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Journal articles on the topic 'Graph fMRI brain resting state functional connectivity'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Razi, Adeel, Mohamed L. Seghier, Yuan Zhou, et al. "Large-scale DCMs for resting-state fMRI." Network Neuroscience 1, no. 3 (2017): 222–41. http://dx.doi.org/10.1162/netn_a_00015.

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This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in term

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Aqil, Marco, Selen Atasoy, Morten L. Kringelbach, and Rikkert Hindriks. "Graph neural fields: A framework for spatiotemporal dynamical models on the human connectome." PLOS Computational Biology 17, no. 1 (2021): e1008310. http://dx.doi.org/10.1371/journal.pcbi.1008310.

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Tools from the field of graph signal processing, in particular the graph Laplacian operator, have recently been successfully applied to the investigation of structure-function relationships in the human brain. The eigenvectors of the human connectome graph Laplacian, dubbed “connectome harmonics”, have been shown to relate to the functionally relevant resting-state networks. Whole-brain modelling of brain activity combines structural connectivity with local dynamical models to provide insight into the large-scale functional organization of the human brain. In this study, we employ the graph La

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Mechling, Anna E., Tanzil Arefin, Hsu-Lei Lee, et al. "Deletion of the mu opioid receptor gene in mice reshapes the reward–aversion connectome." Proceedings of the National Academy of Sciences 113, no. 41 (2016): 11603–8. http://dx.doi.org/10.1073/pnas.1601640113.

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Connectome genetics seeks to uncover how genetic factors shape brain functional connectivity; however, the causal impact of a single gene’s activity on whole-brain networks remains unknown. We tested whether the sole targeted deletion of the mu opioid receptor gene (Oprm1) alters the brain connectome in living mice. Hypothesis-free analysis of combined resting-state fMRI diffusion tractography showed pronounced modifications of functional connectivity with only minor changes in structural pathways. Fine-grained resting-state fMRI mapping, graph theory, and intergroup comparison revealed Oprm1-

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Hamdi, Shah Muhammad, Yubao Wu, Rafal Angryk, Lisa Crystal Krishnamurthy, and Robin Morris. "Identification of Discriminative Subnetwork from fMRI-Based Complete Functional Connectivity Networks." International Journal of Semantic Computing 13, no. 01 (2019): 25–44. http://dx.doi.org/10.1142/s1793351x19400026.

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The comprehensive set of neuronal connections of the human brain, which is known as the human connectomes, has provided valuable insight into neurological and neurodevelopmental disorders. Functional Magnetic Resonance Imaging (fMRI) has facilitated this research by capturing regionally specific brain activity. Resting state fMRI is used to extract the functional connectivity networks, which are edge-weighted complete graphs. In these complete functional connectivity networks, each node represents one brain region or Region of Interest (ROI), and each edge weight represents the strength of fun

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RANGAPRAKASH, D., XIAOPING HU, and GOPIKRISHNA DESHPANDE. "PHASE SYNCHRONIZATION IN BRAIN NETWORKS DERIVED FROM CORRELATION BETWEEN PROBABILITIES OF RECURRENCES IN FUNCTIONAL MRI DATA." International Journal of Neural Systems 23, no. 02 (2013): 1350003. http://dx.doi.org/10.1142/s0129065713500032.

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It is increasingly being recognized that resting state brain connectivity derived from functional magnetic resonance imaging (fMRI) data is an important marker of brain function both in healthy and clinical populations. Though linear correlation has been extensively used to characterize brain connectivity, it is limited to detecting first order dependencies. In this study, we propose a framework where in phase synchronization (PS) between brain regions is characterized using a new metric "correlation between probabilities of recurrence" (CPR) and subsequent graph-theoretic analysis of the ensu

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Faivre, Anthony, Emmanuelle Robinet, Maxime Guye, et al. "Depletion of brain functional connectivity enhancement leads to disability progression in multiple sclerosis: A longitudinal resting-state fMRI study." Multiple Sclerosis Journal 22, no. 13 (2016): 1695–708. http://dx.doi.org/10.1177/1352458516628657.

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Background: The compensatory effect of brain functional connectivity enhancement in relapsing-remitting multiple sclerosis (RRMS) remains controversial. Objective: To characterize the relationships between brain functional connectivity changes and disability progression in RRMS. Methods: Long-range connectivity, short-range connectivity, and density of connections were assessed using graph theoretical analysis of resting-state functional magnetic resonance imaging (fMRI) data acquired in 38 RRMS patients (disease duration: 120 ± 32 months) and 24 controls. All subjects were explored at baselin

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Simos, Nicholas John, Stavros I. Dimitriadis, Eleftherios Kavroulakis, et al. "Quantitative Identification of Functional Connectivity Disturbances in Neuropsychiatric Lupus Based on Resting-State fMRI: A Robust Machine Learning Approach." Brain Sciences 10, no. 11 (2020): 777. http://dx.doi.org/10.3390/brainsci10110777.

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Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity comprised of heterogenous syndromes affecting both the peripheral and central nervous system. Research on the pathophysiological substrate of NPSLE manifestations, including functional neuroimaging studies, is extremely limited. The present study examined person-specific patterns of whole-brain functional connectivity in NPSLE patients (n = 44) and age-matched healthy control participants (n = 39). Static functional connectivity graphs were calculated comprised of connection strengths between 90 brain regions. These

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V. Farahani, Farzad, Magdalena Fafrowicz, Waldemar Karwowski, et al. "Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory." Brain Sciences 11, no. 1 (2021): 111. http://dx.doi.org/10.3390/brainsci11010111.

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Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We fou

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Kim, Kamin, Matthew S. Sherwood, Lindsey K. McIntire, R. Andy McKinley, and Charan Ranganath. "Transcranial Direct Current Stimulation Modulates Connectivity of Left Dorsolateral Prefrontal Cortex with Distributed Cortical Networks." Journal of Cognitive Neuroscience 33, no. 7 (2021): 1381–95. http://dx.doi.org/10.1162/jocn_a_01725.

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Abstract Studies have shown that transcranial direct current stimulation increases neuronal excitability of the targeted region and general connectivity of relevant functional networks. However, relatively little is understood of how the stimulation affects the connectivity relationship of the target with regions across the network structure of the brain. Here, we investigated the effects of transcranial direct current stimulation on the functional connectivity of the targeted region using resting-state fMRI scans of the human brain. Anodal direct current stimulation was applied to the left do

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Song, Ke, Juan Li, Yuanqiang Zhu, Fang Ren, Lingcan Cao, and Zi-Gang Huang. "Altered Small-World Functional Network Topology in Patients with Optic Neuritis: A Resting-State fMRI Study." Disease Markers 2021 (June 14, 2021): 1–9. http://dx.doi.org/10.1155/2021/9948751.

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Aim. This study investigated changes in small-world topology and brain functional connectivity in patients with optic neuritis (ON) by resting-state functional magnetic resonance imaging (rs-fMRI) and based on graph theory. Methods. A total of 21 patients with ON (8 males and 13 females) and 21 matched healthy control subjects (8 males and 13 females) were enrolled and underwent rs-fMRI. Data were preprocessed and the brain was divided into 116 regions of interest. Small-world network parameters and area under the integral curve (AUC) were calculated from pairwise brain interval correlation co

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Filippi, Massimo, Silvia Basaia, Elisa Canu, et al. "Brain network connectivity differs in early-onset neurodegenerative dementia." Neurology 89, no. 17 (2017): 1764–72. http://dx.doi.org/10.1212/wnl.0000000000004577.

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Objective:To investigate functional brain network architecture in early-onset Alzheimer disease (EOAD) and behavioral variant frontotemporal dementia (bvFTD).Methods:Thirty-eight patients with bvFTD, 37 patients with EOAD, and 32 age-matched healthy controls underwent 3D T1-weighted and resting-state fMRI. Graph analysis and connectomics assessed global and local functional topologic network properties, regional functional connectivity, and intrahemispheric and interhemispheric between-lobe connectivity.Results:Despite similarly extensive cognitive impairment relative to controls, patients wit

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Bhaskaran, Bhuvaneshwari, and Kavitha Anandan. "Assessment of Graph Metrics and Lateralization of Brain Connectivity in Progression of Alzheimer's Disease Using fMRI." International Journal of Software Science and Computational Intelligence 9, no. 4 (2017): 46–66. http://dx.doi.org/10.4018/ijssci.2017100104.

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Alzheimer's disease (AD) is a progressive brain disorder which has a long preclinical phase. The beta-amyloid plaques and tangles in the brain are considered as the main pathological causes. Functional connectivity is typically examined in capturing brain network dynamics in AD. A definitive underconnectivity is observed in patients through the progressive stages of AD. Graph theoretic modeling approaches have been effective in understanding the brain dynamics. In this article, the brain connectivity patterns and the functional topology through the progression of Alzheimer's disease are analys

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Xiao, F., L. Zhao, and F. Han. "0761 Independent Components Analysis And Graph Theoretical Analysis In Patients With Narcolepsy." Sleep 43, Supplement_1 (2020): A289. http://dx.doi.org/10.1093/sleep/zsaa056.757.

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Abstract Introduction To evaluate resting state functional connectivity and topological properties of brain network in narcolepsy compared with healthy controls. Methods Resting state fMRI was performed in 26 adult narcolepsy patients and 30 matched healthy controls. MRI data was first analyzed by group independent component analysis, then a graph theoretical method was applied to evaluate topological properties within whole brain. Small-world network parameters and nodal topological properties were measured. Altered topological properties in brain areas between groups were selected as ROI-see

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dos Santos Siqueira, Anderson, Claudinei Eduardo Biazoli Junior, William Edgar Comfort, Luis Augusto Rohde, and João Ricardo Sato. "Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data." BioMed Research International 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/380531.

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The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders. Graph description measures may be useful as predictor variables in classification procedures. Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). The prediction was based on a support vector machines classifier. The analyses wer

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Salvador, Raymond, John Suckling, Christian Schwarzbauer, and Ed Bullmore. "Undirected graphs of frequency-dependent functional connectivity in whole brain networks." Philosophical Transactions of the Royal Society B: Biological Sciences 360, no. 1457 (2005): 937–46. http://dx.doi.org/10.1098/rstb.2005.1645.

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We explored properties of whole brain networks based on multivariate spectral analysis of human functional magnetic resonance imaging (fMRI) time-series measured in 90 cortical and subcortical subregions in each of five healthy volunteers studied in the (no-task) resting state. We note that undirected graphs representing conditional independence between multivariate time-series can be more readily approached in the frequency domain than the time domain. Estimators of partial coherency and normalized partial mutual information ϕ , an integrated measure of partial coherence over an arbitrary fre

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Ikeda, KM, SM Mirsattari, AR Khan, I. Johnsrude, JG Burneo, and TM Peters. "GP.04 Network connectivity following a single unprovoked seizure using 7 Tesla resting-state fMRI." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 44, S2 (2017): S8. http://dx.doi.org/10.1017/cjn.2017.63.

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Background: Predicting epilepsy following a first seizure is difficult. Network abnormalities are observed in patients with epilepsy using resting-state functional MRI (rs-fMRI), which worsen with duration of epilepsy. We use rs-fMRI to identify network abnormalities in patients after a first seizure that can be used as a biomarker to predict development of epilepsy. Methods: Patients after a single, unprovoked seizure and age/sex matched healthy controls underwent 7 Tesla structural and resting-state functional MRI. Data were analyzed using graph theory measures. Patients were followed for de

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Kim, Seong-Ho, Min-Woo Lee, Min-Jae Kang, Sung Gun Lee, Jung-Goo Lee, and Chi-Woong Mun. "Comparison Analysis between the Medication Efficacy of the Milnacipran and Functional Connectivity of Neural Networks in Fibromyalgia Patients." Brain Sciences 10, no. 5 (2020): 295. http://dx.doi.org/10.3390/brainsci10050295.

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Milnacipran is a reuptake inhibitor of both serotonin and noradrenaline, used in the treatment of fibromyalgia with severe depression. However, few studies have been conducted on the efficacies of milnacipran drug on the functional connectivity of the neural network. The authors aimed to find the correlation between the drug efficacy and the changes in neural network in fibromyalgia patients. Resting-state-functional magnetic resonance imaging (rs-fMRI) were obtained before and after milnacipran drug administration. Graph theory indexes and small-worldness were calculated using preprocessed bl

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Gao, Zhongke, Yanhua Feng, Chao Ma, Kai Ma, Qing Cai, and and for the Alzheimer’s Disease Neuroimaging Initiative. "Disrupted Time-Dependent and Functional Connectivity Brain Network in Alzheimer's Disease: A Resting-State fMRI Study Based on Visibility Graph." Current Alzheimer Research 17, no. 1 (2020): 69–79. http://dx.doi.org/10.2174/1567205017666200213100607.

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Background: Alzheimer's Disease (AD) is a progressive neurodegenerative disease with insidious onset, which is difficult to be reversed and cured. Therefore, discovering more precise biological information from neuroimaging biomarkers is crucial for accurate and automatic detection of AD. Methods: We innovatively used a Visibility Graph (VG) to construct the time-dependent brain networks as well as functional connectivity network to investigate the underlying dynamics of AD brain based on functional magnetic resonance imaging. There were 32 AD patients and 29 Normal Controls (NCs) from the Alz

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Li, Wenjing, Jianhong Li, Jieqiong Wang, et al. "Functional Reorganizations of Brain Network in Prelingually Deaf Adolescents." Neural Plasticity 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/9849087.

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Previous neuroimaging studies suggested structural or functional brain reorganizations occurred in prelingually deaf subjects. However, little is known about the reorganizations of brain network architectures in prelingually deaf adolescents. The present study aims to investigate alterations of whole-brain functional network using resting-state fMRI and graph theory analysis. We recruited 16 prelingually deaf adolescents (10~18 years) and 16 normal controls matched in age and gender. Brain networks were constructed from mean time courses of 90 regions. Widely distributed network was observed i

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Lei, Du, Jun Ma, Jilei Zhang, et al. "Connectome-Scale Assessments of Functional Connectivity in Children with Primary Monosymptomatic Nocturnal Enuresis." BioMed Research International 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/463708.

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Primary monosymptomatic nocturnal enuresis (PMNE) is a common developmental disorder in children. Previous literature has suggested that PMNE not only is a micturition disorder but also is characterized by cerebral structure abnormalities and dysfunction. However, the biological mechanisms underlying the disease are not thoroughly understood. Graph theoretical analysis has provided a unique tool to reveal the intrinsic attributes of the connectivity patterns of a complex network from a global perspective. Resting-state fMRI was performed in 20 children with PMNE and 20 healthy controls. Brain

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Huang, Zirui, Henry (Hap) Davis IV, Annemarie Wolff, and Georg Northoff. "Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes." Neural Plasticity 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/1473783.

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Brain plasticity studies have shown functional reorganization in participants with outstanding motor expertise. Little is known about neural plasticity associated with exceptionally long motor training or of its predictive value for motor performance excellence. The present study utilised resting-state functional magnetic resonance imaging (rs-fMRI) in a unique sample of world-class athletes: Olympic, elite, and internationally ranked swimmers (n=30). Their world ranking ranged from 1st to 250th: each had prepared for participation in the Olympic Games. Combining rs-fMRI graph-theoretical and

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Fan, Xiaoxuan, Yujia Wu, Lei Cai, et al. "The Differences in the Whole-Brain Functional Network between Cantonese-Mandarin Bilinguals and Mandarin Monolinguals." Brain Sciences 11, no. 3 (2021): 310. http://dx.doi.org/10.3390/brainsci11030310.

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Cantonese-Mandarin bilinguals are logographic-logographic bilinguals that provide a unique population for bilingual studies. Whole brain functional connectivity analysis makes up for the deficiencies of previous bilingual studies on the seed-based approach and helps give a complete picture of the brain connectivity profiles of logographic-logographic bilinguals. The current study is to explore the effect of the long-term logographic-logographic bilingual experience on the functional connectivity of the whole-brain network. Thirty Cantonese-Mandarin bilingual and 30 Mandarin monolingual college

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Dimech, Christina J., John A. E. Anderson, Amber W. Lockrow, R. Nathan Spreng, and Gary R. Turner. "Sex differences in the relationship between cardiorespiratory fitness and brain function in older adulthood." Journal of Applied Physiology 126, no. 4 (2019): 1032–41. http://dx.doi.org/10.1152/japplphysiol.01046.2018.

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We investigated sex differences in the association between a measure of physical health, cardiorespiratory fitness (CRF), and brain function using resting-state functional connectivity fMRI. We examined these sex differences in the default, frontoparietal control, and cingulo-opercular networks, assemblies of functionally connected brain regions known to be impacted by both age and fitness level. Healthy older adults ( n = 49; 29 women) were scanned to obtain measures of intrinsic connectivity within and across these 3 networks. We calculated global efficiency (a measure of network integration

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Zhang, Wei, Viktoria Muravina, Robert Azencott, Zili D. Chu, and Michael J. Paldino. "Mutual Information Better Quantifies Brain Network Architecture in Children with Epilepsy." Computational and Mathematical Methods in Medicine 2018 (October 22, 2018): 1–9. http://dx.doi.org/10.1155/2018/6142898.

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Purpose. Metrics of the brain network architecture derived from resting-state fMRI have been shown to provide physiologically meaningful markers of IQ in children with epilepsy. However, traditional measures of functional connectivity (FC), specifically the Pearson correlation, assume a dominant linear relationship between BOLD time courses; this assumption may not be valid. Mutual information is an alternative measure of FC which has shown promise in the study of complex networks due to its ability to flexibly capture association of diverse forms. We aimed to compare network metrics derived f

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Zang, Zhenxiang, Lena S. Geiger, Urs Braun, et al. "Resting-state brain network features associated with short-term skill learning ability in humans and the influence of N-methyl-d-aspartate receptor antagonism." Network Neuroscience 2, no. 4 (2018): 464–80. http://dx.doi.org/10.1162/netn_a_00045.

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Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliabili

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Boutière, Clémence, Caroline Rey, Wafaa Zaaraoui, et al. "Improvement of spasticity following intermittent theta burst stimulation in multiple sclerosis is associated with modulation of resting-state functional connectivity of the primary motor cortices." Multiple Sclerosis Journal 23, no. 6 (2016): 855–63. http://dx.doi.org/10.1177/1352458516661640.

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Background: Intermittent theta burst stimulation (iTBS) of the primary motor cortex improves transiently lower limbs spasticity in multiple sclerosis (MS). However, the cerebral mechanisms underlying this effect have never been investigated. Objective: To assess whether modulation of spasticity induced by iTBS is underlined by functional reorganization of the primary motor cortices. Methods: A total of 17 patients with MS suffering from lower limbs spasticity were randomized to receive real iTBS or sham iTBS during the first half of a 5-week indoor rehabilitation programme. Spasticity was asse

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Schoonheim, M. M., J. J. G. Geurts, O. T. Wiebenga, et al. "Changes in functional network centrality underlie cognitive dysfunction and physical disability in multiple sclerosis." Multiple Sclerosis Journal 20, no. 8 (2013): 1058–65. http://dx.doi.org/10.1177/1352458513516892.

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Background: Cognitive dysfunction in multiple sclerosis (MS) has a large impact on the quality of life and is poorly understood. Objective: The aim of this study was to investigate functional network integrity in MS, and relate this to cognitive dysfunction and physical disability. Methods: Resting state fMRI scans were included of 128 MS patients and 50 controls. Eigenvector centrality mapping (ECM) was applied, a graph analysis technique that ranks the importance of brain regions based on their connectivity patterns. Significant ECM changes were related to physical disability and cognitive d

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Guo, Shuixia, Ningning He, Zhening Liu, Zeqiang Linli, Haojuan Tao, and Lena Palaniyappan. "Brain-Wide Functional Dysconnectivity in Schizophrenia: Parsing Diathesis, Resilience, and the Effects of Clinical Expression." Canadian Journal of Psychiatry 65, no. 1 (2019): 21–29. http://dx.doi.org/10.1177/0706743719890174.

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Background: The functional dysconnectivity observed from functional magnetic resonance imaging (fMRI) studies in schizophrenia is also seen in unaffected siblings indicating its association with the genetic diathesis. We intended to apportion resting-state dysconnectivity into components that represent genetic diathesis, clinical expression or treatment effect, and resilience. Methods: fMRI data were acquired from 28 schizophrenia patients, 28 unaffected siblings, and 60 healthy controls. Based on Dosenbach’s atlas, we extracted time series of 160 regions of interest. After constructing functi

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Naidu, D. J. Samatha, and G. Anand Kumar Reddy. "EARLIER DETECTION OF ALZHEIMER’S DISEASE USING IMAGE PROCESSING AND MACHINE LEARNING ALGORITHMS WITH GRAPH THEORY." International Journal of Computer Science and Mobile Computing 10, no. 8 (2021): 36–40. http://dx.doi.org/10.47760/ijcsmc.2021.v10i08.006.

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Alzheimer’s disease is one of the brain disease which is irreversible, progressive brain disorder that slowly destroys memory and thinking skills and, eventually, the ability to carry out the simplest tasks. There is no cure for Alzheimer’s disease but we prevent it’s by early detection. In existing work, limited with Alzheimer’s are irreversible, effect on daily activities, high memory loss and reducing the size of brain, etc. previous works focused on 2D and 3D formats now we considering 4D images. In proposed work, this work aims to present an automated method that assists in the diagnosis

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Weng, Jun-Cheng, Yu-Syuan Chou, Yuan-Hsiung Tsai, Chun-Te Lee, Ming-Hong Hsieh, and Vincent Chin-Hung Chen. "Connectome Analysis of Brain Functional Network Alterations in Depressive Patients with Suicidal Attempt." Journal of Clinical Medicine 8, no. 11 (2019): 1966. http://dx.doi.org/10.3390/jcm8111966.

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Our study aimed to clarify the neuroimaging correlates of suicide attempt by comparing differences in functional magnetic resonance imaging (fMRI) among depressed suicide attempters, depressed patients without suicide attempt history, and healthy controls through comprehensive and novel fMRI analyses and methods in the same study population. The association between depression severity and aspects of the brain imaging was also discussed. Our study recruited 109 participants who were assigned to three groups: 33 depressed patients with suicide attempt (SA), 32 depressed patients without suicide

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Cisler, J. M., G. A. James, S. Tripathi, et al. "Differential functional connectivity within an emotion regulation neural network among individuals resilient and susceptible to the depressogenic effects of early life stress." Psychological Medicine 43, no. 3 (2012): 507–18. http://dx.doi.org/10.1017/s0033291712001390.

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BackgroundEarly life stress (ELS) is a significant risk factor for depression. The effects of ELS exposure on neural network organization have not been differentiated from the effect of depression. Furthermore, many individuals exposed to ELS do not develop depression, yet the network organization patterns differentiating resiliency versus susceptibility to the depressogenic effects of ELS are not clear.MethodWomen aged 18–44 years with either a history of ELS and no history of depression (n = 7), a history of ELS and current or past depression (n = 19), or a history of neither ELS nor depress

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He, Shihao, Ziqi Liu, Zongsheng Xu, et al. "Brain Functional Network in Chronic Asymptomatic Carotid Artery Stenosis and Occlusion: Changes and Compensation." Neural Plasticity 2020 (September 23, 2020): 1–11. http://dx.doi.org/10.1155/2020/9345602.

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Asymptomatic carotid artery stenosis (CAS) and occlusion (CAO) disrupt cerebral hemodynamics. There are few studies on the brain network changes and compensation associated with the progression from chronic CAS to CAO. In the current study, our goal is to improve the understanding of the specific abnormalities and compensatory phenomena associated with the functional connection in patients with CAS and CAO. In this prospective study, 27 patients with CAO, 29 patients with CAS, and 15 healthy controls matched for age, sex, education, handedness, and risk factors underwent neuropsychological tes

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Monroe, Derek C., David Keator, Robert Blumenfeld, James Hicks, and Steven L. Small. "Changes in functional connectivity are associated with one season of head-to-ball impact exposure in male collegiate soccer athletes." Neurology 91, no. 23 Supplement 1 (2018): S14.2—S15. http://dx.doi.org/10.1212/01.wnl.0000550677.08469.57.

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ObjectivesReturn-to-play protocols could be improved by a better understanding of the physiologic effects of mild traumatic brain injury (mTBI). Autonomic dysregulation is thought to underlie many of the multi-dimensional symptoms following mTBI and may derive from altered connectivity in the brain central autonomic network (CAN). Understanding the relationship between injury and CAN connectivity could lead to a useful biomarker for mTBI. Toward this end, the present study aimed to establish a formal relationship between non-symptomatic head-to-ball impacts (“headers”) and CAN connectivity in

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Lo, Chun-Yi Zac, Tsung-Wei Su, Chu-Chung Huang, et al. "Randomization and resilience of brain functional networks as systems-level endophenotypes of schizophrenia." Proceedings of the National Academy of Sciences 112, no. 29 (2015): 9123–28. http://dx.doi.org/10.1073/pnas.1502052112.

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Schizophrenia is increasingly conceived as a disorder of brain network organization or dysconnectivity syndrome. Functional MRI (fMRI) networks in schizophrenia have been characterized by abnormally random topology. We tested the hypothesis that network randomization is an endophenotype of schizophrenia and therefore evident also in nonpsychotic relatives of patients. Head movement-corrected, resting-state fMRI data were acquired from 25 patients with schizophrenia, 25 first-degree relatives of patients, and 29 healthy volunteers. Graphs were used to model functional connectivity as a set of e

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He, Xiaosong, Gaelle E. Doucet, Dorian Pustina, Michael R. Sperling, Ashwini D. Sharan, and Joseph I. Tracy. "Presurgical thalamic “hubness” predicts surgical outcome in temporal lobe epilepsy." Neurology 88, no. 24 (2017): 2285–93. http://dx.doi.org/10.1212/wnl.0000000000004035.

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Objective:To characterize the presurgical brain functional architecture presented in patients with temporal lobe epilepsy (TLE) using graph theoretical measures of resting-state fMRI data and to test its association with surgical outcome.Methods:Fifty-six unilateral patients with TLE, who subsequently underwent anterior temporal lobectomy and were classified as obtaining a seizure-free (Engel class I, n = 35) vs not seizure-free (Engel classes II–IV, n = 21) outcome at 1 year after surgery, and 28 matched healthy controls were enrolled. On the basis of their presurgical resting-state functiona

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Neyland, Blake R., Robert Kraft, Mary Lyles, et al. "EFFECTS OF FUNCTIONAL BRAIN NETWORKS AND WHITE MATTER DISEASE ON MOBILITY OF OLDER ADULTS IN AN EXERCISE INTERVENTION." Innovation in Aging 3, Supplement_1 (2019): S851—S852. http://dx.doi.org/10.1093/geroni/igz038.3132.

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Abstract Declining mobility is associated with increased accumulation of white matter hyperintensities (WMH). However, a high WMH burden is not always accompanied by impaired mobility. Our previous work demonstrates that some variance in mobility may be explained by brain network connectivity. Here, we extended this work by measuring WMHs and brain networks in older adults participating in a lifestyle intervention. The Short Physical Performance Battery (SPPB) and resting state functional magnetic resonance imaging (fMRI) were collected before and after a 5-month caloric restriction plus aerob

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Smitha, KA, K. Akhil Raja, KM Arun, et al. "Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks." Neuroradiology Journal 30, no. 4 (2017): 305–17. http://dx.doi.org/10.1177/1971400917697342.

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The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at ‘resting state’. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the s

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Shim, Miseon, Han-Jeong Hwang, Ulrike Kuhl, and Hyeon-Ae Jeon. "Resting-State Functional Connectivity in Mathematical Expertise." Brain Sciences 11, no. 4 (2021): 430. http://dx.doi.org/10.3390/brainsci11040430.

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To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians an

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Schutte, Nienke M., Narelle K. Hansell, Eco J. C. de Geus, Nicholas G. Martin, Margaret J. Wright, and Dirk J. A. Smit. "Heritability of Resting State EEG Functional Connectivity Patterns." Twin Research and Human Genetics 16, no. 5 (2013): 962–69. http://dx.doi.org/10.1017/thg.2013.55.

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We examined the genetic architecture of functional brain connectivity measures in resting state electroencephalographic (EEG) recordings. Previous studies in Dutch twins have suggested that genetic factors are a main source of variance in functional brain connectivity derived from EEG recordings. In addition, qualitative descriptors of the brain network derived from graph analysis — network clustering and average path length — are also heritable traits. Here we replicated previous findings for connectivity, quantified by the synchronization likelihood, and the graph theoretical parameters clus

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Mendez-Torrijos, Andrea, Silke Kreitz, Claudiu Ivan, et al. "Snack food as a modulator of human resting-state functional connectivity." CNS Spectrums 23, no. 5 (2018): 321–32. http://dx.doi.org/10.1017/s1092852918000767.

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ObjectiveTo elucidate the mechanisms of how snack foods may induce non-homeostatic food intake, we used resting state functional magnetic resonance imaging (fMRI), as resting state networks can individually adapt to experience after short time exposures. In addition, we used graph theoretical analysis together with machine learning techniques (support vector machine) to identifying biomarkers that can categorize between high-caloric (potato chips) vs. low-caloric (zucchini) food stimulation.MethodsSeventeen healthy human subjects with body mass index (BMI) 19 to 27 underwent 2 different fMRI s

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Wirsich, Jonathan, Enrico Amico, Anne-Lise Giraud, Joaquín Goñi, and Sepideh Sadaghiani. "Multi-timescale hybrid components of the functional brain connectome: A bimodal EEG-fMRI decomposition." Network Neuroscience 4, no. 3 (2020): 658–77. http://dx.doi.org/10.1162/netn_a_00135.

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Concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) bridge brain connectivity across timescales. During concurrent EEG-fMRI resting-state recordings, whole-brain functional connectivity (FC) strength is spatially correlated across modalities. However, cross-modal investigations have commonly remained correlational, and joint analysis of EEG-fMRI connectivity is largely unexplored. Here we investigated if there exist (spatially) independent FC networks linked between modalities. We applied the recently proposed hybrid connectivity independent component analy

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Chan, Russell W., Alex T. L. Leong, Leon C. Ho, et al. "Low-frequency hippocampal–cortical activity drives brain-wide resting-state functional MRI connectivity." Proceedings of the National Academy of Sciences 114, no. 33 (2017): E6972—E6981. http://dx.doi.org/10.1073/pnas.1703309114.

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The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal–cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain

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Zhu, Jiating, and Jiannong Cao. "Distributional representation of resting-state fMRI for functional brain connectivity analysis." Neurocomputing 427 (February 2021): 156–68. http://dx.doi.org/10.1016/j.neucom.2020.07.106.

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Nikolaou, F., C. Orphanidou, P. Papakyriakou, K. Murphy, R. G. Wise, and G. D. Mitsis. "Spontaneous physiological variability modulates dynamic functional connectivity in resting-state functional magnetic resonance imaging." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, no. 2067 (2016): 20150183. http://dx.doi.org/10.1098/rsta.2015.0183.

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It is well known that the blood oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging (fMRI) is influenced—in addition to neuronal activity—by fluctuations in physiological signals, including arterial CO 2 , respiration and heart rate/heart rate variability (HR/HRV). Even spontaneous fluctuations of the aforementioned physiological signals have been shown to influence the BOLD fMRI signal in a regionally specific manner. Related to this, estimates of functional connectivity between different brain regions, performed when the subject is at rest, may be confounde

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Kazazian, Karnig, Loretta Norton, Teneille E. Gofton, Derek Debicki, and Adrian M. Owen. "Cortical Function in Acute Severe Traumatic Brain Injury and at Recovery: A Longitudinal fMRI Case Study." Brain Sciences 10, no. 9 (2020): 604. http://dx.doi.org/10.3390/brainsci10090604.

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Differences in the functional integrity of the brain from acute severe brain injury to subsequent recovery of consciousness have not been well documented. Functional magnetic resonance imaging (fMRI) may elucidate this issue as it allows for the objective measurement of brain function both at rest and in response to stimuli. Here, we report the cortical function of a patient with a severe traumatic brain injury (TBI) in a critically ill state and at subsequent functional recovery 9-months post injury. A series of fMRI paradigms were employed to assess sound and speech perception, command follo

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Petti, Manuela, Jlenia Toppi, Fabio Babiloni, Febo Cincotti, Donatella Mattia, and Laura Astolfi. "EEG Resting-State Brain Topological Reorganization as a Function of Age." Computational Intelligence and Neuroscience 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/6243694.

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Resting state connectivity has been increasingly studied to investigate the effects of aging on the brain. A reduced organization in the communication between brain areas was demonstrated by combining a variety of different imaging technologies (fMRI, EEG, and MEG) and graph theory. In this paper, we propose a methodology to get new insights into resting state connectivity and its variations with age, by combining advanced techniques of effective connectivity estimation, graph theoretical approach, and classification by SVM method. We analyzed high density EEG signals recorded at rest from 71

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Schulte, Laura H., Mareike M. Menz, Jan Haaker, and Arne May. "The migraineur’s brain networks: Continuous resting state fMRI over 30 days." Cephalalgia 40, no. 14 (2020): 1614–21. http://dx.doi.org/10.1177/0333102420951465.

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Objective The aim of the current study was to identify typical alterations in resting state connectivity within different stages of the migraine cycle and to thus explore task-free mechanisms of headache attack generation in migraineurs. Background Recent evidence in migraine pathophysiology suggests that hours and even days before headache certain changes in brain activity take place, ultimately leading to an attack. Here, we investigate changes before headache onset using resting state functional magnetic resonance imaging (fMRI). Methods Nine episodic migraineurs underwent daily resting sta

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Pijnenburg, Rory, Lianne H. Scholtens, Dante Mantini, Wim Vanduffel, Lisa Feldman Barrett, and Martijn P. van den Heuvel. "Biological Characteristics of Connection-Wise Resting-State Functional Connectivity Strength." Cerebral Cortex 29, no. 11 (2019): 4646–53. http://dx.doi.org/10.1093/cercor/bhy342.

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Abstract Functional connectivity is defined as the statistical dependency of neurophysiological activity between 2 separate brain areas. To investigate the biological characteristics of resting-state functional connectivity (rsFC)—and in particular the significance of connection-wise variation in time-series correlations—rsFC was compared with strychnine-based connectivity measured in the macaque. Strychnine neuronography is a historical technique that induces activity in cortical areas through means of local administration of the substance strychnine. Strychnine causes local disinhibition thr

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Di (邸新), Xin, and Bharat B. Biswal. "Characterizations of resting-state modulatory interactions in the human brain." Journal of Neurophysiology 114, no. 5 (2015): 2785–96. http://dx.doi.org/10.1152/jn.00893.2014.

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Functional connectivity between two brain regions, measured using functional MRI (fMRI), has been shown to be modulated by other regions even in a resting state, i.e., without performing specific tasks. We aimed to characterize large-scale modulatory interactions by performing region-of-interest (ROI)-based physiophysiological interaction analysis on resting-state fMRI data. Modulatory interactions were calculated for every possible combination of three ROIs among 160 ROIs sampling the whole brain. Firstly, among all of the significant modulatory interactions, there were considerably more nega

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Tomasi, Dardo, and Nora D. Volkow. "Association Between Brain Activation and Functional Connectivity." Cerebral Cortex 29, no. 5 (2018): 1984–96. http://dx.doi.org/10.1093/cercor/bhy077.

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Abstract The origin of the “resting-state” brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have l

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