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Effect of Vestibular Rehabilitation on Spontaneous Brain Activity in Patients With Vestibular Migraine: A Resting-State Functional Magnetic Resonance Imaging Study.

Wed, 07/01/2020 - 23:32
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Effect of Vestibular Rehabilitation on Spontaneous Brain Activity in Patients With Vestibular Migraine: A Resting-State Functional Magnetic Resonance Imaging Study.

Front Hum Neurosci. 2020;14:227

Authors: Liu L, Hu X, Zhang Y, Pan Q, Zhan Q, Tan G, Wang K, Zhou J

Abstract
Previous studies have shown that vestibular migraine (VM) is a cerebral disease with recurrent vertigo. Vestibular rehabilitation (VR) is an effective type of physical therapy for minimizing vestibular symptoms, as it improves vestibular compensation in patients with VM. Currently, the cerebral regions that are associated with the pathogenesis of VM are largely unknown. To further understand the underlying mechanisms of VM, we performed resting-state functional magnetic resonance imaging (fMRI) before and after 1 month of VR in 14 patients with VM. The Dizziness Handicap Inventory (DHI), the 36-Item Short-Form Health Survey (SF-36), the Hamilton Depression Scale (HAMD) and the Hamilton Anxiety Scale (HAMA) scores were included as clinical outcomes. The amplitude of low-frequency fluctuation (ALFF) was assessed to characterize spontaneous brain activity. The correlations between the clinical characteristics and ALFF values were assessed. After 1 month of VR training, the DHI scores in patients with VM were significantly lower than those at baseline (p = 0.03), as were the HAMA scores (p = 0.02). We also found that the ALFF values in the left posterior cerebellum of VM patients increased significantly after 1 month of VR training. Moreover, the ALFF values in the left cerebellum were inversely correlated with the patients' DHI scores. Overall, this study showed that VR exercise for 1 month has a positive effect on vestibular symptoms in patients with VM. Asymmetric cerebellar hyperactivity might be a functional compensation for vestibular dysfunction in patients with VM.

PMID: 32595463 [PubMed]

The Profiles of Non-stationarity and Non-linearity in the Time Series of Resting-State Brain Networks.

Wed, 07/01/2020 - 23:32
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The Profiles of Non-stationarity and Non-linearity in the Time Series of Resting-State Brain Networks.

Front Neurosci. 2020;14:493

Authors: Guan S, Jiang R, Bian H, Yuan J, Xu P, Meng C, Biswal B

Abstract
The linearity and stationarity of fMRI time series need to be understood due to their important roles in the choice of approach for brain network analysis. In this paper, we investigated the stationarity and linearity of resting-state fMRI (rs-fMRI) time-series data from the Midnight Scan Club datasets. The degree of stationarity (DS) and the degree of non-linearity (DN) were, respectively, estimated for the time series of all gray matter voxels. The similarity and difference between the DS and DN were assessed in terms of voxels and intrinsic brain networks, including the visual network, somatomotor network, dorsal attention network, ventral attention network, limbic network, frontoparietal network, and default-mode network. The test-retest scans were utilized to quantify the reliability of DS and DN. We found that DS and DN maps had overlapping spatial distribution. Meanwhile, the probability density estimate function of DS had a long tail, and that of DN had a more normal distribution. Specifically, stronger DS was present in the somatomotor, limbic, and ventral attention networks compared to other networks, and stronger DN was found in the somatomotor, visual, limbic, ventral attention, and default-mode networks. The percentage of overlapping voxels between DS and DN in different networks demonstrated a decreasing trend in the order default mode, ventral attention, somatomotor, frontoparietal, dorsal attention, visual, and limbic. Furthermore, the ICC values of DS were higher than those of DN. Our results suggest that different functional networks have distinct properties of non-stationarity and non-linearity owing to the complexity of rs-fMRI time series. Thus, caution should be taken when analyzing fMRI data (both resting-state and task-activation) using simplified models.

PMID: 32595440 [PubMed]

Modeling task-based fMRI data via deep belief network with neural architecture search.

Wed, 07/01/2020 - 23:32
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Modeling task-based fMRI data via deep belief network with neural architecture search.

Comput Med Imaging Graph. 2020 Jun 06;83:101747

Authors: Qiang N, Dong Q, Zhang W, Ge B, Ge F, Liang H, Sun Y, Gao J, Liu T

Abstract
It has been shown that deep neural networks are powerful and flexible models that can be applied on fMRI data with superb representation ability over traditional methods. However, a challenge of neural network architecture design has also attracted attention: due to the high dimension of fMRI volume images, the manual process of network model design is very time-consuming and not optimal. To tackle this problem, we proposed an unsupervised neural architecture search (NAS) framework on a deep belief network (DBN) that models volumetric fMRI data, named NAS-DBN. The NAS-DBN framework is based on Particle Swarm Optimization (PSO) where the swarms of neural architectures can evolve and converge to a feasible optimal solution. The experiments showed that the proposed NAS-DBN framework can quickly find a robust architecture of DBN, yielding a hierarchy organization of functional brain networks (FBNs) and temporal responses. Compared with 3 manually designed DBNs, the proposed NAS-DBN has the lowest testing loss of 0.0197, suggesting an overall performance improvement of up to 47.9 %. For each task, the NAS-DBN identified 260 FBNs, including task-specific FBNs and resting state networks (RSN), which have high overlap rates to general linear model (GLM) derived templates and independent component analysis (ICA) derived RSN templates. The average overlap rate of NAS-DBN to GLM on 20 task-specific FBNs is as high as 0.536, indicating a performance improvement of up to 63.9 % in respect of network modeling. Besides, we showed that the NAS-DBN can simultaneously generate temporal responses that resemble the task designs very well, and it was observed that widespread overlaps between FBNs from different layers of NAS-DBN model form a hierarchical organization of FBNs. Our NAS-DBN framework contributes an effective, unsupervised NAS method for modeling volumetric task fMRI data.

PMID: 32593949 [PubMed - as supplied by publisher]

Regularized-Ncut: Robust and homogeneous functional parcellation of neonate and adult brain networks.

Wed, 07/01/2020 - 23:32
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Regularized-Ncut: Robust and homogeneous functional parcellation of neonate and adult brain networks.

Artif Intell Med. 2020 Jun;106:101872

Authors: Peng Q, Ouyang M, Wang J, Yu Q, Zhao C, Slinger M, Li H, Fan Y, Hong B, Huang H

Abstract
Brain network parcellation based on resting-state functional MRI (rs-fMRI) is affected by noise, resulting in spurious small patches and decreased functional homogeneity within each network. Obtaining robust and homogeneous parcellation of neonate brain is more difficult, because neonate rs-fMRI is associated with relatively higher level of noise and no prior knowledge from a functional neonate atlas is available as spatial constraints. To meet these challenges, we developed a novel data-driven Regularized Normalized-cut (RNcut) method. RNcut is formulated by adding two regularization terms, a smoothing term using Markov random fields and a small-patch removal term, to conventional normalized-cut (Ncut) method. The RNcut and competing methods were tested with simulated datasets with known ground truth and then applied to both adult and neonate rs-fMRI datasets. Based on the parcellated networks generated by RNcut, intra-network connectivity was quantified. The test results from simulated datasets demonstrated that the RNcut method is more robust (p < 0.01) to noise and can delineate parcellated functional networks with significantly better (p < 0.01) spatial contiguity and significantly higher (p < 0.01) functional homogeneity than competing methods. Application of RNcut to neonate and adult rs-fMRI dataset revealed distinctive functional brain organization of neonate brains from that of adult brains. Collectively, we developed a novel data-driven RNcut method by integrating conventional Ncut with two regularization terms, generating robust and homogeneous functional parcellation without imposing spatial constraints. A broad range of brain network applications and analyses, especially neonate and infant brain parcellation with noisy and large sample of datasets, can potentially benefit from this RNcut method.

PMID: 32593397 [PubMed - in process]

Graph Fourier transform of fMRI temporal signals based on an averaged structural connectome for the classification of neuroimaging.

Wed, 07/01/2020 - 23:32
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Graph Fourier transform of fMRI temporal signals based on an averaged structural connectome for the classification of neuroimaging.

Artif Intell Med. 2020 Jun;106:101870

Authors: Brahim A, Farrugia N

Abstract
Graph signal processing (GSP) is a framework that enables the generalization of signal processing to multivariate signals described on graphs. In this paper, we present an approach based on Graph Fourier Transform (GFT) and machine learning for the analysis of resting-state functional magnetic resonance imaging (rs-fMRI). For each subject, we use rs-fMRI time series to compute several descriptive statistics in regions of interest (ROI). Next, these measures are considered as signals on an averaged structural graph built using tractography of the white matter of the brain, defined using the same ROI. GFT of these signals is computed using the structural graph as a support, and the obtained feature vectors are subsequently benchmarked in a supervised learning setting. Further analysis suggests that GFT using structural connectivity as a graph and the standard deviation of fMRI time series as signals leads to more accurate supervised classification using a world-wide multi-site database known as ABIDE (Autism Brain Imaging Data Exchange) when compared to several other statistical metrics. Moreover, the proposed approach outperforms several approaches, based on using functional connectomes or complex functional network measures as features for classification.

PMID: 32593395 [PubMed - in process]

Functional Organization of the Insula in Men and Women with Obstructive Sleep Apnea during Valsalva.

Sun, 06/28/2020 - 23:26
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Functional Organization of the Insula in Men and Women with Obstructive Sleep Apnea during Valsalva.

Sleep. 2020 Jun 27;:

Authors: Pal A, Ogren JA, Aguila AP, Aysola R, Kumar R, Henderson LA, Harper RM, Macey PM

Abstract
STUDY OBJECTIVES: Obstructive sleep apnea (OSA) patients show impaired autonomic regulation, perhaps related to functional reorganization of the insula, which in healthy individuals shows sex-specific anterior and right-dominance during sympathetic activation. We examined insular organization of responses to a Valsalva maneuver in OSA with functional magnetic resonance imaging (fMRI).
METHODS: We studied 43 newly-diagnosed OSA (age mean±std:46.8±8.7years; AHI±std:32.1±20.1events/hour;34male) and 63 healthy (47.2±8.8years;40male) participants. Participants performed four 18s Valsalva maneuvers (1min intervals, pressure≥30mmHg) during scanning. fMRI timetrends from five insular gyri-anterior short (ASG); mid short (MSG); posterior short (PSG); anterior long (ALG); and posterior long (PLG)-were assessed for within-group responses and between-group differences with repeated measures ANOVA (p<0.05); age and resting heart-rate (HR) influences were also assessed.
RESULTS: Right and anterior fMRI signal dominance appeared in OSA and controls, with no between-group differences. Separation by sex revealed group differences. Left-ASG anterior signal dominance was lower in OSA versus control males. Left-ASG and ALG anterior-dominance was higher in OSA versus control females. In all right gyri, only OSA females showed greater anterior-dominance than controls. Right-dominance was apparent in PSG and ALG in all groups; females showed right-dominance in MSG and PLG. OSA males did not show PLG right-dominance. Responses were influenced substantially by HR but modestly by age.
CONCLUSIONS: Anterior and right insular fMRI dominance appears similar in OSA vs control participants during the sympathetic phase of the Valsalva maneuver. OSA and control similarities were present in just males, but not necessarily females, which may reflect sex-specific neural injury.

PMID: 32592491 [PubMed - as supplied by publisher]

Resting-State Power and Regional Connectivity After Pediatric Mild Traumatic Brain Injury.

Sun, 06/28/2020 - 23:26
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Resting-State Power and Regional Connectivity After Pediatric Mild Traumatic Brain Injury.

J Magn Reson Imaging. 2020 Jun 27;:

Authors: Stephenson DD, Meier TB, Pabbathi Reddy S, Robertson-Benta CR, Hergert DC, Dodd AB, Shaff NA, Ling JM, Oglesbee SJ, Campbell RA, Phillips JP, Sapien RE, Mayer AR

Abstract
BACKGROUND: Physiological recovery from pediatric mild traumatic brain injury (pmTBI) as a function of age remains actively debated, with the majority of studies relying on subjective symptom report rather than objective markers of brain physiology.
PURPOSE: To examine potential abnormalities in fractional amplitude of low-frequency fluctuations (fALFF) or regional homogeniety (ReHo) during resting-state fMRI following pmTBI.
STUDY TYPE: Prospective cohort.
POPULATION: Consecutively recruited pmTBI (N = 105; 8-18 years old) and age- and sex-matched healthy controls (HC; N = 113).
FIELD STRENGTH/SEQUENCE: 3T multiecho gradient T1 -weighted and single-shot gradient-echo echo-planar imaging.
ASSESSMENT: All pmTBI participants were assessed 1 week and 4 months postinjury (HC assessed at equivalent timepoints after the first visit). Comprehensive demographic, clinical, and cognitive batteries were performed in addition to primary investigation of fALFF and ReHo. All pmTBI were classified as "persistent" or "recovered" based on both assessment periods.
STATISTICAL TESTS: Chi-square, nonparametric, and generalized linear models for demographic data. Generalized estimating equations for clinical and cognitive data. Voxelwise general linear models (AFNI's 3dMVM) for fALFF and ReHo assessment.
RESULTS: Evidence of recovery was observed for some, but not all, clinical and cognitive measures at 4 months postinjury. fALFF was increased in the left striatum for pmTBI relative to HC both at 1 week and 4 months postinjury; whereas no significant group differences (P > 0.001) were observed for ReHo. Age-at-injury did not moderate either resting-state metric across groups. In contrast to analyses of pmTBI as a whole, there were no significant (P > 0.001) differences in either fALFF or ReHo in patients with persistent postconcussive symptoms compared to recovered patients and controls at 4 months postinjury.
DATA CONCLUSIONS: Our findings suggest prolonged clinical recovery and alterations in the relative amplitude of resting-state fluctuations up to 4 months postinjury, but no clear relationship with age-at-injury or subjective symptom report.
LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: 2.

PMID: 32592270 [PubMed - as supplied by publisher]

Individual differences in local functional brain connectivity affect TMS effects on behavior.

Sun, 06/28/2020 - 23:26
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Individual differences in local functional brain connectivity affect TMS effects on behavior.

Sci Rep. 2020 Jun 26;10(1):10422

Authors: Gießing C, Alavash M, Herrmann CS, Hilgetag CC, Thiel CM

Abstract
Behavioral effects of transcranial magnetic stimulation (TMS) often show substantial differences between subjects. One factor that might contribute to these inter-individual differences is the interaction of current brain states with the effects of local brain network perturbation. The aim of the current study was to identify brain regions whose connectivity before and following right parietal perturbation affects individual behavioral effects during a visuospatial target detection task. 20 subjects participated in an fMRI experiment where their brain hemodynamic response was measured during resting state, and then during a visuospatial target detection task following 1 Hz rTMS and sham stimulation. To select a parsimonious set of associated brain regions, an elastic net analysis was used in combination with a whole-brain voxel-wise functional connectivity analysis. TMS-induced changes in accuracy were significantly correlated with the pattern of functional connectivity during the task state following TMS. The functional connectivity of the left superior temporal, angular, and precentral gyri was identified as key explanatory variable for the individual behavioral TMS effects. Our results suggest that the brain must reach an appropriate state in which right parietal TMS can induce improvements in visual target detection. The ability to reach this state appears to vary between individuals.

PMID: 32591568 [PubMed - as supplied by publisher]

Children with developmental coordination disorder show altered functional connectivity compared to peers.

Sat, 06/27/2020 - 23:23
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Children with developmental coordination disorder show altered functional connectivity compared to peers.

Neuroimage Clin. 2020 Jun 12;27:102309

Authors: Rinat S, Izadi-Najafabadi S, Zwicker JG

Abstract
Developmental Coordination Disorder (DCD) is a neurodevelopmental disorder that affects a child's ability to learn motor skills and participate in self-care, educational, and leisure activities. The cause of DCD is unknown, but evidence suggests that children with DCD have atypical brain structure and function. Resting-state MRI assesses functional connectivity by identifying brain regions that have parallel activation during rest. As only a few studies have examined functional connectivity in this population, our objective was to compare whole-brain resting-state functional connectivity of children with DCD and typically-developing children. Using Independent Component Analysis (ICA), we compared functional connectivity of 8-12 year old children with DCD (N = 35) and typically-developing children (N = 23) across 19 networks, controlling for age and sex. Children with DCD demonstrate altered functional connectivity between the sensorimotor network and the posterior cingulate cortex (PCC), precuneus, and the posterior middle temporal gyrus (pMTG) (p < 0.0001). Previous evidence suggests the PCC acts as a link between functionally distinct networks. Our results indicate that ineffective communication between the sensorimotor network and the PCC might play a role in inefficient motor learning seen in DCD. The pMTG acts as hub for action-related information and processing, and its involvement could explain some of the functional difficulties seen in DCD. This study increases our understanding of the neurological differences that characterize this common motor disorder.

PMID: 32590334 [PubMed - as supplied by publisher]

Disrupted functional network connectivity predicts cognitive impairment after acute mild traumatic brain injury.

Sat, 06/27/2020 - 23:23
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Disrupted functional network connectivity predicts cognitive impairment after acute mild traumatic brain injury.

CNS Neurosci Ther. 2020 Jun 25;:

Authors: Li F, Lu L, Shang S, Hu L, Chen H, Wang P, Zhang H, Chen YC, Yin X

Abstract
AIMS: This study aimed to detect alterations of brain functional connectivity (FC) in acute mild traumatic brain injury (mTBI) and to estimate the extent to which these FC differences predicted the characteristics of posttraumatic cognitive impairment.
METHODS: Resting-state fMRI data were acquired from acute mTBI patients (n = 50) and healthy controls (HCs) (n = 43). Resting-state networks (RSNs) were established based on independent component analysis (ICA), and functional network connectivity (FNC) analysis was performed. Subsequently, we analyzed the correlations between FNC abnormalities and cognitive impairment outcomes.
RESULTS: Altered FC within the salience network (SN), sensorimotor network (SMN), default mode network (DMN), executive control network (ECN), visual network (VN), and cerebellum network (CN) was found in the mTBI group relative to the HC group. Moreover, different patterns of altered network interactions were found between the mTBI patients and HCs, including the SN-CN, VN-SMN, and ECN-DMN connections. Correlations between functional disconnection and cognitive impairment measurements in acute mTBI patients were also found.
CONCLUSION: This study indicated that widespread FNC impairment and altered integration existed in mTBI patients at acute stage, suggesting that FNC disruption as a biomarker may be applied for the early diagnosis and prediction of cognitive impairment in mTBI.

PMID: 32588522 [PubMed - as supplied by publisher]

Decreased interhemispheric connectivity and increased cortical excitability in unmedicated schizophrenia: A prefrontal interleaved TMS fMRI study.

Fri, 06/26/2020 - 23:21
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Decreased interhemispheric connectivity and increased cortical excitability in unmedicated schizophrenia: A prefrontal interleaved TMS fMRI study.

Brain Stimul. 2020 Jun 22;:

Authors: Webler RD, Hamady C, Molnar C, Johnson K, Bonilha L, Anderson BS, Bruin C, Bohning DE, George MS, Nahas Z

Abstract
BACKGROUND: Prefrontal abnormalities in schizophrenia have consistently emerged from resting state and cognitive neuroimaging studies. However, these correlative findings require causal verification via combined imaging/stimulation approaches. To date, no interleaved transcranial magnetic stimulation and functional magnetic resonance imaging study (TMS fMRI) has probed putative prefrontal cortex abnormalities in schizophrenia.
OBJECTIVE: /Hypothesis: We hypothesized that subjects with schizophrenia would show significant hyperexcitability at the site of stimulation (BA9) and decreased interhemispheric functional connectivity.
METHODS: We enrolled 19 unmedicated subjects with schizophrenia and 22 controls. All subjects underwent brain imaging using a 3T MRI scanner with a SENSE coil. They also underwent a single TMS fMRI session involving motor threshold (rMT) determination, structural imaging, and a parametric TMS fMRI protocol with 10Hz triplet pulses at 0, 80, 100 and 120% rMT. Scanning involved a surface MR coil optimized for bilateral prefrontal cortex image acquisition.
RESULTS: Of the original 41 enrolled subjects, 8 subjects with schizophrenia and 11 controls met full criteria for final data analyses. At equal TMS intensity, subjects with schizophrenia showed hyperexcitability in left BA9 (p=0.0157; max z-score=4.7) and neighboring BA46 (p=0.019; max z-score=4.47). Controls showed more contralateral functional connectivity between left BA9 and right BA9 through increased activation in right BA9 (p=0.02; max z-score=3.4). GM density in subjects with schizophrenia positively correlated with normalized prefrontal to motor cortex ratio of the corresponding distance from skull to cortex ratio (S-BA9/S-MC) (r = 0.83, p=0.004).
CONCLUSIONS: Subjects with schizophrenia showed hyperexcitability in left BA9 and impaired interhemispheric functional connectivity compared to controls. Interleaved TMS fMRI is a promising tool to investigate prefrontal dysfunction in schizophrenia.

PMID: 32585355 [PubMed - as supplied by publisher]

The relationship between individual variation in macroscale functional gradients and distinct aspects of ongoing thought.

Fri, 06/26/2020 - 23:21
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The relationship between individual variation in macroscale functional gradients and distinct aspects of ongoing thought.

Neuroimage. 2020 Jun 22;:117072

Authors: Mckeown B, Strawson WH, Wang HT, Karapanagiotidis T, Vos de Wael R, Benkarim O, Turnbull A, Margulies D, Jefferies E, McCall C, Bernhardt B, Smallwood J

Abstract
Contemporary accounts of ongoing thought recognise it as a heterogeneous and multidimensional construct, varying in both form and content. An emerging body of evidence demonstrates that distinct types of experience are associated with unique neurocognitive profiles, that can be described at the whole-brain level as interactions between multiple large-scale networks. The current study sought to explore the possibility that whole-brain functional connectivity patterns at rest may be meaningfully related to patterns of ongoing thought that occurred over this period. Participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) followed by a questionnaire retrospectively assessing the content and form of their ongoing thoughts during the scan. A non-linear dimension reduction algorithm was applied to the rs-fMRI data to identify components explaining the greatest variance in whole-brain connectivity patterns, and ongoing thought patterns during the resting-state were measured retrospectively at the end of the scan. Multivariate analyses revealed that individuals for whom the connectivity of the sensorimotor system was maximally distinct from the visual system were most likely to report thoughts related to finding solutions to problems or goals and least likely to report thoughts related to the past. These results add to an emerging literature that suggests that unique patterns of experience are associated with distinct distributed neurocognitive profiles and highlight that unimodal systems may play an important role in this process.

PMID: 32585346 [PubMed - as supplied by publisher]

Both Stationary and Dynamic Functional Interhemispheric Connectivity Are Strongly Associated With Performance on Cognitive Tests in Multiple Sclerosis.

Fri, 06/26/2020 - 23:21
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Both Stationary and Dynamic Functional Interhemispheric Connectivity Are Strongly Associated With Performance on Cognitive Tests in Multiple Sclerosis.

Front Neurol. 2020;11:407

Authors: Lin SJ, Kolind S, Liu A, McMullen K, Vavasour I, Wang ZJ, Traboulsee A, McKeown MJ

Abstract
Although functional connectivity has been extensively studied in MS, robust estimates of both stationary (static connectivity at the time) and dynamic (connectivity variation across time) functional connectivity has not been commonly evaluated and neither has its association to cognition. In this study, we focused on interhemispheric connections as previous research has shown links between anatomical homologous connections and cognition. We examined functional interhemispheric connectivity (IC) in MS during resting-state functional MRI using both stationary and dynamic strategies and related connectivity measures to processing speed performance. Twenty-five patients with relapsing-remitting MS and 41 controls were recruited. Stationary functional IC was assessed between homologous Regions of Interest (ROIs) using correlation. For dynamic IC, a sliding window approach was used to quantify changes between homologous ROIs across time. We related IC measures to cognitive performance with correlation and regression. Compared to control subjects, MS demonstrated increased IC across homologous regions, which accurately predicted performance on the symbol digit modalities test (SDMT) (R 2 = 0.96) and paced auditory serial addition test (PASAT) (R 2 = 0.59). Dynamic measures were not different between the 2 groups, but dynamic IC was related to PASAT scores. The associations between stationary/dynamic connectivity and cognitive tests demonstrated that different aspects of functional IC were associated with cognitive processes. Processing speed measured in SDMT was associated with static interhemispheric connections and better PASAT performance, which requires working memory, sustain attention, and processing speed, was more related to rigid IC, underlining the neurophysiological mechanism of cognition in MS.

PMID: 32581993 [PubMed]

Distinct Insular Functional Connectivity Changes Related to Mood and Fatigue Improvements in Major Depressive Disorder Following Tai Chi Training: A Pilot Study.

Fri, 06/26/2020 - 23:21
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Distinct Insular Functional Connectivity Changes Related to Mood and Fatigue Improvements in Major Depressive Disorder Following Tai Chi Training: A Pilot Study.

Front Integr Neurosci. 2020;14:25

Authors: Xu A, Zimmerman CS, Lazar SW, Ma Y, Kerr CE, Yeung A

Abstract
Objective: Tai chi (TC), a contemplative practice combining slow movements and deep breathing, has been shown to be clinically effective in alleviating depressive symptoms. Feelings of fatigue or low vitality often accompany major depressive disorder (MDD) though they are commonly overlooked and not well understood neurologically. By using resting state functional connectivity (rs-FC) using the insula as the seed, this study examines the relationship between mood and vitality symptoms in MDD and how they are impacted by TC training. Methods: Patients (N = 16) with MDD participated in a 10-week TC intervention. Self-report scores of vitality (using the SF-36 scale) and depressed mood (using the Beck Depression Inventory) as well as rs-fMRI were collected pre- and post-intervention. A seed-to-voxel approach was used to test whether changes in insular rs-FC were related to therapeutic improvement in MDD-related symptoms resulting from TC practice. Results: We found decreased self-reported depressed mood and increased vitality following the TC intervention. Furthermore, decreases in depressed mood were associated with increased rs-FC between the right anterior insula (AIC) and superior temporal gyrus and caudate (cluster-corrected p < 0.05). Increased vitality was associated with increased rs-FC between the right posterior insula (PIC) and regions associated with sensorimotor processes (cluster-corrected p < 0.05). Conclusion: These results provide support for differential changes in insula connectivity as neural correlates of symptom improvement in MDD.

PMID: 32581734 [PubMed]

Brain networks of rats under anesthesia using resting-state fMRI: comparison with dead rats, random noise and generative models of networks.

Thu, 06/25/2020 - 23:20
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Brain networks of rats under anesthesia using resting-state fMRI: comparison with dead rats, random noise and generative models of networks.

J Neural Eng. 2020 Jun 24;:

Authors: Becq GGJC, Barbier E, Achard S

Abstract
ObjectiveConnectivity networks are crucial to understand the brain resting-state activity using functional magnetic resonance imaging (rs-fMRI). Alterations of these brain networks may highlight important findings concerning the resilience of the brain to different disorders. The focus of this paper is to evaluate the robustness of brain network estimations, discriminate them under anesthesia and compare them to generative models.ApproachThe extraction of brain functional connectivity (FC) networks is difficult and biased due the properties of the data: low signal to noise ratio, high dimension low sample size. We propose to use wavelet correlations to assess FC between brain areas under anesthesia using four anesthetics (isoflurane, etomidate, medetomidine, urethane). The networks are then deduced from the functional connectivity matrices by applying statistical thresholds computed using the number of samples at a given scale of wavelet decomposition. Graph measures are extracted and extensive comparisons with generative models of structured networks are conducted.Main resultsThe sample size and filtering are critical to obtain significant correlations values and thereby detect connections between regions. This is necessary to construct networks different from random ones as shown using rs-fMRI brain networks of dead rats. Brain networks under anesthesia on rats have topological features that are mixing small-world, scale-free and random networks. Betweenness centrality indicates that hubs are present in brain networks obtained from anesthetized rats but locations of these hubs are altered by anesthesia.SignificanceUnderstanding the effects of anesthesia on brain areas is of particular importance in the context of animal research since animal models are commonly used to explore functions, evaluate lesions or illnesses, and test new drugs. More generally, results indicate that the use of correlations in the context of fMRI signals is robust but must be treated with caution. Solutions are proposed in order to control spurious correlations by setting them to zero.

PMID: 32580176 [PubMed - as supplied by publisher]

Differences of connectivity between ESRD patients with PD and HD.

Thu, 06/25/2020 - 23:20
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Differences of connectivity between ESRD patients with PD and HD.

Brain Behav. 2020 Jun 24;:e01708

Authors: Park BS, Seong M, Ko J, Park SH, Kim YW, Hwan Kim I, Park JH, Lee YJ, Park S, Park KM

Abstract
OBJECTIVES: The aim of this study was to investigate alterations in structural and functional brain connectivity between patients with end-stage renal disease (ESRD) who were undergoing peritoneal dialysis (PD) and hemodialysis (HD).
METHODS: We enrolled 40 patients with ESRD who were undergoing PD (20 patients) and HD (20 patients). We also enrolled healthy participants as a control group. All of the subjects underwent diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI). Using data from the structural and functional connectivity matrix based on DTI and rs-fMRI, we calculated several network measures using graph theoretical analysis.
RESULTS: The measures of global structural connectivity were significantly different between the patients with ESRD who were undergoing PD and healthy subjects. The global efficiency and local efficiency in the patients with PD were significantly decreased compared with those in healthy participants. However, all of the measures of global structural connectivity in the patients with HD were not different from those in healthy participants. Conversely, in the global functional connectivity, the characteristic path length was significantly increased and the small-worldness index was decreased in patients with HD. However, the measures of the global functional connectivity in the patients with PD were not different from those in healthy subjects.
CONCLUSION: This study revealed that alterations in structural and functional connectivity in patients who were undergoing PD and HD were different than those in healthy controls. These findings suggest that brain networks may be affected by different types of renal replacement therapy.

PMID: 32578955 [PubMed - as supplied by publisher]

Propagation of BOLD Activity Reveals Task-dependent Directed Interactions Across Human Visual Cortex.

Thu, 06/25/2020 - 23:20
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Propagation of BOLD Activity Reveals Task-dependent Directed Interactions Across Human Visual Cortex.

Cereb Cortex. 2020 Jun 24;:

Authors: Gravel N, Renken RJ, Harvey BM, Deco G, Cornelissen FW, Gilson M

Abstract
It has recently been shown that large-scale propagation of blood-oxygen-level-dependent (BOLD) activity is constrained by anatomical connections and reflects transitions between behavioral states. It remains to be seen, however, if the propagation of BOLD activity can also relate to the brain's anatomical structure at a more local scale. Here, we hypothesized that BOLD propagation reflects structured neuronal activity across early visual field maps. To explore this hypothesis, we characterize the propagation of BOLD activity across V1, V2, and V3 using a modeling approach that aims to disentangle the contributions of local activity and directed interactions in shaping BOLD propagation. It does so by estimating the effective connectivity (EC) and the excitability of a noise-diffusion network to reproduce the spatiotemporal covariance structure of the data. We apply our approach to 7T fMRI recordings acquired during resting state (RS) and visual field mapping (VFM). Our results reveal different EC interactions and changes in cortical excitability in RS and VFM, and point to a reconfiguration of feedforward and feedback interactions across the visual system. We conclude that the propagation of BOLD activity has functional relevance, as it reveals directed interactions and changes in cortical excitability in a task-dependent manner.

PMID: 32577717 [PubMed - as supplied by publisher]

Spontaneous cognition and its relationship to human creativity: a functional connectivity study involving a chain free association task.

Wed, 06/24/2020 - 23:19
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Spontaneous cognition and its relationship to human creativity: a functional connectivity study involving a chain free association task.

Neuroimage. 2020 Jun 20;:117064

Authors: Marron TR, Berant E, Axelrod V, Faust M

Abstract
Resting-state functional connectivity (RSFC) between various brain regions is thought to be associated with creative abilities. Extensive research correlating RSFC with performance on creativity tasks has revealed some of the RSFC patterns characterizing 'the creative brain'. Yet, our understanding of the neurocognitive processes underlying creative thinking still remains limited. This limitation results, in part, from the fact that standard creativity tasks used in these studies do not distinguish between the different modes of cognitive processing that are critical in creative cognition (e.g., spontaneous cognition vs. controlled cognition). In the present fMRI research we address this limitation by using a chain free association task - a task that we have recently refined and validated for the purpose of isolating measures of spontaneous cognition that are relevant for creative thinking (referred to as associative fluency and associative flexibility). In our study, 27 female participants completed standardized creativity tasks, a chain free association task, and an fMRI scan in which RSFC was measured. Our results indicate that higher scores on associative fluency are associated with stronger positive RSFC within the default mode network (DMN; i.e., between DMN regions). Critically, we provide evidence that the previously-identified relationship between performance on creativity tasks and connectivity within the DMN is partially mediated by associative fluency. Thus, our observations suggest that the heightened DMN connectivity observed in 'the creative brain' can be explained, at least to some extent, by spontaneous cognition. Overall, our study identifies unique RSFC patterns that are related specifically to spontaneous cognitive processes involved in creative ideation, thus shedding new light on mechanisms of creative processing.

PMID: 32574810 [PubMed - as supplied by publisher]

The same, but different: Preserved distractor suppression in old age is implemented through an age-specific reactive ventral fronto-parietal network.

Wed, 06/24/2020 - 23:19
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The same, but different: Preserved distractor suppression in old age is implemented through an age-specific reactive ventral fronto-parietal network.

Hum Brain Mapp. 2020 Jun 23;:

Authors: Ashinoff BK, Mayhew SD, Mevorach C

Abstract
Previous studies have shown age-related impairments in the ability to suppress salient distractors. One possibility is that this is mediated by age-related impairments in the recruitment of the left intraparietal sulcus (Left IPS), which has been shown to mediate the suppression of salient distractors in healthy, young participants. Alternatively, this effect may be due to a shift in engagement from proactive control to reactive control, possibly to compensate for age-related impairments in proactive control. Another possibility is that this is due to changes in the functional specificity of brain regions that mediate salience suppression, expressed in changes in spontaneous connectivity of these regions. We assessed these possibilities by having participants engage in a proactive distractor suppression task while in an fMRI scanner. Although we did not find any age-related differences in behavior, the young (N = 15) and older (N = 15) cohorts engaged qualitatively distinctive brain networks to complete the task. Younger participants engaged the predicted proactive control network, including the Left IPS. On the other hand, older participants simultaneously engaged both a proactive and a reactive network, but this was not a consequence of reduced network specificity as resting state functional connectivity was largely comparable in both age groups. Furthermore, improved behavioral performance for older adults was associated with increased resting state functional connectivity between these two networks. Overall, the results of this study suggest that age-related differences in the recruitment of a left lateralized ventral fronto-parietal network likely reflect the specific recruitment of reactive control mechanisms for distractor inhibition.

PMID: 32573907 [PubMed - as supplied by publisher]

Heterogeneity of Outcomes and Network Connectivity in Early-Stage Psychosis: A Longitudinal Study.

Wed, 06/24/2020 - 23:19
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Heterogeneity of Outcomes and Network Connectivity in Early-Stage Psychosis: A Longitudinal Study.

Schizophr Bull. 2020 Jun 23;:

Authors: Chan SY, Brady R, Hwang M, Higgins A, Nielsen K, Öngür D, Hall MH

Abstract
Imaging studies in psychotic disorders typically examine cross-sectional relationships between magnetic resonance imaging (MRI) signals and diagnosis or symptoms. We sought to examine changes in network connectivity identified using resting-state functional MRI (fMRI) corresponding to divergent functional recovery trajectories and relapse in early-stage psychosis (ESP). Prior studies have linked schizophrenia to hyperconnectivity in the default mode network (DMN). Given the correlations between the DMN and behavioral impairments in psychosis, we hypothesized that dynamic changes in DMN connectivity reflect the heterogeneity of outcomes in ESP. Longitudinal data were collected from 66 ESP patients and 20 healthy controls. Longitudinal cluster analysis identified subgroups of patients with similar trajectories in terms of symptom severity and functional outcomes. DMN connectivity was measured in a subset of patients (n = 36) longitudinally over 2 scans separated by a mean of 12 months. We then compared connectivity between patients and controls, and among the different outcome trajectory subgroups. Among ESP participants, 4 subgroups were empirically identified corresponding to: "Poor," "Middle," "Catch-up," and "Good" trajectory outcomes in the complete dataset (n = 36), and an independent replication (n = 30). DMN connectivity changes differed significantly between functional subgroups (F3,32 = 6.06, P-FDR corrected = .01); DMN connectivity increased over time in the "Poor" outcome cluster (β = +0.145) but decreased over time in the "Catch-up" cluster (β = -0.212). DMN connectivity is dynamic and correlates with a change in functional status over time in ESP. This approach identifies a brain-based marker that reflects important neurobiological processes required to sustain functional recovery.

PMID: 32572485 [PubMed - as supplied by publisher]