Is brain connectome research the future frontier for subjective cognitive decline? A systematic review

Lazarou, Ioulietta; Nikolopoulos, Spiros; Dimitriadis, Stavros I.; Kompatsiaris, Ioannis; Spilioti, Martha; Tsolaki, Magda

doi:10.1016/j.clinph.2019.07.004

Cited by 29 publications

(28 citation statements)

References 132 publications

(219 reference statements)

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“…[32]. Moreover, SCD showed intermediate changes of DMN connectivity between MCI and HC[31][33]. Analogously, this study found that SCD showed intermediate changes of DMN-dominated FC/fALFF states, which was in line with previous reports.…”

supporting

confidence: 92%

“…Studies found variable and complex patterns of altered activity or connectivity of DMN in MCI [29], and the study of DMN hyperconnectivity suggested functional disconnection and compensation for the damage in early AD [27] [30]. As a high-risk state of AD, SCD shared similar pattern of brain abnormality to AD, and the disrupted manner of the brain connectivity in SCD was similar to that was observed in MCI [31] frequency between SCD and HC. In this regard, we speculate DMN dysfunction or disconnection occurred in SCD and MCI patients resulting in whole brain network dynamic decline, but DMN kept predominantly active during the resting state.…”

Section: The Key Role Of Dmn-dominated Statesmentioning

confidence: 65%

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Recurrent and Concurrent Patterns of Regional BOLD Dynamics and Functional Connectivity Dynamics in Cognitive Decline

Liang

Yuan

Wei

et al. 2020

Preprint

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Background: The brain’s dynamic spontaneous neural activity and dynamic functional connectivity (dFC) are both important in supporting cognition, but how these two types of brain dynamics evolve and co-evolve in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remain unclear. The aim of this study is to investigate recurrent and concurrent patterns of two types of dynamic brain states correlated with cognitive decline. Methods: the present study analyzed resting-state fMRI from 62 SCD, 75 MCI and 70 healthy controls (HC). Results: We identified a few recurrent states of dynamic regional spontaneous activity (measured as dynamic fractional amplitude of low-frequency fluctuations, dfALFF) and dFC, and further ascertained the co-occurrent patterns of two types of dynamic brain states (i.e., dfALFF and dFC states). Importantly, the occurrence frequency of a default mode network (DMN)-dominated dFC state was significantly different between HC and SCD, while the co-occurrence frequency of a DMN-dominated dFC state and a DMN-dominated dfALFF state was significantly different between SCD and MCI. These two dynamic features were both significantly positively correlated with Mini Mental State Examination scores. Conclusion: This study discovered new neural signatures of cognitive decline from recurrent and concurrent patterns of dfALFF and dFC, providing strong evidence supporting SCD as the transition phase between normal aging and MCI. This finding holds the potential to differentiate SCD from HC by using both dFC and dfALFF as objective neuroimaging biomarkers, and thus helps the early diagnosis and intervention of AD.

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supporting

confidence: 92%

Section: The Key Role Of Dmn-dominated Statesmentioning

confidence: 65%

Recurrent and Concurrent Patterns of Regional BOLD Dynamics and Functional Connectivity Dynamics in Cognitive Decline

Liang

Yuan

Wei

et al. 2020

Preprint

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“…Moreover, SCD shows intermediate changes in DMN connectivity between MCI patients and HCs[51,53]. Analogously, our present study found that SCD showed intermediate changes in DMN-dominated FC/fALFF states.…”

supporting

confidence: 86%

Recurrent and Concurrent Patterns of Regional BOLD Dynamics and Functional Connectivity Dynamics in Cognitive Decline

Liang

Yuan

Wei

et al. 2020

Preprint

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Background : The brain’s dynamic spontaneous neural activity and dynamic functional connectivity (dFC) are both important in supporting cognition, but how these two types of brain dynamics evolve and co-evolve in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remain unclear. The aim of the present study was to investigate recurrent and concurrent patterns of two types of dynamic brain states correlated with cognitive decline.Methods : The present study analyzed resting-state functional magnetic resonance imaging data from 62 SCD patients, 75 MCI patients, and 70 healthy controls (HCs). We used the sliding-window and clustering method to identify two types of recurrent brain states from both dFC and dynamic regional spontaneous activity, as measured by dynamic fractional amplitude of low-frequency fluctuations (dfALFF). Then, the occurrence frequency of a dFC or dfALFF state and the co-occurrence frequency of a pair of dFC and dfALFF states among all time points are extracted for each participant to describe their dynamics brain patterns.Results : We identified a few recurrent states of dfALFF and dFC, and further ascertained the co-occurrent patterns of these two types of dynamic brain states (i.e., dfALFF and dFC states). Importantly, the occurrence frequency of a default-mode network (DMN)-dominated dFC state was significantly different between HCs and SCD patients, and the co-occurrence frequencies of a DMN-dominated dFC state and a DMN-dominated dfALFF state were also significantly different between SCD and MCI patients. These two dynamic features were both significantly positively correlated with Mini Mental State Examination scores.Conclusion : Our findings revealed novel fMRI-based neural signatures of cognitive decline from recurrent and concurrent patterns of dfALFF and dFC, providing strong evidence supporting SCD as the transition phase between normal aging and MCI. This finding holds potential to differentiate SCD patients from HCs via both dFC and dfALFF as objective neuroimaging biomarkers, which may aid in the early diagnosis and intervention of Alzheimer’s disease.

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“…Moreover, early existing research has found different brain alterations in healthy controls compared to amnestic MCI and AD patients during the encoding process over the superior parietal lobe, cingulate cortex, middle temporal lobe and precuneus [60][61][62]. Despite the fact that a wide variety of the previous reported studies have found that connectivity over multiple brain regions was partially interrupted in SCD compared to healthy controls, a great amount of network properties was widely preserved in the first ones [63], which underlines that the brains of SCD individuals still maintain a few network properties since their brains have not been completely damaged. These findings reveal that the disintegrated strength of the DMN nodes of posterior and temporal brain areas, with a simultaneous increase in nodal strength over anterior regions, is manifested in SCD individuals in a similar way as in the more advanced dementia spectrum (e.g., MCI and AD) [64].…”

Section: Brain Connectome In Scdmentioning

confidence: 96%

“…In detail, we considered a local network of selected electrodes (parietal region), which is the most prominent choice for the examination of resting state network(s) [35,73,75,[100][101][102]. Regarding the local parietal network, we chose the following electrodes according to the EGI system, numbering: 78,87,100,101,63,142,154,35,87,99,110,119,63,141,153,163,86,98,109,118,127,140,152,162,96,97,108,170 and 161 [103], which represent the respective parietal area.…”

Section: Global Brain and Local Parietal Network Analysismentioning

confidence: 99%

A Novel Connectome-based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer’s Disease by Using Resting-state High-density EEG EGI GES 300

et al. 2020

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Aim: To investigate for the first time the brain network in the Alzheimer’s disease (AD) spectrum by implementing a high-density electroencephalography (HD-EEG - EGI GES 300) study with 256 channels in order to seek if the brain connectome can be effectively used to distinguish cognitive impairment in preclinical stages. Methods: Twenty participants with AD, 30 with mild cognitive impairment (MCI), 20 with subjective cognitive decline (SCD) and 22 healthy controls (HC) were examined with a detailed neuropsychological battery and 10 min resting state HD-EEG. We extracted correlation matrices by using Pearson correlation coefficients for each subject and constructed weighted undirected networks for calculating clustering coefficient (CC), strength (S) and betweenness centrality (BC) at global (256 electrodes) and local levels (29 parietal electrodes). Results: One-way ANOVA presented a statistically significant difference among the four groups at local level in CC [F (3, 88) = 4.76, p = 0.004] and S [F (3, 88) = 4.69, p = 0.004]. However, no statistically significant difference was found at a global level. According to the independent sample t-test, local CC was higher for HC [M (SD) = 0.79 (0.07)] compared with SCD [M (SD) = 0.72 (0.09)]; t (40) = 2.39, p = 0.02, MCI [M (SD) = 0.71 (0.09)]; t (50) = 0.41, p = 0.004 and AD [M (SD) = 0.68 (0.11)]; t (40) = 3.62, p = 0.001 as well, while BC showed an increase at a local level but a decrease at a global level as the disease progresses. These findings provide evidence that disruptions in brain networks in parietal organization may potentially represent a key factor in the ability to distinguish people at early stages of the AD continuum. Conclusions: The above findings reveal a dynamically disrupted network organization of preclinical stages, showing that SCD exhibits network disorganization with intermediate values between MCI and HC. Additionally, these pieces of evidence provide information on the usefulness of the 256 HD-EEG in network construction.

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Is brain connectome research the future frontier for subjective cognitive decline? A systematic review

Cited by 29 publications

References 132 publications

Recurrent and Concurrent Patterns of Regional BOLD Dynamics and Functional Connectivity Dynamics in Cognitive Decline

Recurrent and Concurrent Patterns of Regional BOLD Dynamics and Functional Connectivity Dynamics in Cognitive Decline

Recurrent and Concurrent Patterns of Regional BOLD Dynamics and Functional Connectivity Dynamics in Cognitive Decline

A Novel Connectome-based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer’s Disease by Using Resting-state High-density EEG EGI GES 300

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