Understanding brain function in vascular cognitive impairment and dementia with EEG and MEG: A systematic review

Torres-Simón, Lucía; Doval, Sandra; Nebreda, Alberto; Llinas, Sophia J.; Marsh, Elisabeth B.; Maestú, Fernando

doi:10.1016/j.nicl.2022.103040

Cited by 17 publications

(17 citation statements)

References 121 publications

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“…To the best of our knowledge, this is the first study using MEG spectral analysis to compare MCI populations with and without cerebrovascular damage, specifically assessing the presence of WMH. The lack of literature regarding electrophysiological spectral patterns measured with MEG related to VCI makes it impossible to directly compare our results with previous literature, but we can confirm that our findings are in line with those described in EEG studies (Torres-Simón et al, 2022 ). It is worth mentioning that in many of these EEG studies, the inclusion criteria for the VCI population are vague or broad.…”

Section: Discussionsupporting

confidence: 79%

“…According to the cerebrovascular factors they can also be found in studies analyzing MEG spectral features for patients with stroke (Tecchio et al, 2006 ; Chu et al, 2015 ; Kielar et al, 2016 ; Johnston et al, 2022 ), which is one of the major causes of major VCI, even using ultrasonography measures to assess carotid blood flow (Matsumoto et al, 2021 ). Nevertheless, to the best of our knowledge, no article has been published performing spectral analysis with MEG in older people diagnosed with mild or major VCI, and only a few can be found with EEG, as described in a recent systematic review performed by our research group (Torres-Simón et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

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The effects of white matter hyperintensities on MEG power spectra in population with mild cognitive impairment

Torres-Simón

Cuesta²,

Cerro-León³

et al. 2023

Front. Hum. Neurosci.

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Cerebrovascular disease is responsible for up to 20% of cases of dementia worldwide, but also it is a major comorbid contributor to the progression of other neurodegenerative diseases, like Alzheimer’s disease. White matter hyperintensities (WMH) are the most prevalent imaging marker in cerebrovascular disease. The presence and progression of WMH in the brain have been associated with general cognitive impairment and the risk to develop all types of dementia. The aim of this piece of work is the assessment of brain functional differences in an MCI population based on the WMH volume. One-hundred and twenty-nine individuals with mild cognitive impairment (MCI) underwent a neuropsychological evaluation, MRI assessment (T1 and Flair), and MEG recordings (5 min of eyes closed resting state). Those participants were further classified into vascular MCI (vMCI; n = 61, mean age 75 ± 4 years, 35 females) or non-vascular MCI (nvMCI; n = 56, mean age 72 ± 5 years, 36 females) according to their WMH total volume, assessed with an automatic detection toolbox, LST (SPM12). We used a completely data-driven approach to evaluate the differences in the power spectra between the groups. Interestingly, three clusters emerged: One cluster with widespread larger theta power and two clusters located in both temporal regions with smaller beta power for vMCI compared to nvMCI. Those power signatures were also associated with cognitive performance and hippocampal volume. Early identification and classification of dementia pathogenesis is a crucially important goal for the search for more effective management approaches. These findings could help to understand and try to palliate the contribution of WMH to particular symptoms in mixed dementia progress.

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Section: Discussionsupporting

confidence: 79%

Section: Introductionmentioning

confidence: 99%

The effects of white matter hyperintensities on MEG power spectra in population with mild cognitive impairment

Torres-Simón

Cuesta²,

Cerro-León³

et al. 2023

Front. Hum. Neurosci.

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“…Much information on the function of brain networks is available in neurophysiologic studies, such as EEG and evoked potentials in dementia [ 44 , 45 , 46 , 47 ] and should be included in the patient database when available…”

Section: Specific Challengesmentioning

confidence: 99%

A Perspective: Challenges in Dementia Research

Stecker

2022

Medicina

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Although dementia is a common and devastating disease that has been studied intensely for more than 100 years, no effective disease modifying treatment has been found. At this impasse, new approaches are important. The purpose of this paper is to provide, in the context of current research, one clinician’s perspective regarding important challenges in the field in the form of specific challenges. These challenges not only illustrate the scope of the problems inherent in finding treatments for dementia, but can also be specific targets to foster discussion, criticism and new research. One common theme is the need to transform research activities from small projects in individual laboratories/clinics to larger multinational projects, in which each clinician and researcher works as an integral part. This transformation will require collaboration between researchers, large corporations, regulatory/governmental authorities and the general population, as well as significant financial investments. However, the costs of transforming the approach are small in comparison with the cost of dementia.

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“…Functional connectivity, which is defined as the degree of synchronization and information flow between neurally activated areas of different brain regions (strong synchronization and large information flow corresponding to strong functional connectivity), has been widely utilized for evaluating pathological and aging brain network changes and the brain network characteristics that support cognitive functions in healthy individuals (Stam et al, 2007a ; Zhou and Seeley, 2014 ; Sala-Llonch et al, 2015 ; Torres-Simón et al, 2022 ). In particular, the relationship between functional connectivity and cognitive status has been elucidated in diverse dementia cases involving mild cognitive impairment, AD, and dementia with Lewy bodies (Zhou and Seeley, 2014 ; van Dellen et al, 2015 ; Zhang et al, 2016 ; Nobukawa et al, 2020a ; Torres-Simón et al, 2022 ). In this relationship, most of the reduced functional connectivity correlates with decreasing cognitive functions (Zhou and Seeley, 2014 ; van Dellen et al, 2015 ; Nobukawa et al, 2020a ).…”

Section: Introductionmentioning

confidence: 99%

“…However, some functional connectivity is enhanced, especially in mild cognitive impairments (Zhang et al, 2016 ). Therefore, to estimate the cognitive state in older individuals, capturing disease-specific (Zhou and Seeley, 2014 ; van Dellen et al, 2015 ; Zhang et al, 2016 ; Nobukawa et al, 2020a ; Torres-Simón et al, 2022 ), age-specific (Scally et al, 2018 ; Ando et al, 2022 ), and level-of-cognitive-functional-specific (Nobukawa et al, 2020b ) spatial patterns of functional connectivity is important. Moreover, among the many approaches to estimate functional connectivity, such as coherence measure and transform entropy, instantaneous phase synchronization, typified as the phase lag index (PLI), is an effective approach for estimating functional connectivity with higher spatial resolution compared to other synchronization approaches, by virtue of suppressing the influence of volume conduction (Stam et al, 2007b ; Tobe and Nobukawa, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Hub structure in functional network of EEG signals supporting high cognitive functions in older individuals

Tobe

Nobukawa

Mizukami

et al. 2023

Front. Aging Neurosci.

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IntroductionMaintaining high cognitive functions is desirable for “wellbeing” in old age and is particularly relevant to a super-aging society. According to their individual cognitive functions, optimal intervention for older individuals facilitates the maintenance of cognitive functions. Cognitive function is a result of whole-brain interactions. These interactions are reflected in several measures in graph theory analysis for the topological characteristics of functional connectivity. Betweenness centrality (BC), which can identify the “hub” node, i.e., the most important node affecting whole-brain network activity, may be appropriate for capturing whole-brain interactions. During the past decade, BC has been applied to capture changes in brain networks related to cognitive deficits arising from pathological conditions. In this study, we hypothesized that the hub structure of functional networks would reflect cognitive function, even in healthy elderly individuals.MethodTo test this hypothesis, based on the BC value of the functional connectivity obtained using the phase lag index from the electroencephalogram under the eyes closed resting state, we examined the relationship between the BC value and cognitive function measured using the Five Cognitive Functions test total score.ResultsWe found a significant positive correlation of BC with cognitive functioning and a significant enhancement in the BC value of individuals with high cognitive functioning, particularly in the frontal theta network.DiscussionThe hub structure may reflect the sophisticated integration and transmission of information in whole-brain networks to support high-level cognitive function. Our findings may contribute to the development of biomarkers for assessing cognitive function, enabling optimal interventions for maintaining cognitive function in older individuals.

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Understanding brain function in vascular cognitive impairment and dementia with EEG and MEG: A systematic review

Cited by 17 publications

References 121 publications

The effects of white matter hyperintensities on MEG power spectra in population with mild cognitive impairment

The effects of white matter hyperintensities on MEG power spectra in population with mild cognitive impairment

A Perspective: Challenges in Dementia Research

Hub structure in functional network of EEG signals supporting high cognitive functions in older individuals

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