Dataset Information

Impact of physiological noise in characterizing the functional MRI default-mode network in Alzheimer's disease.

ABSTRACT: The functional connectivity of the default-mode network (DMN) monitored by functional magnetic resonance imaging (fMRI) in Alzheimer's disease (AD) patients has been found weaker than that in healthy participants. Since breathing and heart beating can cause fluctuations in the fMRI signal, these physiological activities may affect the fMRI data differently between AD patients and healthy participants. We collected resting-state fMRI data from AD patients and age-matched healthy participants. With concurrent cardiac and respiratory recordings, we estimated both physiological responses phase-locked and non-phase-locked to heart beating and breathing. We found that the cardiac and respiratory physiological responses in AD patients were 3.00 ± 0.51 s and 3.96 ± 0.52 s later (both p < 0.0001) than those in healthy participants, respectively. After correcting the physiological noise in the resting-state fMRI data by population-specific physiological response functions, the DMN estimated by seed-correlation was more localized to the seed region. The DMN difference between AD patients and healthy controls became insignificant after suppressing physiological noise. Our results indicate the importance of controlling physiological noise in the resting-state fMRI analysis to obtain clinically related characterizations in AD.

SUBMITTER: Li YT

PROVIDER: S-EPMC7747160 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Impact of physiological noise in characterizing the functional MRI default-mode network in Alzheimer's disease.

Li Yi-Tien YT Chang Chun-Yuan CY Hsu Yi-Cheng YC Fuh Jong-Ling JL Kuo Wen-Jui WJ Yeh Jhy-Neng Tasso JT Lin Fa-Hsuan FH

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism 20200218 1

The functional connectivity of the default-mode network (DMN) monitored by functional magnetic resonance imaging (fMRI) in Alzheimer's disease (AD) patients has been found weaker than that in healthy participants. Since breathing and heart beating can cause fluctuations in the fMRI signal, these physiological activities may affect the fMRI data differently between AD patients and healthy participants. We collected resting-state fMRI data from AD patients and age-matched healthy participants. Wit ...[more]

PMID: 32070180

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Project description:BackgroundAt present, clinical use of MRI in Alzheimer's disease (AD) is mostly focused on the assessment of brain atrophy, namely in the hippocampal region. Despite this, multiple biomarkers reflecting structural and functional brain connectivity changes have shown promising results in the assessment of AD. To help identify the most relevant ones that may stand a chance of being used in clinical practice, we compared multiple biomarker in terms of their value to discriminate AD from healthy controls and analyzed their age dependency.Methods20 AD patients and 20 matched controls underwent MRI-scanning (3T GE), including T1-weighted, diffusion-MRI, and resting-state-fMRI (rsfMRI). Whole brain, white matter, gray matter, cortical gray matter and hippocampi volumes were measured using icobrain. rsfMRI between regions of the default-mode-network (DMN) was assessed using group independent-component-analysis. Median diffusivity and kurtosis were determined in gray and white-matter. DTI data was used to evaluate pairwise structural connectivity between lobar regions and the hippocampi.Logistic-Regression and Random-Forest models were trained to classify AD-status based on, respectively different isolated features and age, and feature-groups combined with age.ResultsHippocampal features, features reflecting the functional connectivity between the medial-Pre-Frontal-Cortex (mPFC) and the posterior regions of the DMN, and structural interhemispheric frontal connectivity showed the strongest differences between AD-patients and controls. Structural interhemispheric parietal connectivity, structural connectivity between the parietal lobe and hippocampus in the right hemisphere, and mPFC-DMN-features, showed only an association with AD-status (p < 0.05) but not with age. Hippocampi volumes showed an association both with age and AD-status (p < 0.05).Smallest-hippocampus-volume was the most discriminative feature. The best performance (accuracy:0.74, sensitivity:0.74, specificity:0.74) was obtained with an RF-model combining the best feature from each feature-group (smallest hippocampus volume, WM volume, median GM MD, lTPJ-mPFC connectivity and structural interhemispheric frontal connectivity) and age.ConclusionsBrain connectivity changes caused by AD are reflected in multiple MRI-biomarkers. Decline in both the functional DMN-connectivity and the parietal interhemispheric structural connectivity may assist sepparating healthy-aging driven changes from AD, complementing hippocampal volumes which are affected by both aging and AD.

Project 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.

Dataset Information

Impact of physiological noise in characterizing the functional MRI default-mode network in Alzheimer's disease.

Publications

Impact of physiological noise in characterizing the functional MRI default-mode network in Alzheimer's disease.

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