Fractal dimension distributions of resting-state EEG improve detection of dementia and Alzheimer's disease compared to traditional fractal analysis
Yoder, K. J.; Brookshire, G.; Glatt, R.; Merrill, D. A.; Gerrol, S.; Quirk, C.; Lucero, C.
Show abstract
Across many resting-state electroencephalography (EEG) studies, dementia is associated with changes to the power spectrum and fractal dimension. Here we describe a novel method to examine changes in fractal dimension over time and within frequency bands. This method, which we call Fractal Dimension Distributions (FDD), combines spectral and complexity information. In this study, we illustrate this new method by applying it to resting-state EEG data recorded from patients with subjective cognitive impairment (SCI) or dementia. We compared the performance of FDD with the performance of standard fractal dimension metrics (Higuchi and Katz FD). FDD revealed larger group differences detectable at greater numbers of EEG recording sites. Moreover, linear models using FDD features had lower AIC and higher R2 than models using standard full time-course measures of fractal dimension. FDD metrics also outperformed the full time-course metrics when comparing SCI with a subset of dementia patients diagnosed with Alzheimers disease (AD). FDD offers unique information beyond traditional full time-course fractal analyses and may help to identify AD dementia and non-AD dementia.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Greek High Phenolic Early Harvest Extra Virgin Olive Oil Reduces the Over-Excitation of Information Flow based on Dominant Coupling Model in patients with Mild Cognitive Impairment: An EEG Resting-State Validation Approach 94%
- Screening for early-stage Alzheimer's disease using optimized feature sets and machine learning 94%
- Effect of cognitive reserve on physiological measures of cognitive workload in older adults with cognitive impairments 94%
Similar papers in this journal
- Examining heterogeneity in dementia using data-driven unsupervised clustering of cognitive profiles 95%
- Olfactory Response as a Marker for Alzheimer's Disease: Evidence from Perceptual and Frontal Oscillation Coherence Deficit 94%
- Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment 94%
Similar papers in this journal
- Whole-brain functional connectivity predicts regional tau PET in preclinical Alzheimer's disease 93%
- The PREVENT Dementia programme: Baseline demographic, lifestyle, imaging and cognitive data from a midlife cohort study investigating risk factors for dementia 92%
- Dementia is strongly associated with medial temporal atrophy even after accounting for neuropathologies 92%
Similar papers in this journal
- Detection of cognitive decline using a single-channel EEG with an interactive assessment tool 96%
- Phenotyping Neuropsychiatric Symptoms Profiles of Alzheimer's Disease Using Cluster Analysis on EEG Power 95%
- Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.