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independent component analysis fMRI

Amanda Elton, Christopher T Smith, Michael H Parrish, Charlotte A Boettiger
Excessively choosing immediate over larger future rewards, or delay discounting (DD), associates with multiple clinical conditions. Individual differences in DD likely depend on variations in the activation of and functional interactions between networks, representing possible endophenotypes for associated disorders, including alcohol use disorders. Numerous fMRI studies have probed the neural bases of DD, but investigations of large-scale networks remain scant. We addressed this gap by testing whether activation within large-scale networks during Now/Later decision-making predicts individual differences in DD...
October 25, 2016: Journal of Cognitive Neuroscience
Michael F Regner, Naomi Saenz, Keeran Maharajh, Dorothy J Yamamoto, Brianne Mohl, Korey Wylie, Jason Tregellas, Jody Tanabe
OBJECTIVE: We hypothesized that compared to healthy controls, long-term abstinent substance dependent individuals (SDI) will differ in their effective connectivity between large-scale brain networks and demonstrate increased directional information from executive control to interoception-, reward-, and habit-related networks. In addition, using graph theory to compare network efficiencies we predicted decreased small-worldness in SDI compared to controls. METHODS: 50 SDI and 50 controls of similar sex and age completed psychological surveys and resting state fMRI...
2016: PloS One
Allison C Nugent, Bruce Luber, Frederick W Carver, Stephen E Robinson, Richard Coppola, Carlos A Zarate
Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies...
October 22, 2016: Human Brain Mapping
Johan van der Meer, André Pampel, Eus van Someren, Jennifer Ramautar, Ysbrand van der Werf, German Gomez-Herrero, Jöran Lepsien, Lydia Hellrung, Hermann Hinrichs, Harald Möller, Martin Walter
This data set contains electroencephalography (EEG) data as well as simultaneous EEG with functional magnetic resonance imaging (EEG/fMRI) data. During EEG/fMRI, the EEG cap was outfitted with a hardware-based add-on consisting of carbon-wire loops (CWL). These yielded six extra׳CWL׳ signals related to Faraday induction of these loops in the main magnetic field "Measurement and reduction of motion and ballistocardiogram artefacts from simultaneous EEG and fMRI recordings" (Masterton et al., 2007) [1]. In this data set, the CWL data make it possible to do a direct regression approach to deal with the BCG and specifically He artifact...
June 2016: Data in Brief
Davide Zanchi, Anne Christin Meyer-Gerspach, Claudia Suenderhauf, Katharina Janach, Carel W le Roux, Sven Haller, Jürgen Drewe, Christoph Beglinger, Bettina K Wölnerhanssen, Stefan Borgwardt
Depending on their protein content, single meals can rapidly influence the uptake of amino acids into the brain and thereby modify brain functions. The current study investigates the effects of two different amino acids on the human gut-brain system, using a multimodal approach, integrating physiological and neuroimaging data. In a randomized, placebo-controlled trial, L-tryptophan, L-leucine, glucose and water were administered directly into the gut of 20 healthy subjects. Functional MRI (fMRI) in a resting state paradigm (RS), combined with the assessment of insulin and glucose blood concentration, was performed before and after treatment...
October 20, 2016: Scientific Reports
Kristoffer H Madsen, Nathan W Churchill, Morten Mørup
Functional magnetic resonance imaging (fMRI) is increasingly used to characterize functional connectivity between brain regions. Given the vast number of between-voxel interactions in high-dimensional fMRI data, it is an ongoing challenge to detect stable and generalizable functional connectivity in the brain among groups of subjects. Component models can be used to define subspace representations of functional connectivity that are more interpretable. It is, however, unclear which component model provides the optimal representation of functional networks for multi-subject fMRI datasets...
October 14, 2016: Human Brain Mapping
Qingbao Yu, Lei Wu, David A Bridwell, Erik B Erhardt, Yuhui Du, Hao He, Jiayu Chen, Peng Liu, Jing Sui, Godfrey Pearlson, Vince D Calhoun
The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA)...
2016: Frontiers in Human Neuroscience
Svyatoslav Vergun, Wolfgang Gaggl, Veena A Nair, Joshua I Suhonen, Rasmus M Birn, Azam S Ahmed, M Elizabeth Meyerand, James Reuss, Edgar A DeYoe, Vivek Prabhakaran
Functional magnetic resonance imaging studies have significantly expanded the field's understanding of functional brain activity of healthy and patient populations. Resting state (rs-) fMRI, which does not require subjects to perform a task, eliminating confounds of task difficulty, allows examination of neural activity and offers valuable functional mapping information. The purpose of this work was to develop an automatic resting state network (RSN) labeling method which offers value in clinical workflow during rs-fMRI mapping by organizing and quickly labeling spatial maps into functional networks...
2016: Frontiers in Neuroscience
Mona Maneshi, Shahabeddin Vahdat, Jean Gotman, Christophe Grova
Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named "shared and specific independent component analysis" (SSICA) to perform between-group comparisons in the ICA framework. SSICA is sensitive to extract those components which represent a significant difference in functional connectivity between groups or conditions, i...
2016: Frontiers in Neuroscience
Feng Liu, Yifeng Wang, Meiling Li, Wenqin Wang, Rong Li, Zhiqiang Zhang, Guangming Lu, Huafu Chen
Idiopathic generalized epilepsy (IGE) has been linked with disrupted intra-network connectivity of multiple resting-state networks (RSNs); however, whether impairment is present in inter-network interactions between RSNs, remains largely unclear. Here, 50 patients with IGE characterized by generalized tonic-clonic seizures (GTCS) and 50 demographically matched healthy controls underwent resting-state fMRI scans. A dynamic method was implemented to investigate functional network connectivity (FNC) in patients with IGE-GTCS...
October 11, 2016: Human Brain Mapping
Jon M Houck, Mustafa S Çetin, Andrew R Mayer, Juan R Bustillo, Julia Stephen, Cheryl Aine, Jose Cañive, Nora Perrone-Bizzozero, Robert J Thoma, Matthew J Brookes, Vince D Calhoun
Examination of intrinsic functional connectivity using functional MRI (fMRI) has provided important findings regarding dysconnectivity in schizophrenia. Extending these results using a complementary neuroimaging modality, magnetoencephalography (MEG), we present the first direct comparison of functional connectivity between schizophrenia patients and controls, using these two modalities combined. We developed a novel MEG approach for estimation of networks using MEG that incorporates spatial independent component analysis (ICA) and pairwise correlations between independent component timecourses, to estimate intra- and intern-network connectivity...
October 7, 2016: NeuroImage
Lauren Marussich, Kun-Han Lu, Haiguang Wen, Zhongming Liu
Despite wide applications of functional magnetic resonance imaging (fMRI) to mapping brain activation and connectivity in cortical gray matter, it has rarely been utilized to study white-matter functions. In this study, we investigated the spatiotemporal characteristics of fMRI data within the white matter acquired from humans in the resting state or watching a naturalistic movie. By using independent component analysis and hierarchical clustering, resting-state fMRI data in the white matter were denoised and decomposed into spatially independent components, further assembled into hierarchically organized axonal fiber bundles...
October 5, 2016: NeuroImage
Jieqiong Wang, Ting Li, Peng Zhou, Ningli Wang, Junfang Xian, Huiguang He
To explore the alterations of functional connectivity (FC) and connections within and between the subnetworks of the visual network and the default mode network in glaucoma. We applied the independent component analysis to obtain two resting-state networks (RSNs), which were the visual network and the default mode network (DMN), from the resting-state fMRI data of 25 primary open-angle glaucoma (POAG) patients and 25 well-matched normal controls. Then FC analysis was performed to obtain the altered FC within the RSNs, whereas the functional network connectivity (FNC) analysis was performed within and between these two RSNs...
October 4, 2016: Brain Imaging and Behavior
Ahmad Mayeli, Vadim Zotev, Hazem Refai, Jerzy Bodurka
BACKGROUND: Simultaneous acquisition of EEG and fMRI data results in EEG signal contamination by imaging (MR) and ballistocardiogram (BCG) artifacts. Artifact correction of EEG data for real-time applications, such as neurofeedback studies, is the subject of ongoing research. To date, average artifact subtraction (AAS) is the most widespread real-time method used to partially remove BCG and imaging artifacts without requiring extra hardware equipment; no alternative software-only real time methods for removing EEG artifacts are available...
September 30, 2016: Journal of Neuroscience Methods
Burak Akin, Hsu-Lei Lee, Jürgen Hennig, Pierre LeVan
Resting-state networks have become an important tool for the study of brain function. An ultra-fast imaging technique that allows to measure brain function, called Magnetic Resonance Encephalography (MREG), achieves an order of magnitude higher temporal resolution than standard echo-planar imaging (EPI). This new sequence helps to correct physiological artifacts and improves the sensitivity of the fMRI analysis. In this study, EPI is compared with MREG in terms of capability to extract resting-state networks...
October 3, 2016: Human Brain Mapping
Shuang Zhang, Jian-Mei Chen, Li Kuang, Jun Cao, Han Zhang, Ming Ai, Wo Wang, Shu-Dong Zhang, Su-Ya Wang, Shi-Jing Liu, Wei-Dong Fang
BACKGROUND: Suicide is the second leading cause of death among 15- to 29-year-olds in China, and 60 % of suicidal patients have a history of depression. Previous brain imaging studies have shown that depression and suicide may be associated with abnormal activity in default mode network (DMN) regions. However, no study has specifically investigated the relationship between DMN functional activity and suicidal behavior in depressed individuals. Therefore, in the present study, we directly investigated features of DMN brain activity in adolescent patients with histories of depression and attempted suicide...
September 29, 2016: BMC Psychiatry
X Li, A Andres, K Shankar, R T Pivik, C M Glasier, R H Ramakrishnaiah, Y Zhang, T M Badger, X Ou
Recent studies have shown associations between maternal obesity at pre- or early pregnancy and long-term neurodevelopment in children, suggesting in utero effects of maternal obesity on offspring brain development. In this study, we examined whether brain functional connectivity to the prefrontal lobe network is different in newborns from normal-weight or obese mothers. Thirty-four full-term healthy infants from uncomplicated pregnancies were included, with 18 born to normal-weight and 16 born to obese mothers...
September 28, 2016: International Journal of Obesity: Journal of the International Association for the Study of Obesity
Jianping Li, Xuemei Chen, Wei Ye, Wenyu Jiang, Huihua Liu, Jinou Zheng
OBJECTIVES: This study aimed to investigate alterations in the alertness-related network in patients with right temporal lobe epilepsy (rTLE) and explore the functional mechanisms of impaired alertness. METHODS: We recruited twenty patients with rTLE and eighteen matched healthy controls. All participants took a neuropsychological attention network test (ANT) and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We extracted the alertness-related network using multiple independent component analysis (MICA)...
September 16, 2016: Epilepsy Research
Tie-Qiang Li, Yanlu Wang, Rolf Hallin, Jan-Erik Juto
Kinetic oscillatory stimulation (KOS) in the nasal cavity is a non-invasive cranial nerve stimulation method with promising efficacy for acute migraine and other inflammatory disorders. For a better understanding of the underlying neurophysiological mechanisms of KOS treatment, we conducted a resting-state functional magnetic resonance imaging (fMRI) study of 10 acute migraine patients and 10 normal control subjects during KOS treatment in a 3 T clinical MRI scanner. The fMRI data were first processed using a group independent component analysis (ICA) method and then further analyzed with a voxel-wise 3-way ANOVA modeling and region of interest (ROI) of functional connectivity metrics...
2016: NeuroImage: Clinical
Judith M Ford, Brian J Roach, Vanessa A Palzes, Daniel H Mathalon
Perceptional abnormalities in schizophrenia are associated with hallucinations and delusions, but also with negative symptoms and poor functional outcome. Perception can be studied using EEG-derived event related potentials (ERPs). Because of their excellent temporal resolution, ERPs have been used to ask when perception is affected by schizophrenia. Because of its excellent spatial resolution, functional magnetic resonance imaging (fMRI) has been used to ask where in the brain these effects are seen. We acquired EEG and fMRI data simultaneously to explore when and where auditory perception is affected by schizophrenia...
2016: NeuroImage: Clinical
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