Discovering EEG resting state alterations of semantic dementia

Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars‐Olof; Dierks, Thomas; Nishida, Keiichiro

doi:10.1016/j.clinph.2016.01.025

Cited by 44 publications

(37 citation statements)

References 45 publications

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“…Previous works showed that a modification of microstate topography and metrics is possible by cognitive manipulation 19 . Moreover, altered topographies and metrics have been found in the acute phase of the stroke as a consequence of a mono-hemispheric lesion 18 , as well as in neurodegenerative or psychiatric diseases 20 . Our study adds the evidence that the topography and metrics of microstates can be modified also by active inhibition by means of magnetic stimulation.…”

Section: Discussionmentioning

confidence: 99%

Offline stimulation of human parietal cortex differently affects resting EEG microstates

Croce

Zappasodi

Capotosto

2018

Sci Rep

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The interference effects of transcranial magnetic stimulation (TMS) on several electroencephalographic (EEG) measures in both temporal and frequency domains have been reported. We tested the hypothesis whether the offline external inhibitory interference, although focal, could result in a global reorganization of the functional brain state, as assessed by EEG microstates. In 16 healthy subjects, we inhibited five parietal areas and used a pseudo stimulation (Sham) at rest. The EEG microstates were extracted before and after each stimulation. The canonical A, B, C and D templates were found before and after all stimulation conditions. The Sham, as well as the stimulation of a ventral site did not modify any resting EEG microstates’ topography. On the contrary, interfering with parietal key-nodes of both dorsal attention (DAN) and default mode networks (DMN), we observed that the microstate C clearly changes, whereas the other three topographies are not affected. These results provide the first causal evidence of a microstates modification following magnetic interference. Since the microstate C has been associated to the activity in regions belonging to the cingulo-opercular network (CON), the regional specificity of such inhibition seems to support the theory of a link between CON and both DAN and DMN at rest.

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Section: Discussionmentioning

confidence: 99%

Offline stimulation of human parietal cortex differently affects resting EEG microstates

Croce

Zappasodi

Capotosto

2018

Sci Rep

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“…The idea of electric microstates of the brain comes from the observation that the topography of the electric field recorded by EEG over the scalp does not fluctuate randomly, but is instead comprised of short periods of stability (Lehmann 1971 ). Four canonical microstates (Koenig et al 2002a , b ), conventionally labelled A, B, C and D, have been shown to be consistent across recording sessions (Khanna et al 2014 ) and have been repeatedly confirmed in a wide range of health conditions and cognitive tasks across multiple studies (Britz et al 2010 ; Brodbeck et al 2012a , b ; Grieder et al 2016 ; Katayama et al 2007 ; Kikuchi et al 2011 ; Koenig et al 1999 ; Kuhn et al 2015 ; Milz et al 2015 ; Nishida et al 2013 ; Pascual-Marqui et al 2014 ; Schlegel et al 2012 ; Strelets et al 2003 ; Tomescu et al 2014a , b ; Van de Ville et al 2010 ).…”

Section: Methodsmentioning

confidence: 99%

Transient Topographical Dynamics of the Electroencephalogram Predict Brain Connectivity and Behavioural Responsiveness During Drowsiness

2018

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As we fall sleep, our brain traverses a series of gradual changes at physiological, behavioural and cognitive levels, which are not yet fully understood. The loss of responsiveness is a critical event in the transition from wakefulness to sleep. Here we seek to understand the electrophysiological signatures that reflect the loss of capacity to respond to external stimuli during drowsiness using two complementary methods: spectral connectivity and EEG microstates. Furthermore, we integrate these two methods for the first time by investigating the connectivity patterns captured during individual microstate lifetimes. While participants performed an auditory semantic classification task, we allowed them to become drowsy and unresponsive. As they stopped responding to the stimuli, we report the breakdown of alpha networks and the emergence of theta connectivity. Further, we show that the temporal dynamics of all canonical EEG microstates slow down during unresponsiveness. We identify a specific microstate (D) whose occurrence and duration are prominently increased during this period. Employing machine learning, we show that the temporal properties of microstate D, particularly its prolonged duration, predicts the response likelihood to individual stimuli. Finally, we find a novel relationship between microstates and brain networks as we show that microstate D uniquely indexes significantly stronger theta connectivity during unresponsiveness. Our findings demonstrate that the transition to unconsciousness is not linear, but rather consists of an interplay between transient brain networks reflecting different degrees of sleep depth. Electronic supplementary material The online version of this article (10.1007/s10548-018-0689-9) contains supplementary material, which is available to authorized users.

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“…Simultaneous fMRI-EEG studies as well as EEG source imaging studies suggest that these microstate classes correspond to the activity of previously identified networks for phonological processing, the visual network, the saliency network, and attention network, respectively ( Britz et al, 2010 ; Custo et al, 2017 ). Alterations in the expression of these microstates have been observed in a variety of neuropsychiatric conditions including depression ( Atluri et al, 2017 ), Alzheimer’s disease ( Dierks et al, 1997 ; Strik et al, 1997 ; Nishida et al, 2013 ), frontotemporal dementia ( Strik et al, 1997 ; Nishida et al, 2013 ; Grieder et al, 2016 ), stroke ( Zappasodi et al, 2017 ), and schizophrenia ( Merrin et al, 1990 ; Stevens et al, 1997 ; Strelets et al, 2003 ; Lehmann et al, 2005 ; Kikuchi et al, 2007 ; Kindler et al, 2011 ; Nishida et al, 2013 ; Tomescu et al, 2014 ; Sverak et al, 2017 ). However, to date, only two such studies have been done in persons with ASD.…”

Section: Introductionmentioning

confidence: 99%

Children With Autism Produce a Unique Pattern of EEG Microstates During an Eyes Closed Resting-State Condition

Kalburgi

Whitten

Key

2020

Front. Hum. Neurosci.

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Although fMRI studies have produced considerable evidence for differences in the spatial connectivity of resting-state brain networks in persons with autism spectrum disorder (ASD) relative to typically developing (TD) peers, little is known about the temporal dynamics of these brain networks in ASD. The aim of this study was to examine the EEG microstate architecture in children with ASD as compared to TD at rest in two separate conditions – eyes-closed (EC) and eyes-open (EO). EEG microstate analysis was performed on resting-state data of 13 ASD and 13 TD children matched on age, gender, and IQ. We found that children with ASD and TD peers produced topographically similar canonical microstates at rest. Group differences in the duration and frequency of these microstates were found primarily in the EC resting-state condition. In line with previous fMRI findings that have reported differences in spatial connectivity within the salience network (previously correlated with the activity of microstate C) in ASD, we found that the duration of activation of microstate C was increased, and the frequency of microstate C was decreased in ASD as compared to TD in EC resting-state. Functionally, these results may be reflective of alterations in interoceptive processes in ASD. These results suggest a unique pattern of EEG microstate architecture in ASD relative to TD during resting-states and also that EEG microstate parameters in ASD are susceptible to differences in resting-state conditions.

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Discovering EEG resting state alterations of semantic dementia

Cited by 44 publications

References 45 publications

Offline stimulation of human parietal cortex differently affects resting EEG microstates

Offline stimulation of human parietal cortex differently affects resting EEG microstates

Transient Topographical Dynamics of the Electroencephalogram Predict Brain Connectivity and Behavioural Responsiveness During Drowsiness

Children With Autism Produce a Unique Pattern of EEG Microstates During an Eyes Closed Resting-State Condition

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