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Relationship between changes in resting-state spontaneous brain activity and cognitive impairment in patients with CADASIL.

Sat, 04/20/2019 - 01:32
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Relationship between changes in resting-state spontaneous brain activity and cognitive impairment in patients with CADASIL.

J Headache Pain. 2019 Apr 17;20(1):36

Authors: Su J, Wang M, Ban S, Wang L, Cheng X, Hua F, Tang Y, Zhou H, Zhai Y, Du X, Liu J

Abstract
BACKGROUND: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) mainly manifests with cognitive impairment. Cognitive deficits in patients with CADASIL are correlated with structural brain changes such as lacunar lesion burden, normalized brain volume, and anterior thalamic radiation lesions, but changes in resting-state functional brain activity in patients with CADASIL have not been reported.
METHODS: This study used resting-state functional magnetic resonance imaging (fMRI) to measure the amplitude of low-frequency fluctuation (ALFF) in 22 patients with CADASIL and 44 healthy matched controls. A seed-based functional connectivity (FC) analysis was used to investigate whether the dysfunctional areas identified by ALFF analysis exhibited abnormal FC with other brain areas. Pearson's correlation analysis was used to detect correlations between the ALFF z-score of abnormal brain areas and clinical scores in patients with CADASIL.
RESULTS: Patients with CADASIL exhibited significantly lower ALFF values in the right precuneus and cuneus (Pcu/CU) and higher ALFF values in the bilateral superior frontal gyrus (SFG) and left cerebellar anterior and posterior lobes compared with controls. Patients with CADASIL showed weaker FC between the areas with abnormal ALFF (using peaks in the left and right SFG and the right Pcu/CU) and other brain areas. Importantly, the ALFF z-scores for the left and right SFG were negatively associated with cognitive performance, including Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment scores (MoCA), respectively, whereas those of the right Pcu/CU were positively correlated with the MMSE score.
CONCLUSIONS: This preliminary study provides evidence for changes in ALFF of the right Pcu/CU, bilateral SFG and left cerebellar anterior and posterior lobes, and associations between ALFF values for abnormal brain areas and cognitive performance in patients with CADASIL. Therefore, spontaneous brain activity may be a novel imaging biomarker of cognitive impairment in this population.

PMID: 30995925 [PubMed - in process]

Seed-based connectivity analysis of resting-state fMRI in patients with brain tumors: a practical approach.

Thu, 04/18/2019 - 18:04

Seed-based connectivity analysis of resting-state fMRI in patients with brain tumors: a practical approach.

World Neurosurg. 2019 Apr 14;:

Authors: Metwali H, Samii A

Abstract
OBJECTIVE: In this study, we are presenting our experience using resting state functional magnetic resonsce imaging (rs-fMRI) in preoperative planning. We performed goup analysis to demonestrate the effects of brain tumor on resting state networks (RSNs) METHODS: Thirty patients with supratentorial gliomas were included in the study. Preoperative rs-fMRI and structural MRI were performed in all cases. The rs-fMRI was preprocessed ( realignment, slice time correction, coregistration to structural images, normalization and smoothing). The structural images were segmented and normalized. Band filtering and denoising were applied to the functional images. Connectivity analysis was performed using seed based connectivity analysis (SCA) at single subject level and group level. Correlation algorism has been used with r>0.5.
RESULTS: RSNs could be detected in all patients. They showed similarity to the results of the task based fMRI, when task based fMRI was feasible. Detection of the networks was also possible in patients with neurological deficits, in whom task based fMRI was not possible. We could use SCA in patients under anesthesia. High level networks ( default mode, salience, and dorsal attention networks) were detectable but showed wide spectrum of spatial alterations and components disconnections.
CONCLUSION: Rs-fMRI is a feasible method for extended brain mapping. Diverse RSNs could be detected in patients with brain tumors and could be applied in preoperative planning. SCA was a robust and direct approach for data analysis and could answer specific clinically relevant questions. However, further studies are needed to validate the technique and its clinical impact.

PMID: 30995557 [PubMed - as supplied by publisher]

ALTERED BRAIN ACTIVITY IN PATIENTS WITH DIABETIC RETINOPATHY USING REGIONAL HOMOGENEITY: A RESTING-STATE fMRI STUDY.

Thu, 04/18/2019 - 18:04

ALTERED BRAIN ACTIVITY IN PATIENTS WITH DIABETIC RETINOPATHY USING REGIONAL HOMOGENEITY: A RESTING-STATE fMRI STUDY.

Endocr Pract. 2019 Apr;25(4):320-327

Authors: Liao XL, Yuan Q, Shi WQ, Li B, Su T, Lin Q, Min YL, Zhu PW, Ye L, Shao Y

Abstract
Objective: Previous neuroimaging studies have shown that diabetic retinopathy (DR) is accompanied by abnormal spontaneous brain activity. The purpose of the current study was to investigate changes in brain neural homogeneity in patients with DR using regional homogeneity (ReHo). Methods: A total of 56 subjects were recruited, including 28 patients with DR (16 female and 12 male patients) and 28 healthy controls (HCs) (16 female and 12 male patients) approximately matched for age and sex. All subjects underwent resting-state functional magnetic resonance imaging scans. The ReHo method was applied to explore neural homogeneity in the brain. The patients with DR were distinguished from HCs following the construction of receiver operating characteristic curves. The ReHo method was applied to assess changes in synchronous neural activity. Results: Compared to HCs, the ReHo values in the left and right posterior lobes of the cerebellum in patients with DR were significantly increased, whereas ReHo values in the right anterior cingulate gyrus, right cuneus, bilateral precuneus, and left-middle frontal gyrus were significantly decreased. In addition, the ReHo value in the right cuneus showed a positive correlation with the best corrected visual acuity in patients with DR. Conclusion: Dysfunctional brain homology may reveal the pathological mechanisms underlying the visual pathways of patients with DR. Abbreviations: AUC = area under the curve; BA = Brodmann area; DR = diabetic retinopathy; fMRI = functional magnetic resonance imaging; HC = healthy control; MRI = magnetic resonance imaging; rs-fMRI = resting-state fMRI; ReHo = regional homogeneity; ROC = receiver operating characteristic.

PMID: 30995427 [PubMed - in process]

Machine-learning identifies parkinson's disease patients based on resting-state between-network functional connectivity.

Thu, 04/18/2019 - 18:04

Machine-learning identifies parkinson's disease patients based on resting-state between-network functional connectivity.

Br J Radiol. 2019 Apr 17;:20180886

Authors: Rubbert C, Mathys C, Jockwitz C, Hartmann CJ, Eickhoff SB, Hoffstaedter F, Caspers S, Eickhoff CR, Sigl B, Teichert NA, Südmeyer M, Turowski B, Schnitzler A, Caspers J

Abstract
OBJECTIVES: Evaluation of a data-driven, model-based classification approach to discriminate idiopathic Parkinson's disease (PD) patients from healthy controls (HC) based on between-network connectivity in whole-brain resting-state functional MRI (rs-fMRI).
METHODS: Whole-brain rs-fMRI (EPI/TR = 2.2  s/TE = 30  ms/flip angle = 90°/resolution = 3.1 × 3.1 × 3.1  mm/acquisition time≈11  min) was assessed in 42 PD patients (medical OFF) and 47 HC matched for age and gender. Between-network connectivity based on full and L2-regularized partial correlation measures were computed for each subject based on canonical functional network architectures of two cohorts at different levels of granularity (Human Connectome Project: 15/25/50/100/200 networks; 1000BRAINS: 15/25/50/70 networks). A Boosted Logistic Regression model was trained on the correlation matrices using a nested cross-validation (CV) with 10 outer and 10 inner folds for an unbiased performance estimate, treating the canonical functional network architecture and the type of correlation as hyperparameters. The number of boosting iterations was fixed at 100. The model with the highest mean accuracy over the inner folds was trained using an non-nested 10- fold 20-repeats CV over the whole dataset to determine feature importance.
RESULTS: Over the outer folds the mean accuracy was found to be 76.2 % (median 77.8%, SD 18.2, IQR 69.4 - 87.1 %). Mean sensitivity was 81 % (median 80%, SD 21.1, IQR 75 - 100 %) and mean specificity was 72.7 % (median 75%, SD 20.4, IQR 66.7 - 80 %). The 1000BRAINS 50-network-parcellation, using full correlations, performed best over the inner folds. The top features predominantly included sensorimotor as well as sensory networks.
CONCLUSIONS: A rs-fMRI whole-brain-connectivity, data-driven, model-based approach to discriminate PD patients from healthy controls shows a very good accuracy and a high sensitivity. Given the high sensitivity of the approach, it may be of use in a screening setting.
ADVANCES IN KNOWLEDGE: Resting-state functional MRI could prove to be a valuable, non-invasive neuroimaging biomarker for neurodegenerative diseases. The current model-based, data-driven approach on whole-brain between-network connectivity to discriminate Parkinson's disease patients from healthy controls shows promising results with a very good accuracy and a very high sensitivity.

PMID: 30994036 [PubMed - as supplied by publisher]

Intrinsic insular-frontal networks predict future nicotine dependence severity.

Thu, 04/18/2019 - 18:04
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Intrinsic insular-frontal networks predict future nicotine dependence severity.

J Neurosci. 2019 Apr 16;:

Authors: Hsu LM, Keeley RJ, Liang X, Brynildsen JK, Lu H, Yang Y, Stein EA

Abstract
Although 60% of the US population have tried smoking cigarettes, only 16% smoke regularly. Identifying this susceptible subset of the population before the onset of nicotine dependence may encourage targeted early interventions to prevent regular smoking and/or minimize severity. While prospective neuroimaging in human populations can be challenging, preclinical neuroimaging models prior to chronic nicotine administration can help develop translational biomarkers of disease risk. Chronic, intermittent nicotine (0, 1.2 or 4.8 mg/kg/d (N = 10-11/group)) was administered to male Sprague Dawley rats for 14 days; dependence severity was quantified using precipitated withdrawal behaviors collected prior to, during and following forced nicotine abstinence. Resting state fMRI functional connectivity (FC) prior to drug administration was subjected to a graph theory analytical framework to form a predictive model of subsequent individual differences in nicotine dependence. Whole brain modularity analysis identified 5 modules in the rat brain. A metric of inter-module connectivity, participation coefficient (PC), of an identified insular-frontal cortical module predicted subsequent dependence severity, independent of nicotine dose. To better spatially isolate this effect, this module was subjected to a secondary exploratory modularity analysis, which segregated it into three submodules (frontal-motor, insula and sensory). Higher FC between these 3 sub-modules and 3 of the 5 originally identified modules (striatal, frontal-executive and sensory association) also predicted dependence severity. These data suggest that pre-dispositional, intrinsic differences in circuit strength between insular-frontal based brain networks prior to drug exposure may identify those at highest risk to the development of nicotine dependence.Significance statement:Developing biomarkers of individuals at high risk for addiction before the onset of this brain-based disease is essential for prevention, early intervention and/or subsequent treatment decisions. Using a rodent model of nicotine dependence and a novel data-driven, network-based analysis of resting state fMRI data collected prior to drug exposure, functional connections centered on an intrinsic insular-frontal module predicted the severity of nicotine dependence after drug exposure. The predictive capacity of baseline network measures was specific to inter-regional but not within-region connectivity. While insular and frontal regions have consistently been implicated in nicotine dependence, this is the first study to reveal that innate, individual differences in their circuit strength have the predictive capacity to identify those at greatest risk for and resilience to drug dependence.

PMID: 30992371 [PubMed - as supplied by publisher]

Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer's disease.

Thu, 04/18/2019 - 18:04
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Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer's disease.

Neuroimage Clin. 2019 Apr 03;22:101812

Authors: Schumacher J, Peraza LR, Firbank M, Thomas AJ, Kaiser M, Gallagher P, O'Brien JT, Blamire AM, Taylor JP

Abstract
We studied the dynamic functional connectivity profile of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) compared to controls, how it differs between the two dementia subtypes, and a possible relation between dynamic connectivity alterations and temporally transient clinical symptoms in DLB. Resting state fMRI data from 31 DLB, 29 AD, and 31 healthy control participants were analyzed using dual regression to determine between-network functional connectivity. Subsequently, we used a sliding window approach followed by k-means clustering and dynamic network analyses to study dynamic functional connectivity. Dynamic connectivity measures that showed significant group differences were tested for correlations with clinical symptom severity. Our results show that AD and DLB patients spent more time than controls in sparse connectivity configurations with absence of strong positive and negative connections and a relative isolation of motor networks from other networks. Additionally, DLB patients spent less time in a more strongly connected state and the variability of global brain network efficiency was reduced in DLB compared to controls. There were no significant correlations between dynamic connectivity measures and clinical symptom severity. An inability to switch out of states of low inter-network connectivity into more highly and specifically connected network configurations might be related to the presence of dementia in general as it was observed in both AD and DLB. In contrast, the loss of global efficiency variability in DLB might indicate the presence of an abnormally rigid brain network and the lack of economical dynamics, factors which could contribute to cognitive slowing and an inability to respond appropriately to situational demands.

PMID: 30991620 [PubMed - as supplied by publisher]

Intrinsic brain activity changes associated with adjuvant chemotherapy in older women with breast cancer: a pilot longitudinal study.

Wed, 04/17/2019 - 18:02
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Intrinsic brain activity changes associated with adjuvant chemotherapy in older women with breast cancer: a pilot longitudinal study.

Breast Cancer Res Treat. 2019 Apr 13;:

Authors: Chen BT, Jin T, Patel SK, Ye N, Ma H, Wong CW, Rockne RC, Root JC, Saykin AJ, Ahles TA, Holodny AI, Prakash N, Mortimer J, Waisman J, Yuan Y, Li D, Sedrak MS, Vazquez J, Katheria V, Dale W

Abstract
PURPOSE: Older cancer patients are at increased risk of cancer-related cognitive impairment. The purpose of this study was to assess the alterations in intrinsic brain activity associated with adjuvant chemotherapy in older women with breast cancer.
METHODS: Chemotherapy treatment (CT) group included sixteen women aged ≥ 60 years (range 60-82 years) with stage I-III breast cancers, who underwent both resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological testing with NIH Toolbox for Cognition before adjuvant chemotherapy, at time point 1 (TP1), and again within 1 month after completing chemotherapy, at time point 2 (TP2). Fourteen age- and sex-matched healthy controls (HC) underwent the same assessments at matched intervals. Three voxel-wise rs-fMRI parameters: amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity, were computed at each time point. The changes in rs-fMRI parameters from TP1 to TP2 for each group, the group differences in changes (the CT group vs. the HC group), and the group difference in the baseline rs-fMRI parameters were assessed. In addition, correlative analysis between the rs-fMRI parameters and neuropsychological testing scores was also performed.
RESULTS: In the CT group, one brain region, which included parts of the bilateral subcallosal gyri and right anterior cingulate gyrus, displayed increased ALFF from TP1 to TP2 (cluster p-corrected = 0.024); another brain region in the left precuneus displayed decreased fALFF from TP1 to TP2 (cluster level p-corrected = 0.025). No significant changes in the rs-fMRI parameters from TP1 to TP2 were observed in the HC group. Although ALFF and fALFF alterations were observed only in the CT group, none of the between-group differences in rs-fMRI parameter changes reached statistical significance.
CONCLUSIONS: Our study results of ALFF and fALFF alterations in the chemotherapy-treated women suggest that adjuvant chemotherapy may affect intrinsic brain activity in older women with breast cancer.

PMID: 30989462 [PubMed - as supplied by publisher]

Effects of Childhood Maltreatment on Social Cognition and Brain Functional Connectivity in Borderline Personality Disorder Patients.

Wed, 04/17/2019 - 18:02
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Effects of Childhood Maltreatment on Social Cognition and Brain Functional Connectivity in Borderline Personality Disorder Patients.

Front Psychiatry. 2019;10:156

Authors: Duque-Alarcón X, Alcalá-Lozano R, González-Olvera JJ, Garza-Villarreal EA, Pellicer F

Abstract
Borderline personality disorder (BPD) is a chronic condition characterized by high levels of impulsivity, affective instability, and difficulty to establish and manage interpersonal relationships. However, little is known about its etiology and neurobiological substrates. In our study, we wanted to investigate the influence of child abuse in the psychopathology of BPD by means of social cognitive paradigms [the Movie for the Assessment of Social Cognition (MASC) and the reading the mind in the eyes test (RMET)], and resting state functional magnetic resonance imaging (rs-fMRI). For this, we recruited 33 participants, 18 BPD patients, and 15 controls. High levels of self-reported childhood maltreatment were reported by BPD patients. For the sexual abuse subdimension, there were no differences between the BPD and the control groups, but there was a negative correlation between MASC scores and total childhood maltreatment levels, as well as between physical abuse, physical negligence, and MASC. Both groups showed that the higher the level of childhood maltreatment, the lower the performance on the MASC social cognitive test. Further, in the BPD group, there was hypoconnectivity between the structures responsible for emotion regulation and social cognitive responses that have been described as part of the frontolimbic circuitry (i.e., amygdala). Differential levels of connectivity, associated with different types and levels of abuse were also observed.

PMID: 30988667 [PubMed]

Functional connectomics of affective and psychotic pathology.

Wed, 04/17/2019 - 18:02
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Functional connectomics of affective and psychotic pathology.

Proc Natl Acad Sci U S A. 2019 Apr 15;:

Authors: Baker JT, Dillon DG, Patrick LM, Roffman JL, Brady RO, Pizzagalli DA, Öngür D, Holmes AJ

Abstract
Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation, we obtained fMRI data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic "fingerprints" that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. The presence of affective and psychotic illnesses was associated with graded disruptions in frontoparietal network connectivity (encompassing aspects of dorsolateral prefrontal, dorsomedial prefrontal, lateral parietal, and posterior temporal cortices). Conversely, other properties of network connectivity, including default network integrity, were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease.

PMID: 30988201 [PubMed - as supplied by publisher]

Fusion of ULS Group Constrained High- and Low-Order Sparse Functional Connectivity Networks for MCI Classification.

Mon, 04/15/2019 - 18:00

Fusion of ULS Group Constrained High- and Low-Order Sparse Functional Connectivity Networks for MCI Classification.

Neuroinformatics. 2019 Apr 13;:

Authors: Li Y, Liu J, Peng Z, Sheng C, Kim M, Yap PT, Wee CY, Shen D

Abstract
Functional connectivity networks, derived from resting-state fMRI data, have been found as effective biomarkers for identifying mild cognitive impairment (MCI) from healthy elderly. However, the traditional functional connectivity network is essentially a low-order network with the assumption that the brain activity is static over the entire scanning period, ignoring temporal variations among the correlations derived from brain region pairs. To overcome this limitation, we proposed a new type of sparse functional connectivity network to precisely describe the relationship of temporal correlations among brain regions. Specifically, instead of using the simple pairwise Pearson's correlation coefficient as connectivity, we first estimate the temporal low-order functional connectivity for each region pair based on an ULS Group constrained-UOLS regression algorithm, where a combination of ultra-least squares (ULS) criterion with a Group constrained topology structure detection algorithm is applied to detect the topology of functional connectivity networks, aided by an Ultra-Orthogonal Least Squares (UOLS) algorithm to estimate connectivity strength. Compared to the classical least squares criterion which only measures the discrepancy between the observed signals and the model prediction function, the ULS criterion takes into consideration the discrepancy between the weak derivatives of the observed signals and the model prediction function and thus avoids the overfitting problem. By using a similar approach, we then estimate the high-order functional connectivity from the low-order connectivity to characterize signal flows among the brain regions. We finally fuse the low-order and the high-order networks using two decision trees for MCI classification. Experimental results demonstrate the effectiveness of the proposed method on MCI classification.

PMID: 30982183 [PubMed - as supplied by publisher]

Functional resting-state brain connectivity is accompanied by dynamic correlations of application-dependent [18F]FDG PET-tracer fluctuations.

Mon, 04/15/2019 - 18:00

Functional resting-state brain connectivity is accompanied by dynamic correlations of application-dependent [18F]FDG PET-tracer fluctuations.

Neuroimage. 2019 Apr 11;:

Authors: Amend M, Ionescu TM, Di X, Pichler BJ, Biswal BB, Wehrl HF

Abstract
Brain function is characterized by a convolution of various biochemical and physiological processes, raising the interest whether resting-state functional connectivity derived from hemodynamic scales shows underlying metabolic synchronies. Increasing evidence suggests that metabolic connectivity based on glucose consumption associated PET recordings may serve as a marker of cognitive functions and neuropathologies. However, to what extent fMRI-derived resting-state brain connectivity can also be characterized based on dynamic fluctuations of glucose metabolism and how metabolic connectivity is influenced by [18F]FDG pharmacokinetics remains unsolved. Simultaneous PET/MRI measurements were performed in a total of 26 healthy male Lewis rats. Simultaneously to resting-state fMRI scans, one cohort (n = 15) received classical bolus [18F]FDG injections and dynamic PET images were recorded. In a second cohort (n = 11) [18F]FDG was constantly infused over the entire functional PET/MRI scans. Resting-state fMRI and [18F]FDG-PET connectivity was evaluated using a graph-theory based correlation approach and compared on whole-brain level and for a default-mode network-like structure. Further, pharmacokinetic and tracer uptake influences on [18F]FDG-PET connectivity results were investigated based on the different PET protocols. By integrating simultaneous resting-state fMRI and dynamic [18F]FDG-PET measurements in the rat brain, we identified homotopic correlations between both modalities, suggesting an underlying synchrony between hemodynamic processes and glucose consumption. Furthermore, the presence of the prominent resting-state default-mode network-like structure was not only depicted on a functional scale but also from dynamic fluctuations of [18F]FDG. In addition, the present findings demonstrated strong pharmacokinetic and tracer uptake dependencies of [18F]FDG-PET connectivity outcomes. This study highlights the application of dynamic [18F]FDG-PET to study cognitive brain functions and to decode underlying brain networks in the resting-state. Thereby, PET-derived connectivity outcomes indicated strong dependencies on tracer application regimens and subsequent time-varying tracer pharmacokinetics.

PMID: 30981858 [PubMed - as supplied by publisher]

Abnormal coupling among spontaneous brain activity metrics and cognitive deficits in major depressive disorder.

Sun, 04/14/2019 - 20:59
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Abnormal coupling among spontaneous brain activity metrics and cognitive deficits in major depressive disorder.

J Affect Disord. 2019 Apr 08;252:74-83

Authors: Zhu J, Zhang Y, Zhang B, Yang Y, Wang Y, Zhang C, Zhao W, Zhu DM, Yu Y

Abstract
BACKGROUND: A variety of functional metrics derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been employed to explore spontaneous brain activity changes in major depressive disorder (MDD) and have enjoyed significant success in unraveling the neurobiological mechanisms underlying this disorder. However, it is unclear whether spatial and temporal coupling relationships among these rs-fMRI metrics are altered in MDD.
METHODS: 50 patients with MDD and 36 well-matched healthy controls underwent rs-fMRI scans. A dynamic analysis was applied to compute multiple frequently used metrics including fractional amplitude of low frequency fluctuations, regional homogeneity, voxel-mirrored homotopic connectivity, degree centrality and global signal connectivity. Kendall's W was used to calculate volume-wise (across voxels) and voxel-wise (across time windows) concordance among these metrics. Inter-group differences in the concordance and their associations with clinical and cognitive variables were tested.
RESULTS: Compared to healthy controls, patients with MDD showed decreased whole gray matter volume-wise concordance. Despite similar spatial distributions, quantitative comparison analysis revealed that MDD patients exhibited reduced voxel-wise concordance in multiple cortical and subcortical regions. Moreover, the lower concordance was associated with worse performances in prospective memory and sustained attention in the MDD group.
LIMITATIONS: The study design of fairly modest sample size did not allow us to perform a full analysis of the potential effects of medication and illness duration.
CONCLUSIONS: Our findings suggest that spatial and temporal decoupling of multiple resting-state brain activity metrics may help elucidate the neural mechanisms of cognitive deficits in depression.

PMID: 30981059 [PubMed - as supplied by publisher]

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

Sun, 04/14/2019 - 20:59
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Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

Proc Natl Acad Sci U S A. 2019 Apr 12;:

Authors: Yan CG, Chen X, Li L, Castellanos FX, Bai TJ, Bo QJ, Cao J, Chen GM, Chen NX, Chen W, Cheng C, Cheng YQ, Cui XL, Duan J, Fang YR, Gong QY, Guo WB, Hou ZH, Hu L, Kuang L, Li F, Li KM, Li T, Liu YS, Liu ZN, Long YC, Luo QH, Meng HQ, Peng DH, Qiu HT, Qiu J, Shen YD, Shi YS, Wang CY, Wang F, Wang K, Wang L, Wang X, Wang Y, Wu XP, Wu XR, Xie CM, Xie GR, Xie HY, Xie P, Xu XF, Yang H, Yang J, Yao JS, Yao SQ, Yin YY, Yuan YG, Zhang AX, Zhang H, Zhang KR, Zhang L, Zhang ZJ, Zhou RB, Zhou YT, Zhu JJ, Zou CJ, Si TM, Zuo XN, Zhao JP, Zang YF

Abstract
Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

PMID: 30979801 [PubMed - as supplied by publisher]

Ventral attention-network effective connectivity predicts individual differences in adolescent depression.

Sat, 04/13/2019 - 20:58
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Ventral attention-network effective connectivity predicts individual differences in adolescent depression.

J Affect Disord. 2019 Apr 08;252:55-59

Authors: Liu J, Xu P, Zhang J, Jiang N, Li X, Luo Y

Abstract
BACKGROUND: Stimulus-driven negative attention bias is a central deficit in depression and might play an important role in vulnerability to depression Adolescents are susceptible to depression. Thus, investigating the neural correlates of attention bias in adolescents is a critical step for identifying neural markers of early onset of depression. Previous studies have shown that the ventral attention network (VAN), which includes bilateral ventrolateral prefrontal cortex (VLPFC) and bilateral temporal-parietal junction (TPJ), is the key brain network for stimulus-driven attention. However, the relationship between depression and effective connectivity within the VAN in adolescents is poorly understood.
METHOD: We employed resting-state fMRI to assess the relationship between directional effective connectivity within the VAN and depression scores in 216 healthy adolescents.
RESULTS: Using stochastic dynamic modeling, we found that individuals who exhibited higher self-reported depression showed stronger effective connectivity between right VLPFC and left TPJ within the VAN.
LIMITATION: The level of depression in this study was assessed with self-reported questionnaire. This measure might be more influenced by current mood in adolescents than that in adults. Future studies should emplo more objective measures to index levels of depression.
CONCLUSIONS: Our findings indicate that effective connectivity between right VLPFC and left TPJ could at least partially serve as a biomarker for bottom-up processing of depression in adolescents.

PMID: 30978625 [PubMed - as supplied by publisher]

Phasic alerting effects on visual processing speed are associated with intrinsic functional connectivity in the cingulo-opercular network.

Sat, 04/13/2019 - 20:58
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Phasic alerting effects on visual processing speed are associated with intrinsic functional connectivity in the cingulo-opercular network.

Neuroimage. 2019 Apr 09;:

Authors: Haupt M, Ruiz-Rizzo AL, Sorg C, Finke K

Abstract
Phasic alertness refers to short-lived increases in the brain's "state of readiness", and thus to optimized performance following warning cues. Parametric modelling of whole report task performance based on the computational theory of visual attention (TVA) has demonstrated that visual processing speed is increased in such cue compared to no-cue conditions. Furthermore, with respect to the underlying neural mechanisms, individual visual processing speed has been related to intrinsic functional connectivity (iFC) within the cingulo-opercular network, suggesting that this network's iFC is relevant for the tonic maintenance of an appropriate readiness or alertness state. In the present study, we asked whether iFC in the cingulo-opercular network is also related to the individual ability to actively profit from warning cues, i.e. to the degree of phasic alerting. We obtained resting-state functional magnetic resonance imaging (rs-fMRI) data from 32 healthy young participants and combined an independent component analysis of rs-fMRI time courses and dual regression approach to determine iFC in the cingulo-opercular network. In a separate behavioural testing session, we parametrically assessed the effects of auditory phasic alerting cues on visual processing speed in a TVA-based whole report paradigm. A voxel-wise multiple regression revealed that higher individual phasic alerting effects on visual processing speed were significantly associated with lower iFC in the cingulo-opercular network, with a peak in the left superior orbital gyrus. As phasic alertness was neither related to iFC in other attention-relevant, auditory, or visual networks nor associated with any inter-network connectivity pattern, the results suggest that the individual profit in visual processing speed gained from phasic alerting is primarily associated with iFC in the cingulo-opercular network.

PMID: 30978493 [PubMed - as supplied by publisher]

Causal Interactions in Human Amygdala Cortical Networks across the Lifespan.

Sat, 04/13/2019 - 20:58
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Causal Interactions in Human Amygdala Cortical Networks across the Lifespan.

Sci Rep. 2019 Apr 11;9(1):5927

Authors: Jiang Y, Tian Y, Wang Z

Abstract
There is growing evidence that the amygdala serves as the base for dealing with complex human social communication and emotion. Although amygdalar networks plays a central role in these functions, causality connectivity during the human lifespan between amygdalar subregions and their corresponding perception network (PerN), affiliation network (AffN) and aversion network (AveN) remain largely unclear. Granger causal analysis (GCA), an approach to assess directed functional interactions from time series data, was utilized to investigated effective connectivity between amygdalar subregions and their related networks as a function of age to reveal the maturation and degradation of neural circuits during development and ageing in the present study. For each human resting functional magnetic resonance imaging (fMRI) dataset, the amygdala was divided into three subareas, namely ventrolateral amygdala (VLA), medial amygdala (MedA) and dorsal amygdala (DorA), by using resting-state functional connectivity, from which the corresponding networks (PerN, AffN and AveN) were extracted. Subsequently, the GC interaction of the three amygdalar subregions and their associated networks during life were explored with a generalised linear model (GLM). We found that three causality flows significantly varied with age: the GC of VLA → PerN showed an inverted U-shaped trend with ageing; the GC of MedA→ AffN had a U-shaped trend with ageing; and the GC of DorA→ AveN decreased with ageing. Moreover, during ageing, the above GCs were significantly correlated with Social Responsiveness Scale (SRS) and State-Trait Anxiety Inventory (STAI) scores. In short, PerN, AffN and AveN associated with the amygdalar subregions separately presented different causality connectivity changes with ageing. These findings provide a strong constituent framework for normal and neurological diseases associated with social disorders to analyse the neural basis of social behaviour during life.

PMID: 30976115 [PubMed - in process]

Neural Correlates of Cognitive-Attentional Syndrome: An fMRI Study on Repetitive Negative Thinking Induction and Resting State Functional Connectivity.

Sat, 04/13/2019 - 02:56
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Neural Correlates of Cognitive-Attentional Syndrome: An fMRI Study on Repetitive Negative Thinking Induction and Resting State Functional Connectivity.

Front Psychol. 2019;10:648

Authors: Kowalski J, Wypych M, Marchewka A, Dragan M

Abstract
Aim: Cognitive-attentional syndrome (CAS) is the main factor underlying depressive and anxiety disorders in the metacognitive approach to psychopathology and psychotherapy. This study explore neural correlates of this syndrome during induced negative thinking, abstract thinking, and resting states.
Methods: n = 25 people with high levels of CAS and n = 33 people with low levels of CAS were chosen from a population-based sample (N = 1225). These groups filled-in a series of measures of CAS, negative affect, and psychopathology; they also underwent a modified rumination induction procedure and a resting state fMRI session. Resonance imaging data were analyzed using static general linear model and functional connectivity approaches.
Results: The two groups differed with large effect sizes on all used measures of CAS, negative affect, and psychopathology. We did not find any group differences in general linear model analyses. Functional connectivity analyses showed that high levels of CAS were related to disrupted patterns of connectivity within and between various brain networks: the default mode network, the salience network, and the central executive network.
Conclusion: We showed that low- and high-CAS groups differed in functional connectivity during induced negative and abstract thinking and also in resting state fMRI. Overall, our results suggest that people with high levels of CAS tend to have disrupted neural processing related to self-referential processing, task-oriented processing, and emotional processing.

PMID: 30971987 [PubMed]

Loss of Parietal Memory Network Integrity in Alzheimer's Disease.

Sat, 04/13/2019 - 02:56
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Loss of Parietal Memory Network Integrity in Alzheimer's Disease.

Front Aging Neurosci. 2019;11:67

Authors: Hu Y, Du W, Zhang Y, Li N, Han Y, Yang Z

Abstract
A functional brain network, termed the parietal memory network (PMN), has been shown to reflect the familiarity of stimuli in both memory encoding and retrieval. The function of this network has been separated from the commonly investigated default mode network (DMN) in both resting-state fMRI and task-activations. This study examined the deficit of the PMN in Alzheimer's disease (AD) patients using resting-state fMRI and independent component analysis (ICA) and investigated its diagnostic value in identifying AD patients. The DMN was also examined as a reference network. In addition, the robustness of the findings was examined using different types of analysis methods and parameters. Our results showed that the integrity as an intrinsic connectivity network for the PMN was significantly decreased in AD and this feature showed at least equivalent predictive ability to that for the DMN. These findings were robust to varied methods and parameters. Our findings suggest that the intrinsic connectivity of the PMN is disrupted in AD and further call for considering the PMN and the DMN separately in clinical neuroimaging studies.

PMID: 30971912 [PubMed]

Selected Topics Relating to Functional MRI Study of the Brain.

Sat, 04/13/2019 - 02:56
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Selected Topics Relating to Functional MRI Study of the Brain.

Keio J Med. 2019 Apr 11;:

Authors: Ogawa S, Sung YW

Abstract
The authors selected some interesting current topics among many in the field of functional MRI (fMRI) of the brain. The selection was based on authours' immediate interests in exploring these aspects further; the topics are presented and discussed along with their perspectives. If progress can be made in these areas, it would be very advantageous to the field of brain research. The topics are (I) Detectable MRI signals in response to functional activity of the brain, including the current status of neurocurrent MRI; (II) Vascular-dependent and vascular-independent MRI signals, leading to the distinction of functional and structural MRI; (III) Functional specificity and functional connectivity of local sites, including differences between task-fMRI and resting state fMRI; (IV) Functional networks: an example of application to assessing the vocational aptitude test by fMRI; (V) Neural oscillation relevant to the formation of fMRI signals and of networks; (VI) Upgrading fMRI to "information-content-reflecting" fMRI, discussed as one of the prospects of near-future fMRI.

PMID: 30971631 [PubMed - as supplied by publisher]

Recent advances in the neurosurgical treatment of pediatric epilepsy: JNSPG 75th Anniversary Invited Review Article

Thu, 04/11/2019 - 20:55
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Recent advances in the neurosurgical treatment of pediatric epilepsy: JNSPG 75th Anniversary Invited Review Article

J Neurosurg Pediatr. 2019 Apr 05;23(4):411-421

Authors: Roland JL, Smyth MD

Abstract
The field of epilepsy surgery has seen tremendous growth in recent years. Innovative new devices have driven much of this growth, but some has been driven by revisions of existing products. Devices have also helped to rejuvenate existing procedures, as in the case of robotic assistance for electrode placement for stereo-electroencephalography, and these devices have brought significant attention along with their introduction. Other devices, such as responsive neurostimulators or laser interstitial thermal therapy systems, have introduced novel treatment modalities and broadened the surgical indications. Collectively, these advances are rapidly changing much of the landscape in the world of pediatric neurosurgery for medically refractory epilepsy. The foundations for indications for neurosurgical intervention are well supported in strong research data, which has also been expanded in recent years. In this article, the authors review advances in the neurosurgical treatment of pediatric epilepsy, beginning with trials that have repeatedly demonstrated the value of neurosurgical procedures for medically refractory epilepsy and following with several recent advances that are largely focused on less-invasive intervention. ABBREVIATIONS AED = antiepileptic drug; ANT = anterior nucleus of the thalamus; BOLD = blood oxygen level dependent; CCEP = cortico-cortical evoked potential; DBS = deep brain stimulation; ECoG = electrocorticography; ERSET = Early Randomized Surgical Epilepsy Trial; FCD = focal cortical dysplasia; HH = hypothalamic hamartoma; LITT = laser interstitial thermal therapy; RCT = randomized controlled trial; r-fMRI = resting-state functional MRI; RNS = responsive neurostimulation; SEEG = stereo-electroencephalography; VNS = vagus nerve stimulation.

PMID: 30970205 [PubMed - as supplied by publisher]