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Tuija Keinänen, Seppo Rytky, Vesa Korhonen, Niko Huotari, Juha Nikkinen, Osmo Tervonen, J Matias Palva, Vesa Kiviniemi
Both functional magnetic resonance imaging (fMRI) and electrophysiological recordings have revealed that resting-state functional connectivity is temporally variable in human brain. Combined full-band electroencephalography-fMRI (fbEEG-fMRI) studies have shown that infraslow (<.1 Hz) fluctuations in EEG scalp potential are correlated with the blood-oxygen-level-dependent (BOLD) fMRI signals and that also this correlation appears variable over time. Here, we used simultaneous fbEEG-fMRI to test the hypothesis that correlation dynamics between BOLD and fbEEG signals could be explained by fluctuations in the activation properties of resting-state networks (RSNs) such as the extent or strength of their activation...
May 14, 2018: Journal of Neuroscience Research
Yifei He, Miriam Steines, Jens Sommer, Helge Gebhardt, Arne Nagels, Gebhard Sammer, Tilo Kircher, Benjamin Straube
The semantic integration between gesture and speech (GSI) is mediated by the left posterior temporal sulcus/middle temporal gyrus (pSTS/MTG) and the left inferior frontal gyrus (IFG). Evidence from electroencephalography (EEG) suggests that oscillations in the alpha and beta bands may support processes at different stages of GSI. In the present study, we investigated the relationship between electrophysiological oscillations and blood-oxygen-level-dependent (BOLD) activity during GSI. In a simultaneous EEG-fMRI study, German participants (n = 19) were presented with videos of an actor either performing meaningful gestures in the context of a comprehensible German (GG) or incomprehensible Russian sentence (GR), or just speaking a German sentence (SG)...
May 8, 2018: Brain Structure & Function
Siwei Liu, Jia-Hou Poh, Huili Koh, Eric Kwun-Kei Ng, Yng Miin Loke, Joseph Kai Wei Lim, Joanna Su Xian Chong, Juan Zhou
Spatial working memory (SWM) relies on the interplay of anatomically separated and interconnected large-scale brain networks. EEG studies often observe load-associated sustained negative activity during SWM retention. Yet, whether and how such sustained negative activity in retention relates to network-specific functional activation/deactivation and relates to individual differences in SWM capacity remain to be elucidated. To cover these gaps, we recorded concurrent EEG-fMRI data in 70 healthy young adults during the Sternberg delayed-match-to-sample SWM task with three memory load levels...
April 9, 2018: NeuroImage
Chung-Ki Wong, Qingfei Luo, Vadim Zotev, Raquel Phillips, Kam Wai Clifford Chan, Jerzy Bodurka
BACKGROUND: In simultaneous EEG-fMRI, identification of the period of cardioballistic artifact (BCG) in EEG is required for the artifact removal. Recording the electrocardiogram (ECG) waveform during fMRI is difficult, often causing inaccurate period detection. NEW METHOD: Since the waveform of the BCG extracted by independent component analysis (ICA) is relatively invariable compared to the ECG waveform, we propose a multiple-scale peak-detection algorithm to determine the BCG cycle directly from the EEG data...
March 31, 2018: Journal of Neuroscience Methods
José L Ferreira, Yan Wu, Ronald M Aarts
A recurring problem regarding the use of conventional comb filter approaches for elimination of periodic waveforms is the degree of selectivity achieved by the filtering process. Some applications, such as the gradient artefact correction in EEG recordings during coregistered EEG-fMRI, require a highly selective comb filtering that provides effective attenuation in the stopbands and gain close to unity in the pass-bands. In this paper, we present a novel comb filtering implementation whereby the iterative filtering application of FIR moving average-based approaches is exploited in order to enhance the comb filtering selectivity...
2018: Journal of Healthcare Engineering
Fan-Chi Hsiao, Pei-Jung Tsai, Timothy Joseph Lane, Changwei W Wu, Hsin-Chien Lee, Ling-Chun Chen, We-Kang Lee, Lu-Hsin Lu, Yu-Zu Wu, Chien-Ming Yang
Subjective perception of sleep is not necessarily consistent with EEG indications of sleep. The mismatch between subjective reports and objective measures is often referred to as "sleep state misperception" (SSM). Previous studies evince that this mismatch is found in both insomnia patients and in normal sleepers, but the neurophysiological mechanism remains unclear. The aim of the study is to explore the neurophysiological basis of this mechanism, from the perspective of both EEG power and fMRI fluctuations...
March 24, 2018: Sleep
Maryam Falahpour, Catie Chang, Chi Wah Wong, Thomas T Liu
Changes in vigilance or alertness during a typical resting state fMRI scan are inevitable and have been found to affect measures of functional brain connectivity. Since it is not often feasible to monitor vigilance with EEG during fMRI scans, it would be of great value to have methods for estimating vigilance levels from fMRI data alone. A recent study, conducted in macaque monkeys, proposed a template-based approach for fMRI-based estimation of vigilance fluctuations. Here, we use simultaneously acquired EEG/fMRI data to investigate whether the same template-based approach can be employed to estimate vigilance fluctuations of awake humans across different resting-state conditions...
July 1, 2018: NeuroImage
Kai Wang, Wenjie Li, Li Dong, Ling Zou, Changming Wang
Combination of electroencephalogram (EEG) recording and functional magnetic resonance imaging (fMRI) plays a potential role in neuroimaging due to its high spatial and temporal resolution. However, EEG is easily influenced by ballistocardiogram (BCG) artifacts and may cause false identification of the related EEG features, such as epileptic spikes. There are many related methods to remove them, however, they do not consider the time-varying features of BCG artifacts. In this paper, a novel method using clustering algorithm to catch the BCG artifacts' features and together with the constrained ICA (ccICA) is proposed to remove the BCG artifacts...
2018: Frontiers in Neuroscience
Jing Lu, Sijia Guo, Mingming Chen, Weixia Wang, Hua Yang, Daqing Guo, Dezhong Yao
Many methods have been developed to translate a human electroencephalogram (EEG) into music. In addition to EEG, functional magnetic resonance imaging (fMRI) is another method used to study the brain and can reflect physiological processes. In 2012, we established a method to use simultaneously recorded fMRI and EEG signals to produce EEG-fMRI music, which represents a step toward scale-free brain music. In this study, we used a neural mass model, the Jansen-Rit model, to simulate activity in several cortical brain regions...
January 2018: Medicine (Baltimore)
Huaze Xu, Jianpo Su, Jian Qin, Ming Li, Ling-Li Zeng, Dewen Hu, Hui Shen
Recently, resting-state functional magnetic resonance imaging (fMRI) studies have been extended to explore fluctuations in correlations over shorter timescales, referred to as dynamic functional connectivity (dFC). However, the impact of global signal regression (GSR) on dFC is not well established, despite the intensive investigations of the influence of GSR on static functional connectivity (sFC). This study aimed to examine the effect of GSR on the performance of the sliding-window correlation, a commonly used method for capturing functional connectivity (FC) dynamics based on resting-state fMRI and simultaneous electroencephalograph (EEG)-fMRI data...
June 2018: NeuroImage
Rodolfo Abreu, Alberto Leal, Patrícia Figueiredo
The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data...
2018: Frontiers in Human Neuroscience
Rodolfo Abreu, Alberto Leal, Fernando Lopes da Silva, Patrícia Figueiredo
OBJECTIVE: We hypothesize that the hypersynchronization associated with epileptic activity is best described by EEG synchronization measures, and propose to use these as predictors of epilepsy-related BOLD fluctuations. METHODS: We computed the phase synchronization index (PSI) and global field synchronization (GFS), within two frequency bands, a broadband (1-45 Hz) and a narrower band focused on the presence of epileptic activity (3-10 Hz). The associated epileptic networks were compared with those obtained using conventional unitary regressors and two power-weighted metrics (total power and root mean square frequency), on nine simultaneous EEG-fMRI datasets from four epilepsy patients, exhibiting inter-ictal epileptiform discharges (IEDs)...
March 2018: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
Hong Ji, Nathan M Petro, Badong Chen, Zejian Yuan, Jianji Wang, Nanning Zheng, Andreas Keil
Over the past decade, the simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data has garnered growing interest because it may provide an avenue towards combining the strengths of both imaging modalities. Given their pronounced differences in temporal and spatial statistics, the combination of EEG and fMRI data is however methodologically challenging. Here, we propose a novel screening approach that relies on a Cross Multivariate Correlation Coefficient (xMCC) framework...
February 6, 2018: Journal of Neuroscience Research
Matthias F J Sperl, Christian Panitz, Isabelle M Rosso, Daniel G Dillon, Poornima Kumar, Andrea Hermann, Alexis E Whitton, Christiane Hermann, Diego A Pizzagalli, Erik M Mueller
Human functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) studies, as well as animal studies, indicate that the amygdala and frontomedial brain regions are critically involved in conditioned fear and that frontomedial oscillations in the theta range (4-8 Hz) may support communication between these brain regions. However, few studies have used a multimodal approach to probe interactions among these key regions in humans. Here, our goal was to bridge the gap between prior human fMRI, EEG, and animal findings...
January 24, 2018: Cerebral Cortex
Satoshi Maesawa, Epifanio Bagarinao, Daisuke Nakatsubo, Toshihiko Wakabayashi
No abstract text is available yet for this article.
January 2018: No Shinkei Geka. Neurological Surgery
Ashish Kaul Sahib, Michael Erb, Justus Marquetand, Pascal Martin, Adham Elshahabi, Silke Klamer, Serge Vulliemoz, Klaus Scheffler, Thomas Ethofer, Niels K Focke
The human brain is known to contain several functional networks that interact dynamically. Therefore, it is desirable to analyze the temporal features of these networks by dynamic functional connectivity (dFC). A sliding window approach was used in an event-related fMRI (visual stimulation using checkerboards) to assess the impact of repetition time (TR) and window size on the temporal features of BOLD dFC. In addition, we also examined the spatial distribution of dFC and tested the feasibility of this approach for the analysis of interictal epileptiforme discharges...
2018: PloS One
Yongfu Hao, Hui Ming Khoo, Nicolas von Ellenrieder, Natalja Zazubovits, Jean Gotman
Presurgical evaluation that can precisely delineate the epileptogenic zone (EZ) is one important step for successful surgical resection treatment of refractory epilepsy patients. The noninvasive EEG-fMRI recording technique combined with general linear model (GLM) analysis is considered an important tool for estimating the EZ. However, the manual marking of interictal epileptic discharges (IEDs) needed in this analysis is challenging and time-consuming because the quality of the EEG recorded inside the scanner is greatly deteriorated compared to the usual EEG obtained outside the scanner...
2018: NeuroImage: Clinical
Epifanio Bagarinao, Satoshi Maesawa, Yuji Ito, Naotaka Usui, Jun Natsume, Hirohisa Watanabe, Minoru Hoshiyama, Toshihiko Wakabayashi, Gen Sobue, Shinji Naganawa, Haruo Isoda
OBJECTIVE: Epileptic spikes are associated with rapidly changing brain activation involving the epileptic foci and other brain regions in the "epileptic network". We aim to resolve these activation changes using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. METHODS: Simultaneous EEG-fMRI recordings from 9 patients with epilepsy were used in the analysis. Our method employed the whole scalp EEG data to generate regressors for the analysis of fMRI data using the general linear model...
November 27, 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
Florian Gompf, Anja Pflug, Helmut Laufs, Christian A Kell
Functional imaging studies using BOLD contrasts have consistently reported activation of the supplementary motor area (SMA) both during motor and internal timing tasks. Opposing findings, however, have been shown for the modulation of beta oscillations in the SMA. While movement suppresses beta oscillations in the SMA, motor and non-motor tasks that rely on internal timing increase the amplitude of beta oscillations in the SMA. These independent observations suggest that the relationship between beta oscillations and BOLD activation is more complex than previously thought...
2017: Frontiers in Human Neuroscience
Mareike Bayer, Michael T Rubens, Tom Johnstone
The speed of visual processing is central to our understanding of face perception. Yet the extent to which early visual processing influences later processing in distributed face processing networks, and the top-down modulation of such bottom-up effects, remains unclear. We used simultaneous EEG-fMRI to investigate cortical activity that showed unique covariation with ERP components of face processing (C1, P1, N170, P3), while manipulating sustained attention and transient cognitive conflict employing an emotional face-word Stroop task...
February 2018: Biological Psychology
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