Decreased complexity in Alzheimer's disease

Resting-state fMRI evidence of brain entropy mapping

for the Alzheimer's Disease Neuroimaging Initiative

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD.

Original languageEnglish
Article number378
JournalFrontiers in Aging Neuroscience
Volume9
Issue numberNOV
DOIs
Publication statusPublished - Nov 20 2017

Fingerprint

Brain Mapping
Entropy
Alzheimer Disease
Magnetic Resonance Imaging
Brain
Occipital Lobe
Cognitive Dysfunction
Brain Diseases
Frontal Lobe
Temporal Lobe
Systems Analysis
Neuroimaging
Sex Characteristics
Dementia
Analysis of Variance

Keywords

  • Alzheimer's disease
  • Complexity
  • Mild cognitive impairment
  • Permutation entropy
  • Resting-state functional magnetic resonance imaging

ASJC Scopus subject areas

  • Ageing
  • Cognitive Neuroscience

Cite this

Decreased complexity in Alzheimer's disease : Resting-state fMRI evidence of brain entropy mapping. / for the Alzheimer's Disease Neuroimaging Initiative.

In: Frontiers in Aging Neuroscience, Vol. 9, No. NOV, 378, 20.11.2017.

Research output: Contribution to journalArticle

for the Alzheimer's Disease Neuroimaging Initiative. / Decreased complexity in Alzheimer's disease : Resting-state fMRI evidence of brain entropy mapping. In: Frontiers in Aging Neuroscience. 2017 ; Vol. 9, No. NOV.
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abstract = "Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD.",
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