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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.)

Endo-microscopy is crucial for real-time 3D visualization of internal tissues and subcellular structures. Conventional methods rely on axial movement of optical components for precise focus adjustment, limiting miniaturization and complicating procedures. Meta-device, composed of artificial nanostructures, is an emerging optical flat device that can freely manipulate the phase and amplitude of light. Here, an intelligent fluorescence endo-microscope is developed based on varifocal meta-lens and deep learning (DL). The breakthrough enables in vivo 3D imaging of mouse brains, where varifocal meta-lens focal length adjusts through relative rotation angle. The system offers key advantages such as invariant magnification, a large field-of-view, and optical sectioning at a maximum focal length tuning range of ≈2 mm with 3 µm lateral resolution. Using a DL network, image acquisition time and system complexity are significantly reduced, and in vivo high-resolution brain images of detailed vessels and surrounding perivascular space are clearly observed within 0.1 s (≈50 times faster). The approach will benefit various surgical procedures, such as gastrointestinal biopsies, neural imaging, brain surgery, etc., (© 2024 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

Much recent attention has been directed toward investigating the spatial and temporal organization of brain dynamics, but the rules which constrain the variation of spatio-temporal organization in functional connectivity under different brain states remain unclear. Here, we developed a novel computational approach based on tensor decomposition and regularization to represent dynamic functional connectivity as a linear combination of dynamic modules and time-varying weights. In this approach, dynamic modules represent co-activating functional connectivity patterns, and time-varying weights represent the temporal expression of dynamic modules. We applied this dynamic decomposition model (DDM) on a resting-state fMRI dataset and found that whole-brain dynamic functional connectivity can be decomposed as a linear combination of eight dynamic modules which we summarize as 'high order modules' and 'primary-high order modules', according to their spatial attributes and correspondence with existing intrinsic functional brain networks. By clustering the time-varying weights, we identified five brain states including three major states and two minor states. We found that state transitions mainly occurred between the three major states, and that temporal variation of dynamic modules may contribute to brain state transitions. We then conceptualized the variability of weights as the flexibility of the corresponding dynamic modules and found that different dynamic modules exhibit different amounts of flexibility and contribute to different cognitive measures. Finally, we applied DDM to a schizophrenia resting-state fMRI dataset and found that atypical flexibility of dynamic modules correlates with impaired cognitive flexibility in schizophrenia. Overall, this work provides a quantitative framework that characterizes temporal variation in the topology of dynamic functional connectivity., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Marital attachment plays an important role in maintaining intimate personal relationships and sustaining psychological well-being. Mate-selection theories suggest that people are more likely to marry someone with a similar personality and social status, yet evidence for the association between personality-based couple similarity measures and marital satisfaction has been inconsistent. A more direct and useful approach for understanding fundamental processes underlying marital satisfaction is to probe similarity of dynamic brain responses to maritally and socially relevant communicative cues, which may better reflect how married couples process information in real time and make sense of their mates and themselves. Here, we investigate shared neural representations based on intersubject synchronization (ISS) of brain responses during free viewing of marital life-related, and nonmarital, object-related movies. Compared to randomly selected pairs of couples, married couples showed significantly higher levels of ISS during viewing of marital movies and ISS between married couples predicted higher levels of marital satisfaction. ISS in the default mode network emerged as a strong predictor of marital satisfaction and canonical correlation analysis revealed a specific relation between ISS in this network and shared communication and egalitarian components of martial satisfaction. Our findings demonstrate that brain similarities that reflect real-time mental responses to subjective perceptions, thoughts, and feelings about interpersonal and social interactions are strong predictors of marital satisfaction, reflecting shared values and beliefs. Our study advances foundational knowledge of the neurobiological basis of human pair bonding.

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Accumulating evidence has shown transcranial low-intensity ultrasound can be potentially a non-invasive neural modulation tool to treat brain diseases. However, the underlying mechanism remains elusive and the majority of studies on animal models applying rather high-intensity ultrasound that cannot be safely used in humans. Here, we showed low-intensity ultrasound was able to activate neurons in the mouse brain and repeated ultrasound stimulation resulted in adult neurogenesis in specific brain regions. In vitro calcium imaging studies showed that a specific ultrasound stimulation mode, which combined with both ultrasound-induced pressure and acoustic streaming mechanotransduction, is required to activate cultured cortical neurons. ASIC1a and cytoskeletal proteins were involved in the low-intensity ultrasound-mediated mechanotransduction and cultured neuron activation, which was inhibited by ASIC1a blockade and cytoskeleton-modified agents. In contrast, the inhibition of mechanical-sensitive channels involved in bilayer-model mechanotransduction like Piezo or TRP proteins did not repress the ultrasound-mediated neuronal activation as efficiently. The ASIC1a-mediated ultrasound effects in mouse brain such as immediate response of ERK phosphorylation and DCX marked neurogenesis were statistically significantly compromised by ASIC1a gene deletion. Collated data suggest that ASIC1a is the molecular determinant involved in the mechano-signaling of low-intensity ultrasound that modulates neural activation in mouse brain., Competing Interests: JL, HT, WL, YC, CH, YH, CL, SL, SH, YC, DL, WC, CC, JW No competing interests declared, (© 2021, Lim et al.)

Major depressive disorder (MDD) has been shown to be associated with structural abnormalities in a variety of spatially diverse brain regions. However, the correlation between brain structural changes in MDD and gene expression is unclear. Here, we examine the link between brain-wide gene expression and morphometric changes in individuals with MDD, using neuroimaging data from two independent cohorts and a publicly available transcriptomic dataset. Morphometric similarity network (MSN) analysis shows replicable cortical structural differences in individuals with MDD compared to control subjects. Using human brain gene expression data, we observe that the expression of MDD-associated genes spatially correlates with MSN differences. Analysis of cell type-specific signature genes suggests that microglia and neuronal specific transcriptional changes account for most of the observed correlation with MDD-specific MSN differences. Collectively, our findings link molecular and structural changes relevant for MDD.

Radiation encephalopathy (RE) is a common complication in patients with nasopharyngeal carcinoma (NPC) who have received radiotherapy (RT), and recent neuroimaging studies have shown brain alterations in Post-RT patients prior to RE. However, whether there are functional alterations between those Post-RT patients who are proved to have RE in follow-up and those who do not develop it remains largely unknown. Here, we used resting state functional MRI to explore regional homogeneity (ReHo) and functional connectivity (FC) alterations in Post-RT patients with (Post-RT RE proved ; n = 18) or without (Post-RT non-RE ; n = 22) RE at follow-up, also making comparisons with a Pre-RT group (n = 23). Compared with the Pre-RT group, patients in Post-RT non-RE and Post-RT RE proved groups showed concurrent increased and decreased ReHo values in different brain regions inside and/or outside the radiation field, with the alterations in ReHo tending to increase if RE occurred. Seed-based FC analysis showed that compared with the Post-RT non-RE group, patients in the Post-RT RE proved group had different changing patterns of FC between a region of interest (ROI) in the right temporal lobe and distant brain regions (mainly in the sensorimotor system and default mode network). Receiver operating characteristic (ROC) curve analysis showed that the altered ReHo value in the ROI had excellent diagnostic performance for differentiating NPC patients who developed RE in follow-up from those who did not, with an area under the curve (AUC) value of 0.94. These ReHo and FC findings may provide new insights into the early diagnosis of RE.

Accumulating neuroimaging evidence shows that age estimation obtained from brain connectomics reflects the level of brain maturation along with neural development. It is well known that autism spectrum disorder (ASD) alters neurodevelopmental trajectories of brain connectomics, but the precise relationship between chronological age (ChA) and brain connectome age (BCA) during development in ASD has not been addressed. This study uses neuroimaging data collected from 50 individuals with ASD and 47 age- and gender-matched typically developing controls (TDCs; age range: 5-18 years). Both functional and structural connectomics were assessed using resting-state functional magnetic resonance imaging and diffusion tensor imaging data from the Autism Brain Imaging Data Exchange repository. For each participant, BCA was estimated from structure-function connectomics through linear support vector regression. We found that BCA matched well with ChA in TDC children and adolescents, but not in ASD. In particular, our findings revealed that individuals with ASD exhibited accelerated brain maturation in youth, followed by a delay of brain development starting at preadolescence. Our results highlight the critical role of BCA in understanding aberrant developmental trajectories in ASD and provide the new insights into the pathophysiological mechanisms of this disorder., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

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.

Objective: The high prevalence of cigarette smoking in schizophrenia (SZ) is generally explained by the self-medication theory. However, its neurobiological mechanism remains unclear. The impaired dynamic of influences among unifying neuropsychiatric triple networks in SZ, including the central executive network (CEN), the default mode network (DMN), and the salience network (SN), might explain the nature of their syndromes, whereas smoking could regulate the dynamics within networks. Therefore, this study examined whether cigarette smoking could elicit a distinct improvement in the dynamics of triple networks in SZ and associated with the alleviation of symptoms., Methods: Four groups were recruited, namely, SZ smoking (n = 22)/nonsmoking (n = 25), and healthy controls smoking (n = 22)/nonsmoking (n = 21). All participants underwent a resting-state functional magnetic resonance imaging (fMRI). The dynamics among unifying neuropsychiatric triple networks were measured using Granger causality analysis on the resting-sate fMRI signal. Interaction effects between SZ and smoking on dynamics were detected using 2-way analysis of covariance, correcting for sex, age, and education level., Results: Whereas smoking reduced SN→DMN dynamic in healthy controls, it preserved the dynamic in SZ, thus suggesting a preservation effect. Moreover, smoking additionally increased DMN→CEN dynamic in SZ., Conclusions: This finding from neural pathways shed new insights into the prevailing self-medication hypothesis in SZ. More broadly, this study elaborates on the neurobiological dynamics that may assist in the treatment of the symptomatology of SZ., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

This study compared the topological organization of brain function in never-treated and treated long-term schizophrenia patients. In a cross-sectional study, 21 never-treated schizophrenia patients with illness duration over 5 years, 26 illness duration-matched antipsychotic-treated patients and 24 demographically-matched healthy controls underwent a resting-state functional magnetic resonance imaging (MRI) scan. The topological properties of brain functional networks were compared across groups, and then we tested for differential age-related effects in regions with significant group differences. Both never-treated and antipsychotic-treated schizophrenia patient groups showed altered nodal centralities in left pre-/postcentral gyri relative to controls. Never-treated patients demonstrated reduced global efficacy, decreased nodal centralities in right amygdala/hippocampus and bilateral putamen/caudate relative to antipsychotic-treated patients and controls. No significant relationships of age and altered functional metrics were seen in either patient group, and no alterations were greater in the treated group. These findings provide insight into brain function deficits over the longer-term course of schizophrenia independent from potential effects of antipsychotic medication. The presence of greater alterations in never-treated than treated patients suggests that long-term antipsychotic treatment may partially protect or enhance brain global and nodal topological function over the course of schizophrenia, notably involving the amygdala, hippocampus, and striatum that have long been associated with the disorder.

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.)

Introduction: Dangguishaoyao-San (DSS) is composed of six traditional Chinese medicines, including Angelica sinensis, Paeoniae radix, Rhizoma Ligusticum, Poria cocos, Rhizoma Atractylodis Macrocephalae, and Rhizoma Alismatis. DSS has been reported to be effective in alleviating the symptoms of Alzheimer's disease (AD). The aim of this study was to investigate the mechanism of action of DSS in vitro using lipopolysaccharide (LPS)-stimulated BV-2 microglia cells., Materials and Methods: BV-2 cells were pretreated with 0.58-1.16 mg/mL of DSS for 2 h and then treated with 1 μg/mL LPS for 24 h. Cell viability was determined by an 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The protein expression levels were measured by Western blots. Inflammatory factors were detected by enzyme-linked immunosorbent assays (ELISAs). The mRNA levels of inflammatory factors were analyzed by quantitative real-time PCR (qRT-PCR)., Results: DSS treatment at concentrations of 0.58-1.16 mg/mL resulted in no significant cytotoxicity. DSS attenuated the release of pro-inflammatory factors, such as interleukin-1β (IL-1β), iNOS and tumor necrosis factor-α (TNF-α) in LPS-induced BV-2 cells. DSS attenuated the mRNA expression of pro-inflammatory cytokines, TLR2, and TLR4 and decreased TLR4 and TLR protein levels as well as the phosphorylation of IκB in LPS-induced BV-2 cells. DSS also down-regulated the nuclear translocation of p65., Conclusion: This study demonstrated that DSS has a protective effect on neuroinflammation in LPS-induced BV-2 microglia cells through the TLRs/NF-κB signaling pathway., (Copyright © 2018 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

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.

Traditional task-evoked brain activations are based on detection and estimation of signal change from the mean signal. By contrast, the low-frequency steady-state brain response (lfSSBR) reflects frequency-tagging activity at the fundamental frequency of the task presentation and its harmonics. Compared to the activity at these resonant frequencies, brain responses at nonresonant frequencies are largely unknown. Additionally, because the lfSSBR is defined by power change, we hypothesize using Parseval's theorem that the power change reflects brain signal variability rather than the change of mean signal. Using a face recognition task, we observed power increase at the fundamental frequency (0.05 Hz) and two harmonics (0.1 and 0.15 Hz) and power decrease within the infra-slow frequency band (<0.1 Hz), suggesting a multifrequency energy reallocation. The consistency of power and variability was demonstrated by the high correlation (r > .955) of their spatial distribution and brain-behavior relationship at all frequency bands. Additionally, the reallocation of finite energy was observed across various brain regions and frequency bands, forming a particular spatiotemporal pattern. Overall, results from this study strongly suggest that frequency-specific power and variability may measure the same underlying brain activity and that these results may shed light on different mechanisms between lfSSBR and brain activation, and spatiotemporal characteristics of energy reallocation induced by cognitive tasks., (© 2018 Wiley Periodicals, Inc.)

Previous studies have demonstrated that alterations of gray matter exist in post-stroke aphasia (PSA) patients. However, so far, few studies combined structural alterations of gray matter volume (GMV) and intrinsic functional connectivity (iFC) imbalances of resting-state functional MRI to investigate the mechanism underlying PSA. The present study investigated specific regions with GMV abnormality in patients with PSA (n = 17) and age- and sex- matched healthy controls (HCs, n = 20) using voxel-based morphometry. In addition, we examined whether there is a link between abnormal gray matter and altered iFC. Furthermore, we explored the correlations between abnormal iFC and clinical scores in aphasic patients. We found significantly increased GMV in the right superior temporal gyrus, right inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and left middle occipital gyrus. Decreased GMV was found in the right caudate gyrus, bilateral thalami in PSA patients. Patients showed increased remote interregional FC between the right IPL/SMG and right precuneus, right angular gyrus, right superior occipital gyrus; while reduced FC in the right caudate gyrus and supplementary motor area, dorsolateral superior frontal gyrus. Moreover, iFC strength between the left middle occipital gyrus and the left orbital middle frontal gyrus was positively correlated with the performance quotient. We suggest that GMV abnormality contributes to interregional FC in PSA. These results may provide useful information to understand the pathogenesis of post-stroke aphasia.

Benign epilepsy with centrotemporal spikes (BECTS) is a common childhood epilepsy syndrome associated with abnormalities in neurocognitive domains, particularly during interictal epileptiform discharges (IEDs). Here, we investigated the effects of IEDs on brain's intrinsic connectivity networks in 43 BECTS patients and 28 matched healthy controls (HCs). Patients were further divided into IED and non-IED subgroups based on simultaneous EEG-fMRI recordings. Functional connectivity within and between five networks, corresponding to seizure origination and cognitive processes, were analyzed to measure IED effects. We found that patients exhibited increased connectivity within the auditory network (AN) and the somato-motor network (SMN), and decreased connectivity within the basal ganglia network and the dorsal attention network, suggesting that both transient and chronic seizure activity may disturb normal network organization. The IED group showed decreased functional connectivity within the default mode network (DMN) compared with the non-IED group and HCs, implying that the DMN was selectively impaired during epileptiform discharges associated with altered self-referential cognitive functions. Moreover, the IED group exhibited increased positive correlations between the AN and the SMN, which suggests a possible excessive influence of centrotemporal spiking on information processing in the auditory system. The association between epileptic activity and network dysfunctions highlights their importance in investigating the pathological mechanism underlying BECTS.

Parkinson's disease (PD) is a chronic, progressive, and degenerative neurological disorder that is characterized by the degeneration of dopamine neurons in the substantia nigra and the formation of intracellular Lewy inclusion bodies. Resting-state functional magnetic resonance imaging (RS-fMRI) has demonstrated evidence of changes in metabolic patterns in individuals with PD. The purpose of this study was to determine whether the presence of PD could be "predicted" based on resting fluctuations in the blood oxygenation level dependent signal. We utilized RS-fMRI to measure the amplitude of low-frequency fluctuation (ALFF) and the fractional ALFF (fALFF) in 51 patients with PD and 50 age- and sex-matched healthy controls. Compared with the healthy controls, the individuals with PD exhibited altered ALFFs in the bilateral lingual gyrus and left putamen and an altered fALFF in the right cerebellum posterior lobe. Support vector machines (SVMs), which comprise a supervised pattern recognition method that enables predictions at the individual level, were trained to separate individuals with PD from healthy controls based on the ALFF and fALFF. Using the leave-one-out cross-validation method to analyze our sample, we reliably distinguished the participants with PD from the controls with 92% sensitivity and 87% specificity. Overall, these findings suggest that the SVM-neuroimaging approach may be of particular clinical value because it enables the accurate identification of PD at the individual level. RS-fMRI should be considered for development as a biomarker and an analytical tool for the evaluation of PD., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Previous regional-based diffusion tensor imaging (DTI) studies focused on impairment of the arcuate fasciculus in aphasia; little is known about the extent to which aphasia severity is affected by damage to both ventral and dorsal language white matter (WM) pathways. To understand whether disconnection of these pathways contributes to clinical symptoms, we assessed the relationship between the alterations of WM integrity and clinical characteristics in acute aphasia after stroke. Eighteen patients with acute aphasia and age-, gender-, and education-matched healthy controls underwent language assessment and DTI scanning. The whole brain unbiased tract-based spatial statistics method was employed to quantitate WM integrity (fractional anisotropy) for both groups. Linear correlation analyses were performed to evaluate the relationship between WM integrity and clinical features. The aphasic patients showed decreased WM integrity in the left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus (IFOF/ILF) and the left uncinate fasciculus, which represents components of ventral language pathway, and the left superior longitudinal fasciculus (SLF), which relates to dorsal language pathway. In addition, WM integrity of the left IFOF and SLF showed a positive correlation with aphasia quotient, performance quotient, and cortical quotient, respectively. These findings suggested that impaired WM integrity in both language pathways not only contributed to language performance, but also to general cognitive status. We suggest that aphasia involves a breakdown of multiple connections of dorsal and ventral streams that directly contributes to language deficits. Damage to these dual-streams may serve as a neuromarker for aphasias after stroke.

The purpose of this study was to investigate the effect of enriched environment (EE) on cerebral angiogenesis after ischemia-reperfusion injury. Middle cerebral artery occlusion (MCAO) followed by reperfusion was performed in rats to set up an animal model of ischemia-reperfusion injury. In a set of behavioral tests, we demonstrated that the animals in the IEE (ischemia + enriched environment) group exhibited significantly improved neurological functions compared to those in the standard housing condition group. In consistent with the functional tests, smaller infarction volumes were observed in the animals of IEE group. Laser scanning confocal microscopy and 3D quantitative analysis of cerebral microvessels revealed that EE treatment increased the total vessel surface area and number of branch point in the ischemic boundary zone. IgG extraction assay showed that the blood brain barrier (BBB) leakage in the ischemic brain was attenuated after EE treatment. EE treatment also enhanced endothelial cells (ECs) proliferation and increased the expression levels of VEGF and its receptor Flk-1 after ischemia-reperfusion injury. Analyses of Spearman's correlation coefficients indicated a correlation of mNSS scores with enhanced cerebral angiogenesis. Together, the results suggest that EE treatment-induced cerebral angiogenesis may contribute to the improved neurological outcome of stroke animals after ischemia-reperfusion injury., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Oxytocin (OT) and arginine vasopressin (AVP) exert robust and sexually dimorphic influences on cognition and emotion. How these hormones regulate relevant functional brain systems is not well understood. OT and AVP serum concentrations were assayed in 60 healthy individuals (36 women). Brain functional networks assessed with resting-state functional magnetic resonance imaging (rs-fMRI) were constructed with graph theory-based approaches that characterize brain networks as connected nodes. Sex differences were demonstrated in rs-fMRI. Men showed higher nodal degree (connectedness) and efficiency (information propagation capacity) in left inferior frontal gyrus (IFG) and bilateral superior temporal gyrus (STG) and higher nodal degree in left rolandic operculum. Women showed higher nodal betweenness (being part of paths between nodes) in right putamen and left inferior parietal gyrus (IPG). Higher hormone levels were associated with less intrinsic connectivity. In men, higher AVP was associated with lower nodal degree and efficiency in left IFG (pars orbitalis) and left STG and less efficiency in left IFG (pars triangularis). In women, higher AVP was associated with lower betweenness in left IPG, and higher OT was associated with lower nodal degree in left IFG (pars orbitalis). Hormones differentially correlate with brain networks that are important for emotion processing and cognition in men and women. AVP in men and OT in women may regulate orbital frontal cortex connectivity, which is important in emotion processing. Hormone associations with STG and pars triangularis in men and parietal cortex in women may account for well-established sex differences in verbal and visuospatial abilities, respectively. © 2016 Wiley Periodicals, Inc., Competing Interests: statement Dr. Bishop has served as an advisory board member for Physician Choice Laboratory Services (PCLS). Dr. Sweeney has consulted to Eli Lilly, Roche, and Takeda. The other authors have nothing to disclose., (© 2016 Wiley Periodicals, Inc.)

Network studies have demonstrated that a small set of highly connected regions may play a central role in global information integration, together forming a rich club organization. Given that generalized tonic-clonic seizure (GTCS) has been conceptualized as a network disorder, we hypothesized that the rich club disturbances may be related to the network abnormalities of GTCS. Here, we used graph theoretical analysis to investigate the rich club organization of both structural and functional connectome in patients with GTCS (n = 50) and healthy controls (n = 60). We further measured the level of global efficiency and clustering in rich club and non-rich club organization. We, respectively, identified a small number of highly connected hubs as rich club organization from structural and functional networks. Patients were found to exhibit significantly reduced rich club connectivity among the central hubs. Meanwhile, both structural and functional network showed changed levels of global efficiency and clustering of rich club organization in GTCS. Furthermore, in patients, lower levels of rich club connectivity were found to be correlated with longer duration of illness and seizure frequency. Together, these findings suggest that GTCS is characterized by a selective disruption of rich club organization due to the long-term injurious effects of epileptic actions on the central hub regions, which potentially contribute to a reduced level of brain integration capacity among different functional domains and an added effect of illness on a preexisting vulnerability. Our findings emphasize a central role for abnormal rich club organization in the pathophysiological mechanism underlying GTCS. Hum Brain Mapp 37:4487-4499, 2016. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

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., Competing Interests: The authors have no conflicts of interest to disclose.

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.

Although acute impact of traumatic experiences on brain function in disaster survivors is similar to that observed in post-traumatic stress disorders (PTSD), little is known about the long-term impact of this experience. We have used structural and functional magnetic resonance imaging to investigate resting-state functional connectivity and gray and white matter (WM) changes occurring in the brains of healthy Wenchuan earthquake survivors both 3 weeks and 2 years after the disaster. Results show that while functional connectivity changes 3 weeks after the disaster involved both frontal-limbic-striatal and default-mode networks (DMN), at the 2-year follow-up only changes in the latter persisted, despite complete recovery from high initial levels of anxiety. No gray or WM volume changes were found at either time point. Taken together, our findings provide important new evidence that while altered functional connectivity in the frontal-limbic-striatal network may underlie the post-trauma anxiety experienced by survivors, parallel changes in the DMN persist despite the apparent absence of anxiety symptoms. This suggests that long-term changes occur in neural networks involved in core aspects of self-processing, cognitive and emotional functioning in disaster survivors which are independent of anxiety symptoms and which may also confer increased risk of subsequent development of PTSD., (© The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

To establish a method for detecting microdialysis recovery of tetramethylpyrazine (TMP) and ferulic acid (FA) and investigating the influencing factors, providing the basis for further in vivo microdialysis experiments. The concentration of FA and TMP in dialysates were determined by high pressure liquid chromatography ( HPLC) and probe recovery were calculated respectively. The influence of the flow rates, medium concentration, temperature and in vivo probe stability on the recovery of FA and TMP were investigated by using concentration difference method (incremental method and decrement method). The recovery obtained by incremental method were similar to by decrement method. The in vitro recovery rate of FA and TMP decreased with the increase of 1-2.5 μL min(-1), and increased obviously with the temperature of 25-42 degrees C under the same conditions. The concentration of FA and TMP had no obvious effect on the probe recovery under the same flow rate. In addition, the recovery of TMP and FA remained stable and showed similar trends under the condition of four concentration cycles, indicating that the intra day reproducibility of the concentration difference method was good. The recovery of brain microdialysis probes in vivo 8 h maintained a relatively stable, but certain differences existed between different brain microdialysis probes, demonstrating that each probe was required for recovery correction in vivo experiment. Microdialysis sampling can be used for the local brain pharmacokinetic study of FA and TMP, and retrodialysis method can be used in probe recovery of FA and TMP in vivo.

To identify the distinct pattern of anatomical network reorganization in surgically refractory mesial temporal lobe epilepsy (MTLE) patients using a longitudinal design. We collected longitudinal diffusion-weighted images of 19 MTLE patients before and after anterior temporal lobectomy. Patients were classified as seizure-free (SF) or nonseizure-free (NSF) at least 1 year after surgery. We constructed whole-brain anatomical networks derived from white matter tractography and evaluated network connectivity measures by graph theoretical analysis. The reorganization trajectories of network measures in SF and NSF patients were investigated by two-way mixed analysis of variance, with factors "group" (SF vs NSF) and "treatment" (presurgery vs postsurgery). Widespread brain structures showed opposite reorganization trajectories in FS and NSF groups (interaction effect). Most of them showed group difference before surgery and then converge after surgery, suggesting that surgery remodeled these structures into a similar status. Conversly, contralateral amygdala-planum-temporale and thalamic-parietal tracts showed higher connectivity strength in NSF than in SF patients after surgery, indicating maladaptive neuroplastic responses to surgery in NSF patients. Our findings suggest that surgical outcomes are associated not only with the preoperative pattern of anatomical connectivity, but also with connectome reconfiguration following surgery. The reorganization of contralateral temporal lobe and corticothalamic tracts may be particularly important for seizure control in MTLE.

Benign epilepsy with centrotemporal spikes (BECTS) is often associated with neural circuit dysfunction, particularly during the transient active state characterized by interictal epileptiform discharges (IEDs). Little is known, however, about the functional neural circuit abnormalities in BECTS without IEDs, or if such abnormalities could be used to differentiate BECTS patients without IEDs from healthy controls (HCs) for early diagnosis. To this end, we conducted resting-state functional magnetic resonance imaging (RS-fMRI) and simultaneous Electroencephalogram (EEG) in children with BECTS (n = 43) and age-matched HC (n = 28). The simultaneous EEG recordings distinguished BECTS with IEDs (n = 20) from without IEDs (n = 23). Intrinsic brain activity was measured in all three groups using the amplitude of low frequency fluctuation at rest. Compared to HC, BECTS patients with IEDs exhibited an intrinsic activity abnormality in the thalamus, suggesting that thalamic dysfunction could contribute to IED emergence while patients without IEDs exhibited intrinsic activity abnormalities in middle frontal gyrus and superior parietal gyrus. Using multivariate pattern classification analysis, we were able to differentiate BECTS without IEDs from HCs with 88.23% accuracy. BECTS without epileptic transients can be distinguished from HC and BECTS with IEDs by unique regional abnormalities in resting brain activity. Both transient abnormalities as reflected by IEDs and chronic abnormalities as reflected by RS-fMRI may contribute to BECTS development and expression. Intrinsic brain activity and multivariate pattern classification techniques are promising tools to diagnose and differentiate BECTS syndromes. Hum Brain Mapp 36:3878-3889, 2015. © 2015 Wiley Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)

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.

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.

Objective. Electroconvulsive therapy (ECT) is considered one of the most effective and fast-acting treatment options for depressive episodes. Little is known, however, about ECT's enabling brain (neuro)plasticity effects, particular for plasticity of white matter pathway. Materials and Methods. We collected longitudinal diffusion tensor imaging in the first-episode, drug-naïve major depressive disorder (MDD) patients (n = 24) before and after a predefined time window ECT treatment. We constructed large-scale anatomical networks derived from white matter fiber tractography and evaluated the topological reorganization using graph theoretical analysis. We also assessed the relationship between topological reorganization with improvements in depressive symptoms. Results. Our investigation revealed three main findings: (1) the small-worldness was persistent after ECT series; (2) anatomical connections changes were found in limbic structure, temporal and frontal lobes, in which the connection changes between amygdala and parahippocampus correlate with depressive symptom reduction; (3) significant nodal strength changes were found in right paralimbic network. Conclusions. ECT elicits neuroplastic processes associated with improvements in depressive symptoms that act to specific local ventral frontolimbic circuits, but not small-world property. Overall, ECT induced topological reorganization in large-scale brain structural network, opening up new avenues to better understand the mode of ECT action in MDD.

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: The roles of iron in epilepsy and its pathophysiological significance are poorly understood, especially whether iron levels are abnormal in subcortcal structures. This study aims to demonstrate whole-brain iron alterations and its clinical relevancies in mesial temporal lobe epilepsy (mTLE) in vivo, using susceptibility-weighted magnetic resonance imaging (SWI)., Methods: We studied 62 patients with mTLE and 62 healthy controls. Brain iron concentration was quantified using SWI phase values. Voxel-wise analysis was carried out to compare iron levels between mTLE and controls, and to assess the relationship between altered iron concentration and clinical parameters in mTLE., Results: Patients with mTLE showed decreases of iron levels in the subcortical structures such as substantia nigra, red nucleus, and basal ganglia. Conversely, iron levels were decreased in the cortex. Subcortical iron levels were negatively correlated to those in the cortex. Moreover, cortical and basal ganglia iron levels were related to clinical variables including epilepsy duration, age at seizures onset, and histories of precipitating factors., Conclusions: Our SWI findings suggest a redistribution of iron between subcortical and cortical structures in mTLE. The degree of redistribution is affected by both progression of epilepsy and precipitating factors. Investigation on brain iron redistribution offers new insights into the pathogenesis of mTLE, and may be a potential biomarker for monitoring the clinical progression of epilepsy.

Epilepsy is characterized by recurrent and temporary brain dysfunction due to discharges of interconnected groups of neurons. The brain of epilepsy patients has a dynamic bifurcation that switches between epileptic and normal states. The dysfunctional state involves large-scale brain networks. It is very important to understand the network mechanisms of seizure initiation, maintenance, and termination in epilepsy. Absence epilepsy provides a unique model for neuroimaging investigation on dynamic evolutions of brain networks over seizure repertoire. By using a dynamic functional connectivity and graph theoretical analyses to study absence seizures (AS), we aimed to obtain transition of network properties that account for seizure onset and offset. We measured resting-state functional magnetic resonance imaging and simultaneous electroencephalography (EEG) from children with AS. We used simultaneous EEG to define the preictal, ictal and postictal intervals of seizures. We measured dynamic connectivity maps of the thalamus network and the default mode network (DMN), as well as functional connectome topologies, during the three different seizure intervals. The analysis of dynamic changes of anti-correlation between the thalamus and the DMN is consistent with an inhibitory effect of seizures on the default mode of brain function, which gradually fades out after seizure onset. Also, we observed complex transitions of functional network topology, implicating adaptive reconfiguration of functional brain networks. In conclusion, our work revealed novel insights into modifications in large-scale functional connectome during AS, which may contribute to a better understanding the network mechanisms of state bifurcations in epileptogenesis.

Purpose: Psychogenic non-epileptic seizures (PNES) are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Some neuroimaging studies have reported that PNES exhibits aberrant functional connectivity in specific brain networks. Thus, advanced neuroimaging technologies may aid clinical diagnosis and treatment of PNES., Methods: We investigated changes in brain functional connectivity in 18 patients with PNES and 20 healthy controls. Functional connectivity density mapping (FCDM), a voxelwise data-driven technique, was employed to compute local and global FCD maps. Then, short-range and long-range FCD values were calculated and group analyses performed between patents with PNES and healthy controls. A correlation analysis with clinical variables was also performed., Results: We found that patients with PNES showed abnormal FCD regions mainly in the frontal cortex, sensorimotor cortex, cingulate gyrus, insula and occipital cortex. Seed-voxel correlation analyses also showed disrupted functional connectivity between these regions. In addition, the occipital cortex FCD correlated with duration of disease., Conclusion: The present results support the hypothesis that patients with PNES are associated with altered attention, sensorimotor and emotion systems. Furthermore, correlations between altered regions in the occipital cortex and duration of disease may reflect an adaptation in these patients for long-term hypervigilance and increased response to external stimuli. This study adds new knowledge to our understanding of the pathophysiological mechanisms underlying PNES., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Purpose: Amplitude of low-frequency fluctuation (ALFF) of blood-oxygenation level-dependent (BOLD) has proven a promising way to detect disease-related local brain activity. However, routine approach employs an arbitrary frequency band of 0.01-0.08 Hz, which lacks frequency specificity and blinds to the information contained in other frequency bands. This study investigated the amplitude of fluctuations in full BOLD frequency bands, and addressed how amplitudes of fluctuations change in each specific frequency range in idiopathic generalized epilepsy (IGE)., Methods: Thirty-four IGE patients with generalized tonic-clonic seizure and the same number of age- and sex-matched healthy controls were included. Functional MRI data were acquired using a 2s repetition time. Routine amplitude of low-frequency fluctuation analysis was first performed. The regions showing group difference were set as Region-of-interest for analysis of amplitudes of full-frequency. The amplitudes of BOLD fluctuations were consecutively performed at each frequency bin of 0.002 Hz, and specific frequency amplitude analyses were performed in five different frequency ranges (0-0.01 Hz, 0.01-0.027 Hz, 0.027-0.073 Hz, 0.073-0.198 Hz, and 0.198-0.25 Hz)., Key Findings: The thalamus and prefrontal cortex showed significant group differences in routine amplitude analysis. For amplitude of full-frequency analysis, a reverse pattern was found in the dynamic changes between the thalamus and prefrontal cortex in IGE. Moreover, the prefrontal cortex showed amplitude difference in the 0.01-0.027 Hz band, while the thalamus showed amplitude difference in the 0.027-0.073 Hz band. Both these two regions showed amplitude differences in 0.198-0.25 Hz band., Significance: We demonstrated the characteristic alterations of amplitude of BOLD fluctuations in IGE in frequency domain. The amplitude analysis of full frequency may potentially help to select specific frequency range for detecting epilepsy-related brain activity, and provide insights into the pathophysiological mechanism of IGE., (Copyright © 2014 Elsevier B.V. All rights reserved.)

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.

Background: Several task-based functional MRI (fMRI) studies have highlighted abnormal activation in specific regions involving the low-level perceptual (auditory, visual, and somato-motor) network in posttraumatic stress disorder (PTSD) patients. However, little is known about whether the functional connectivity of the low-level perceptual and higher-order cognitive (attention, central-execution, and default-mode) networks change in medication-naïve PTSD patients during the resting state., Methods: We investigated the resting state networks (RSNs) using independent component analysis (ICA) in 18 chronic Wenchuan earthquake-related PTSD patients versus 20 healthy survivors (HSs)., Results: Compared to the HSs, PTSD patients displayed both increased and decreased functional connectivity within the salience network (SN), central executive network (CEN), default mode network (DMN), somato-motor network (SMN), auditory network (AN), and visual network (VN). Furthermore, strengthened connectivity involving the inferior temporal gyrus (ITG) and supplementary motor area (SMA) was negatively correlated with clinical severity in PTSD patients., Limitations: Given the absence of a healthy control group that never experienced the earthquake, our results cannot be used to compare alterations between the PTSD patients, physically healthy trauma survivors, and healthy controls. In addition, the breathing and heart rates were not monitored in our small sample size of subjects. In future studies, specific task paradigms should be used to reveal perceptual impairments., Conclusions: These findings suggest that PTSD patients have widespread deficits in both the low-level perceptual and higher-order cognitive networks. Decreased connectivity within the low-level perceptual networks was related to clinical symptoms, which may be associated with traumatic reminders causing attentional bias to negative emotion in response to threatening stimuli and resulting in emotional dysregulation.

Intrinsic connectivity network (ICN) technique provides a feasible way for evaluating cognitive impairments in epilepsy. This EEG-fMRI study aims to comprehensively assess the alterations of ICNs affected by generalized spike-and-wave discharge (GSWD) during absence seizure (AS). Twelve fMRI sessions with GSWD, and individually paired non-GSWD sessions were acquired from 16 patients with AS. Ten ICNs corresponding to seizure origination and cognitive processes were extracted using independent component analysis. Intra- and inter-network connectivity alterations of the ICNs were observed through comparisons between GSWD and non-GSWD sessions. Sequential correlation analysis between GSWD and the ICN time courses addressed the immediate effects of GSWD on ICNs during AS. GSWD-related increase of intra-network connectivity was found only in the thalamus, and extensive decreases were found in the ICNs corresponding to higher-order cognitive processes including the default-mode network, dorsal attention network, central executive network and salience network. The perceptive networks and motor network were less affected by GSWD. Sequential correlation analysis further demonstrated different responses of the ICNs to GSWD. In addition to GSWD-related functional excitation in the thalamus and functional suspension in the default-mode network, this study revealed extensive inhibitions in the other ICNs corresponding to higher-order cognitive processes, and spared perceptive and motor processes in AS. GSWD elevated synchronization of brain network activity and sequentially affected the ICNs., (© 2013. Published by Elsevier B.V. All rights reserved.)

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.

Psychogenic non-epileptic seizures (PNES) are paroxysmal behaviors that resemble epileptic seizures but lack abnormal electrical activity. Recent studies suggest aberrant functional connectivity involving specific brain regions in PNES. Little is known, however, about alterations of topological organization of whole-brain functional and structural connectivity networks in PNES. We constructed functional connectivity networks from resting-state functional MRI signal correlations and structural connectivity networks from diffusion tensor imaging tractography in 17 PNES patients and 20 healthy controls. Graph theoretical analysis was employed to compute network properties. Moreover, we investigated the relationship between functional and structural connectivity networks. We found that PNES patients exhibited altered small-worldness in both functional and structural networks and shifted towards a more regular (lattice-like) organization, which could serve as a potential imaging biomarker for PNES. In addition, many regional characteristics were altered in structural connectivity network, involving attention, sensorimotor, subcortical and default-mode networks. These regions with altered nodal characteristics likely reflect disease-specific pathophysiology in PNES. Importantly, the coupling strength of functional-structural connectivity was decreased and exhibited high sensitivity and specificity to differentiate PNES patients from healthy controls, suggesting that the decoupling strength of functional-structural connectivity might be an important characteristic reflecting the mechanisms of PNES. This is the first study to explore the altered topological organization in PNES combining functional and structural connectivity networks, providing a new way to understand the pathophysiological mechanisms of PNES.

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.)

The human brain can be modeled as a network, whose structure can be revealed by either anatomical or functional connectivity analyses. Little is known, so far, about the topological features of the large-scale interregional functional covariance network (FCN) in the brain. Further, the relationship between the FCN and the structural covariance network (SCN) has not been characterized yet, in the intact as well as in the diseased brain. Here, we studied 59 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 59 healthy controls. We estimated the FCN and the SCN by measuring amplitude of low-frequency fluctuations (ALFF) and gray matter volume (GMV), respectively, and then we conducted graph theoretical analyses. Our ALFF-based FCN and GMV-based results revealed that the normal human brain is characterized by specific topological properties such as small worldness and highly-connected hub regions. The patients had an altered overall topology compared to the controls, suggesting that epilepsy is primarily a disorder of the cerebral network organization. Further, the patients had altered nodal characteristics in the subcortical and medial temporal regions and default-mode regions, for both the FCN and SCN. Importantly, the correspondence between the FCN and SCN was significantly larger in patients than in the controls. These results support the hypothesis that the SCN reflects shared long-term trophic mechanisms within functionally synchronous systems. They can also provide crucial information for understanding the interactions between the whole-brain network organization and pathology in generalized tonic-clonic seizures.

Recovering directed pathways of information transfer between brain areas is an important issue in neuroscience and helps to shed light on the brain function in several physiological and cognitive states. Granger causality (GC) analysis is a valuable tool to detect directed dynamical connectivity, and it is being increasingly used. Unfortunately, this approach encounters some limitations in particularly when applied to neuroimaging datasets, often consisting in short and noisy data and for which redundancy plays an important role. In this article, we address one of these limitations, namely, the computational and conceptual problems arising when conditional GC, necessary to disambiguate direct and mediated influences, is used on short and noisy datasets of many variables, as it is typically the case in some electroencephalography (EEG) protocols and in functional magnetic resonance imaging (fMRI). We show that considering GC in the framework of information theory we can limit the conditioning to a limited number of variables chosen as the most informative, obtaining more stable and reliable results both in EEG and fMRI data.

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.

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.

The previous task-based or resting perfusion studies in social anxiety disorder (SAD) patients have highlighted specific differences in brain response. Little is known about the changes in the local synchronization of spontaneous functional magnetic resonance imaging (fMRI) blood oxygen level-dependent (BOLD) signals that occur in SAD during the resting state. We investigated altered neural activity in the resting state using a regional homogeneity (ReHo) analysis on 20 SAD and 20 healthy controls (HC). Compared with HC, SAD patients exhibited decreased coherence (ReHo) in the bilateral angular gyrus and the left medial prefrontal cortex within the default mode network (DMN), suggesting functional impairment of the perception of socially relevant emotional state and self-related mental representations; and also in the right dorsolateral prefrontal cortex and right inferior parietal gyrus within the central-executive network (CEN), reflecting the deficit of cognitive control of social anxiety. Significantly increased coherence (ReHo) was found in the left middle occipital gyrus, which would be consistent with their hypervigilance and hyperprosexia to the social communication even in the resting state. Our results might supply a novel way to look into neuro-pathophysiological mechanisms in SAD patients., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)