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Frequency-Dependent Intrinsic Electrophysiological Functional Architecture of the Human Verbal Language Network.

Sat, 06/13/2020 - 23:01
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Frequency-Dependent Intrinsic Electrophysiological Functional Architecture of the Human Verbal Language Network.

Front Integr Neurosci. 2020;14:27

Authors: Coolen T, Wens V, Vander Ghinst M, Mary A, Bourguignon M, Naeije G, Peigneux P, Sadeghi N, Goldman S, De Tiège X

Abstract
Functional magnetic resonance imaging (fMRI) allowed the spatial characterization of the resting-state verbal language network (vLN). While other resting-state networks (RSNs) were matched with their electrophysiological equivalents at rest and could be spectrally defined, such correspondence is lacking for the vLN. This magnetoencephalography (MEG) study aimed at defining the spatio-spectral characteristics of the neuromagnetic intrinsic functional architecture of the vLN. Neuromagnetic activity was recorded at rest in 100 right-handed healthy adults (age range: 18-41 years). Band-limited power envelope correlations were performed within and across frequency bands (θ, α, β, and low γ) from a seed region placed in the left Broca's area, using static orthogonalization as leakage correction. K-means clustering was used to segregate spatio-spectral clusters of resting-state functional connectivity (rsFC). Remarkably, unlike other RSNs, within-frequency long-range rsFC from the left Broca's area was not driven by one main carrying frequency but was characterized by a specific spatio-spectral pattern segregated along the ventral (predominantly θ and α) and dorsal (β and low-γ bands) vLN streams. In contrast, spatial patterns of cross-frequency vLN functional integration were spectrally more widespread and involved multiple frequency bands. Moreover, the static intrinsic functional architecture of the neuromagnetic human vLN involved clearly left-hemisphere-dominant vLN interactions as well as cross-network interactions with the executive control network and postero-medial nodes of the DMN. Overall, this study highlighted the involvement of multiple modes of within and cross-frequency power envelope couplings at the basis of long-range electrophysiological vLN functional integration. As such, it lays the foundation for future works aimed at understanding the pathophysiology of language-related disorders.

PMID: 32528258 [PubMed]

Corrigendum: Increased Activation of Default Mode Network in Early Parkinson's With Excessive Daytime Sleepiness.

Sat, 06/13/2020 - 23:01
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Corrigendum: Increased Activation of Default Mode Network in Early Parkinson's With Excessive Daytime Sleepiness.

Front Neurosci. 2020;14:426

Authors: Ooi LQR, Wen MC, Ng SY, Chia NS, Chew IHM, Lee W, Xu Z, Hartono S, Tan EK, Chan LL, Tan LC

Abstract
[This corrects the article DOI: 10.3389/fnins.2019.01334.].

PMID: 32528240 [PubMed - in process]

A dataset of long-term consistency values of resting-state fMRI connectivity maps in a single individual derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol.

Thu, 06/11/2020 - 22:56
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A dataset of long-term consistency values of resting-state fMRI connectivity maps in a single individual derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol.

Data Brief. 2020 Aug;31:105699

Authors: Badhwar A, Collin-Verreault Y, Lussier D, Sharmarke H, Orban P, Urchs S, Chouinard I, Vogel J, Potvin O, Duchesne S, Bellec P

Abstract
The impact of multisite acquisition on resting-state functional MRI (rsfMRI) connectivity has recently gained attention. We provide consistency values (Pearson's correlation) between rsfMRI connectivity maps of an adult volunteer (Csub) scanned 25 times over 3.5 years at 13 sites using the Canadian Dementia Imaging Protocol (CDIP, www.cdip-pcid.ca). This dataset was generated as part of the following article: Multivariate consistency of resting-state fMRI connectivity maps acquired on a single individual over 2.5 years, 13 sites and 3 vendors [1]. Acquired on three 3T scanner vendors (GE, Siemens and Philips), the Csub dataset is part of an ongoing effort to monitor the quality and comparability of MRI data collected across the Canadian Consortium on Neurodegeneration in Aging (CCNA) imaging network. The participant was scanned 25 times in the above-mentioned article: multiple times at six sites over a period of 2.5 years, and once at the remaining seven sites. Since then the participant was scanned an additional 45 times, allowing us to extend the dataset to 70 rsfMRI scans over a period of >4 years. In addition, we provide intra- and inter-subject consistency values of rsfMRI connectivity maps derived from 26 adult participants belonging to the publicly released Hangzhou Normal University dataset (HNU1). All HNU1 participants underwent 10 rsfMRI scans over one month on a single 3T scanner (GE). Connectivity maps of seven canonical networks were generated for each scan in the two datasets (Csub and HNU1). All consistency values, along with the scripts used to preprocess the rsfMRI data and generate connectivity maps and pairwise consistency values, have been made available on two public repositories, Github and Zenodo. We have also made available four Jupyter notebooks that use the provided consistency values to (a) generate interactive graphical summaries - 1 notebook, (b) perform statistical analyses - 2 notebooks, and (c) perform data-driven cluster analysis for the recovery of subject identity (i.e. rsfMRI fingerprinting) - 1 notebook. In addition, we provide two interactive dashboards that allow visualization of individual connectivity maps from the two datasets. Finally, we also provide minimally preprocessed rsfMRI data in Brain Imaging Data Standard (BIDS) format on all 70 scans in the extended dataset.

PMID: 32518809 [PubMed]

Reduced spatiotemporal brain dynamics are associated with increased depressive symptoms after a relationship breakup.

Wed, 06/10/2020 - 22:54
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Reduced spatiotemporal brain dynamics are associated with increased depressive symptoms after a relationship breakup.

Neuroimage Clin. 2020 May 26;27:102299

Authors: Alonso Martínez S, Marsman JC, Kringelbach ML, Deco G, Ter Horst GJ

Abstract
Depressive symptoms following a stressful life event, such as a relationship breakup, are common, and constitute a potent risk factor for the onset of a major depressive episode. Resting-state neuroimaging studies have increasingly identified abnormal whole-brain communication in patients with depression, but it is currently unclear whether depressive symptoms in individuals without a clinical diagnosis have reliable neural underpinnings. We investigated to what extent the severity of depressive symptoms in a non-clinical sample was associated with imbalances in the complex dynamics of the brain during rest. To this end, a novel intrinsic ignition approach was applied to resting-state neuroimaging data from sixty-nine participants with varying degrees of depressive symptoms following a relationship breakup. Ignition-based measures of integration, hierarchy, and metastability were calculated for each participant, revealing a negative correlation between these measures and depressive ratings. We found that the severity of depressive symptoms was associated with deficits in the brain's capacity to globally integrate and process information over time. Furthermore, we found that increased depressive symptoms were associated with reduced spatial diversity (i.e., hierarchy) and reduced temporal variability (i.e., metastability) in the functional organization of the brain. These findings suggest the merit of investigating constrained dynamical complexity as it is sensitive to the level of depressive symptoms even in a non-clinical sample.

PMID: 32516738 [PubMed - as supplied by publisher]

Evaluating the Sensitivity of Resting-State BOLD Variability to Age and Cognition after Controlling for Motion and Cardiovascular Influences: A Network-Based Approach.

Wed, 06/10/2020 - 22:54
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Evaluating the Sensitivity of Resting-State BOLD Variability to Age and Cognition after Controlling for Motion and Cardiovascular Influences: A Network-Based Approach.

Cereb Cortex. 2020 Jun 09;:

Authors: Millar PR, Petersen SE, Ances BM, Gordon BA, Benzinger TLS, Morris JC, Balota DA

Abstract
Recent functional magnetic resonance imaging (fMRI) studies report that moment-to-moment variability in the BOLD signal is related to differences in age and cognition and, thus, may be sensitive to age-dependent decline. However, head motion and/or cardiovascular health (CVH) may contaminate these relationships. We evaluated relationships between resting-state BOLD variability, age, and cognition, after characterizing and controlling for motion-related and cardiovascular influences, including pulse, blood pressure, BMI, and white matter hyperintensities (WMH), in a large (N = 422) resting-state fMRI sample of cognitively normal individuals (age 43-89). We found that resting-state BOLD variability was negatively related to age and positively related to cognition after maximally controlling for head motion. Age relationships also survived correction for CVH, but were greatly reduced when correcting for WMH alone. Our results suggest that network-based machine learning analyses of resting-state BOLD variability might yield reliable, sensitive measures to characterize age-related decline across a broad range of networks. Age-related differences in resting-state BOLD variability may be largely sensitive to processes related to WMH burden.

PMID: 32515824 [PubMed - as supplied by publisher]

Dynamical mechanisms of interictal resting-state functional connectivity in epilepsy.

Wed, 06/10/2020 - 22:54
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Dynamical mechanisms of interictal resting-state functional connectivity in epilepsy.

J Neurosci. 2020 Jun 08;:

Authors: Courtiol J, Guye M, Bartolomei F, Petkoski S, Jirsa VK

Abstract
Drug-resistant focal epilepsy is a large-scale brain networks disorder characterized by altered spatiotemporal patterns of functional connectivity (FC), even during interictal resting-state (RS). Although RS-FC-based metrics can detect these changes, results from RS functional magnetic resonance imaging (RS-fMRI) studies are unclear and difficult to interpret, and the underlying dynamical mechanisms are still largely unknown. To better capture the RS dynamics, we phenomenologically extended the neural mass model of partial seizures, the Epileptor, by including two neuron sub-populations of epileptogenic and non-epileptogenic type, making it capable of producing physiological oscillations besides the epileptiform activity. Using the neuroinformatics platform The Virtual Brain (TVB), we reconstructed 14 epileptic and 5 healthy human (of either sex) brain network models (BNMs), based on individual anatomical connectivity and clinically defined-epileptogenic heatmaps. Through systematic parameter exploration and fitting to neuroimaging data, we demonstrated that epileptic brains during interictal RS are associated with lower global excitability induced by a shift in the model's working point, indicating that epileptic brains operate closer to a stable equilibrium point than healthy brains. Moreover, we showed that functional networks are unaffected by interictal spikes, corroborating previous experimental findings; additionally, we observed higher excitability in epileptogenic regions, in agreement with the data. We shed light on new dynamical mechanisms responsible for altered RS-FC in epilepsy, involving two key factors: (1) a shift of the whole brain's excitability leading to increased stability, and (2) a locally increased excitability in the epileptogenic regions supporting the mixture of hyper and hypo-connectivity in these areas.SIGNIFICANCE STATEMENTAdvances in functional neuroimaging provide compelling evidence for epilepsy-related network alterations in brain connectivity, even during interictal RS. However, the dynamical mechanisms underlying these changes are still elusive. To identify local and network processes behind the RS-FC spatiotemporal patterns, we systematically manipulated the local excitability and the global coupling in the virtual human epileptic patient BNMs, complemented by the analysis of the impact of interictal spikes, and fitting to the neuroimaging data. Our results suggest that behind epileptic processes, a combination of a global shift of the brain's dynamic working point and locally hyperexcitable node dynamics in epileptogenic networks provides a mechanistic explanation for the epileptic brain during interictal RS period that, in turn, are associated with changes in FC.

PMID: 32513827 [PubMed - as supplied by publisher]

Placebo-induced pain reduction is associated with negative coupling between brain networks at rest.

Tue, 06/09/2020 - 22:53
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Placebo-induced pain reduction is associated with negative coupling between brain networks at rest.

Neuroimage. 2020 Jun 05;:117024

Authors: Wagner IC, Rütgen M, Hummer A, Windischberger C, Lamm C

Abstract
Placebos can reduce pain by inducing beliefs in the effectiveness of an actually inert treatment. Such top-down effects on pain typically engage lateral and medial prefrontal regions, the insula, somatosensory cortex, as well as the thalamus and brainstem during pain anticipation or perception. Considering the level of large-scale brain networks, these regions spatially align with fronto-parietal/executive control, salience, and sensory-motor networks, but it is unclear if and how placebos alter interactions between them during rest. Here, we investigated how placebo analgesia affected intrinsic network coupling. Ninety-nine human participants were randomly assigned to a placebo or control group and underwent resting-state fMRI after pain processing. Results revealed inverse coupling between two resting-state networks in placebo but not control participants. Specifically, networks comprised the bilateral somatosensory cortex and posterior insula, as well as the brainstem, thalamus, striatal regions, dorsal and rostral anterior cingulate cortex, and the anterior insula, respectively. Across participants, more negative between-network coupling was associated with lower individual pain intensity as assessed during a preceding pain task, and there was no significant relation with expectations of medication effectiveness in the placebo group. Altogether, these findings provide initial evidence that placebo analgesia affects the intrinsic communication between large-scale brain networks, even in the absence of pain. We suggest a theoretical model where placebo analgesia might affect processing within a descending pain-modulatory network, potentially segregating it from somatosensory regions that may code for painful experiences.

PMID: 32512124 [PubMed - as supplied by publisher]

Abnormal Regional Neural Activity and Reorganized Neural Network in Obesity: Evidence from Resting-State fMRI.

Tue, 06/09/2020 - 22:53
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Abnormal Regional Neural Activity and Reorganized Neural Network in Obesity: Evidence from Resting-State fMRI.

Obesity (Silver Spring). 2020 Jun 08;:

Authors: Zhang P, Wu GW, Yu FX, Liu Y, Li MY, Wang Z, Ding HY, Li XS, Wang H, Jin M, Zhang ZY, Zhao PF, Li J, Yang ZH, Lv H, Zhang ZT, Wang ZC

Abstract
OBJECTIVE: This study aimed to investigate regional neural activity and regulation of patterns in the reorganized neural network of obesity and explore the correlation between brain activities and eating behavior.
METHODS: A total of 23 individuals with obesity and 23 controls with normal weight were enrolled. Functional magnetic resonance imaging (fMRI) data were acquired using 3.0-T MRI. Amplitude of low-frequency fluctuation and functional connectivity (FC) analyses were conducted using Data Processing Assistant for resting-state fMRI and Resting-State fMRI Data Analysis Toolkit (REST).
RESULTS: The group with obesity showed increased amplitude of low-frequency values in left fusiform gyrus/amygdala, inferior temporal gyrus (ITG), hippocampus/parahippocampal gyrus, and bilateral caudate but decreased values in right superior temporal gyrus. The group with obesity showed increased FC between left caudate and right superior temporal gyrus, left fusiform gyrus/amygdala and left ITG, right caudate and left fusiform gyrus/amygdala, and right caudate and left hippocampus/parahippocampal gyrus. Dutch Eating Behavior Questionnaire-Emotional scores were positively correlated with FC between left hippocampus/parahippocampal gyrus and right caudate but negatively correlated with FC between left fusiform gyrus/amygdala and left ITG.
CONCLUSIONS: The study indicated the reorganized neural network presented as a bilateral cross-regulation pattern across hemispheres between reward and various appetite-related functional processing, thus affecting emotional and external eating behavior. These results could provide further evidence for neuropsychological underpinnings of food intake and their neuromodulatory therapeutic potential in obesity.

PMID: 32510870 [PubMed - as supplied by publisher]

Altered resting activity patterns and connectivity in individuals with complex regional pain syndrome.

Tue, 06/09/2020 - 22:53
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Altered resting activity patterns and connectivity in individuals with complex regional pain syndrome.

Hum Brain Mapp. 2020 Jun 08;:

Authors: Di Pietro F, Lee B, Henderson LA

Abstract
Complex regional pain syndrome (CRPS) is a chronic neuropathic pain disorder that typically occurs in the limbs, usually the upper limb. CRPS usually develops from a peripheral event but its maintenance relies on changes within the central nervous system. While functional abnormalities in the thalamus and primary somatosensory cortex (S1) of the brain are some of the most consistently reported brain findings in CRPS, the mechanisms are yet to be explored in full, not least of all how these two regions interact and how they might relate to clinical deficits, such as the commonly reported poor tactile acuity in this condition. This study recruited 15 upper-limb CRPS subjects and 30 healthy controls and used functional magnetic resonance imaging (fMRI) to investigate infra-slow oscillations (ISOs) in critical pain regions of the brain in CRPS. As hypothesised, we found CRPS was associated with increases in resting signal intensity ISOs (0.03-0.06 Hz) in the thalamus contralateral to the painful limb in CRPS subjects. Interestingly, there was no such difference between groups in S1, however CRPS subjects displayed stronger thalamo-S1 functional connectivity than controls, and this was related to pain. As predicted, CRPS subjects displayed poor tactile acuity on the painful limb which, interestingly, was also related to thalamo-S1 functional connectivity strength. Our findings provide novel evidence of altered patterns of resting activity and connectivity in CRPS which may underlie altered thalamocortical loop dynamics and the constant perception of pain.

PMID: 32510695 [PubMed - as supplied by publisher]

Determination of Differences in Seed-Based Resting State Functional Magnetic Resonance Imaging Language Networks in Pediatric Patients with Left- and Right-Lateralized Language: A Pilot Study.

Tue, 06/09/2020 - 22:53
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Determination of Differences in Seed-Based Resting State Functional Magnetic Resonance Imaging Language Networks in Pediatric Patients with Left- and Right-Lateralized Language: A Pilot Study.

J Epilepsy Res. 2019 Dec;9(2):93-102

Authors: Nath A, Robinson M, Magnotti J, Karas P, Curry D, Paldino M

Abstract
Background and Purpose: The current tools available for localization of expressive language, including functional magnetic resonance imaging (fMRI) and cortical stimulation mapping (CSM), require that the patient remain stationary and follow language commands with precise timing. Many pediatric epilepsy patients, however, have intact language skills but are unable to participate in these tasks due to cognitive impairments or young age. In adult subjects, there is evidence that language laterality can be determined by resting state (RS) fMRI activity, however there are few studies on the use of RS to accurately predict language laterality in children.
Methods: A retrospective review of pediatric patients at Texas Children's Hospital was performed to identify patients who have undergone epilepsy surgical planning over 3 years with language localization using traditional methods of Wada testing, CSM, or task-based fMRI with calculated laterality index, as well as a 7-minute RS scan available without excessive motion or noise. We found the correlation between each subject's left and right Broca's region activity and each of 68 cortical regions.
Results: A group of nine patients with left-lateralized language were found to have greater voxel-wise correlations than a group of six patients with right-lateralized language between a left hemispheric Broca's region seed and the following six cortical regions: left inferior temporal, left lateral orbitofrontal, left pars triangularis, right lateral orbitofrontal, right pars orbitalis and right superior frontal regions.
Conclusions: In a cohort of children with epilepsy, we found that patients with left- and right-hemispheric language lateralization have different RS networks.

PMID: 32509544 [PubMed]

Interpretable Learning Approaches in Resting-State Functional Connectivity Analysis: The Case of Autism Spectrum Disorder.

Tue, 06/09/2020 - 22:53
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Interpretable Learning Approaches in Resting-State Functional Connectivity Analysis: The Case of Autism Spectrum Disorder.

Comput Math Methods Med. 2020;2020:1394830

Authors: Hu J, Cao L, Li T, Liao B, Dong S, Li P

Abstract
Deep neural networks have recently been applied to the study of brain disorders such as autism spectrum disorder (ASD) with great success. However, the internal logics of these networks are difficult to interpret, especially with regard to how specific network architecture decisions are made. In this paper, we study an interpretable neural network model as a method to identify ASD participants from functional magnetic resonance imaging (fMRI) data and interpret results of the model in a precise and consistent manner. First, we propose an interpretable fully connected neural network (FCNN) to classify two groups, ASD versus healthy controls (HC), based on input data from resting-state functional connectivity (rsFC) between regions of interests (ROIs). The proposed FCNN model is a piecewise linear neural network (PLNN) which uses piecewise linear function LeakyReLU as its activation function. We experimentally compared the FCNN model against widely used classification models including support vector machine (SVM), random forest, and two new classes of deep neural network models in a large dataset containing 871 subjects from ABIDE I database. The results show the proposed FCNN model achieves the highest classification accuracy. Second, we further propose an interpreting method which could explain the trained model precisely with a precise linear formula for each input sample and decision features which contributed most to the classification of ASD versus HC participants in the model. We also discuss the implications of our proposed approach for fMRI data classification and interpretation.

PMID: 32508974 [PubMed - in process]

Imaging of Morphological Background in Selected Functional and Inflammatory Gastrointestinal Diseases in fMRI.

Tue, 06/09/2020 - 22:53
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Imaging of Morphological Background in Selected Functional and Inflammatory Gastrointestinal Diseases in fMRI.

Front Psychiatry. 2020;11:461

Authors: Skrobisz K, Piotrowicz G, Naumczyk P, Sabisz A, Markiet K, Rydzewska G, Szurowska E

Abstract
The study focuses on evaluation of the Default Mode Network (DMN) activity in functional magnetic resonance imaging (fMRI) in resting state in patients with functional dyspepsia (FD) and irritable bowel syndrome (IBS), Crohn's disease and colitis ulcerosa (IBD) in comparison to healthy volunteers. We assume that etiology of both functional and non-specific inflammatory bowel diseases is correlated with disrupted structure of axonal connections. We would like to identify the network of neuronal connections responsible for presentation of symptoms in these diseases. 56 patients (functional dyspepsia, 18; Crohn's disease and colitis ulcerosa, 18; irritable bowel syndrome, 20) and 18 healthy volunteers underwent examination in MRI of the brain with assessment of brain morphology and central nervous system activity in functional imaging in resting state performed in 3T scanner. Compared to healthy controls' DMN in patients with non-specific digestive tract diseases comprised additional areas in superior frontal gyrus of left hemisphere, in left cingulum and in the left supplementary motor area. Discovered differences in the DMNs can be interpreted as altered processing of homeostatic stimuli. Our study group involved patients suffering from both functional and non-specific inflammatory bowel diseases. Nevertheless a spectrum of changes in the study group (superior frontal gyrus of the left hemisphere, in the left cingulum and in the left supplementary motor area) we were able to find common features, differentiating the whole study group from the healthy controls.

PMID: 32508692 [PubMed]

Structural plasticity of the bilateral hippocampus in glioma patients.

Tue, 06/09/2020 - 22:53
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Structural plasticity of the bilateral hippocampus in glioma patients.

Aging (Albany NY). 2020 Jun 05;12:

Authors: Yuan T, Ying J, Zuo Z, Gui S, Gao Z, Li G, Zhang Y, Li C

Abstract
This study investigates the structural plasticity and neuronal reaction of the hippocampus in glioma patient pre-surgery. Ninety-nine glioma patients without bilateral hippocampus involvement (low-grade, n=52; high-grade, n=47) and 80 healthy controls with 3D T1 images and resting-fMRI were included. Hippocampal volume and dynamic amplitude of low-frequency fluctuation (dALFF) were analyzed among groups. Relationships between hippocampal volume and clinical characteristics were assessed. We observed remote hippocampal volume increases in low- and high-grade glioma and a greater response of the ipsilateral hippocampus than the contralesional hippocampus. The bilateral hippocampal dALFF was significantly increased in high-grade glioma. Tumor-associated epilepsy and the IDH-1 mutation did not affect hippocampal volume in glioma patients. No significant relationship between hippocampal volume and age was observed in high-grade glioma. The Kaplan-Meier curve and log-rank test revealed that large hippocampal volume was associated with shorter overall survival (OS) compared with small hippocampal volume (p=0.007). Multivariate Cox regression analysis revealed that large hippocampal volume was an independent predictor of unfavorable OS (HR=3.597, 95% CI: 1.160-11.153, p=0.027) in high-grade glioma. Our findings suggest that the hippocampus has a remarkable degree of plasticity in response to pathological stimulation of glioma and that the hippocampal reaction to glioma may be related to tumor malignancy.

PMID: 32507763 [PubMed - as supplied by publisher]

Diagnostic and Predictive Neuroimaging Biomarkers for Posttraumatic Stress Disorder.

Tue, 06/09/2020 - 22:53
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Diagnostic and Predictive Neuroimaging Biomarkers for Posttraumatic Stress Disorder.

Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 Apr 11;:

Authors: Zilcha-Mano S, Zhu X, Suarez-Jimenez B, Pickover A, Tal S, Such S, Marohasy C, Chrisanthopoulos M, Salzman C, Lazarov A, Neria Y, Rutherford BR

Abstract
BACKGROUND: Comorbidity between posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) has been commonly overlooked by studies examining resting-state functional connectivity patterns in PTSD. The current study used a data-driven approach to identify resting-state functional connectivity biomarkers to 1) differentiate individuals with PTSD (with or without MDD) from trauma-exposed healthy control subjects (TEHCs), 2) compare individuals with PTSD alone with those with comorbid PTSD+MDD, and 3) explore the clinical utility of the identified biomarkers by testing their associations with clinical symptoms and treatment response.
METHODS: Resting-state magnetic resonance images were obtained from 51 individuals with PTSD alone, 52 individuals with PTSD+MDD, and 76 TEHCs. Of the 103 individuals with PTSD, 55 were enrolled in prolonged exposure treatment. A support vector machine model was used to identify resting-state functional connectivity biomarkers differentiating individuals with PTSD (with or without MDD) from TEHCs and differentiating individuals with PTSD alone from those with PTSD+MDD. The associations between the identified features and symptomatology were tested with Pearson correlations.
RESULTS: The support vector machine model achieved 70.6% accuracy in discriminating between individuals with PTSD and TEHCs and achieved 76.7% accuracy in discriminating between individuals with PTSD alone and those with PTSD+MDD for out-of-sample prediction. Within-network connectivity in the executive control network, prefrontal network, and salience network discriminated individuals with PTSD from TEHCs. The basal ganglia network played an important role in differentiating individuals with PTSD alone from those with PTSD+MDD. PTSD scores were inversely correlated with within-executive control network connectivity (p < .001), and executive control network connectivity was positively correlated with treatment response (p < .001).
CONCLUSIONS: Results suggest that unique brain-based abnormalities differentiate individuals with PTSD from TEHCs, differentiate individuals with PTSD from those with PTSD+MDD, and demonstrate clinical utility in predicting levels of symptomatology and treatment response.

PMID: 32507508 [PubMed - as supplied by publisher]

Dynamic visual cortical connectivity analysis based on functional magnetic resonance imaging.

Tue, 06/09/2020 - 22:53
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Dynamic visual cortical connectivity analysis based on functional magnetic resonance imaging.

Brain Behav. 2020 Jun 07;:e01698

Authors: Zhao L, Zeng W, Shi Y, Nie W, Yang J

Abstract
BACKGROUND: Studies of brain functional connectivity (FC) and effective connectivity (EC) using the functional magnetic resonance imaging (fMRI) have advanced our understanding of functional organization on visual cortex of human brain. The current studies mainly focus on static or dynamic connectivity, while the relationships between them have not been well characterized especially for static EC (sEC) and dynamic EC (dEC), as well as the consistency characteristics of changing trend of dFCs and dECs, which is of great importance to reveal the neural information processing mechanism in visual cortex region.
METHOD: In this study, we explore these relationships among several subareas of human visual cortex (V1-V5) by calculating the connection intensity and information flow among them over time by sliding window method, which are defined by Pearson correlation coefficient and Granger causality analysis, respectively, in each window.
RESULTS: The results demonstrate that there are extensive connections existing in human visual network, which are time-varying both in resting and task-related states. sFC intensity is negatively correlated with the variance of dFC, while sEC intensity is positively correlated with the variance of dEC. Furthermore, we also find that dFC within visual cortex at rest shows more consistency, while dEC shows less compared with task state in changing trend.
CONCLUSION: Therefore, this study provides novel findings about dynamics of connectivity in human visual cortex from the perspective of functional and effective connectivity.

PMID: 32506636 [PubMed - as supplied by publisher]

Disturbances across whole brain networks during reward anticipation in an abstinent addiction population.

Sun, 06/07/2020 - 22:50
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Disturbances across whole brain networks during reward anticipation in an abstinent addiction population.

Neuroimage Clin. 2020 May 26;27:102297

Authors: Nestor LJ, Suckling J, Ersche KD, Murphy A, McGonigle J, Orban C, Paterson LM, Reed L, Taylor E, Flechais R, Smith D, Bullmore ET, Elliott R, Deakin B, Rabiner I, Hughes AL, Sahakian BJ, Robbins TW, Nutt DJ, ICCAM Consortium

Abstract
The prevalent spatial distribution of abnormalities reported in cognitive fMRI studies in addiction suggests there are extensive disruptions across whole brain networks. Studies using resting state have reported disruptions in network connectivity in addiction, but these studies have not revealed characteristics of network functioning during critical psychological processes that are disrupted in addiction populations. Analytic methods that can capture key features of whole brain networks during psychological processes may be more sensitive in revealing additional and widespread neural disturbances in addiction, that are the provisions for relapse risk, and targets for medication development. The current study compared a substance addiction (ADD; n = 83) group in extended abstinence with a control (CON; n = 68) group on functional MRI (voxel-wise activation) and global network (connectivity) measures related to reward anticipation on a monetary incentive delay task. In the absence of group differences on MID performance, the ADD group showed reduced activation predominantly across temporal and visual regions, but not across the striatum. The ADD group also showed disruptions in global network connectivity (lower clustering coefficient and higher characteristic path length), and significantly less connectivity across a sub-network comprising frontal, temporal, limbic and striatal nodes. These results show that an addiction group in extended abstinence exhibit localised disruptions in brain activation, but more extensive disturbances in functional connectivity across whole brain networks. We propose that measures of global network functioning may be more sensitive in highlighting latent and more widespread neural disruptions during critical psychological processes in addiction and other psychiatric disorders.

PMID: 32505119 [PubMed - as supplied by publisher]

BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks.

Sun, 06/07/2020 - 22:50
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BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks.

Neuroinformatics. 2020 Jun 05;:

Authors: Kook JH, Vaughn KA, DeMaster DM, Ewing-Cobbs L, Vannucci M

Abstract
In this paper we propose BVAR-connect, a variational inference approach to a Bayesian multi-subject vector autoregressive (VAR) model for inference on effective brain connectivity based on resting-state functional MRI data. The modeling framework uses a Bayesian variable selection approach that flexibly integrates multi-modal data, in particular structural diffusion tensor imaging (DTI) data, into the prior construction. The variational inference approach we develop allows scalability of the methods and results in the ability to estimate subject- and group-level brain connectivity networks over whole-brain parcellations of the data. We provide a brief description of a user-friendly MATLAB GUI released for public use. We assess performance on simulated data, where we show that the proposed inference method can achieve comparable accuracy to the sampling-based Markov Chain Monte Carlo approach but at a much lower computational cost. We also address the case of subject groups with imbalanced sample sizes. Finally, we illustrate the methods on resting-state functional MRI and structural DTI data on children with a history of traumatic injury.

PMID: 32504259 [PubMed - as supplied by publisher]

Relationships between abnormal neural activities and cognitive impairments in patients with drug-naive first-episode schizophrenia.

Sun, 06/07/2020 - 22:50
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Relationships between abnormal neural activities and cognitive impairments in patients with drug-naive first-episode schizophrenia.

BMC Psychiatry. 2020 Jun 05;20(1):283

Authors: Yan W, Zhang R, Zhou M, Lu S, Li W, Xie S, Zhang N

Abstract
BACKGROUND: Prior resting state functional Magnetic Resonance Imaging studies (rs-fMRI) via the regional homogeneity (ReHo) method have demonstrated inconsistent and conflicting results because of several confounding factors, such as small sample size, medicinal influence, and illness duration. Relationships between ReHo measures and cognitive impairments in patients with drug-naive First-Episode Schizophrenia (dn-FES) are rarely reported. This study was conducted to explore the correlations between ReHo measures and cognitive deficits and clinical symptoms in patients with dn-FES.
METHODS: A total of 69 patients with dn-FES and 74 healthy controls were recruited. MATRICS Consensus Cognitive Battery (MCCB), Wechsler Adult Intelligence Scale (WAIS), and Positive And Negative Syndrome Scale (PANSS) were used to assess cognitive function, Intelligence Quotient (IQ), and clinical symptoms, respectively. The correlations between ReHo maps and cognitive deficits and the severity of symptoms were examined using strict correlation analysis.
RESULTS: ReHo values in right Middle Frontal Gyrus (MFG) and Superior Frontal Gyrus (SFG) increased in dn-FES group, whereas ReHo values in right cuneus decreased. Correlation analysis showed that the ReHo values in right MFG positively correlated with attention/vigilance impairments, social cognition deficits, and the severity of clinical manifestations.
CONCLUSIONS: These findings suggested that abnormal spontaneous activities in right MFG reflect illness severity and cognitive deficits, which also serve as a basis for establishing objective diagnostic markers and might be a clinical intervention target for treating patients with schizophrenia.

PMID: 32503481 [PubMed - as supplied by publisher]

Spatial patterns of intrinsic brain activity and functional connectivity in facial synkinesis patients.

Sat, 06/06/2020 - 22:49
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Spatial patterns of intrinsic brain activity and functional connectivity in facial synkinesis patients.

Br J Neurosurg. 2020 Jun 05;:1-6

Authors: Ma J, Hua XY, Zheng MX, Wu JJ, Huo BB, Xing XX, Ding W, Xu JG

Abstract
Objectives: As one of the most objectionable sequelae of facial paralysis, patients with facial synkinesis are more likely to be depressed and have lower quality of life than other facial paralysis patients. However, there is no research on the spatial patterns of intrinsic brain activity and functional connectivity in these patients. The objective of this study was to investigate the spatial patterns and cerebral plasticity of facial synkinesis patients.Methods: A total of 20 facial synkinesis patients (18 men and 2 women; mean age: 33.35 ± 6.97 years old) and 19 healthy controls (17 men and 2 women; mean age: 33.21 ± 6.75 years old) were enrolled in this study. resting-state functional magnetic resonance imaging (rs-fMRI) data were collected, and the amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated for each participant. Two-sample t-tests were performed to compare the ALFF, ReHo, and DC maps between the two groups.Results: Compared with the healthy controls, facial synkinesis patients exhibited decreased ALFF in the fusiform gyrus, lingual gyrus, parahippocampal gyrus, triangular inferior frontal gyrus, precentral gyrus, postcentral gyrus, cingulate gyrus, superior frontal gyrus, precuneus, caudate nucleus and thalamus; decreased ReHo in the cingulate gyrus, superior frontal gyrus, insula, superior temporal gyrus, orbital middle frontal gyrus, caudate nucleus and thalamus; and decreased DC in the frontal lobe, insula, cingulate gyrus, superior temporal gyrus, lenticular putamen, hippocampus and parahippocampal gyrus. We found significant overlap in the superior frontal gyrus across the ALFF, ReHo and DC analyses.Conclusions: In facial synkinesis patients, the neurological activity in brain areas is reduced and the local synchronization in motion-related brain regions is decreased. The superior frontal gyrus could be a crucial region in the unique spatial patterns of intrinsic brain activity and functional connectivity in these patients.

PMID: 32500814 [PubMed - as supplied by publisher]

Changes in functional connectivity in people with HIV switching antiretroviral therapy.

Sat, 06/06/2020 - 22:49
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Changes in functional connectivity in people with HIV switching antiretroviral therapy.

J Neurovirol. 2020 Jun 04;:

Authors: Toniolo S, Cercignani M, Mora-Peris B, Underwood J, Alagaratnam J, Bozzali M, Boffito M, Nelson M, Winston A, Vera JH

Abstract
We assessed changes in functional connectivity by fMRI (functional magnetic resonance imaging) and cognitive measures in otherwise neurologically asymptomatic people with HIV (PWH) switching combination antiretroviral therapy (cART). In a prospective study (baseline and follow-up after at least 4 months), virologically suppressed PWH switched non-nuclease reverse-transcriptase inhibitors (NNRTI; tenofovir-DF/emtricitabine with efavirenz to rilpivirine) and integrase-strand-transfer inhibitors (INSTI; tenofovir-DF/emtricitabine with raltegravir to dolutegravir). PWH were assessed by resting-state fMRI and stop-signal reaction time (SSRT) task fMRI as well as with a cognitive battery (CogState™) at baseline and follow-up. Switching from efavirenz to rilpivirine (n = 10) was associated with increased functional connectivity in the dorsal attention network (DAN) and a reduction in SSRTs (p = 0.025) that positively correlated with the time previously on efavirenz (mean = 4.8 years, p = 0.02). Switching from raltegravir to dolutegravir (n = 12) was associated with increased connectivity in the left DAN and bilateral sensory-motor and associative visual networks. In the NNRTI study, significant improvements in the cognitive domains of executive function, working memory and speed of visual processing were observed, whereas no significant changes in cognitive function were observed in the INSTI study. Changes in fMRI are evident in PWH without perceived neuropsychiatric complaints switching cART. fMRI may be a useful tool in assisting to elucidate the underlying pathogenic mechanisms of cART-related neuropsychiatric effects.

PMID: 32500477 [PubMed - as supplied by publisher]