EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease

Tait, Luke; Tamagnini, Francesco; Stothart, George; Barvas, Edoardo; Monaldini, C.; Frusciante, Roberto; Volpini, Mirco; Guttmann, Susanna; Coulthard, Elizabeth; Brown, Jon; Kazanina, Nina; Goodfellow, Marc

doi:10.1101/833244

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…We studied a number of spatiotemporal statistics of the resulting source MEG microstate sequences. Global statistics of the microstate sequences include GEV 65 , mean duration of microstates 67 , Hurst exponent of the sequences 68 , and microstate complexity 45 . Microstate complexity values were normalized against its theoretical asymptotic upper bound [69][70][71] , to result in a measure ∈ (0, 1].…”

Section: Microstate Statisticsmentioning

confidence: 99%

MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses

Tait

Zhang

2021

Preprint

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EEG microstate analysis is an approach to study brain states and their fast transitions in healthy cognition and disease. A key limitation of conventional microstate analysis is that it must be performed at the sensor level, and therefore gives limited anatomical insight. Here, we generalise the microstate methodology to be applicable to source-reconstructed electrophysiological data. Using simulations of a neural-mass network model, we first established the validity and robustness of the proposed method. Using MEG resting-state data, we uncovered ten microstates with distinct spatial distributions of cortical activation. Multivariate pattern analysis demonstrated that source-level microstates were associated with distinct functional connectivity patterns. We further demonstrated that the occurrence probability of MEG microstates were altered by auditory stimuli, exhibiting a hyperactivity of the microstate including the auditory cortex. Our results support the use of source-level microstates as a method for investigating brain dynamic activity and connectivity at the millisecond scale.

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Section: Microstate Statisticsmentioning

confidence: 99%

MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses

Tait

Zhang

2021

Preprint

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“…12 Thus, EEG microstate analysis can represent sub-second brain network alterations. In the last decade, EEG microstate analysis has been widely used in neurological and psychiatric disorders, including schizophrenia, [13][14][15] autism spectrum disorders, [16][17][18] Alzheimer's disease, 19,20 Parkinson's disease, 21,22 multiple sclerosis, 23 stroke, 24,25 etc. Notably, EEG microstate analysis has been increasingly used in the last 2 years to assess resting brain network changes in patients with MWA and MWoA.…”

Section: Introductionmentioning

confidence: 99%

Resting‐state electroencephalography microstate dynamics altered in patients with migraine with and without aura—A pilot study

Lei,

Wei,

Wang

et al. 2023

Headache

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ObjectiveTo evaluate electroencephalography (EEG) microstate differences between patients with migraine with aura (MWA), patients with migraine without aura (MWoA), and healthy controls (HC).BackgroundPrevious research employing microstate analysis found unique microstate alterations in patients with MWoA; however, it is uncertain how microstates appear in patients with MWA.MethodsThis study was conducted at the Headache Clinic of the First Affiliated Hospital of Xi'an Jiaotong University. In total, 30 patients with MWA, 30 with MWoA, and 30 HC were enrolled in this cross‐sectional study. An EEG was recorded for all participants under resting state. The microstate parameters of four widely recognized microstate classes A–D were calculated and compared across the three groups.ResultsThe occurrence of microstate B (MsB) in the MWoA group was significantly higher than in the HC (p = 0.006, Cohen's d = 0.72) and MWA (p = 0.016, Cohen's d = 0.57) groups, while the contribution of MsB was significantly increased in the MWoA group compared to the HC group (p = 0.016, Cohen's d = 0.64). Microstate A (MsA) displayed a longer duration in the MWA group compared to the MWoA group (p = 0.007, Cohen's d = 0.69). Furthermore, the transition probability between MsB and microstate D was significantly increased in the MWoA group compared to the HC group (p = 0.009, Cohen's d = 0.68 for B to D; p = 0.007, Cohen's d = 0.71 for D to B). Finally, the occurrence and contribution of MsB were positively related to headache characteristics in the MWoA group but negatively in the MWA group, whereas the duration of MsA was positively related to the visual analog scale in the MWA group (all p < 0.05).ConclusionsPatients with MWA and MWoA have altered microstate dynamics, indicating that resting‐state brain network disorders may play a role in migraine pathogenesis. Microstate parameters may have the potential to aid clinical management, which needs to be investigated further.

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State switching and high-order spatiotemporal organization of dynamic Functional Connectivity are disrupted by Alzheimer’s Disease

Arbabyazd

Petkoski

Breakspear

et al. 2023

Preprint

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Spontaneous activity during the resting state, tracked by BOLD fMRI imaging, or shortly rsfMRI, gives rise to brain-wide dynamic patterns of inter-regional correlations, whose structured flexibility relates to cognitive performance. Here we analyze resting state dynamic Functional Connectivity (dFC) in a cohort of older adults, including amnesic Mild Cognitive Impairment (aMCI, N = 34) and Alzheimer's Disease (AD, N = 13) patients, as well as normal control (NC, N = 16) and cognitively "super-normal" (SN, N = 10) subjects. Using complementary state-based and state-free approaches, we find that resting state fluctuations of different functional links are not independent but are constrained by high-order correlations between triplets or quadruplets of functionally connected regions. When contrasting patients with healthy subjects, we find that dFC between cingulate and other limbic regions is increasingly bursty and intermittent when ranking the four groups from SNC to NC, aMCI and AD. Furthermore, regions affected at early stages of AD pathology are less involved in higher-order interactions in patient than in control groups, while pairwise interactions are not significantly reduced. Our analyses thus suggest that the spatiotemporal complexity of dFC organization is precociously degraded in AD and provides a richer window into the underlying neurobiology than time-averaged FC connections.

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EEG microstate complexity for aiding early diagnosis of Alzheimer’s disease

Cited by 3 publications

References 49 publications

MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses

MEG cortical microstates: spatiotemporal characteristics, dynamic functional connectivity and stimulus-evoked responses

Resting‐state electroencephalography microstate dynamics altered in patients with migraine with and without aura—A pilot study

State switching and high-order spatiotemporal organization of dynamic Functional Connectivity are disrupted by Alzheimer’s Disease

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