Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease
The human resting-state is characterized by spatially coherent brain activity at a low temporal frequency. The default mode network (DMN), one of so-called resting-state networks, has been associated with cognitive processes that are directed toward the self, such as introspection and autobiographic...
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doaj-9953bb1bc1ea4f2e8e7dc88cee7d15e42020-11-24T22:50:03ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2018-10-011210.3389/fnins.2018.00770388987Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s DiseaseMatthias Grieder0Danny J. J. Wang1Thomas Dierks2Lars-Olof Wahlund3Kay Jann4Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, SwitzerlandUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United StatesTranslational Research Center, University Hospital of Psychiatry, University of Bern, Bern, SwitzerlandDivision of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, NVS, Karolinska Institute, Stockholm, SwedenUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United StatesThe human resting-state is characterized by spatially coherent brain activity at a low temporal frequency. The default mode network (DMN), one of so-called resting-state networks, has been associated with cognitive processes that are directed toward the self, such as introspection and autobiographic memory. The DMN’s integrity appears to be crucial for mental health. For example, patients with Alzheimer’s disease or other psychiatric conditions show disruptions of functional connectivity within the brain regions of the DMN. However, in prodromal or early stages of Alzheimer’s disease, physiological alterations are sometimes elusive, despite manifested cognitive impairment. While functional connectivity assesses the signal correlation between brain areas, multi-scale entropy (MSE) measures the complexity of the blood-oxygen level dependent signal within an area and thus might show local changes before connectivity is affected. Hence, we investigated alterations of functional connectivity and MSE within the DMN in fifteen mild Alzheimer’s disease patients as compared to fourteen controls. Potential associations of MSE with functional connectivity and cognitive abilities [i.e., mini-mental state examination (MMSE)] were assessed. A moderate decrease of DMN functional connectivity between posterior cingulate cortex and right hippocampus in Alzheimer’s disease was found, whereas no differences were evident for whole-network functional connectivity. In contrast, the Alzheimer’s disease group yielded lower global DMN-MSE than the control group. The most pronounced regional effects were localized in left and right hippocampi, and this was true for most scales. Moreover, MSE significantly correlated with functional connectivity, and DMN-MSE correlated positively with the MMSE in Alzheimer’s disease. Most interestingly, the right hippocampal MSE was positively associated with semantic memory performance. Thus, our results suggested that cognitive decline in Alzheimer’s disease is reflected by decreased signal complexity in DMN nodes, which might further lead to disrupted DMN functional connectivity. Additionally, altered entropy in Alzheimer’s disease found in the majority of the scales indicated a disturbance of both local information processing and information transfer between distal areas. Conclusively, a loss of nodal signal complexity potentially impairs synchronization across nodes and thus preempts functional connectivity changes. MSE presents a putative functional marker for cognitive decline that might be more sensitive than functional connectivity alone.https://www.frontiersin.org/article/10.3389/fnins.2018.00770/fullmulti-scale entropycomplexityfunctional connectivityresting-state fMRIdefault mode networkAlzheimer’s disease |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Matthias Grieder Danny J. J. Wang Thomas Dierks Lars-Olof Wahlund Kay Jann |
spellingShingle |
Matthias Grieder Danny J. J. Wang Thomas Dierks Lars-Olof Wahlund Kay Jann Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease Frontiers in Neuroscience multi-scale entropy complexity functional connectivity resting-state fMRI default mode network Alzheimer’s disease |
author_facet |
Matthias Grieder Danny J. J. Wang Thomas Dierks Lars-Olof Wahlund Kay Jann |
author_sort |
Matthias Grieder |
title |
Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease |
title_short |
Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease |
title_full |
Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease |
title_fullStr |
Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease |
title_full_unstemmed |
Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer’s Disease |
title_sort |
default mode network complexity and cognitive decline in mild alzheimer’s disease |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroscience |
issn |
1662-453X |
publishDate |
2018-10-01 |
description |
The human resting-state is characterized by spatially coherent brain activity at a low temporal frequency. The default mode network (DMN), one of so-called resting-state networks, has been associated with cognitive processes that are directed toward the self, such as introspection and autobiographic memory. The DMN’s integrity appears to be crucial for mental health. For example, patients with Alzheimer’s disease or other psychiatric conditions show disruptions of functional connectivity within the brain regions of the DMN. However, in prodromal or early stages of Alzheimer’s disease, physiological alterations are sometimes elusive, despite manifested cognitive impairment. While functional connectivity assesses the signal correlation between brain areas, multi-scale entropy (MSE) measures the complexity of the blood-oxygen level dependent signal within an area and thus might show local changes before connectivity is affected. Hence, we investigated alterations of functional connectivity and MSE within the DMN in fifteen mild Alzheimer’s disease patients as compared to fourteen controls. Potential associations of MSE with functional connectivity and cognitive abilities [i.e., mini-mental state examination (MMSE)] were assessed. A moderate decrease of DMN functional connectivity between posterior cingulate cortex and right hippocampus in Alzheimer’s disease was found, whereas no differences were evident for whole-network functional connectivity. In contrast, the Alzheimer’s disease group yielded lower global DMN-MSE than the control group. The most pronounced regional effects were localized in left and right hippocampi, and this was true for most scales. Moreover, MSE significantly correlated with functional connectivity, and DMN-MSE correlated positively with the MMSE in Alzheimer’s disease. Most interestingly, the right hippocampal MSE was positively associated with semantic memory performance. Thus, our results suggested that cognitive decline in Alzheimer’s disease is reflected by decreased signal complexity in DMN nodes, which might further lead to disrupted DMN functional connectivity. Additionally, altered entropy in Alzheimer’s disease found in the majority of the scales indicated a disturbance of both local information processing and information transfer between distal areas. Conclusively, a loss of nodal signal complexity potentially impairs synchronization across nodes and thus preempts functional connectivity changes. MSE presents a putative functional marker for cognitive decline that might be more sensitive than functional connectivity alone. |
topic |
multi-scale entropy complexity functional connectivity resting-state fMRI default mode network Alzheimer’s disease |
url |
https://www.frontiersin.org/article/10.3389/fnins.2018.00770/full |
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