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independent component analysis fMRI

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https://www.readbyqxmd.com/read/29164505/network-level-dysconnectivity-in-patients-with-nasopharyngeal-carcinoma-npc-early-post-radiotherapy-longitudinal-resting-state-fmri-study
#1
Yingwei Qiu, Zheng Guo, Lujun Han, Yadi Yang, Jing Li, Shiliang Liu, Xiaofei Lv
In this study, we seek to longitudinally investigate the network-level functional connectivity (FC) alternations and its association with irradiation dose and cognition changes in the early stage post radiotherapy (RT) in nasopharyngeal carcinoma (NPC) patients. We performed independent component analysis (ICA) of resting state blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) from 39 newly diagnosed NPC patients before receiving treatment (baseline), and 3 months post-RT. the default mode network (DMN), salience network (SN), and executive control network (ECN) were extracted with well-validated software (GIFT)...
November 21, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/29163087/localized-fluctuant-oscillatory-activity-by-working-memory-load-a-simultaneous-eeg-fmri-study
#2
Xiaojie Zhao, Xiaoyun Li, Li Yao
Working memory (WM) is a resource-limited memory system for temporary storage and processing of brain information during the execution of cognitive tasks. Increased WM load will increase the amount and difficulty of memory information. Several studies have used electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) to explore load-dependent cognition processing according to the time courses of electrophysiological activity or the spatial pattern of blood oxygen metabolic activity. However, the relationships between these two activities and the underlying neural mechanism are still unclear...
2017: Frontiers in Behavioral Neuroscience
https://www.readbyqxmd.com/read/29161884/accounting-for-non-gaussian-sources-of-spatial-correlation-in-parametric-fmri-paradigms-ii-a-method-to-obtain-first-level-analysis-residuals-with-uniform-and-gaussian-spatial-autocorrelation-function-and-independent-and-identically-distributed-time-series
#3
Kaundinya Gopinath, Venkatagiri Krishnamurthy, Simon Lacey, K Sathian
A recent study (Eklund et al., 2016) has shown that cluster-wise family-wise error (FWE) rate corrected inferences made in parametric statistical methods based fMRI studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACF) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggests otherwise (Eklund et al., 2016). Hence the residuals from general linear model (GLM) based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF (Eklund et al...
November 22, 2017: Brain Connectivity
https://www.readbyqxmd.com/read/29158202/dynamic-effective-connectivity-in-resting-state-fmri
#4
REVIEW
Hae-Jeong Park, Karl Friston, Chongwon Pae, Bumhee Park, Adeel Razi
Context-sensitive and activity-dependent fluctuations in connectivity underlie functional integration in the brain and have been studied widely in terms of synaptic plasticity, learning and condition-specific (e.g., attentional) modulations of synaptic efficacy. This dynamic aspect of brain connectivity has recently attracted a lot of attention in the resting state fMRI community. To explain dynamic functional connectivity in terms of directed effective connectivity among brain regions, we introduce a novel method to identify dynamic effective connectivity using spectral dynamic causal modelling (spDCM)...
November 17, 2017: NeuroImage
https://www.readbyqxmd.com/read/29155080/a-comprehensive-analysis-of-resting-state-fmri-measures-to-classify-individual-patients-with-alzheimer-s-disease
#5
Frank de Vos, Marisa Koini, Tijn M Schouten, Stephan Seiler, Jeroen van der Grond, Anita Lechner, Reinhold Schmidt, Mark de Rooij, Serge A R B Rombouts
Alzheimer's disease (AD) patients show altered patterns of functional connectivity (FC) on resting state functional magnetic resonance imaging (RSfMRI) scans. It is yet unclear which RSfMRI measures are most informative for the individual classification of AD patients. We investigated this using RSfMRI scans from 77 AD patients (MMSE = 20.4 ± 4.5) and 173 controls (MMSE = 27.5 ± 1.8). We calculated i) FC matrices between resting state components as obtained with independent component analysis (ICA), ii) the dynamics of these FC matrices using a sliding window approach, iii) the graph properties (e...
November 14, 2017: NeuroImage
https://www.readbyqxmd.com/read/29154365/is-neural-processing-of-negative-stimuli-altered-in-addiction-independent-of-drug-effects-findings-from-drug-na%C3%A3-ve-youth-with-internet-gaming-disorder
#6
Sarah W Yip, James J Gross, Megha Chawla, Shan-Shan Ma, Xing-Hui Shi, Lu Liu, Yuan-Wei Yao, Lei Zhu, Patrick D Worhunsky, Jintao Zhang
Difficulties in emotion regulation are commonly reported among individuals with alcohol and drug addictions and contribute to the acquisition and maintenance of addictive behaviors. Alterations in neural processing of negative affective stimuli have further been demonstrated among individuals with addictions. However, it is unclear whether these alterations are a general feature of addictions or are a result of prolonged exposure to drugs-of-abuse. To test the hypothesis of altered negative affect processing independent of drug effects, this study assessed neural function among drug-naïve youth with a behavioral addiction-Internet gaming disorder (IGD)...
November 20, 2017: Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology
https://www.readbyqxmd.com/read/29152692/left-frontoparietal-network-activity-is-modulated-by-drug-stimuli-in-cocaine-addiction
#7
Víctor Costumero, Patricia Rosell-Negre, Juan Carlos Bustamante, Paola Fuentes-Claramonte, Juan José Llopis, Cesar Ávila, Alfonso Barrós-Loscertales
Cocaine addicts present reduced activity in the left frontoparietal network, a brain network associated with cognitive control, during the processing of non-drug reward related stimuli (Costumero et al., Addiction Biology 22:479-489, 2015). However, the involvement of this network in drug-related stimuli processing remains unclear. Here, fifteen cocaine-dependent men and fifteen healthy matched controls viewed cocaine-related, erotic, aversive, and neutral pictures during an fMRI session. Group independent component analysis was then performed to investigate how functional networks were modulated by the different emotional images...
November 20, 2017: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/29124352/brain-waves-from-an-isolated-cortex-contribution-of-the-anterior-insula-to-cognitive-functions
#8
Rinaldo Livio Perri, Marika Berchicci, Valentina Bianco, Donatella Spinelli, Francesco Di Russo
Using two independent electrical neuroimaging techniques (BESA and sLORETA), we tested a fMRI-seeded source modeling indicating that in visual discriminative tasks the anterior insula (aIns) participates in the generation of three prefrontal ERP components: the pN1 (at 115 ms), the pP1 (at 170 ms), and the pP2 (at 300 ms). This latter component represented the focus of the present study. Results showed that the pP2 had different activation profiles across hemispheres. The left aIns activity peaked at 420 ms (30 ms before the response) for both Go and No-go trials, that is independently from the ultimate choice (response or inhibition)...
November 9, 2017: Brain Structure & Function
https://www.readbyqxmd.com/read/29075569/the-effect-of-preprocessing-in-dynamic-functional-network-connectivity-used-to-classify-mild-traumatic-brain-injury
#9
Victor M Vergara, Andrew R Mayer, Eswar Damaraju, Vince D Calhoun
INTRODUCTION: Dynamic functional network connectivity (dFNC), derived from magnetic resonance imaging (fMRI), is an important technique in the search for biomarkers of brain diseases such as mild traumatic brain injury (mTBI). At the individual level, mTBI can affect cognitive functions and change personality traits. Previous research aimed at detecting significant changes in the dFNC of mTBI subjects. However, one of the main concerns in dFNC analysis is the appropriateness of methods used to correct for subject movement...
October 2017: Brain and Behavior
https://www.readbyqxmd.com/read/29071309/kernel-regularized-ica-for-computing-functional-topography-from-resting-state-fmri
#10
Junyan Wang, Yonggang Shi
Topographic regularity is a fundamental property in brain connectivity. In this work, we present a novel method for studying topographic regularity of functional connectivity based on resting-state fMRI (rfMRI), which is widely available and easy to acquire in large-scale studies. The main idea in our method is the incorporation of topographically regular structural connectivity for independent component analysis (ICA). This is enabled by the recent development of novel tractography and tract filtering algorithms that can generate highly organized fiber bundles connecting different brain regions...
September 2017: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/29065364/effects-of-behavioral-activation-on-default-mode-network-connectivity-in-subthreshold-depression-a-preliminary-resting-state-fmri-study
#11
Satoshi Yokoyama, Yasumasa Okamoto, Koki Takagaki, Go Okada, Masahiro Takamura, Asako Mori, Syouichi Shiota, Naho Ichikawa, Ran Jinnin, Shigeto Yamawaki
BACKGROUND: Subthreshold depression is a risk factor for major depressive disorder, and it is known to have a negative impact on quality of life (QOL). Although behavioral activation, which is one type of cognitive behavioral therapy, is an effective psychological intervention for subthreshold depression, neural mechanisms of behavioral activation are unclear. Enhanced functional connectivity between default mode network (DMN) and the other regions has been demonstrated in participants with subthreshold depression...
October 7, 2017: Journal of Affective Disorders
https://www.readbyqxmd.com/read/29062010/an-automated-method-for-identifying-an-independent-component-analysis-based-language-related-resting-state-network-in-brain-tumor-subjects-for-surgical-planning
#12
Junfeng Lu, Han Zhang, N U Farrukh Hameed, Jie Zhang, Shiwen Yuan, Tianming Qiu, Dinggang Shen, Jinsong Wu
As a noninvasive and "task-free" technique, resting-state functional magnetic resonance imaging (rs-fMRI) has been gradually applied to pre-surgical functional mapping. Independent component analysis (ICA)-based mapping has shown advantage, as no a priori information is required. We developed an automated method for identifying language network in brain tumor subjects using ICA on rs-fMRI. In addition to standard processing strategies, we applied a discriminability-index-based component identification algorithm to identify language networks in three different groups...
October 23, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29060678/ica-on-sensor-or-source-data-a-comparison-study-in-deriving-resting-state-networks-from-eeg
#13
Chuang Li, Han Yuan, Diamond Urbano, Yoon-Hee Cha, Lei Ding
Resting state networks (RSNs) are human brain networks formed by spontaneous activity fluctuations in distributed brain regions when people are in task-free and awake state. RSNs have been so far extensively studied using functional magnetic resonance imaging (fMRI). Recently, electroencephalography (EEG) and magnetoencephalography (MEG) have also been used to derive RSNs, in which independent component analysis (ICA) is the key step. In these studies, ICA has been either directly applied to recorded data at sensors (sensor-space ICA) or estimated source data from sensors using inverse source imaging techniques (source-space ICA)...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29059918/investigating-the-bold-spectral-power-of-the-intrinsic-connectivity-networks-in-fibromyalgia-patients-a-resting-state-fmri-study
#14
Behnaz Jarrahi, Katherine T Martucci, Aneesha S Nilakantan, Sean Mackey
Recent advances in multivariate statistical analysis of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) have provided novel insights into the network organization of the human brain. Here, we applied group independent component analysis, a well-established approach for detecting brain intrinsic connectivity networks, to examine the spontaneous BOLD fluctuations in patients with fibromyalgia and healthy controls before and after exposure to a stressor. The BOLD spectral power characteristics of component time courses were calculated using the fast Fourier transform (FFT) algorithm, and group comparison was performed at six frequency bins between 0 and 0...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/29055719/functional-brain-connectivity-in-resting-state-fmri-using-phase-and-magnitude-data
#15
Zikuan Chen, Arvind Caprihan, Eswar Damaraju, Srinivas Rachakonda, Vince Calhoun
BACKGROUND: The output of BOLD fMRI consists of a pair of magnitude and phase components. While the magnitude data has been widely accepted for brain function analysis, we can also make use of the phase data (unwrapped) since this is a good representation of the internal magnetic field. In this work, we discuss the use of fMRI phase data for brain function analysis. NEW METHODS: The fMRI phase data taken from 100 subjects are preprocessed using standard SPM approaches...
October 18, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/29040743/anger-sensitive-networks-characterising-neural-systems-recruited-during-aggressive-social-interactions-using-data-driven-analysis
#16
Frederike Beyer, Ulrike M Krämer, Christian F Beckmann
Social neuroscience uses increasingly complex paradigms to improve ecological validity, as investigating aggressive interactions with functional magnetic resonance imaging (fMRI; Krämer, Jansma, Tempelmann, & Münte, 2007). Standard analyses for fMRI data typically use general linear models (GLM), which require a priori models of task effects on neural processes. These may inadequately model non-stimulus-locked or temporally overlapping cognitive processes, as mentalizing about other agents.We used the data-driven approach of independent component analysis (ICA) to investigate neural processes involved in a competitive interaction...
October 4, 2017: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/29034316/large-scale-network-coupling-with-the-fusiform-cortex-facilitates-future-social-motivation
#17
Amanda V Utevsky, David V Smith, Jacob S Young, Scott A Huettel
Large-scale functional networks, as identified through the coordinated activity of spatially distributed brain regions, have become central objects of study in neuroscience because of their contributions to many processing domains. Yet, it remains unclear how these domain-general networks interact with focal brain regions to coordinate thought and action. Here, we investigated how the default-mode network (DMN) and executive control network (ECN), two networks associated with goal-directed behavior, shape task performance through their coupling with other cortical regions several seconds in advance of behavior...
September 2017: ENeuro
https://www.readbyqxmd.com/read/29030069/sex-differences-and-menstrual-cycle-effects-in-cognitive-and-sensory-resting-state-networks
#18
Susanne Weis, Sophie Hodgetts, Markus Hausmann
It has not yet been established if resting state (RS) connectivity reflects stable characteristics of the brain, or if it is modulated by the psychological and/or physiological state of the participant. Based on research demonstrating sex hormonal effects in task-related brain activity, the present study aimed to investigate corresponding differences in RS networks. RS functional Magnetic Resonance Imaging (RS fMRI) was conducted in women during three different menstrual cycle phases, while men underwent three repeated RS fMRI testing sessions...
October 10, 2017: Brain and Cognition
https://www.readbyqxmd.com/read/28988830/effects-of-neonatal-deafness-on-resting-state-functional-network-connectivity
#19
Daniel Stolzberg, Blake E Butler, Stephen G Lomber
Normal brain development depends on early sensory experience. Behavioral consequences of brain maturation in the absence of sensory input early in life are well documented. For example, experiments with mature, neonatally deaf human or animal subjects have revealed improved peripheral visual motion detection and spatial localization abilities. Such supranormal behavioral abilities in the nondeprived sensory modality are evidence of compensatory plasticity occurring in deprived brain regions at some point or throughout development...
October 6, 2017: NeuroImage
https://www.readbyqxmd.com/read/28985929/ten-key-observations-on-the-analysis-of-resting-state-functional-mr-imaging-data-using-independent-component-analysis
#20
REVIEW
Vince D Calhoun, Nina de Lacy
For more than 20 years, the powerful, flexible family of independent component analysis (ICA) techniques has been used to examine spatial, temporal, and subject variation in functional magnetic resonance (fMR) imaging data. This article provides an overview of 10 key principles in the basic and advanced application of ICA to resting-state fMR imaging. ICA's core advantages include robustness to artifact; false-positives and autocorrelation; adaptability to variant study designs; agnosticism to the temporal evolution of fMR imaging signals; and ability to extract, identify, and analyze neural networks...
November 2017: Neuroimaging Clinics of North America
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