New resting-state fMRI related studies at PubMed

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Sensorimotor Connectivity after Motor Exercise with Neurofeedback in Post-Stroke Patients with Hemiplegia.

Tue, 07/30/2019 - 10:20

Sensorimotor Connectivity after Motor Exercise with Neurofeedback in Post-Stroke Patients with Hemiplegia.

Neuroscience. 2019 Jul 26;:

Authors: Tsuchimoto S, Shindo K, Hotta F, Hanakawa T, Liu M, Ushiba J

Abstract
Impaired finger motor function in post-stroke hemiplegia is a debilitating condition with no evidence-based or accessible treatments. Here, we evaluated the neurophysiological effectiveness of direct brain control of robotic exoskeleton that provides movement support contingent with brain activity. To elucidate the mechanisms underlying the neurofeedback intervention, we assessed resting-state functional connectivity with functional magnetic resonance imaging (rsfcMRI) between the ipsilesional sensory and motor cortices before and after a single 1-h intervention. Eighteen stroke patients were randomly assigned to crossover interventions in a double-blind and sham-controlled design. One patient dropped out midway through the study, and seventeen patients were included in this analysis. Interventions involved motor imagery, robotic assistance, and neuromuscular electrical stimulation administered to a paretic finger. The neurofeedback intervention delivered stimulations contingent on desynchronized ipsilesional electroencephalographic (EEG) oscillations during imagined movement, and the control intervention delivered sensorimotor stimulations that were independent of EEG oscillations. There was a significant time × intervention interaction in rsfcMRI in the ipsilesional sensorimotor cortex. Post-hoc analysis showed a larger gain in increased functional connectivity during the neurofeedback intervention. Although the neurofeedback intervention delivered fewer total sensorimotor stimulations compared to the sham-control, rsfcMRI in the ipsilesional sensorimotor cortices was increased during the neurofeedback intervention compared to the sham-control. Higher coactivation of the sensory and motor cortices during neurofeedback intervention enhanced rsfcMRI in the ipsilesional sensorimotor cortices. This study showed neurophysiological evidence that EEG-contingent neurofeedback is a promising strategy to induce intrinsic ipsilesional sensorimotor reorganization, supporting the importance of integrating closed-loop sensorimotor processing at a neurophysiological level.

PMID: 31356896 [PubMed - as supplied by publisher]

Decreased stimulus-driven connectivity of the primary visual cortex during visual motion stimulation in amnestic mild cognitive impairment: An fMRI study.

Tue, 07/30/2019 - 10:20

Decreased stimulus-driven connectivity of the primary visual cortex during visual motion stimulation in amnestic mild cognitive impairment: An fMRI study.

Neurosci Lett. 2019 Jul 26;:134402

Authors: Yamasaki T, Aso T, Kaseda Y, Mimori Y, Doi H, Matsuoka N, Takamiya N, Torii T, Takahashi T, Ohshita T, Yamashita H, Doi H, Inamizu S, Chatani H, Tobimatsu S

Abstract
Motion perceptual deficits are common in Alzheimer's disease (AD). Although the posterior parietal cortex is thought to play a critical role in these deficits, it is currently unclear whether the primary visual cortex (V1) contributes to these deficits in AD. To elucidate this issue, we investigated the net activity or connectivity within V1 in 17 amnestic mild cognitive impairment (aMCI) patients, 17 AD patients and 17 normal controls (NC) using functional magnetic resonance imaging (fMRI). fMRI was recorded under two conditions: visual motion stimulation and resting-state. The net activity or connectivity within V1 extracted by independent component analysis (ICA) was significantly increased during visual motion stimuli compared with that of the resting-state condition in NC, but not in aMCI or AD patients. These findings suggest the alteration of the net activity or connectivity within V1, which may contribute to the previously reported motion perceptual deficits in aMCI and AD. Therefore, the decreased net V1 activity measured as the strength of the ICA component may provide a new disease biomarker for early detection of AD.

PMID: 31356844 [PubMed - as supplied by publisher]

Predicting the Post-therapy Severity Level (UPDRS-III) of Patients With Parkinson's Disease After Drug Therapy by Using the Dynamic Connectivity Efficiency of fMRI.

Tue, 07/30/2019 - 10:20

Predicting the Post-therapy Severity Level (UPDRS-III) of Patients With Parkinson's Disease After Drug Therapy by Using the Dynamic Connectivity Efficiency of fMRI.

Front Neurol. 2019;10:668

Authors: Li X, Xiong Y, Liu S, Zhou R, Hu Z, Tong Y, He L, Niu Z, Ma Y, Guo H

Abstract
Parkinson's disease (PD) is a multi-systemic disease in the brain arising from the dysfunction of several neural networks. The diagnosis and treatment of PD have gained more attention for clinical researchers. While there have been many fMRI studies about functional topological changes of PD patients, whether the dynamic changes of functional connectivity can predict the drug therapy effect is still unclear. The primary objective of this study was to assess whether large-scale functional efficiency changes of topological network are detectable in PD patients, and to explore whether the severity level (UPDRS-III) after drug treatment can be predicted by the pre-treatment resting-state fMRI (rs-fMRI). Here, we recruited 62 Parkinson's disease patients and calculated the dynamic nodal efficiency networks based on rs-fMRI. With connectome-based predictive models using the least absolute shrinkage and selection operator, we demonstrated that the dynamic nodal efficiency properties predict drug therapy effect well. The contributed regions for the prediction include hippocampus, post-central gyrus, cingulate gyrus, and orbital gyrus. Specifically, the connections between hippocampus and cingulate gyrus, hippocampus and insular gyrus, insular gyrus, and orbital gyrus are positively related to the recovery (post-therapy severity level) after drug therapy. The analysis of these connection features may provide important information for clinical treatment of PD patients.

PMID: 31354605 [PubMed]

Increased Temporal Dynamics of Intrinsic Brain Activity in Sensory and Perceptual Network of Schizophrenia.

Tue, 07/30/2019 - 10:20

Increased Temporal Dynamics of Intrinsic Brain Activity in Sensory and Perceptual Network of Schizophrenia.

Front Psychiatry. 2019;10:484

Authors: Zhang Y, Guo G, Tian Y

Abstract
Schizophrenic subject is thought as a self-disorder patient related with abnormal brain functional network. It has been hypothesized that self-disorder is associated with the deficient functional integration of multisensory body signals in schizophrenic subjects. To further verify this assumption, 53 chronic schizophrenic subjects and 67 healthy subjects were included in this study and underwent resting-state functional magnetic resonance imaging. The data-driven methods, whole-brain temporal variability of fractional amplitude of low-frequency fluctuations and regional homogeneity (ReHo), were used to investigate dynamic local functional connectivity and dynamic local functional activity changes in schizophrenic subjects. Patients with schizophrenia exhibited increased temporal variability ReHo and fractional amplitude of low-frequency fluctuations across time windows within sensory and perception network (such as occipital gyrus, precentral and postcentral gyri, superior temporal gyrus, and thalamus). Critically, the increased dynamic ReHo of thalamus is significantly correlated with positive and total symptom of schizophrenic subjects. Our findings revealed that deficit in sensory and perception functional networks might contribute to neural physiopathology of self-disorder in schizophrenic subjects.

PMID: 31354546 [PubMed]

Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity.

Tue, 07/30/2019 - 10:20

Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity.

Front Psychiatry. 2019;10:482

Authors: Li S, Hu N, Zhang W, Tao B, Dai J, Gong Y, Tan Y, Cai D, Lui S

Abstract
Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.

PMID: 31354545 [PubMed]

Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study.

Tue, 07/30/2019 - 10:20

Topological Modification of Brain Networks Organization in Children With High Intelligence Quotient: A Resting-State fMRI Study.

Front Hum Neurosci. 2019;13:241

Authors: Suprano I, Delon-Martin C, Kocevar G, Stamile C, Hannoun S, Achard S, Badhwar A, Fourneret P, Revol O, Nusbaum F, Sappey-Marinier D

Abstract
The idea that intelligence is embedded not only in a single brain network, but instead in a complex, well-optimized system of complementary networks, has led to the development of whole brain network analysis. Using graph theory to analyze resting-state functional MRI data, we investigated the brain graph networks (or brain networks) of high intelligence quotient (HIQ) children. To this end, we computed the "hub disruption index κ," an index sensitive to graph network modifications. We found significant topological differences in the integration and segregation properties of brain networks in HIQ compared to standard IQ children, not only for the whole brain graph, but also for each hemispheric graph, and for the homotopic connectivity. Moreover, two profiles of HIQ children, homogenous and heterogeneous, based on the differences between the two main IQ subscales [verbal comprehension index (VCI) and perceptual reasoning index (PRI)], were compared. Brain network changes were more pronounced in the heterogeneous than in the homogeneous HIQ subgroups. Finally, we found significant correlations between the graph networks' changes and the full-scale IQ (FSIQ), as well as the subscales VCI and PRI. Specifically, the higher the FSIQ the greater was the brain organization modification in the whole brain, the left hemisphere, and the homotopic connectivity. These results shed new light on the relation between functional connectivity topology and high intelligence, as well as on different intelligence profiles.

PMID: 31354458 [PubMed]

Characterizing the Dynamical Complexity Underlying Meditation.

Tue, 07/30/2019 - 10:20

Characterizing the Dynamical Complexity Underlying Meditation.

Front Syst Neurosci. 2019;13:27

Authors: Escrichs A, Sanjuán A, Atasoy S, López-González A, Garrido C, Càmara E, Deco G

Abstract
Over the past 2,500 years, contemplative traditions have explored the nature of the mind using meditation. More recently, neuroimaging research on meditation has revealed differences in brain function and structure in meditators. Nevertheless, the underlying neural mechanisms are still unclear. In order to understand how meditation shapes global activity through the brain, we investigated the spatiotemporal dynamics across the whole-brain functional network using the Intrinsic Ignition Framework. Recent neuroimaging studies have demonstrated that different states of consciousness differ in their underlying dynamical complexity, i.e., how the broadness of communication is elicited and distributed through the brain over time and space. In this work, controls and experienced meditators were scanned using functional magnetic resonance imaging (fMRI) during resting-state and meditation (focused attention on breathing). Our results evidenced that the dynamical complexity underlying meditation shows less complexity than during resting-state in the meditator group but not in the control group. Furthermore, we report that during resting-state, the brain activity of experienced meditators showed higher metastability (i.e., a wider dynamical regime over time) than the one observed in the control group. Overall, these results indicate that the meditation state operates in a different dynamical regime compared to the resting-state.

PMID: 31354439 [PubMed]

Functional Connectivity Within the Gustatory Network Is Altered by Fat Content and Oral Fat Sensitivity - A Pilot Study.

Tue, 07/30/2019 - 10:20

Functional Connectivity Within the Gustatory Network Is Altered by Fat Content and Oral Fat Sensitivity - A Pilot Study.

Front Neurosci. 2019;13:725

Authors: Frank-Podlech S, Heinze JM, Machann J, Scheffler K, Camps G, Fritsche A, Rosenberger M, Hinrichs J, Veit R, Preissl H

Abstract
Background: The amount of fat in ingested food dictates specific activation patterns in the brain, particularly in homeostatic and reward-related areas. Taste-specific brain activation changes have also been shown and the sensitivity to the oral perception of fat is associated with differential eating behavior and physiological parameters. The association between oral fat sensitivity and neuronal network functions has, however, not yet been defined. Objective: We aimed to investigate the association between fat-dependent neuronal functional connectivity patterns and oral fat sensitivity. Design: To investigate the underlying changes in network dynamics caused by fat intake, we measured resting-state functional connectivity in 11 normal-weight male participants before and after a high- vs. a low-fat meal on two separate study days. Oral fat sensitivity was also measured on both days. We used a high-resolution functional magnetic resonance imaging (MRI) sequence to measure any connectivity changes in networks with the seed in the brainstem (nucleus tractus solitarii, NTS), in homeostatic (hypothalamus) and in reward regions (ventral and dorsal striatum). Seed-based functional connectivity (FC) maps were analyzed using factorial analyses and correlation analyses with oral fat sensitivity were also performed. Results: Regardless of fat content, FC between NTS and reward and gustatory areas was lower after ingestion. Oral fat sensitivity was positively correlated with FC between homeostatic regions and limbic areas in the high-fat condition, but negatively correlated with FC between the dorsal striatum and somatosensory regions in the low-fat condition. Conclusion: Our results show the interaction of oral fat sensitivity with the network based neuronal processing of high- vs. low-fat meals. Variations in neuronal connectivity network patterns might therefore be a possible moderator of the association of oral fat sensitivity and eating behavior.

PMID: 31354424 [PubMed]

Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis.

Tue, 07/30/2019 - 10:20

Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis.

Front Neurosci. 2019;13:618

Authors: Valsasina P, Hidalgo de la Cruz M, Filippi M, Rocca MA

Abstract
Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called "sliding windows," in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.

PMID: 31354402 [PubMed]

Machine learning techniques in a structural and functional MRI diagnostic approach in schizophrenia: a systematic review.

Tue, 07/30/2019 - 10:20

Machine learning techniques in a structural and functional MRI diagnostic approach in schizophrenia: a systematic review.

Neuropsychiatr Dis Treat. 2019;15:1605-1627

Authors: de Filippis R, Carbone EA, Gaetano R, Bruni A, Pugliese V, Segura-Garcia C, De Fazio P

Abstract
Background: Diagnosis of schizophrenia (SCZ) is made exclusively clinically, since specific biomarkers that can predict the disease accurately remain unknown. Machine learning (ML) represents a promising approach that could support clinicians in the diagnosis of mental disorders.
Objectives: A systematic review, according to the PRISMA statement, was conducted to evaluate its accuracy to distinguish SCZ patients from healthy controls.
Methods: We systematically searched PubMed, Embase, MEDLINE, PsychINFO and the Cochrane Library through December 2018 using generic terms for ML techniques and SCZ without language or time restriction. Thirty-five studies were included in this review: eight of them used structural neuroimaging, twenty-six used functional neuroimaging and one both, with a minimum accuracy >60% (most of them 75-90%). Sensitivity, Specificity and accuracy were extracted from each publication or obtained directly from authors.
Results: Support vector machine, the most frequent technique, if associated with other ML techniques achieved accuracy close to 100%. The prefrontal and temporal cortices appeared to be the most useful brain regions for the diagnosis of SCZ. ML analysis can efficiently detect significantly altered brain connectivity in patients with SCZ (eg, default mode network, visual network, sensorimotor network, frontoparietal network and salience network).
Conclusion: The greater accuracy demonstrated by these predictive models and the new models resulting from the integration of multiple ML techniques will be increasingly decisive for early diagnosis and evaluation of the treatment response and to establish the prognosis of patients with SCZ. To achieve a real benefit for patients, the future challenge is to reach an accurate diagnosis not only through clinical evaluation but also with the aid of ML algorithms.

PMID: 31354276 [PubMed]

Early second-line therapy is associated with improved episodic memory in anti-NMDA receptor encephalitis.

Tue, 07/30/2019 - 10:20
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Early second-line therapy is associated with improved episodic memory in anti-NMDA receptor encephalitis.

Ann Clin Transl Neurol. 2019 Jul;6(7):1202-1213

Authors: Wang K, Chen Z, Wu D, Ding Q, Zheng X, Wang J, Ji C, Luo B

Abstract
OBJECTIVE: To investigate whether the early administration of intravenous second-line immunotherapy correlates with improved long-term cognition and the potential mechanisms via imaging in adult patients with moderate-to-severe anti-N-methyl-D-aspartate (NMDA) receptor encephalitis.
METHODS: Sixteen adult patients with moderate-to-severe anti-NMDA receptor encephalitis past the acute stage and 15 healthy controls (HCs) performed a set of comprehensive neuropsychological tests, and underwent a resting-state fMRI study to analyze resting state functional connectivity (FC). In addition, correlation analyses were performed between hippocampal FC and cognitive performance. All patients were received intravenous first-line immunotherapy, and nine of them were also given intravenous second-line immunotherapy within 3 months of disease onset.
RESULTS: The patients who only received first-line immunotherapy showed significant verbal episodic memory impairments compared with HCs and those who received second-line immunotherapy, while no significant differences were noted between the patients with second-line immunotherapy and the HCs. In line with the results of neuropsychological tests, significant changes in bilateral hippocampal FC were observed in the patients who only received first-line immunotherapy compared with both HCs and those who received second-line immunotherapy. However, no significant differences in hippocampal FC were observed in the patients with second-line immunotherapy compared with the HCs. Importantly, hippocampal-medial prefrontal cortex (mPFC) connectivity positively correlated with memory performance.
INTERPRETATION: In the long term, early administration of intravenous second-line immunotherapy may be associated with more favorable verbal episodic memory outcomes in patients with moderate-to-severe anti-NMDA receptor encephalitis. These results may provide some evidence and guidance for the use of immunotherapy in this population.

PMID: 31353868 [PubMed - in process]

Mindfulness-based cognitive therapy is associated with distinct resting-state neural patterns in patients with generalized anxiety disorder.

Tue, 07/30/2019 - 10:20
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Mindfulness-based cognitive therapy is associated with distinct resting-state neural patterns in patients with generalized anxiety disorder.

Asia Pac Psychiatry. 2019 Jul 28;:e12368

Authors: Zhao XR, Chen ZF, Kang CY, Liu RX, Bai JY, Cao YP, Cheng YQ, Xu XF, Zhang YL

Abstract
INTRODUCTION: Mindfulness-based cognitive therapy (MBCT) may be effective for generalized anxiety disorder (GAD); however, the neural mechanism is poorly understood. In this study, we examined the potential neural mechanisms through which MBCT may reduce anxiety in patients with mild-to-moderate GAD.
METHODS: Eight weekly group MBCT sessions (2 h each) were conducted with 32 GAD patients. Resting-state functional magnetic resonance imaging (fMRI) was used, along with clinical and mindfulness profiles. A regional homogeneity (ReHo) approach was applied, and resting-state functional connectivity in the default mode network (DMN) using the posterior cingulate cortex (PCC) seed was examined.
RESULTS: MBCT reduced the anxiety and increased the mindfulness abilities of patients. After MBCT, patients had reduced ReHo in broad regions of the limbic system, along with increased DMN functional connectivity in the anterior cingulate cortex (ACC) and bilateral insula. Overlapping regions of reduced ReHo and increased DMN functional connectivity were observed in the mid-cingulate cortex (MCC) and bilateral insula. The increased PCC-ACC and PCC-insula functional connectivity following MBCT were related to anxiety improvements, suggesting a potential therapeutic mechanism for mindfulness-based therapies.
DISCUSSION: Group MBCT treatment appears to have effectively reduced anxiety symptoms in patients with mild-to-moderate GAD. Activation and functional connectivity appeared significantly different across some limbic regions after MBCT treatment. The salience network showed reduced ReHo and increased connectivity to the PCC. The DMN functional connectivity of the MCC may indicate reduced anxiety and improved mindfulness in GAD patients.

PMID: 31353828 [PubMed - as supplied by publisher]

Can Resting-State Functional MRI Predict Response to Cholinesterase Inhibitors in Individuals with Cognitive Impairment?

Tue, 07/30/2019 - 10:20
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Can Resting-State Functional MRI Predict Response to Cholinesterase Inhibitors in Individuals with Cognitive Impairment?

Radiology. 2018 12;289(3):786-787

Authors: Chiang GC

PMID: 30204074 [PubMed - indexed for MEDLINE]

Alterations in Regional Homogeneity Assessed by fMRI in Patients with Migraine Without Aura.

Mon, 07/29/2019 - 15:40
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Alterations in Regional Homogeneity Assessed by fMRI in Patients with Migraine Without Aura.

J Med Syst. 2019 Jul 27;43(9):298

Authors: Chen C, Yan M, Yu Y, Ke J, Xu C, Guo X, Lu H, Wang X, Hu L, Wang J, Ni J, Zhao H

Abstract
The aim of this study was to investigate the alterations in regional homogeneity assessed by fMRI in patients with migraine without aura (MWoA). Fifty-six eligible MWoA patients and 32 matched healthy volunteers were enrolled in this study. MWoA patients were divided into three groups according to the headache days per month within 3 months: infrequent episodic migraine (IEM) group, frequent episodic migraine (FEM) group, and chronic migraine (CM) group. Data collection and rest-state fMRI examination were performed in all cases. The ReHo method was used to analyze the blood oxygen level dependent (BLOD) signals of the adjacent voxels in the brain regions of each patient, and the consistency of their fluctuations in the sequences of same time. Compared with normal controls, ReHo values of bilateral thalami, right insula and right middle temporal gyrus increased and both precentral gyri decreased in the IEM group; ReHo values of bilateral thalami and the right middle temporal gyrus increased; ReHo values of both anterior cingulate cortex, precentral gyri and putamen decreased in the FEM group. Compared with control group, ReHo values of left olfactory cortex, right hippocampus, parahippocampal gyrus, suboccipital gyrus and precuneus increased, both precentral gyri, precuneus, putamen and anterior cingulate cortex decreased in the CM group. Compared with IEM group, ReHo values of both putamen, left middle frontal gyrus, right superior frontal gyrus increased, and the left precuneus decreased in the FEM group. Compared with FEM group, ReHo values of left olfactory and left precuneus increased, and the right superior frontal gyrus, insula, middle temporal gyrus, thalami, both superior temporal gyri decreased in the CM group. In the IEM group, the changes of function focus on the regions associated with coding, conduction and regulation of pain signals. In the FEM group, functional alterations mainly concentrated on the regions associated with pain regulation and emotion cognition. In the CM group, the changes focus on the regions related to spatial attention and cognition, affective disorders and pain feedback, which may be associated with migraine production, development and chronification.

PMID: 31352647 [PubMed - in process]

The superior longitudinal fasciculus and its functional triple-network mechanisms in brooding.

Mon, 07/29/2019 - 15:40
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The superior longitudinal fasciculus and its functional triple-network mechanisms in brooding.

Neuroimage Clin. 2019 Jul 19;24:101935

Authors: Pisner DA, Shumake J, Beevers CG, Schnyer DM

Abstract
Brooding, which refers to a repetitive focus on one's distress, is associated with functional connectivity within Default-Mode, Salience, and Executive-Control networks (DMN; SN; ECN), comprising the so-called "triple-network" of attention. Individual differences in brain structure that might perseverate dysfunctional connectivity of brain networks associated with brooding are less clear, however. Using diffusion and functional Magnetic Resonance Imaging, we explored multimodal relationships between brooding severity, white-matter microstructure, and resting-state functional connectivity in depressed adults (N = 32-44), and then examined whether findings directly replicated in a demographically-similar, independent sample (N = 36-45). Among the fully-replicated results, three core findings emerged. First, brooding severity is associated with functional integration and segregation of the triple-network, particularly with a Precuneal subnetwork of the DMN. Second, microstructural asymmetry of the Superior Longitudinal Fasciculus (SLF) provides a robust structural connectivity basis for brooding and may account for over 20% of its severity (Discovery: adj. R2 = 0.18; Replication: adj. R2 = 0.22; MSE = 0.06, Predictive R2 = 0.22). Finally, microstructure of the right SLF and auxiliary white-matter is associated with the functional connectivity correlates of brooding, both within and between components of the triple-network (Discovery: adj. R2 = 0.21; Replication: adj. R2 = 0.18; MSE = 0.03, Predictive R2 = 0.21-0.22). By cross-validating multimodal discovery with replication, the present findings help to reproducibly unify disparate perspectives of brooding etiology. Based on that synthesis, our study reformulates brooding as a microstructural-functional connectivity neurophenotype.

PMID: 31352219 [PubMed - as supplied by publisher]

Uncovering multi-site identifiability based on resting-state functional connectomes.

Mon, 07/29/2019 - 15:40
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Uncovering multi-site identifiability based on resting-state functional connectomes.

Neuroimage. 2019 Jul 25;:

Authors: Bari S, Amico E, Vike N, Talavage TM, Goñi J

Abstract
Multi-site studies are becoming important to increase statistical power, enhance generalizability, and to improve the likelihood of pooling relevant subgroups together-activities which are otherwise limited by the availability of subjects or funds at a single site. Even with harmonized imaging sequences, site-dependent variability can mask the advantages of these multi-site studies. The aim of this study was to assess multi-site reproducibility in resting-state functional connectivity "fingerprints", and to improve identifiability of functional connectomes. The individual fingerprinting of functional connectivity profiles is promising due to its potential as a robust neuroimaging biomarker with which to draw single-subject inferences. We evaluated, on two independent multi-site datasets, individual fingerprints in test-retest visit pairs within and across two sites and present a generalized framework based on principal component analysis to improve identifiability. Those principal components that maximized differential identifiability of a training dataset were used as an orthogonal connectivity basis to reconstruct the individual functional connectomes of training and validation sets. The optimally reconstructed functional connectomes showed a substantial improvement in individual fingerprinting of the subjects within and across the two sites and test-retest visit pairs relative to the original data. A notable increase in ICC values for functional edges and resting-state networks were also observed for reconstructed functional connectomes. Improvements in identifiability were not found to be affected by global signal regression. Post-hoc analyses assessed the effect of the number of fMRI volumes on identifiability and showed that multi-site differential identifiability was for all cases maximized after optimal reconstruction. Finally, the generalizability of the optimal set of orthogonal basis of each dataset was evaluated through a leave-one-out procedure. Overall, results demonstrate that the data-driven framework presented in this study systematically improves identifiability in resting-state functional connectomes in multi-site studies.

PMID: 31352124 [PubMed - as supplied by publisher]

In search of multimodal brain alterations in Alzheimer's and Binswanger's disease.

Mon, 07/29/2019 - 15:40
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In search of multimodal brain alterations in Alzheimer's and Binswanger's disease.

Neuroimage Clin. 2019 Jul 15;:101937

Authors: Fu Z, Iraji A, Caprihan A, Adair JC, Sui J, Rosenberg GA, Calhoun VD

Abstract
Structural and functional brain abnormalities have been widely identified in dementia, but with variable replicability and significant overlap. Alzheimer's disease (AD) and Binswanger's disease (BD) share similar symptoms and common brain changes that can confound diagnosis. In this study, we aimed to investigate correlated structural and functional brain changes in AD and BD by combining resting-state functional magnetic resonance imaging (fMRI) and diffusion MRI. A group independent component analysis was first performed on the fMRI data to extract 49 intrinsic connectivity networks (ICNs). Then we conducted a multi-set canonical correlation analysis on three features, functional network connectivity (FNC) between ICNs, fractional anisotropy (FA) and mean diffusivity (MD). Two inter-correlated components show significant group differences. The first component demonstrates distinct brain changes between AD and BD. AD shows increased cerebellar FNC but decreased thalamic and hippocampal FNC. Such FNC alterations are linked to the decreased corpus callosum FA. AD also has increased MD in the frontal and temporal cortex, but BD shows opposite alterations. The second component demonstrates specific brain changes in BD. Increased FNC is mainly between default mode and sensory regions, while decreased FNC is mainly within the default mode domain and related to auditory regions. The FNC changes are associated with FA changes in posterior/middle cingulum cortex and visual cortex and increased MD in thalamus and hippocampus. Our findings provide evidence of linked functional and structural deficits in dementia and suggest that AD and BD have both common and distinct changes in white matter integrity and functional connectivity.

PMID: 31351845 [PubMed - as supplied by publisher]

Discovering common change-point patterns in functional connectivity across subjects.

Sun, 07/28/2019 - 14:40
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Discovering common change-point patterns in functional connectivity across subjects.

Med Image Anal. 2019 Jul 22;58:101532

Authors: Dai M, Zhang Z, Srivastava A

Abstract
This paper studies change-points in human brain functional connectivity (FC) and seeks patterns that are common across multiple subjects under identical external stimulus. FC relates to the similarity of fMRI responses across different brain regions when the brain is simply resting or performing a task. While the dynamic nature of FC is well accepted, this paper develops a formal statistical test for finding change-points in times series associated with FC. It represents short-term connectivity by a symmetric positive-definite matrix, and uses a Riemannian metric on this space to develop a graphical method for detecting change-points in a time series of such matrices. It also provides a graphical representation of estimated FC for stationary subintervals in between the detected change-points. Furthermore, it uses a temporal alignment of the test statistic, viewed as a real-valued function over time, to remove inter-subject variability and to discover common change-point patterns across subjects. This method is illustrated using data from Human Connectome Project (HCP) database for multiple subjects and tasks.

PMID: 31351229 [PubMed - as supplied by publisher]

Resting-state connectivity reveals a role for sensorimotor systems in vocal emotional processing in children.

Sun, 07/28/2019 - 14:40
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Resting-state connectivity reveals a role for sensorimotor systems in vocal emotional processing in children.

Neuroimage. 2019 Jul 24;:116052

Authors: Correia AI, Branco P, Martins M, Reis AM, Martins N, Castro SL, Lima CF

Abstract
Voices are a primary source of emotional information in everyday interactions. Being able to process non-verbal vocal emotional cues, namely those embedded in speech prosody, impacts on our behaviour and communication. Extant research has delineated the role of temporal and inferior frontal brain regions for vocal emotional processing. A growing number of studies also suggest the involvement of the motor system, but little is known about such potential involvement. Using resting-state fMRI, we ask if the patterns of motor system intrinsic connectivity play a role in emotional prosody recognition in children. Fifty-five 8-year-old children completed an emotional prosody recognition task and a resting-state scan. Better performance in emotion recognition was predicted by a stronger connectivity between the inferior frontal gyrus (IFG) and motor regions including primary motor, lateral premotor and supplementary motor sites. This is mostly driven by the IFG pars triangularis and cannot be explained by differences in domain-general cognitive abilities. These findings indicate that individual differences in the engagement of sensorimotor systems, and in its coupling with inferior frontal regions, underpin variation in children's emotional speech perception skills. They suggest that sensorimotor and higher-order evaluative processes interact to aid emotion recognition, and have implications for models of vocal emotional communication.

PMID: 31351162 [PubMed - as supplied by publisher]

A graph representation of functional diversity of brain regions.

Sun, 07/28/2019 - 14:40
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A graph representation of functional diversity of brain regions.

Brain Behav. 2019 Jul 27;:e01358

Authors: Yin D, Chen X, Zeljic K, Zhan Y, Shen X, Yan G, Wang Z

Abstract
INTRODUCTION: Modern network science techniques are popularly used to characterize the functional organization of the brain. A major challenge in network neuroscience is to understand how functional characteristics and topological architecture are related in the brain. Previous task-based functional neuroimaging studies have uncovered a core set of brain regions (e.g., frontal and parietal) supporting diverse cognitive tasks. However, the graph representation of functional diversity of brain regions remains to be understood.
METHODS: Here, we present a novel graph measure, the neighbor dispersion index, to test the hypothesis that the functional diversity of a brain region is embodied by the topological dissimilarity of its immediate neighbors in the large-scale functional brain network.
RESULTS: We consistently identified in two independent and publicly accessible resting-state functional magnetic resonance imaging datasets that brain regions in the frontoparietal and salience networks showed higher neighbor dispersion index, whereas those in the visual, auditory, and sensorimotor networks showed lower neighbor dispersion index. Moreover, we observed that human fluid intelligence was associated with the neighbor dispersion index of dorsolateral prefrontal cortex, while no such association for the other metrics commonly used for characterizing network hubs was noticed even with an uncorrected p < .05.
CONCLUSIONS: This newly developed graph theoretical method offers fresh insight into the topological organization of functional brain networks and also sheds light on individual differences in human intelligence.

PMID: 31350830 [PubMed - as supplied by publisher]

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