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independent component analysis fMRI

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https://www.readbyqxmd.com/read/28641247/modeling-task-fmri-data-via-deep-convolutional-autoencoder
#1
Heng Huang, Xintao Hu, Yu Zhao, Milad Makkie, Qinglin Dong, Shijie Zhao, Lei Guo, Tianming Liu
Task-based fMRI (tfMRI) has been widely used to study functional brain networks under task performance. Modeling tfMRI data is challenging due to at least two problems: the lack of the ground truth of underlying neural activity and the highly complex intrinsic structure of tfMRI data. To better understand brain networks based on fMRI data, data-driven approaches have been proposed, for instance, Independent Component Analysis (ICA) and Sparse Dictionary Learning (SDL). However, both ICA and SDL only build shallow models, and they are under the strong assumption that original fMRI signal could be linearly decomposed into time series components with their corresponding spatial maps...
June 15, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28641239/automatic-recognition-of-fmri-derived-functional-networks-using-3d-convolutional-neural-networks
#2
Yu Zhao, Qinglin Dong, Shu Zhang, Wei Zhang, Hanbo Chen, Xi Jiang, Lei Guo, Xintao Hu, Junwei Han, Tianming Liu
Current fMRI data modeling techniques such as Independent Component Analysis (ICA) and Sparse Coding methods can effectively reconstruct dozens or hundreds of concurrent interacting functional brain networks simultaneously from the whole brain fMRI signals. However, such reconstructed networks have no correspondences across different subjects. Thus, automatic, effective and accurate classification and recognition of these large numbers of fMRI-derived functional brain networks are very important for subsequent steps of functional brain analysis in cognitive and clinical neuroscience applications...
June 15, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28631281/detecting-large-scale-networks-in-the-human-brain-using-high-density-electroencephalography
#3
Quanying Liu, Seyedehrezvan Farahibozorg, Camillo Porcaro, Nicole Wenderoth, Dante Mantini
High-density electroencephalography (hdEEG) is an emerging brain imaging technique that can be used to investigate fast dynamics of electrical activity in the healthy and the diseased human brain. Its applications are however currently limited by a number of methodological issues, among which the difficulty in obtaining accurate source localizations. In particular, these issues have so far prevented EEG studies from reporting brain networks similar to those previously detected by functional magnetic resonance imaging (fMRI)...
June 20, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28629720/exploring-connectivity-with-large-scale-granger-causality-on-resting-state-functional-mri
#4
Adora M DSouza, Anas Z Abidin, Lutz Leistritz, Axel Wismüller
BACKGROUND: Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. NEW METHOD: We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data...
June 16, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28620292/dynamic-responses-in-brain-networks-to-social-feedback-a-dual-eeg-acquisition-study-in-adolescent-couples
#5
Ching-Chang Kuo, Thao Ha, Ashley M Ebbert, Don M Tucker, Thomas J Dishion
Adolescence is a sensitive period for the development of romantic relationships. During this period the maturation of frontolimbic networks is particularly important for the capacity to regulate emotional experiences. In previous research, both functional magnetic resonance imaging (fMRI) and dense array electroencephalography (dEEG) measures have suggested that responses in limbic regions are enhanced in adolescents experiencing social rejection. In the present research, we examined social acceptance and rejection from romantic partners as they engaged in a Chatroom Interact Task...
2017: Frontiers in Computational Neuroscience
https://www.readbyqxmd.com/read/28608643/spontaneous-activity-in-the-visual-cortex-is-organized-by-visual-streams
#6
Kun-Han Lu, Jun Young Jeong, Haiguang Wen, Zhongming Liu
Large-scale functional networks have been extensively studied using resting state functional magnetic resonance imaging (fMRI). However, the pattern, organization, and function of fine-scale network activity remain largely unknown. Here, we characterized the spontaneously emerging visual cortical activity by applying independent component (IC) analysis to resting state fMRI signals exclusively within the visual cortex. In this subsystem scale, we observed about 50 spatially ICs that were reproducible within and across subjects, and analyzed their spatial patterns and temporal relationships to reveal the intrinsic parcellation and organization of the visual cortex...
June 13, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28598733/task-context-dependent-linear-representation-of-multiple-visual-objects-in-human-parietal-cortex
#7
Su Keun Jeong, Yaoda Xu
A host of recent studies have reported robust representations of visual object information in the human parietal cortex, similar to those found in ventral visual cortex. In ventral visual cortex, both monkey neurophysiology and human fMRI studies showed that the neural representation of a pair of unrelated objects can be approximated by the averaged neural representation of the constituent objects shown in isolation. In this study, we examined whether such a linear relationship between objects exists for object representations in the human parietal cortex...
June 9, 2017: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28588476/age-related-differences-in-dynamic-interactions-among-default-mode-frontoparietal-control-and-dorsal-attention-networks-during-resting-state-and-interference-resolution
#8
Bárbara Avelar-Pereira, Lars Bäckman, Anders Wåhlin, Lars Nyberg, Alireza Salami
Resting-state fMRI (rs-fMRI) can identify large-scale brain networks, including the default mode (DMN), frontoparietal control (FPN) and dorsal attention (DAN) networks. Interactions among these networks are critical for supporting complex cognitive functions, yet the way in which they are modulated across states is not well understood. Moreover, it remains unclear whether these interactions are similarly affected in aging regardless of cognitive state. In this study, we investigated age-related differences in functional interactions among the DMN, FPN and DAN during rest and the Multi-Source Interference task (MSIT)...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28582450/spontaneous-low-frequency-bold-signal-variations-from-resting-state-fmri-are-decreased-in-alzheimer-disease
#9
Samaneh Kazemifar, Kathryn Y Manning, Nagalingam Rajakumar, Francisco A Gómez, Andrea Soddu, Michael J Borrie, Ravi S Menon, Robert Bartha
Previous studies have demonstrated altered brain activity in Alzheimer's disease using task based functional MRI (fMRI), network based resting-state fMRI, and glucose metabolism from 18F fluorodeoxyglucose-PET (FDG-PET). Our goal was to define a novel indicator of neuronal activity based on a first-order textural feature of the resting state functional MRI (RS-fMRI) signal. Furthermore, we examined the association between this neuronal activity metric and glucose metabolism from 18F FDG-PET. We studied 15 normal elderly controls (NEC) and 15 probable Alzheimer disease (AD) subjects from the AD Neuroimaging Initiative...
2017: PloS One
https://www.readbyqxmd.com/read/28579940/comparison-of-iva-and-gig-ica-in-brain-functional-network-estimation-using-fmri-data
#10
Yuhui Du, Dongdong Lin, Qingbao Yu, Jing Sui, Jiayu Chen, Srinivas Rachakonda, Tulay Adali, Vince D Calhoun
Spatial group independent component analysis (GICA) methods decompose multiple-subject functional magnetic resonance imaging (fMRI) data into a linear mixture of spatially independent components (ICs), some of which are subsequently characterized as brain functional networks. Group information guided independent component analysis (GIG-ICA) as a variant of GICA has been proposed to improve the accuracy of the subject-specific ICs estimation by optimizing their independence. Independent vector analysis (IVA) is another method which optimizes the independence among each subject's components and the dependence among corresponding components of different subjects...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28567010/the-what-the-when-and-the-whether-of-intentional-action-in-the-brain-a-meta-analytical-review
#11
Laura Zapparoli, Silvia Seghezzi, Eraldo Paulesu
In their attempt to define discrete subcomponents of intentionality, Brass and Haggard (2008) proposed their What, When, and Whether model (www-model) which postulates that the content, the timing and the possibility of generating an action can be partially independent both at the cognitive level and at the level of their neural implementation. The original proposal was based on a limited number of studies, which were reviewed with a discursive approach. To assess whether the model stands in front of the more recently published data, we performed a systematic review of the literature with a meta-analytic method based on a hierarchical clustering (HC) algorithm...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28566724/aberrant-intra-and-internetwork-functional-connectivity-in-depressed-parkinson-s-disease
#12
Luqing Wei, Xiao Hu, Yajing Zhu, Yonggui Yuan, Weiguo Liu, Hong Chen
Much is known concerning the underlying mechanisms of Parkinson's disease (PD) with depression, but our understanding of this disease at the neural-system level remains incomplete. This study used resting-state functional MRI (rs-fMRI) and independent component analysis (ICA) to investigate intrinsic functional connectivity (FC) within and between large-scale neural networks in 20 depressed PD (dPD) patients, 35 non-depressed PD (ndPD) patients, and 34 healthy controls (HC). To alleviate the influence caused by ICA model order selection, this work reported results from analyses at 2 levels (low and high model order)...
May 31, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28536514/coupling-of-action-perception-brain-networks-during-musical-pulse-processing-evidence-from-region-of-interest-based-independent-component-analysis
#13
Iballa Burunat, Valeri Tsatsishvili, Elvira Brattico, Petri Toiviainen
Our sense of rhythm relies on orchestrated activity of several cerebral and cerebellar structures. Although functional connectivity studies have advanced our understanding of rhythm perception, this phenomenon has not been sufficiently studied as a function of musical training and beyond the General Linear Model (GLM) approach. Here, we studied pulse clarity processing during naturalistic music listening using a data-driven approach (independent component analysis; ICA). Participants' (18 musicians and 18 controls) functional magnetic resonance imaging (fMRI) responses were acquired while listening to music...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28529472/a-comparative-study-of-average-linked-mastoid-and-rest-references-for-erp-components-acquired-during-fmri
#14
Ping Yang, Chenggui Fan, Min Wang, Ling Li
In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28523217/relation-between-patterns-of-intrinsic-network-connectivity-cognitive-functioning-and-symptom-presentation-in-trauma-exposed-patients-with-major-depressive-disorder
#15
Melissa Parlar, Maria Densmore, Geoffrey B Hall, Paul A Frewen, Ruth A Lanius, Margaret C McKinnon
OBJECTIVE: The present study investigated resting fMRI connectivity within the default mode (DMN), salience (SN), and central executive (CEN) networks in relation to neurocognitive performance and symptom severity in trauma-exposed patients with major depressive disorder (MDD). METHOD: Group independent component analysis was conducted among patients with MDD (n = 21), examining DMN, SN, and CEN connectivity in relation to neurocognitive performance and symptom severity...
May 2017: Brain and Behavior
https://www.readbyqxmd.com/read/28487641/concordance-of-the-resting-state-networks-in-typically-developing-6-to-7-year-old-children-and-healthy-adults
#16
Cody L Thornburgh, Shalini Narayana, Roozbeh Rezaie, Bella N Bydlinski, Frances A Tylavsky, Andrew C Papanicolaou, Asim F Choudhri, Eszter Völgyi
Though fairly well-studied in adults, less is known about the manifestation of resting state networks (RSN) in children. We examined the validity of RSN derived in an ethnically diverse group of typically developing 6- to 7-year-old children. We hypothesized that the RSNs in young children would be robust and would reliably show significant concordance with previously published RSN in adults. Additionally, we hypothesized that a smaller sample size using this robust technique would be comparable in quality to pediatric RSNs found in a larger cohort study...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28453543/altered-resting-state-intra-and-inter-network-functional-connectivity-in-patients-with-persistent-somatoform-pain-disorder
#17
Zhiyong Zhao, Tianming Huang, Chaozheng Tang, Kaiji Ni, Xiandi Pan, Chao Yan, Xiaoduo Fan, Dongrong Xu, Yanli Luo
Patients with persistent somatoform pain disorder (PSPD) usually experience various functional impairments in pain, emotion, and cognition, which cannot be fully explained by a physiological process or a physical disorder. However, it is still not clear for the mechanism underlying the pathogenesis of PSPD. The present study aimed to explore the intra- and inter-network functional connectivity (FC) differences between PSPD patients and healthy controls (HCs). Functional magnetic resonance imaging (fMRI) was performed in 13 PSPD patients and 23 age- and gender-matched HCs...
2017: PloS One
https://www.readbyqxmd.com/read/28442422/effects-of-low-frequency-rtms-treatment-on-brain-networks-for-inner-speech-in-patients-with-schizophrenia-and-auditory-verbal-hallucinations
#18
Leonie Bais, Edith Liemburg, Ans Vercammen, Richard Bruggeman, Henderikus Knegtering, André Aleman
INTRODUCTION: Efficacy of repetitive Transcranial Magnetic Stimulation (rTMS) targeting the temporo-parietal junction (TPJ) for the treatment of auditory verbal hallucinations (AVH) remains under debate. We assessed the influence of a 1Hz rTMS treatment on neural networks involved in a cognitive mechanism proposed to subserve AVH. METHODS: Patients with schizophrenia (N=24) experiencing medication-resistant AVH completed a 10-day 1Hz rTMS treatment. Participants were randomized to active stimulation of the left or bilateral TPJ, or sham stimulation...
April 22, 2017: Progress in Neuro-psychopharmacology & Biological Psychiatry
https://www.readbyqxmd.com/read/28434159/decreased-hemispheric-connectivity-and-decreased-intra-and-inter-hemisphere-asymmetry-of-resting-state-functional-network-connectivity-in-schizophrenia
#19
O Agcaoglu, R Miller, E Damaraju, B Rashid, J Bustillo, M S Cetin, T G M Van Erp, S McEwen, A Preda, J M Ford, K O Lim, D S Manoach, D H Mathalon, S G Potkin, V D Calhoun
Many studies have shown that schizophrenia patients have aberrant functional network connectivity (FNC) among brain regions, suggesting schizophrenia manifests with significantly diminished (in majority of the cases) connectivity. Schizophrenia is also associated with a lack of hemispheric lateralization. Hoptman et al. (2012) reported lower inter-hemispheric connectivity in schizophrenia patients compared to controls using voxel-mirrored homotopic connectivity. In this study, we merge these two points of views together using a group independent component analysis (gICA)-based approach to generate hemisphere-specific timecourses and calculate intra-hemisphere and inter-hemisphere FNC on a resting state fMRI dataset consisting of age- and gender-balanced 151 schizophrenia patients and 163 healthy controls...
April 22, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/28418398/intranasal-oxytocin-enhances-intrinsic-corticostriatal-functional-connectivity-in-women
#20
R A I Bethlehem, M V Lombardo, M-C Lai, B Auyeung, S K Crockford, J Deakin, S Soubramanian, A Sule, P Kundu, V Voon, S Baron-Cohen
Oxytocin may influence various human behaviors and the connectivity across subcortical and cortical networks. Previous oxytocin studies are male biased and often constrained by task-based inferences. Here, we investigate the impact of oxytocin on resting-state connectivity between subcortical and cortical networks in women. We collected resting-state functional magnetic resonance imaging (fMRI) data on 26 typically developing women 40 min following intranasal oxytocin administration using a double-blind placebo-controlled crossover design...
April 18, 2017: Translational Psychiatry
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