Search

The human brain is organized as segregation and integration units and follows complex developmental trajectories throughout life. The cortical manifold provides a new means of studying the brain's organization in a multidimensional connectivity gradient space. However, how the brain's morphometric organization changes across the human lifespan remains unclear. Here, leveraging structural magnetic resonance imaging scans from 1,790 healthy individuals aged 8 to 89 years, we investigated age-related global, within- and between-network dispersions to reveal the segregation and integration of brain networks from 3D manifolds based on morphometric similarity network (MSN), combining multiple features conceptualized as a "fingerprint" of an individual's brain. Developmental trajectories of global dispersion unfolded along patterns of molecular brain organization, such as acetylcholine receptor. Communities were increasingly dispersed with age, reflecting more disassortative morphometric similarity profiles within a community. Increasing within-network dispersion of primary motor and association cortices mediated the influence of age on the cognitive flexibility of executive functions. We also found that the secondary sensory cortices were decreasingly dispersed with the rest of the cortices during aging, possibly indicating a shift of secondary sensory cortices across the human lifespan from an extreme to a more central position in 3D manifolds. Together, our results reveal the age-related segregation and integration of MSN from the perspective of a multidimensional gradient space, providing new insights into lifespan changes in multiple morphometric features of the brain, as well as the influence of such changes on cognitive performance., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Radiologists have difficulty distinguishing benign from malignant bone lesions because these lesions may have similar imaging appearances. The purpose of this study was to develop a deep learning algorithm that can differentiate benign and malignant bone lesions using routine magnetic resonance imaging (MRI) and patient demographics., Methods: 1,060 histologically confirmed bone lesions with T1- and T2-weighted pre-operative MRI were retrospectively identified and included, with lesions from 4 institutions used for model development and internal validation, and data from a fifth institution used for external validation. Image-based models were generated using the EfficientNet-B0 architecture and a logistic regression model was trained using patient age, sex, and lesion location. A voting ensemble was created as the final model. The performance of the model was compared to classification performance by radiology experts., Findings: The cohort had a mean age of 30±23 years and was 58.3% male, with 582 benign lesions and 478 malignant. Compared to a contrived expert committee result, the ensemble deep learning model achieved (ensemble vs. experts): similar accuracy (0·76 vs. 0·73, p=0·7), sensitivity (0·79 vs. 0·81, p=1·0) and specificity (0·75 vs. 0·66, p=0·48), with a ROC AUC of 0·82. On external testing, the model achieved ROC AUC of 0·79., Interpretation: Deep learning can be used to distinguish benign and malignant bone lesions on par with experts. These findings could aid in the development of computer-aided diagnostic tools to reduce unnecessary referrals to specialized centers from community clinics and limit unnecessary biopsies., Funding: This work was funded by a Radiological Society of North America Research Medical Student Grant (#RMS2013) and supported by the Amazon Web Services Diagnostic Development Initiative., Competing Interests: Declaration of Competing Interest The authors have nothing to disclose., (Copyright © 2021. Published by Elsevier B.V.)

Epilepsy is a common brain network disorder associated with disrupted large-scale excitatory and inhibitory neural interactions. Recent resting-state fMRI evidence indicates that global signal (GS) fluctuations that have commonly been ignored are linked to neural activity. However, the mechanisms underlying the altered global pattern of fMRI spontaneous fluctuations in epilepsy remain unclear. Here, we quantified GS topography using beta weights obtained from a multiple regression model in a large group of epilepsy with different subtypes (98 focal temporal epilepsy; 116 generalized epilepsy) and healthy population (n = 151). We revealed that the nonuniformly distributed GS topography across association and sensory areas in healthy controls was significantly shifted in patients. Particularly, such shifts of GS topography disturbances were more widespread and bilaterally distributed in the midbrain, cerebellum, visual cortex, and medial and orbital cortex in generalized epilepsy, whereas in focal temporal epilepsy, these networks spread beyond the temporal areas but mainly remain lateralized. Moreover, we found that these abnormal GS topography patterns were likely to evolve over the course of a longer epilepsy disease. Our study demonstrates that epileptic processes can potentially affect global excitation/inhibition balance and shift the normal GS topological distribution. These progressive topographical GS disturbances in subcortical-cortical networks may underlie pathophysiological mechanisms of global fluctuations in human epilepsy., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The amplitude of low-frequency fluctuation (ALFF) measures resting-state functional magnetic resonance imaging (RS-fMRI) signal of each voxel. However, the unit of blood oxygenation level-dependent (BOLD) signal is arbitrary and hence ALFF is sensitive to the scale of raw signal. A well-accepted standardization procedure is to divide each voxel's ALFF by the global mean ALFF, named mALFF. Although fractional ALFF (fALFF), a ratio of the ALFF to the total amplitude within the full frequency band, offers possible solution of the standardization, it actually mixes with the fluctuation power within the full frequency band and thus cannot reveal the true amplitude characteristics of a given frequency band. The current study borrowed the percent signal change in task fMRI studies and proposed percent amplitude of fluctuation (PerAF) for RS-fMRI. We firstly applied PerAF and mPerAF (i.e., divided by global mean PerAF) to eyes open (EO) vs. eyes closed (EC) RS-fMRI data. PerAF and mPerAF yielded prominently difference between EO and EC, being well consistent with previous studies. We secondly performed test-retest reliability analysis and found that (PerAF ≈ mPerAF ≈ mALFF) > (fALFF ≈ mfALFF). Head motion regression (Friston-24) increased the reliability of PerAF, but decreased all other metrics (e.g. mPerAF, mALFF, fALFF, and mfALFF). The above results suggest that mPerAF is a valid, more reliable, more straightforward, and hence a promising metric for voxel-level RS-fMRI studies. Future study could use both PerAF and mPerAF metrics. For prompting future application of PerAF, we implemented PerAF in a new version of REST package named RESTplus., Competing Interests: NO authors have competing interests.

Intrinsic neural activity ubiquitously persists in all physiological states. However, how intrinsic brain activity (iBA) changes over a short time remains unknown. To uncover the brain dynamics' theoretic underpinning, electrophysiological relevance, and neuromodulation, we identified iBA dynamics on simulated data, electroencephalogram-functional magnetic resonance imaging (EEG-fMRI) data, and repetitive transcranial magnetic stimulation (rTMS) fMRI data using sliding-window analysis. The temporal variability (dynamics) of iBA were quantified using the variance of the amplitude of low-frequency fluctuations (ALFF) over time. We first used simulated fMRI data to examine the effects of various parameters including window length, and step size on dynamic ALFF. Second, using EEG-fMRI data, we found that the heteromodal association cortex had the most variable dynamics while the limbic regions had the least, consistent with previous findings. In addition, the temporal variability of dynamic ALFF depended on EEG power fluctuations. Moreover, using rTMS fMRI data, we found that the temporal variability of dynamic ALFF could be modulated by rTMS. Taken together, these results provide evidence about the theory, relevance, and adjustability of iBA dynamics.

A major challenge in neuroscience is understanding how brain function emerges from the connectome. Most current methods have focused on quantifying functional connectomes in gray-matter (GM) signals obtained from functional magnetic resonance imaging (fMRI), while signals from white-matter (WM) have generally been excluded as noise. In this study, we derived a functional connectome from WM resting-state blood-oxygen-level-dependent (BOLD)-fMRI signals from a large cohort (n = 488). The WM functional connectome exhibited weak small-world topology and nonrandom modularity. We also found a long-term (i.e., over 10 months) topological reliability, with topological reproducibility within different brain parcellation strategies, spatial distance effect, global and cerebrospinal fluid signals regression or not. Furthermore, the small-worldness was positively correlated with individuals' intelligence values (r = .17, p corrected = .0009). The current findings offer initial evidence using WM connectome and present additional measures by which to uncover WM functional information in both healthy individuals and in cases of clinical disease., (© 2019 Wiley Periodicals, Inc.)

Schizophrenia (SCZ) is a severe neuropsychiatric disease associated with dysfunction of brain regions and networks. Recent, functional magnetic resonance imaging (fMRI) studies have determined that the global signal (GS) is an important source of the local neuronal activity. However, the dynamics of this effect in SCZ remains unknown. To address this issue, 39 drug-naive patients with early-onset schizophrenia (EOS) and 31 age-, gender- and education-matched healthy controls underwent resting-state fMRI scans. Dynamic functional connectivity (DFC) was employed to assess the dynamic patterns of the GS in EOS. Dynamic analysis demonstrated that the topography of the GS in EOS can be divided into five different states. In the state1, the GS mainly affected the sensory regions. In the state2, the GS mainly affected the default mode network (DMN). In the state3, the GS mainly affected the frontoparietal network and the cingulate-opercular network. In the state4, the GS mainly affected the sensory and subcortical regions. In the state5, the GS mainly affected the sensory regions and DMN. In particular, the changes in the cerebellum, putamen and supramarginal gyrus was inversely proportional to the clinical symptoms. Our findings demonstrate that the influence of the GS on brain networks is dynamic and changes of this relationship may associate with clinical behavior in SCZ., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Objective: To predict the early identification of recurrence based on magnetic resonance imaging (MRI) in nasopharyngeal cancer (NPC) patients., Methods: The clinical and MRI data of 215 patients with local recurrent NPC were retrospectively reviewed. Logistic regression analysis was performed to distinguish the independent risk factors for the short-term (less than 24 months) local recurrence of NPC. The predictive score model was based on the regression coefficients of significant independent variables., Results: Residual disease in the nasopharyngeal cavity (NC), masticator space invasion (MSI), skull base bone erosion (SBBE), and MRI-detected cranial nerve invasion (MDCNI) were all significant independent risk factors for the short-term recurrence of NPC (p < 0.05). The receiver operating characteristic curve showed that the total score had a maximal AUC (area under the curve) value of 0.897, with a cutoff point of 10.50. The sensitivity and specificity were 79.4% and 80.5%, respectively., Conclusion: Residual lesions in NC, MSI, SBBE, and MDCNI are independent risk factors in predicting the short-term recurrence of NPC. The authors' findings suggest that patients with a score of more than 10.50 points should be hypervigilant regarding the possibility of short-term recurrence.

Objective To analyze the routine and functional magnetic resonance imaging(MRI) features and their potential pathological mechanisms of Hashimoto's encephalopathy(HE). Methods The clinical data and routine and functional MRI images of 30 HE patients who were treated in our center from January 2010 to April 2017 were retrospectively reviewed. Among them,15 patients were examined with contrast-enhanced MRI,16 with diffusion-weighed imaging(DWI),8 with magnetic resonance angiography,2 with magnetic resonance spectroscopy,and 1 with both arterial spin labeled perfusion imaging and diffusion tensor imaging. Seven patients had consecutive clinical and imaging data. The distribution,MRI signals,and functional MRI features of HE were analyzed. Results Among 30 HE patients,routine MRI showed negative results in 8 cases and abnormal findings in 22 cases. Among 22 abnormal cases,9 were characterized by small cerebral vascular disease and 13 had non-specific abnormalities;of these 13 cases,12 had lesions mainly located at the supratentorial white matter,11 had multiple lesions,and 2 had lesions complicated with cerebellum atrophy. The lesions were focal or confluent,punctate or small patchy,showing abnormal signal intensity with iso-or hypo-intensity on T1-weighed imaging,hyper-intensity on both T2-weighed imaging and fluid-attenuated inversion recovery. Most of the lesions had no enhancement(12/15). Among 7 cases with abnormalities on DWI,hyper-intensity on DWI and hypo-intensity on apparent diffusion coefficient were seen in 3 sudden acute cases and hyper-intensity on DWI and increased apparent diffusion coefficient value in 4 sub-acute or slow onset cases. Three cases showed localized intracranial artery stenosis. In 2 cases,magnetic resonance spectroscopy revealed significant lower N-acetylaspartate peak,higher choline peak,and visible lactate peak or lipid peak. Of 7 cases with follow-up data,3 cases had no change,4 cases had changes including softening lesions(2/4),remitted and relapsed lesions(1/4),and rapid progression of brain atrophy with negative finding on the initial MRI(1/4). Conclusion Routine MRI combined with functional imaging can show the features of HE from different perspectives. Routine MRI shows multifocal or confluent lesions in the white matter,mostly without enhancement,while functional imaging may reveal pathological characteristics of different phases of acute or chronic ischemia and demyelinating changes of HE. Combined with clinical data,MRI can differentiate HE from other diseases based on routine and functional MRI appearances.

Background: Paroxysmal kinesigenic dyskinesia is associated with macrostructural and microstructural abnormalities in the thalamus., Objectives: To examine functional and structural connectivity of thalamocortical networks in paroxysmal kinesigenic dyskinesia and to further investigate the effect of mutation of the proline-rich transmembrane protein 2 on thalamocortical networks., Methods: Patients with paroxysmal kinesigenic dyskinesia (n = 20), subdivided into proline-rich transmembrane protein 2-mutated (n = 8) and nonmutated patients (n = 12) and healthy controls (n = 20) underwent resting-state functional MRI and diffusion imaging scan. The functional properties of correlations in neural activity (functional connectivity) and the structural properties of white matter probabilistic tractography (structural connectivity) were analyzed to characterize thalamocortical networks. Furthermore, the effect of proline-rich transmembrane protein 2 mutation on functional and structural connectivity of thalamocortical networks were examined using one-way analysis of variance among three groups., Results: Patients had increased functional and structural connectivity between ventral lateral/anterior thalamic nuclei and a lateral motor area, as compared to controls. This functional connectivity positively correlated with disease duration. Interestingly, proline-rich transmembrane protein 2-mutated patients showed decreased functional connectivity and preserved structural connectivity, between mediodorsal nucleus and prefrontal cortex, compared to nonmutated patients and controls., Conclusions: Thalamomotor/premotor hyperconnectivity suggests abnormal communication between thalamus and motor cortex in patients. Furthermore, thalamoprefrontal hypoconnectivity in proline-rich transmembrane protein 2-mutated patients might indicate that proline-rich transmembrane protein 2 mutations result in inefficient thalamoprefrontal integration. Our findings facilitate a deeper understanding of the crucial role of thalamocortical dysconnectivity in the pathophysiological mechanisms of paroxysmal kinesigenic dyskinesia. © 2017 International Parkinson and Movement Disorder Society., (© 2017 International Parkinson and Movement Disorder Society.)

The tau hypothesis has been raised with regard to the pathophysiology of Alzheimer's disease (AD). Mild cognitive impairment (MCI) is associated with a high risk for developing AD. However, no study has directly examined the brain topological alterations based on combined effects of tau protein pathway genes in MCI population. Forty-three patients with MCI and 30 healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) in Chinese Han, and a tau protein pathway-based imaging approaches (7 candidate genes: 17 SNPs) were used to investigate changes in the topological organisation of brain activation associated with MCI. Impaired regional activation is related to tau protein pathway genes (5/7 candidate genes) in patients with MCI and likely in topologically convergent and divergent functional alterations patterns associated with genes, and combined effects of tau protein pathway genes disrupt the topological architecture of cortico-cerebellar loops. The associations between the loops and behaviours further suggest that tau protein pathway genes do play a significant role in non-episodic memory impairment. Tau pathway-based imaging approaches might strengthen the credibility in imaging genetic associations and generate pathway frameworks that might provide powerful new insights into the neural mechanisms that underlie MCI.

Recurrently and abnormally hypersynchronous discharge is a striking feature of idiopathic generalized epilepsy (IGE). Resting-state functional magnetic resonance imaging has revealed aberrant spontaneous brain synchronization, predominately in low-frequency range (<0.1 Hz), in individuals with IGE. Little is known, however, about these changes in local synchronization across different frequency bands. We examined alterations to frequency-specific local synchronization in terms of spontaneous blood oxygen level-dependent (BOLD) fluctuations across 5 bands, spanning 0 to 0.25 Hz. Specifically, we compared brain activity in a large cohort of IGE patients (n = 86) to age- and sex-matched normal controls (n = 86). IGE patients showed decreased local synchronization in low frequency (<0.073 Hz), primarily in the default mode network (DMN). IGE patients also exhibited increased local synchronization in high-frequency (>0.073 Hz) in a "conscious perception network," which is anchored by the pregenual and dorsal anterior cingulate cortex, as well as the bilateral insular cortices, possibly contributing to impaired consciousness. Furthermore, we found frequency-specific alternating local synchronization in the posterior portion of the DMN relative to the anterior part, suggesting an interaction between the disease and frequency bands. Importantly, the aberrant high-frequency local synchronization in the middle cingulate cortex was associated with disease duration, thus linking BOLD frequency changes to disease severity. These findings provide an overview of frequency-specific local synchronization of BOLD fluctuations, and may be helpful in uncovering abnormal synchronous neuronal activity in patients with IGE at specific frequency bands.

Amplitude and functional connectivity are two fundamental parameters for describing the spontaneous brain fluctuations. These two parameters present close coupling in physiological state, and present different alteration patterns in epilepsy revealed by functional MRI (fMRI). We hypothesized that the alteration of coupling between these two imaging parameters may be underpinned by specific pathological factors of epilepsy, and can be employed to improve the capability for epileptic focus detection. Forty-seven patients (26 left- and 21 right-sided) with mesial temporal lobe epilepsy (mTLE) and 32 healthy controls underwent resting-state fMRI scans. All patients were detected to have interictal epileptic discharges on simultaneous electroencephalograph (EEG) recordings. Amplitude-connectivity coupling was calculated by correlating amplitude and functional connectivity density of low-frequency brain fluctuations. We observed reduced amplitude-connectivity coupling associated with epileptic discharges in the mesial temporal regions in both groups of patients, and increased coupling associated with epilepsy durations in the posterior regions of the default-mode network in the right-sided patients. Moreover, we proposed a new index of amplitude subtracting connectivity, which elevated imaging contrast for differentiating the patients from the controls. The findings indicated that epileptic discharges and chronic damaging effect of epilepsy might both contribute to alterations of amplitude-connectivity coupling in different pivotal regions in mTLE. Investigation on imaging coupling provides synergistic approach for describing brain functional changing features in epilepsy., (© 2015 Wiley Periodicals, Inc.)

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 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.

Background: Spinocerebellar ataxia type 3 (SCA3) and Machado-Joseph disease (MJD) are similar diseases that are often referred to jointly as SCA3/MJD. As the most common autosomal-dominantly inherited subtype of hereditary spastic paraplegia (HSP), HSP4 (or SPG4) has overlapping symptoms with SCA3/MJD, which hinders their diagnoses. Arterial spin labeling (ASL) is a noninvasive, contrast-agent free, magnetic resonance perfusion imaging method used to obtain maps of the cerebral blood flow (CBF). Here, we investigated the diagnostic value of ASL in SCA3/MJD and SPG4 patients., Methods: A total of 13 SPG4 cases, 38 SCA3/MJD cases (22 onset patients and 16 genetic abnormality-only patients), and 27 healthy volunteers were examined by ASL. Data were processed to obtain the regional CBF (rCBF) and comparatively studied., Results: In the pons, cerebellar dentate nucleus, and cerebellar cortex, rCBF of the onset SCA3/MJD group was significantly lower than that of the normal control group. In the cerebellar dentate nucleus and cerebellar cortex, the rCBF of the non-onset SCA3/MJD group was significantly lower than that of the control group. In the pons and cerebellar cortex, the rCBF of the onset SCA3/MJD group was significantly lower than that of the SPG4 group., Conclusions: SCA3/MJD lesions are mainly located in the cerebellum and brainstem. Gray matter and white matter were both involved, although the deep cerebellar nuclei may be the earliest involved region. Cerebellar and brainstem lesions of SCA3/MJD were more severe than those of SPG4. ASL can aid the diagnosis of SCA3/MJD and SPG4., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background: EBV-encoded latent membrane protein 1 (EBV-LMP1) is an important oncogenic protein for nasopharyngeal carcinoma (NPC) and has been shown to engage a plethora of signaling pathways. Correspondingly, an LMP1-targeted DNAzyme was found to inhibit the growth of NPC cells both in vivo and in vitro by suppressing cell proliferation and inducing apoptosis. However, it remains unknown whether an LMP1-targeted DNAzyme would affect the vasculature of NPC. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been applied in the clinical trials of anti-angiogenic drugs for more than ten years, and Ktrans has been recommended as a primary endpoint. Therefore, the objective of the current study was to use DCE-MRI to longitudinally study the effect of an EBV-LMP1-targeted DNAzyme on the vasculature of patients with NPC., Methods: Twenty-four patients were randomly divided into two groups: a combined treatment group (radiotherapy + LMP1-targeted DNAzyme) and a radiotherapy alone group (radiotherapy + normal saline). DCE-MRI scans were conducted 1 ~ 2 days before radiotherapy (Pre-RT), during radiotherapy (RT 50 Gy), upon completion of radiotherapy (RT 70 Gy), and three months after radiotherapy (3 months post-RT). Parameters of vascular permeability and intra- and extravascular volumes were subsequently obtained (e.g., Ktrans, kep, ve) using nordicICE software., Results: Both Ktrans and kep values for NPC tumor tissues decreased for both groups after treatment. Moreover, a statistically significant difference in Ktrans values at the pre-therapy and post-therapy timepoints emerged earlier for the combined treatment group (RT 50 Gy, P =0.045) compared to the radiotherapy alone group (3 months post-RT, P = 0.032). For the kep values, the downward trend observed for both the combined treatment group and the radiotherapy alone group were similar. In contrast, ve values for all of the tumor tissues increased following therapy., Conclusions: The EBV-LMP1-targeted DNAzyme that was tested was found to accelerate the decline of Ktrans values for patients with NPC. Correspondingly, the LMP1-targeted DNAzyme treatments were found to affect the angiogenesis and microvascular permeability of NPC., Trial Registration: ClinicalTrials.gov: NCT01449942. Registered 6 October 2011.

Purpose: To characterize interhemispheric functional and anatomic connectivity in patients with idiopathic generalized epilepsy and generalized tonic-clonic seizures (GTCS)., Materials and Methods: This retrospective study was approved by the local institutional review board and was HIPAA compliant. All participants provided written informed consent. Resting-state functional and structural magnetic resonance images were acquired in 52 patients with GTCS and 65 healthy control subjects. The functional connectivity between bilateral homotopic voxels was calculated. Homotopic regions showing abnormal functional connectivity in patients were adopted as regions of interest for an analysis of diffusion-tensor imaging tractography. The fractional anisotropy and fiber length were compared between groups. Two-sample t test and nonparametric correlation analysis were used., Results: Compared with control subjects, patients showed increased interhemispheric functional connectivity between the bilateral cuneus (P = .0008, corrected) and anterior cingulate cortex (P = .0003, corrected) and decreased functional connectivity between the bilateral olfactory cortex (P = .00005, corrected), inferior frontal gyrus (P = .00005, corrected), supramarginal gyrus (P = .0002, corrected), and temporal pole (P = .0003, corrected). Furthermore, the fiber length of the commissural fiber bundles connecting the bilateral anterior cingulate cortex (t = -2.30; P = .03, uncorrected) and the bilateral cuneus was shorter in patients than in control subjects (t = -3.19; P = .002, uncorrected)., Conclusion: Our findings show that the bilateral anterior cingulate cortex may be critical to the pathophysiology of patients with GTCS and suggest that the corresponding commissural fiber bundle in the genu of the corpus callosum is a potential target for future surgical treatment in patients with intractable GTCS.

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.

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.

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.

A great improvement to the insight on brain function that we can get from fMRI data can come from effective connectivity analysis, in which the flow of information between even remote brain regions is inferred by the parameters of a predictive dynamical model. As opposed to biologically inspired models, some techniques as Granger causality (GC) are purely data-driven and rely on statistical prediction and temporal precedence. While powerful and widely applicable, this approach could suffer from two main limitations when applied to BOLD fMRI data: confounding effect of hemodynamic response function (HRF) and conditioning to a large number of variables in presence of short time series. For task-related fMRI, neural population dynamics can be captured by modeling signal dynamics with explicit exogenous inputs; for resting-state fMRI on the other hand, the absence of explicit inputs makes this task more difficult, unless relying on some specific prior physiological hypothesis. In order to overcome these issues and to allow a more general approach, here we present a simple and novel blind-deconvolution technique for BOLD-fMRI signal. In a recent study it has been proposed that relevant information in resting-state fMRI can be obtained by inspecting the discrete events resulting in relatively large amplitude BOLD signal peaks. Following this idea, we consider resting fMRI as 'spontaneous event-related', we individuate point processes corresponding to signal fluctuations with a given signature, extract a region-specific HRF and use it in deconvolution, after following an alignment procedure. Coming to the second limitation, a fully multivariate conditioning with short and noisy data leads to computational problems due to overfitting. Furthermore, conceptual issues arise in presence of redundancy. We thus apply partial conditioning to a limited subset of variables in the framework of information theory, as recently proposed. Mixing these two improvements we compare the differences between BOLD and deconvolved BOLD level effective networks and draw some conclusions., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Background: 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)., Methodology/principal Findings: Thirty five low-grade HE patients and thirty five age- and gender- matched healthy controls participated in the rs-fMRI scans. The effective connectivity networks associated with the globus pallidus, the primarily affected region within basal ganglia in HE, were characterized by using the Granger causality analysis and compared between HE patients and healthy controls. Pearson correlation analysis was performed between the abnormal effective connectivity and venous blood ammonia levels and neuropsychological performances of all HE patients. Compared with the healthy controls, patients with low-grade HE demonstrated mutually decreased influence between the globus pallidus and the anterior cingulate cortex (ACC), cuneus, bi-directionally increased influence between the globus pallidus and the precuneus, and either decreased or increased influence from and to the globus pallidus in many other frontal, temporal, parietal gyri, and cerebellum. Pearson correlation analyses revealed that the blood ammonia levels in HE patients negatively correlated with effective connectivity from the globus pallidus to ACC, and positively correlated with that from the globus pallidus to precuneus; and the number connectivity test scores in patients negatively correlated with the effective connectivity from the globus pallidus to ACC, and from superior frontal gyrus to globus pallidus., Conclusions/significance: Low-grade HE patients had disrupted effective connectivity network of basal ganglia. Our findings may help to understand the neurophysiological mechanisms underlying the HE.

Recent studies have demonstrated that ultra-high resolution MRA imaging using 7 Tessla (T) MRI can be employed to noninvasively visualize the lenticulostriate arteries (LSA) that supply the basal ganglia and internal capsule. Subcortical vascular dementia (SVaD) is believed to involve these regions from an early stage. We investigated whether LSA abnormalities measured by 7T MRA correlate with MRI ischemia markers and neuropsychological/motor deficits. A total of 24 subjects (12 with SVaD, 12 normal controls (NC)) were imaged with 3T and 7T MRIs. We assessed the severity of white matter hyperintensities (WMH) and the number of lacunes and microbleeds (MB) by visually inspecting images obtained from conventional 3T MRI. We also analyzed three-dimensional models of the measured LSAs obtained from 7T MRI. Compared to the NC, the SVaD subjects had fewer branches of LSAs and greater radii of LSAs. The number of branches was correlated with the number of lacunes. The number of branches was correlated with the delayed recall scores on Rey's Complex Figure Test (RCFT). While not quite reaching statistical significance, the immediate recall, recognition scores on the RCFT, recognition scores on the Seoul Verbal Learning Test, and the word and color readings of Stroop trended in the direction of correlation with the number of branches, as well as with the extrapyramidal scores. Our findings suggest that LSA imaging using 7T MRI might be a potent candidate for the detection of SVaD., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background: Small vessel diseases have been studied noninvasively with magnetic resonance imaging. Direct observation or visualization of the connected microvessel to the infarct, however, was not possible due to the limited resolution. Hence, one could not determine whether vessel occlusion or abnormal narrowing is the cause of an infarct., Methods: In this report, we demonstrate that the small vessel related to the infarct can be detected using ultra-high-field (7 T) magnetic resonance imaging and a three dimensional image analysis and modeling technique for microvessels, which thereby enables us to quantify the vessel morphology directly, that is, visualize the vessel that is related to the infarct. We compared vessels of selected stroke patients, who had recovered from stroke, with vessels from typical stroke patients, who had after effects like motor weakness, and age-matched healthy subjects to demonstrate the potential of the technique., Results: The experimental results show that typical stroke patients had overall degradation or loss of small vessels, compared with the selected patients as well as healthy subjects. The selected patients, however, had only minimal loss of vessels, except for one vessel located close to the infarct area., Conclusions: These preliminary results demonstrated that 7 T magnetic resonance imaging together with a three dimensional image analysis and modeling technique could provide information for detection of the vessel related to the infarct. In addition, three dimensional image analysis and modeling of vessels could further provide quantitative information on the microvessel structures comprising diameter, length and tortuosity., (© 2011 The Authors. International Journal of Stroke © 2011 World Stroke Organization.)

Background: 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., Methodology/principal Findings: Resting-state fMRI data were acquired in 47 cirrhotic patients (minimal HE [MHE], n = 20, and non-HE, n = 27) and 25 age-and sex-matched healthy controls. The Kendall's coefficient of concordance (KCC) was used to measure the regional homogeneity. The regional homogeneity maps were compared with ANOVA tests among MHE, non-HE, and healthy control groups and t-tests between each pair in a voxel-wise way. Correlation analyses were performed to explore the relationships between regional ReHo values and Child-Pugh scores, number connection test type A (NCT-A), digit symbol test (DST) scores, venous blood ammonia levels. Compared with healthy controls, both MHE and non-HE patients showed decreased ReHo in the bilateral frontal, parietal and temporal lobes and increased ReHo in the bilateral caudate. Compared with the non-HE, MHE patients showed decreased ReHo in the bilateral precuneus, cuneus and supplementary motor area (SMA). The NCT-A of cirrhotic patients negatively correlated with ReHo values in the precuneus, cuneus and lingual gyrus. DST scores positively correlated with ReHo values in the cuneus, precuneus and lingual gyrus, and negatively correlated with ReHo values in the bilateral caudate (P<0.05, AlphaSim corrected)., Conclusions/significance: Diffused abnormal homogeneity of baseline brain activity was nonspecific for MHE, and only the progressively decreased ReHo in the SMA and the cuneus, especially for the latter, might be associated with the development of MHE. The ReHo analysis may be potentially valuable for detecting the development from non-HE to MHE.

Clustering analysis is a promising data-driven method for analyzing functional magnetic resonance imaging (fMRI) time series data. The huge computational load, however, creates practical difficulties for this technique. We present a novel approach, integrating principal component analysis (PCA) and supervised affinity propagation clustering (SAPC). In this method, fMRI data are initially processed by PCA to obtain a preliminary image of brain activation. SAPC is then used to detect different brain functional activation patterns. We used a supervised Silhouette index to optimize clustering quality and automatically search for the optimal parameter p in SAPC, so that the basic affinity propagation clustering is improved by applying SAPC. Four simulation studies and tests with three in vivo fMRI datasets containing data from both block-design and event-related experiments revealed that functional brain activation was effectively detected and different response patterns were distinguished using our integrated method. In addition, the improved SAPC method was superior to the k -centers clustering and hierarchical clustering methods in both block-design and event-related fMRI data, as measured by the average squared error. These results suggest that our proposed novel integrated approach will be useful for detecting brain functional activation in both block-design and event-related experimental fMRI data.

There is an increasing body of evidence pointing to a relationship between personality and brain markers. The purpose of this study was to identify the associations between personality dimensions of extraversion and neuroticism and the local synchronization of spontaneous blood oxygen level-dependent (BOLD) activity assessed by regional homogeneity (ReHo) approach. Our results revealed the significant negative correlation between neuroticism and ReHo in the left middle frontal gyrus, providing evidence for the left frontal activation involved in pleasant emotion. ReHo was correlated negatively with extraversion in the medial prefrontal cortex (MPFC), an important portion of the default mode network (DMN), thus further indicating the relationship between DMN and personality. In addition, ReHo in the insula, cerebellum and cingulate gyrus was correlated positively with extraversion, suggesting the associations between individual difference in extraversion and specific brain regions involved in affective processing. These findings shed light on the important relationship between the synchronization of spontaneous fluctuations and personality dimensions of extraversion and neuroticism, which provide further evidence for the neural underpinning of individual difference in personality traits., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Dysfunction of the corticolimbic circuitry has been highlighted in social anxiety disorder (SAD) during social stimuli. However, few studies have investigated functional connectivity in SAD during the resting state, which may improve our understanding of SAD pathophysiology. The aim of this study was to investigate whether whole-brain functional connectivity might be aberrant in SAD patients, and if so, whether these changes are related to the measured clinical severity. Seventeen SAD patients and 19 healthy controls participated in resting-state functional magnetic resonance imaging. The brain was first divided into 90 paired brain regions and functional connectivity was then estimated by temporal correlation between each of these regions. Furthermore, connections that were significantly disrupted in SAD patients were correlated with clinical severity measured using the Liebowitz Social Anxiety Scale. Compared with healthy controls, SAD patients showed decreased positive connections within the frontal lobe and decreased negative connections between the frontal and occipital lobes. In particular, the weaker negative connections between the frontal lobe, which mainly involved the right median prefrontal cortex, and the occipital lobe had a significant positive correlation with the severity of SAD symptoms. The results support the hypothesis that some abnormalities of functional connectivity exist in SAD patients, which relate to the frontal cortex and occipital cortex. In addition, decreased functional connectivity between the frontal and occipital lobes and within the frontal lobe might be related to abnormal information processing and reflect disturbed neural organization resulting in defective social cognition, which could represent an early imaging biomarker for SAD., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Dysfunctional default mode network (DMN) has been observed in various mental disorders, including epilepsy (see review Broyd et al. [2009]: Neurosci Biobehav Rev 33:279–296). Because interictal epileptic discharges may affect DMN, resting-state fMRI was used in this study to determine DMN functional connectivity in 14 healthy controls and 12 absence epilepsy patients. To avoid interictal epileptic discharge effects, testing was performed within interictal durations when there were no interictal epileptic discharges. Cross-correlation functional connectivity analysis with seed at posterior cingulate cortex, as well as region-wise calculation in DMN, revealed decreased integration within DMN in the absence epilepsy patients. Region-wise functional connectivity among the frontal, parietal, and temporal lobe was significantly decreased in the patient group. Moreover, functional connectivity between the frontal and parietal lobe revealed a significant negative correlation with epilepsy duration. These findings indicated DMN abnormalities in patients with absence epilepsy, even during resting interictal durations without interictal epileptic discharges. Abnormal functional connectivity in absence epilepsy may reflect abnormal anatomo-functional architectural integration in DMN, as a result of cognitive mental impairment and unconsciousness during absence seizure., (Copyright © 2010 Wiley-Liss, Inc.)

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., (Copyright © 2010 Elsevier Inc. All rights reserved.)

The amygdala is often found to be abnormally recruited in social anxiety disorder (SAD) patients. The question whether amygdala activation is primarily abnormal and affects other brain systems or whether it responds "normally" to an abnormal pattern of information conveyed by other brain structures remained unanswered. To address this question, we investigated a network of effective connectivity associated with the amygdala using Granger causality analysis on resting-state functional MRI data of 22 SAD patients and 21 healthy controls (HC). Implications of abnormal effective connectivity and clinical severity were investigated using the Liebowitz Social Anxiety Scale (LSAS). Decreased influence from inferior temporal gyrus (ITG) to amygdala was found in SAD, while bidirectional influences between amygdala and visual cortices were increased compared to HCs. Clinical relevance of decreased effective connectivity from ITG to amygdala was suggested by a negative correlation of LSAS avoidance scores and the value of Granger causality. Our study is the first to reveal a network of abnormal effective connectivity of core structures in SAD. This is in support of a disregulation in predescribed modules involved in affect control. The amygdala is placed in a central position of dysfunction characterized both by decreased regulatory influence of orbitofrontal cortex and increased crosstalk with visual cortex. The model which is proposed based on our results lends neurobiological support towards cognitive models considering disinhibition and an attentional bias towards negative stimuli as a core feature of the disorder.

Various functional imaging tools have been used to detect epileptic activity in the neural network underlying mesial temporal lobe epilepsy (mTLE). In the present fMRI study, a data-driven approach was employed to map interictal epileptic activity in mTLE patients by measuring the amplitude of low-frequency fluctuation (ALFF) of the blood oxygen level-dependent (BOLD) signal. Twenty-four left mTLE patients and 26 right mTLE patients were investigated by comparing with 25 healthy subjects. In the patients, the regions showing increased ALFF were consistently distributed in the mesial temporal lobe, thalamus, and a few of other cortical and subcortical structures composing a mesial temporal epilepsy network proposed previously, while the regions showing decreased ALFF were mostly located in the areas of so-called default-mode network. Data of simultaneous EEG-fMRI from a portion of the patients suggested that the increases in ALFF might be associated with the interictal epileptic activity. Individual analyses based on statistic parametric mapping revealed a moderate sensitivity and a fairly high specificity for the lateralization of unilateral mTLE. We conclude that the ALFF analysis may provide a useful tool in fMRI study of epilepsy., (Copyright © 2010 Wiley-Liss, Inc.)

Several functional MRI (fMRI) activation studies have highlighted specific differences in brain response in social anxiety disorder (SAD) patients. Little is known, so far, about the changes in the functional architecture of resting state networks (RSNs) in SAD during resting state. We investigated statistical differences in RSNs on 20 SAD and 20 controls using independent component analysis. A diffuse impact on widely distributed RSNs and selective changes of RSN intrinsic functional connectivity were observed in SAD. Functional connectivity was decreased in the somato-motor (primary and motor cortices) and visual (primary visual cortex) networks, increased in a network including medial prefrontal cortex which is thought to be involved in self-referential processes, and increased or decreased in the default mode network (posterior cingulate cortex/precuneus, bilateral inferior parietal gyrus, angular gyrus, middle temporal gyrus, and superior and medial frontal gyrus) which has been suggested to be involved in episodic memory, and self-projection, the dorsal attention network (middle and superior occipital gyrus, inferior and superior parietal gyrus, and middle and superior frontal gyrus) which is thought to mediate goal-directed top-down processing, the core network (insula-cingulate cortices) which is associated with task control function, and the central-executive network (fronto-parietal cortices). A relationship between functional connectivity and disease severity was found in specific regions of RSNs, including medial and lateral prefrontal cortex, as well as parietal and occipital regions. Our results might supply a novel way to look into neuro-pathophysiological mechanisms in SAD patients., (Copyright 2010 Elsevier Inc. All rights reserved.)

Functional magnetic resonance imaging (fMRI) data-processing methods in the time domain include correlation analysis and the general linear model, among others. Virtually, many fMRI processing strategies utilise temporal information and ignore or pay little attention to phase information, resulting in an unnecessary loss of efficiency. We proposed a novel method named Hilbert phase entropy imaging (HPEI) that used the discrete Hilbert transform of the magnitude time series to detect brain functional activation. The data from two simulation studies and two in vivo fMRI studies that both contained block-design and event-related experiments revealed that the HPEI method enabled the effective detection of brain functional activation and the distinction of different response patterns. Our results demonstrate that this method is useful as a complementary analysis, but hypothesis-constrained, in revealing additional information regarding the complex nature of fMRI time series.

Functional MRI (fMRI) data-processing methods based on changes in the time domain involve, among other things, correlation analysis and use of the general linear model with statistical parametric mapping (SPM). Unlike conventional fMRI data analysis methods, which aim to model the blood-oxygen-level-dependent (BOLD) response of voxels as a function of time, the theory of power spectrum (PS) analysis focuses completely on understanding the dynamic energy change of interacting systems. We propose a new convolution PS (CPS) analysis of fMRI data, based on the theory of matched filtering, to detect brain functional activation for fMRI data. First, convolution signals are computed between the measured fMRI signals and the image signal of prior experimental pattern to suppress noise in the fMRI data. Then, the PS density analysis of the convolution signal is specified as the quantitative analysis energy index of BOLD signal change. The data from simulation studies and in vivo fMRI studies, including block-design experiments, reveal that the CPS method enables a more effective detection of some aspects of brain functional activation, as compared with the canonical PS SPM and the support vector machine methods. Our results demonstrate that the CPS method is useful as a complementary analysis in revealing brain functional information regarding the complex nature of fMRI time series.

Although it is accepted that linear Granger causality can reveal effective connectivity in functional magnetic resonance imaging (fMRI), the issue of detecting nonlinear connectivity has hitherto not been considered. In this paper, we address kernel Granger causality (KGC) to describe effective connectivity in simulation studies and real fMRI data of a motor imagery task. Based on the theory of reproducing kernel Hilbert spaces, KGC performs linear Granger causality in the feature space of suitable kernel functions, assuming an arbitrary degree of nonlinearity. Our results demonstrate that KGC captures effective couplings not revealed by the linear case. In addition, effective connectivity networks between the supplementary motor area (SMA) as the seed and other brain areas are obtained from KGC.

Objective: To investigate the value of conventional magnetic resonance imaging (MRI) and diffusion weighed imaging (DWI) in the differentiation of hypoxic-ischemic encephalopathy (HIE) and acute bilirubin encephalopathy in neonates., Methods: The MRI findings along with DWI characteristics in 15 neonates with HIE involving basal ganglia and in 18 neonates with acute bilirubin encephalopathy between November 2006 and June 2008 were retrospectively reviewed., Results: On T1WI, only 5 patients presented hyperintensity in the globus pallidus in the HIE group, but 16 in the acute bilirubin encephalopathy group (p<0.01). Nine patients in the HIE group showed hyperintensity in the putamen, but the hyperintensity in the putamen was not found in the acute bilirubin encephalopathy group. The frequency of hyperintensity in the subthalamus in the acute bilirubin encephalopathy group (55.6%) was significantly higher than that in the HIE group (13.3%) (p<0.05). Eight patients in the HIE group showed abnormal signals in the other regions on T1WI, but only two patients in the acute bilirubin encephalopathy group (p<0.05). On DWI, 7 out of 11 patients with HIE presented hyperintensity in the basal ganglia, while all 10 patients of the acute bilirubin encephalopathy group presented normal in the basal ganglia., Conclusions: Conventional MRI along with DWI is useful in differentiating HIE from acute bilirubin encephalopathy in neonates.

Purpose: To investigate the blood oxygenation level-dependent (BOLD) signal changes correlated with ictal and interictal epileptic discharges using electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) in patients with eyelid myoclonia with absences (EMA) and then to explore the pathophysiological mechanisms of epileptic discharges and their effect on brain function., Methods: Four patients with EMA were investigated through the method of EEG-fMRI. The characteristics of BOLD signal changes linked to ictal and interictal epileptic discharges under different states of consciousness were explored., Results: Seven sessions of EEG-fMRI scanning in the four patients were obtained. The main regions of activation included thalamus, mesial frontal cortex, middle parietal lobe, temporal lobe, insula, midline structures, and cerebellum. Deactivations were mainly in the anterior frontal lobe, posterior parietal lobe, and posterior cingulate gyrus. Thalamic BOLD change was predominantly activation in most of our cases. The distribution of activation associated with ictal epileptic discharges was wider, and the distribution of deactivation was closer to pericortex compared with the BOLD change linked with interictal epileptic discharges., Conclusions: The activation in the thalamus may be associated with generalized spike wave in EMA; the combination of different patterns of activation with consistent pattern of deactivations ("default" pattern) in patients with EMA may prognosticate different states of consciousness in response to ictal and interictal epileptic discharges.

The self-organizing mapping (SOM) and hierarchical clustering (HC) methods are integrated to detect brain functional activation; functional magnetic resonance imaging (fMRI) data are first processed by SOM to obtain a primary merged neural nodes image, and then by HC to obtain further brain activation patterns. The conventional Euclidean distance metric was replaced by the correlation distance metric in SOM to improve clustering and merging of neural nodes. To improve the use of spatial and temporal information in fMRI data, a new spatial distance (node coordinates in the 2-D lattice) and temporal correlation (correlation degree of each time course in the exemplar matrix) are introduced in HC to merge the primary SOM results. Two simulation studies and two in vivo fMRI data that both contained block-design and event-related experiments revealed that brain functional activation can be effectively detected and that different response patterns can be distinguished using these methods. Our results demonstrate that the improved SOM and HC methods are clearly superior to the statistical parametric mapping (SPM), independent component analysis (ICA), and conventional SOM methods in the block-design, especially in the event-related experiment, as revealed by their performance measured by receiver operating characteristic (ROC) analysis. Our results also suggest that the proposed new integrated approach could be useful in detecting block-design and event-related fMRI data.

Purpose: To investigate Blood Oxygen Level Dependent (BOLD) responses to interictal epileptic discharges (IEDs) during EEG-correlated functional MRI (EEG-fMRI) in patients with partial epilepsy., Methods: We studied eight patients who had a diagnosis of partial epilepsy and active spiking on routine scalp EEG recording. Sessions of continuous EEG-fMRI were recorded, and spikes (identified after online artifact removal) were used as events in the fMRI analysis. Regions of BOLD signal change in response to interictal epileptic discharge were assessed and epileptogenic zone localization was electroclinically identified., Results: Eight patients with partial epilepsy were recruited (6 males, 2 females, mean age 18.5, mean onset age range 0.5-29). Two who underwent EEG-fMRI were excluded from further analysis: one due to absence of epileptic discharges, the other due to excessive head motion. Eight sessions of EEG-fMRI scanning in 6 patients were obtained: 6 with activation and deactivation, one with activation only, and one with deactivation only. Focal activations corresponding to electroclinical localization occurred in 7 sessions, 5 of which were maximal., Conclusions: Maximally activated areas detected by EEG-fMRI in patients with partial epilepsy appear to be concordant with epileptogenic areas as defined by electroclinical localization data. In most patients with focal epilepsy, positive BOLD responses seem to be mainly in epileptogenic zones and the corresponding contralateral areas. Responses to deactivation seem less associated with IEDs. So EEG-fMRI is a useful tool to study the pathophysiological mechanisms of epilepsy and may assist in presurgical evaluation of epilepsy.

Using simultaneous EEG-correlated functional MRI (EEG-fMRI), we studied the blood oxygenation level-dependent (BOLD) signals in a juvenile myoclonic epilepsy (JME) patient with interictal epileptiform discharges. Extensive and symmetric activation and deactivation areas were assessed in bilateral hemispheric regions respectively, and these signals decreased gradually from the parieto-occipital region to the frontal region. Activations were found in cuneus, insulae, mesial midfrontal region, midline and bilateral cerebellum and thalamus, while the deactivities were in the bilateral anterior frontal region and parietal region as well as the posterior cingulate gyri. These findings suggest that the synchronized neuronal activities represented by spike and wave complex in EEG be reflected in the activation of BLOD signals in thalamocortical regions. However, those regions of deactivation reflect the suspension of the default state of brain function resulting indirectly from this discharge. There is good correspondence between neuronal activity (EEG) and fMRI. The combination of EEG and fMRI is a powerful tool in studying brain function.

Objective: To explore the correlation between microvascular density (MVD) and dynamic contrast-enhanced MRI in the glioma., Methods: We examined 35 patients with histologically verified glioma. Gadolinium-enhanced dynamic TurboFLASH imaging was performed preoperatively in all patients followed by conventional MRI. The steepest slope (SSmax) of curve and corresponding Tm1 in "first-pass" phase were obtained by analyzing time-signal curve. All specimens were immunostained with anti-human Factor VIII relative antigen monoclonal antibody postoperatively by streptavidin-peroxidase method to obtain the MVD. The correlation between SSmax, Tm1, and MVD was analyzed., Results: SSmax was positively correlated with MVD (r = 0.640, P < 0.01). Tml was negatively correlated with MVD (r = -0.671, P < 0.01)., Conclusion: The MVD correlates obviously with SSmax and Tml in the glioma. Analyzing the time-signal curve of dynamic contrast-enhanced MRI is helpful to predict the angiogenesis in the glioma.

Spinal meningeal melanocytoma is an extremely rare tumour with an estimated annual incidence of 1 per 10 million people. It usually arises from the intradural extramedullary compartment at the cervical levels. Although these tumours are histologically benign, they may behave aggressively. Local recurrence could occur even after total tumour excision. We report a case of a 33-year-old Asian male who developed progressive weakness and numbness of the bilateral lower extremities as well as urinary retention five years after complete tumour resection of lumbar spinal meningeal melanocytoma. Magnetic resonance imaging of the lumbar spine revealed a mass with thecal sac compression which was hypointense on T2-weighted images and hyperintense on T1-weighted images. The patient underwent total tumour removal. Histologic examination was compatible with recurrent meningeal melanocytoma. After a 4-week inpatient rehabilitation programme, he was able to ambulate without assistance and to do clean intermittent catheterisation for micturition on a regular basis. This is the first reported case of intradural extramedullary meningeal melanocytoma located at the lumbar region. Clinicians should consider the possibility of these rare tumours at any level of the spine, and be aware of sphincter dysfunction in addition to motor and sensory deficits of extremities. [ABSTRACT FROM AUTHOR]

Objective: Accurate preoperative localization of abnormal parathyroid glands is crucial for successful surgical management of secondary hyperparathyroidism (SHPT). This study was conducted to compare the effectiveness of preoperative MRI, 4D-CT, and ultrasonography (US) in localizing parathyroid lesions in patients with SHPT. Methods: We performed a retrospective review of prospectively collected data from a tertiary-care hospital and identified 52 patients who received preoperative MRI and/or 4D-CT and/or US and/or 99mTc-MIBI and subsequently underwent surgery for SHPT between May 2013 and March 2020. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each imaging modality to accurately detect enlarged parathyroid glands were determined using histopathology as the criterion standard with confirmation using the postoperative biochemical response. Results: A total of 198 lesions were identified intraoperatively among the 52 patients included in this investigation. MRI outperformed 4D-CT and US in terms of sensitivity (P < 0.01), specificity (P = 0.455), PPV (P = 0.753), and NPV (P = 0.185). The sensitivity and specificity for MRI, 4D-CT, and US were 90.91%, 88.95%, and 66.23% and 58.33%, 63.64%, and 50.00%, respectively. The PPV of combined MRI and 4D-CT (96.52%) was the highest among the combined 2 modalities. The smallest diameter of the parathyroid gland precisely localized by MRI was 8× 3 mm, 5× 5 mm by 4D-CT, and 5× 3 mm by US. Conclusion: MRI has superior diagnostic performance compared with other modalities as a first-line imaging study for patients undergoing renal hyperparathyroidism, especially for ectopic or small parathyroid lesions. We suggest performing US first for diagnosis and then MRI to make a precise localization, and MRI proved to be very helpful in achieving a high success rate in the surgical treatment of renal hyperparathyroidism in our own experience. [ABSTRACT FROM AUTHOR]

The atypical spindle cell/pleomorphic lipomatous tumor (ASPLT) was classified as a new tumor by the World Health Organization (WHO) in 2020. The tumor is benign and commonly occurs in the limbs. Paraspinal presentations are rare. A 38‐year‐old man presented at our clinic complaining of sudden onset back pain. No neurological deficit was found. The magnetic resonance imaging (MRI) revealed a well‐defined heterogeneous mass in the left psoas muscle, from L1 to L3 extending over the L1 and L2 neuroforamen. The tumor was totally excised. Pathology led to an ASPLT diagnosis. Clinical symptoms improved and there was no postsurgical neurological deficit. This case of ASPLT, located in an uncommon location and present an unusual cluster of symptoms, could be treated by surgical excision, usually the first‐treatment strategy. Totally, removal was achieved because there was a clear morphological margin. The risk of metastatic dissemination was minimal, though there remains a nonnegligible risk of local recurrence. [ABSTRACT FROM AUTHOR]

Schizophrenia is a complex and heterogeneous syndrome. Whether quantitative imaging biomarkers can identify discrete subgroups of patients as might be used to foster personalized medicine approaches for patient care remains unclear. Cross-sectional structural MR images of 163 never-treated first-episode schizophrenia patients (FES) and 133 chronically ill patients with midcourse schizophrenia from the Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium and a total of 403 healthy controls were recruited. Morphometric measures (cortical thickness, surface area, and subcortical structures) were extracted for each subject and then the optimized subtyping results were obtained with nonsupervised cluster analysis. Three subgroups of patients defined by distinct patterns of regional cortical and subcortical morphometric features were identified in FES. A similar three subgroup pattern was identified in the independent dataset of patients from the multi-site B-SNIP consortium. Similarities of classification patterns across these two patient cohorts suggest that the 3-group typology is relatively stable over the course of illness. Cognitive functions were worse in subgroup 1 with midcourse schizophrenia than those in subgroup 3. These findings provide novel insight into distinct subgroups of patients with schizophrenia based on structural brain features. Findings of different cognitive functions among the subgroups support clinical differences in the MRI-defined illness subtypes. Regardless of clinical presentation and stage of illness, anatomic MR subgrouping biomarkers can separate neurobiologically distinct subgroups of schizophrenia patients, which represent an important and meaningful step forward in differentiating subtypes of patients for studies of illness neurobiology and potentially for clinical trials. [ABSTRACT FROM AUTHOR]

Background: Postoperative peritumoral brain edema (PTBE) is the progressively exacerbating cerebral edema following meningiomas resection.Objective: The study aims to identify the predictive factors of postoperative PTBE.Materials and Methods: A retrospective study was conducted on the 117 cases of patients who underwent meningioma. The histopathological features of the tumors were re-assessed according to WHO 2016 classification. Clinical and pathohistological features were analyzed.Results: Thirteen patients (11.1%) were diagnosed having postoperative PTBE. Preoperative seizure (odds ratio [OR] = 6.125, P = 0.039) and histological prominent nucleoli (OR = 3.943, P = 0.039) were the independent risk factors for postoperative PTBE. Meningiomas with a parietal localization were more likely to develop postoperative PTBE (OR = 3.576, P = 0.054). Brain invasion and large tumor volume did not increase complication rate. Preoperative edema index was significantly higher in brain invasive meningiomas (3.0 ± 2.2 versus 1.8 ± 1.7, P = 0.001). Patients having moderate preoperative PTBE were prone to the complication (21.4% versus 7.9%, P = 0.100).Conclusions: Preoperative seizure were the predictive factors for postoperative PTBE. Careful venous protection during the operation may be helpful, especially for tumors locating in the parietal lobe. Prominent nucleoli observed in postoperative pathology should warrant surgeons' attention. Comprehensive perioperative management is essential for these patients. [ABSTRACT FROM AUTHOR]