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Eeg microstate

Michelle Case, Huishi Zhang, John Mundahl, Yvonne Datta, Stephen Nelson, Kalpna Gupta, Bin He
Sickle cell disease (SCD) is a red blood cell disorder that causes many complications including life-long pain. Treatment of pain remains challenging due to a poor understanding of the mechanisms and limitations to characterize and quantify pain. In the present study, we examined simultaneously recording functional MRI (fMRI) and electroencephalogram (EEG) to better understand neural connectivity as a consequence of chronic pain in SCD patients. We performed independent component analysis and seed-based connectivity on fMRI data...
2017: NeuroImage: Clinical
Laura Diaz Hernandez, Kathryn Rieger, Thomas Koenig
Neurofeedback is becoming increasingly sophisticated and widespread, although predictors of successful performance still remain scarce. Here, we explored the possible predictive value of psychological factors and report the results obtained from a neurofeedback training study designed to enhance the self-regulation of spontaneous EEG microstates of a particular type (microstate class D). Specifically, we were interested in life satisfaction (including motivational incongruence), body awareness, personality and trait anxiety...
December 20, 2016: Neuroscience
Andreas Pedroni, Lorena R R Gianotti, Thomas Koenig, Dietrich Lehmann, Pascal Faber, Daria Knoch
People seem to have difficulties when perceiving events whose outcome has no influence on the outcome of future events. This illusion that patterns exist where there are none may lead to adverse consequences, such as escalating losses in financial trading or gambling debt. Despite the enormous social consequences of these cognitive biases, however, their neural underpinnings are poorly understood. Attempts to investigate them have so far relied on evoked neural activity, whereas spontaneous brain activity has been treated as noise to be averaged out...
January 2017: Brain Topography
Nathalie Giroud, Ulrike Lemke, Philip Reich, Katarina L Matthes, Martin Meyer
The current study investigates cognitive processes as reflected in late auditory-evoked potentials as a function of longitudinal auditory learning. A normal hearing adult sample (n=15) performed an active oddball task at three consecutive time points (TPs) arranged at two week intervals, and during which EEG was recorded. The stimuli comprised of syllables consisting of a natural fricative (/sh/,/s/,/f/) embedded between two /a/ sounds, as well as morphed transitions of the two syllables that served as deviants...
November 17, 2016: Biological Psychology
Benjamin A Seitzman, Malene Abell, Samuel C Bartley, Molly A Erickson, Amanda R Bolbecker, William P Hetrick
EEG studies of wakeful rest have shown that there are brief periods in which global electrical brain activity on the scalp remains semi-stable (so-called microstates). Topographical analyses of this activity have revealed that much of the variance is explained by four distinct microstates that occur in a repetitive sequence. A recent fMRI study showed that these four microstates correlated with four known functional systems, each of which is activated by specific cognitive functions and sensory inputs. The present study used high density EEG to examine the degree to which spatial and temporal properties of microstates may be altered by manipulating cognitive task (a serial subtraction task vs...
October 11, 2016: NeuroImage
Evaldas Pipinis, Sigita Melynyte, Thomas Koenig, Lina Jarutyte, Klaus Linkenkaer-Hansen, Osvaldas Ruksenas, Inga Griskova-Bulanova
There is a gap in understanding on how physiologically observed activity is related to the subjective, internally oriented experience during resting state. Microstate analysis is a frequent approach to evaluate resting-state EEG. But the relationship of commonly observed resting-state microstates to psychological domains of resting is not clear. The Amsterdam Resting-State Questionnaire (ARSQ) was recently introduced, offering an effective way to quantify subjective states after a period of resting and associate these quantifiers to psychological and physiological variables...
September 19, 2016: Brain Topography
Fei Gao, Huibin Jia, Xiangci Wu, Dongchuan Yu, Yi Feng
The aim of this study was to investigate the resting-state EEG microstate parameters and spatial complexity in male adolescent patients with mild spastic diplegia (MSD). Resting-state EEG data were collected from male adolescent patients with MSD and healthy controls with eyes closed. EEG microstate and omega complexity analysis were performed. Microstate analysis revealed that the occurrence rate of microstate class A and D were significantly higher and the duration of microstate class B was significantly lower in the patients compared to healthy controls, which indicated that the temporal complexity may be higher and certain cognitive functions may be impaired in these patients...
September 17, 2016: Brain Topography
Markus Gschwind, Martin Hardmeier, Dimitri Van De Ville, Miralena I Tomescu, Iris-Katharina Penner, Yvonne Naegelin, Peter Fuhr, Christoph M Michel, Margitta Seeck
Spontaneous fluctuations of neuronal activity in large-scale distributed networks are a hallmark of the resting brain. In relapsing-remitting multiple sclerosis (RRMS) several fMRI studies have suggested altered resting-state connectivity patterns. Topographical EEG analysis reveals much faster temporal fluctuations in the tens of milliseconds time range (termed "microstates"), which showed altered properties in a number of neuropsychiatric conditions. We investigated whether these microstates were altered in patients with RRMS, and if the microstates' temporal properties reflected a link to the patients' clinical features...
2016: NeuroImage: Clinical
Natasha M Drissi, Attila Szakács, Suzanne T Witt, Anna Wretman, Martin Ulander, Henriettae Ståhlbrandt, Niklas Darin, Tove Hallböök, Anne-Marie Landtblom, Maria Engström
Narcolepsy is a chronic sleep disorder caused by a loss of hypocretin-1 producing neurons in the hypothalamus. Previous neuroimaging studies have investigated brain function in narcolepsy during rest using positron emission tomography (PET) and single photon emission computed tomography (SPECT). In addition to hypothalamic and thalamic dysfunction they showed aberrant prefrontal perfusion and glucose metabolism in narcolepsy. Given these findings in brain structure and metabolism in narcolepsy, we anticipated that changes in functional magnetic resonance imaging (fMRI) resting state network (RSN) dynamics might also be apparent in patients with narcolepsy...
2016: Frontiers in Human Neuroscience
Suriya-Prakash Muthukrishnan, Navdeep Ahuja, Nalin Mehta, Ratna Sharma
Humans have limited capacity of processing just up to 4 integrated items of information in the working memory. Thus, it is inevitable to commit more errors when challenged with high memory loads. However, the neural mechanisms that determine the accuracy of response at high memory loads still remain unclear. High temporal resolution of Electroencephalography (EEG) technique makes it the best tool to resolve the temporal dynamics of brain networks. EEG-defined microstate is the quasi-stable scalp electrical potential topography that represents the momentary functional state of brain...
November 1, 2016: Behavioural Brain Research
Rajanikant Panda, Rose D Bharath, Neeraj Upadhyay, Sandhya Mangalore, Srivas Chennu, Shobini L Rao
Current research suggests that human consciousness is associated with complex, synchronous interactions between multiple cortical networks. In particular, the default mode network (DMN) of the resting brain is thought to be altered by changes in consciousness, including the meditative state. However, it remains unclear how meditation alters the fast and ever-changing dynamics of brain activity within this network. Here we addressed this question using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to compare the spatial extents and temporal dynamics of the DMN during rest and meditation...
2016: Frontiers in Human Neuroscience
F von Wegner, E Tagliazucchi, V Brodbeck, H Laufs
We analyze temporal autocorrelations and the scaling behaviour of EEG microstate sequences during wakeful rest. We use the recently introduced random walk approach and compute its fluctuation function analytically under the null hypothesis of a short-range correlated, first-order Markov process. The empirical fluctuation function and the Hurst parameter H as a surrogate parameter of long-range correlations are computed from 32 resting state EEG recordings and for a set of first-order Markov surrogate data sets with equilibrium distribution and transition matrices identical to the empirical data...
November 1, 2016: NeuroImage
Evie Malaia, Erik Bates, Benjamin Seitzman, Katherine Coppess
The heterogeneity of behavioral manifestation of autism spectrum disorders (ASDs) requires a model which incorporates understanding of dynamic differences in neural processing between ASD and typically developing (TD) populations. We use network approach to characterization of spatiotemporal dynamics of EEG data in TD and ASD youths. EEG recorded during both wakeful rest (resting state) and a social-visual task was analyzed using cross-correlation analysis of the 32-channel time series to produce weighted, undirected graphs corresponding to functional brain networks...
December 2016: Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale
Stephanie Cacioppo, Robin M Weiss, John T Cacioppo
We introduce a new analytic technique for the microsegmentation of high-density EEG to identify the discrete brain microstates evoked by the visual reversal checkerboard task. To test the sensitivity of the present analytic approach to differences in evoked brain microstates across experimental conditions, subjects were instructed to (a) passively view the reversals of the checkerboard (passive viewing condition), or (b) actively search for a target stimulus that may appear at the fixation point, and they were offered a monetary reward if they correctly detected the stimulus (active viewing condition)...
October 2016: Psychophysiology
Kostas Michalopoulos, Michalis Zervakis, Marie-Pierre Deiber, Nikolaos Bourbakis
We present a novel synergistic methodology for the spatio-temporal analysis of single Electroencephalogram (EEG) trials. This new methodology is based on the novel synergy of Local Global Graph (LG graph) to characterize define the structural features of the EEG topography as a global descriptor for robust comparison of dominant topographies (microstates) and Hidden Markov Models (HMM) to model the topographic sequence in a unique way. In particular, the LG graph descriptor defines similarity and distance measures that can be successfully used for the difficult comparison of the extracted LG graphs in the presence of noise...
September 2016: International Journal of Neural Systems
Martin Dinov, Romy Lorenz, Gregory Scott, David J Sharp, Erik D Fagerholm, Robert Leech
Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms...
2016: Frontiers in Computational Neuroscience
Florian Hatz, Martin Hardmeier, Habib Bousleiman, Stephan Rüegg, Christian Schindler, Peter Fuhr
Connectivity analysis characterizes normal and altered brain function, for example, using the phase lag index (PLI), which is based on phase relations. However, reliability of PLI over time is limited, especially for single- or regional-link analysis. One possible cause is repeated changes of network configuration during registration. These network changes may be associated with changes of the surface potential fields, which can be characterized by microstate analysis. Microstate analysis describes repeating periods of quasistable surface potential fields lasting in the subsecond time range...
July 2016: Brain Connectivity
Matthias Grieder, Thomas Koenig, Toshihiko Kinoshita, Keita Utsunomiya, Lars-Olof Wahlund, Thomas Dierks, Keiichiro Nishida
OBJECTIVE: Diagnosis of semantic dementia relies on cost-intensive MRI or PET, although resting EEG markers of other dementias have been reported. Yet the view still holds that resting EEG in patients with semantic dementia is normal. However, studies using increasingly sophisticated EEG analysis methods have demonstrated that slightest alterations of functional brain states can be detected. METHODS: We analyzed the common four resting EEG microstates (A, B, C, and D) of 8 patients with semantic dementia in comparison with 8 healthy controls and 8 patients with Alzheimer's disease...
May 2016: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
Guy Cheron, Géraldine Petit, Julian Cheron, Axelle Leroy, Anita Cebolla, Carlos Cevallos, Mathieu Petieau, Thomas Hoellinger, David Zarka, Anne-Marie Clarinval, Bernard Dan
Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport...
2016: Frontiers in Psychology
Kathryn Rieger, Laura Diaz Hernandez, Anja Baenninger, Thomas Koenig
Schizophrenia patients show abnormalities in a broad range of task demands. Therefore, an explanation common to all these abnormalities has to be sought independently of any particular task, ideally in the brain dynamics before a task takes place or during resting state. For the neurobiological investigation of such baseline states, EEG microstate analysis is particularly well suited, because it identifies subsecond global states of stable connectivity patterns directly related to the recruitment of different types of information processing modes (e...
2016: Frontiers in Psychiatry
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