimotor cortex (PSMC), we also detected high-frequency (primarily in 0.1-0.35 Hz) differences. The high-frequency results without covariates regression exhibited noisy patterns. For the data with nuisance covariates regression, we found a significant and reproducible reduction in high-frequency AF between EO and EC in the bilateral PSMC and the supplementary motor area (SMA), and an increase in high-frequency AF in the left middle occipital gyrus (MOG). Furthermore, we investigated the effect of sampling rate by down-sampling the data to effective TR = 2 s. Briefly, by using the rapid sampling rate, we were able to detect more regions with significant differences while identifying fewer artifactual differences in the high-frequency bands as compared to the down-sampled dataset. We concluded that (1) high-frequency fluctuations of rs-fMRI signals can be modulated by different resting states and thus may be of physiological importance; and (2) the regression of covariates and the use of fast sampling rates are superior for revealing high-frequency differences in rs-fMRI signals.

Essential tremor (ET) is one of the most common movement disorders in human adults. It can be characterized as a progressive neurological disorder of which the most recognizable feature is a tremor of the arms or hands that is apparent during voluntary movements such as eating and writing. The pathology of ET remains unclear. Resting-state fMRI (RS-fMRI), as a non-invasive imaging technique, was employed to investigate abnormalities of functional connectivity in ET in the brain. Regional homogeneity (ReHo) was used as a metric of RS-fMRI to assess the local functional connectivity abnormality in ET with 20 ET patients and 20 age- and gender-matched healthy controls (HC). The ET group showed decreased ReHo in the anterior and posterior bilateral cerebellar lobes, the bilateral thalamus and the insular lobe, and increased ReHo in the bilateral prefrontal and parietal cortices, the left primary motor cortex and left supplementary motor area. The abnormal ReHo value of ET patients in the bilateral anterior cerebellar lobes and the right posterior cerebellar lobe were negatively correlated with the tremor severity score, while positively correlated with that in the left primary motor cortex. These findings suggest that the abnormality in cerebello-thalamo-cortical motor pathway is involved in tremor generation and propagation, which may be related to motor-related symptoms in ET patients. Meanwhile, the abnormality in the prefrontal and parietal regions may be associated with non-motor symptoms in ET. These findings suggest that the ReHo could be utilized for investigations of functional-pathological mechanism of ET.

The neurobiological basis of paroxysmal kinesigenic dyskinesia (PKD) is poorly defined due to the lack of reliable neuroimaging differences that can distinguish PKD with dystonia (PKD-D) from PKD with chorea (PKD-C). Consequently, diagnosis of PKD remains largely based on the clinical phenotype. Understanding the pathophysiology of PKD may facilitate discrimination between PKD-D and PKD-C, potentially contributing to more accurate diagnosis. We conducted resting-state functional magnetic resonance imaging on patients with PKD-D (n = 22), PKD-C (n = 10), and healthy controls (n = 32). Local synchronization was measured in all 3 groups via regional homogeneity (ReHo) and evaluated using receiver operator characteristic analysis to distinguish between PKD-C and PKD-D. Cortical-basal ganglia circuitry differed significantly between the 2 groups at a specific frequency. Furthermore, the PKD-D and PKD-C patients were observed to show different spontaneous brain activity in the right precuneus, right putamen, and right angular gyrus at the slow-5 frequency band (0.01-0.027 Hz). The frequency-specific abnormal local synchronization between the 2 types of PKD offers new insights into the pathophysiology of this disorder to some extent.

Cognitive performance relies on the coordination of large-scale networks of brain regions that are not only temporally correlated during different tasks, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual differences in cognitive performance. Therefore, we aimed to examine the influence of cognitive expertise on four networks associated with cognitive task performance: the default mode network (DMN) and three other cognitive networks (central-executive network, dorsal attention network, and salience network). During fMRI scanning, fifteen grandmaster and master level Chinese chess players (GM/M) and fifteen novice players carried out a Chinese chess task and a task-free resting state. Modulations of network activity during task were assessed, as well as resting-state functional connectivity of those networks. Relative to novices, GM/Ms showed a broader task-induced deactivation of DMN in the chess problem-solving task, and intrinsic functional connectivity of DMN was increased with a connectivity pattern associated with the caudate nucleus in GM/Ms. The three other cognitive networks did not exhibit any difference in task-evoked activation or intrinsic functional connectivity between the two groups. These findings demonstrate the effect of long-term learning and practice in cognitive expertise on large-scale brain networks, suggesting the important role of DMN deactivation in expert performance and enhanced functional integration of spontaneous activity within widely distributed DMN-caudate circuitry, which might better support high-level cognitive control of behavior.

Neuroimaging studies have revealed that the task-related functional brain activities are impaired in internet gaming disorder (IGD) subjects. However, little is known about the alternations in spontaneous brain activities about them. Recent studies have proposed that the brain activities of different frequency ranges are generated by different nervous activities and have different physiological and psychological functions. Thus, in this study, we set to explore the spontaneous brain activities in IGD subjects by measuring the fractional amplitude of low-frequency fluctuation (fALFF), to investigate band-specific changes of resting-state fALFF. We subdivided the frequency range into five bands based on literatures. Comparing to healthy controls, the IGD group showed decreased fALFF values in the cerebellum posterior lobe and increased fALFF values in superior temporal gyrus. Significant interactions between frequency bands and groups were found in the cerebellum, the anterior cingulate, the lingual gyrus, the middle temporal gyrus, and the middle frontal gyrus. Those brain regions are proved related to the executive function and decision-making. These results revealed the changed spontaneous brain activity of IGD, which contributed to understanding the underlying pathophysiology of IGD.

As the multi-center studies with resting-state functional magnetic resonance imaging (RS-fMRI) have been more and more applied to neuropsychiatric studies, both intra- and inter-scanner reliability of RS-fMRI are becoming increasingly important. The amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) are 3 main RS-fMRI metrics in a way of voxel-wise whole-brain (VWWB) analysis. Although the intra-scanner reliability (i.e., test-retest reliability) of these metrics has been widely investigated, few studies has investigated their inter-scanner reliability. In the current study, 21 healthy young subjects were enrolled and scanned with blood oxygenation level dependent (BOLD) RS-fMRI in 3 visits (V1 - V3), with V1 and V2 scanned on a GE MR750 scanner and V3 on a Siemens Prisma. RS-fMRI data were collected under two conditions, eyes open (EO) and eyes closed (EC), each lasting 8 minutes. We firstly evaluated the intra- and inter-scanner reliability of ALFF, ReHo, and DC. Secondly, we measured systematic difference between two scanning visits of the same scanner as well as between two scanners. Thirdly, to account for the potential difference of intra- and inter-scanner local magnetic field inhomogeneity, we measured the difference of relative BOLD signal intensity to the mean BOLD signal intensity of the whole brain between each pair of visits. Last, we used percent amplitude of fluctuation (PerAF) to correct the difference induced by relative BOLD signal intensity. The inter-scanner reliability was much worse than intra-scanner reliability; Among the VWWB metrics, DC showed the worst (both for intra-scanner and inter-scanner comparisons). PerAF showed similar intra-scanner reliability with ALFF and the best reliability among all the 4 metrics. PerAF reduced the influence of BOLD signal intensity and hence increase the inter-scanner reliability of ALFF. For multi-center studies, inter-scanner reliability should be taken into account.

Conventional functional magnetic resonance imaging (fMRI) studies on motor feedback employ periodical blocked paradigm which does not allow frequency analysis of brain activity. Here, we carried out an fMRI study by using a continuous paradigm, that is, continuous (8 min) feedback of finger force. Borrowing an analytic method widely used in resting-state fMRI studies, that is, regional homogeneity (ReHo), we compared the local synchronization in some subfrequency bands between real and sham feedback, and the subbands were defined as Slow-6 (0.0-0.01 Hz), Slow-5 (0.01-0.027 Hz), Slow-4 (0.027-0.073 Hz), Slow-3 (0.073-0.198 Hz), and Slow-2 (0.198-0.25 Hz). Our results revealed that the five subfrequency bands of brain activity contributed to the changes of ReHo between real and sham feedback differently, and, more importantly, the changes in basal ganglia were only manifested in Slow-6, implicating the fact that ReHo in ultraslow band may be associated with the functional significance of BG, that is, motor control. These findings provide novel insights into the neural substrate underlying motor feedback, and properties of the ultraslow band of local synchronization deserve more attention in future explorations.

The amplitude of low-frequency fluctuation (ALFF) measures low-frequency oscillations of the blood-oxygen-level-dependent signal, characterizing local spontaneous activity during the resting state. ALFF is a commonly used measure for resting-state functional magnetic resonance imaging (rs-fMRI) in numerous basic and clinical neuroscience studies. Using a test-retest rs-fMRI dataset consisting of 21 healthy subjects and three repetitive scans, we found that several key brain regions with high ALFF intensities (or magnitude) had poor reliability. Such regions included the posterior cingulate cortex, the medial prefrontal cortex in the default mode network, parts of the right and left thalami, and the primary visual and motor cortices. The above finding was robust with regard to different sample sizes (number of subjects), different scanning parameters (repetition time) and variations of test-retest intervals (i.e., intra-scan, intra-session, and inter-session reliability), as well as with different scanners. Moreover, the qualitative, map-wise results were validated further with a region-of-interest-based quantitative analysis using "canonical" coordinates as reported previously. Therefore, we suggest that the reliability assessments be incorporated in future ALFF studies, especially for the brain regions with a large ALFF magnitude as listed in our paper. Splitting single data into several segments and assessing within-scan "test-retest" reliability is an acceptable alternative if no "real" test-retest datasets are available. Such evaluations might become more necessary if the data are collected with clinical scanners whose performance is not as good as those that are used for scientific research purposes and are better maintained because the lower signal-to-noise ratio may further dampen ALFF reliability.

The superior capability of chess experts largely depends on quick automatic processing skills which are considered to be mediated by the caudate nucleus. We asked whether continued practice or rehearsal of the skill over a long period of time can lead to structural changes in this region. We found that, comparing to novice controls, grandmaster and master level Chinese chess players (GM/Ms), who had a mean period of over 10years of tournament and training practice, exhibited significant smaller gray-matter volume in the bilateral caudate nuclei. When these regions were used as seeds in functional connectivity analysis in resting-state fMRI, significantly enhanced integration was found in GM/Ms between the caudate and the default mode network (DMN), a constellation of brain areas important for goal-directed cognitive performance and theory of mind. These findings demonstrate the structural changes in the caudate nucleus in response to its extensive engagement in chess problem solving, and its enhanced functional integration with widely distributed circuitry to better support high-level cognitive control of behavior.

Globus pallidus interna (GPi) is an effective deep brain stimulation site for the treatment of Tourette syndrome (TS), and plays a crucial role in the pathophysiology of TS. To investigate the functional network feature of GPi in TS patients, we retrospectively studied 24 boys with 'pure' TS and 32 age-/education-matched healthy boys by resting state functional magnetic resonance images. Amplitude of low-frequency fluctuation (ALFF) and functional connectivity were used to estimate the local activity in GPi and its functional coordinate with the whole brain regions, respectively. We found decreased ALFF in patients' bilateral GPi, which was also negatively correlated with clinical symptoms. Functional connectivity analysis indicated abnormal regions within motor and motor-control networks in patients (inferior part of sensorimotor area, cerebellum, prefrontal cortex, cingulate gyrus, caudate nucleus, and brain stem). Transcranial magnetic stimulation sites defined by previous studies ("hand knob" area, premotor area, and supplementary motor area) did not show significantly different functional connectivity with GPi between groups. In summary, this study characterized the disrupted functional network of GPi and provided potential regions-of-interest for further basic and clinical studies on TS.