Related Experiment Video
Updated: Apr 18, 2026
07:28
Full- versus Sub-Regional Quantification of Amyloid-Beta Load on Mouse Brain Sections
Published on: May 19, 2022
4.9K
Using static and dynamic canonical correlation coefficients as quantitative EEG markers for Alzheimer's disease
Summary
Quantitative electroencephalography (qEEG) markers show a close relationship with Alzheimer's disease (AD) severity. These markers may aid in diagnosing early-stage AD, despite an ambiguous trend in synchrony changes.
Area of Science:
- Neuroscience
- Medical Imaging
- Biomarkers
Background:
- Alzheimer's disease (AD) diagnosis relies on cognitive assessments, but objective biomarkers are needed.
- Quantitative electroencephalography (qEEG) offers potential for non-invasive brain activity analysis.
- Understanding the relationship between brain activity and AD severity is crucial for early detection.
Purpose of the Study:
- To investigate the relationship between Alzheimer's disease (AD) severity, measured by Mini-Mental State Examination (MMSE) scores, and quantitative electroencephalographic (qEEG) markers.
- To explore EEG synchrony patterns using canonical correlation analysis in relation to AD progression.
- To assess the potential of qEEG markers as diagnostic aids for early-stage AD.
Main Methods:
- Analysis of EEG data from 79 participants with probable AD from the PRODEM-Austria cohort.
- Recording of resting-state and cognitive task EEG data under a homogeneous protocol.
- Application of canonical correlation analysis to derive qEEG synchrony markers and quadratic regression to model the MMSE-qEEG relationship.
Main Results:
- A significant relationship was found between MMSE scores and qEEG synchrony markers, particularly in the δ and θ frequency bands during resting state.
- During a cognitive task, the strongest relations were observed between left-hemispheric central, temporal, and parietal channels.
- MMSE scores explained up to 40% of the variation in qEEG markers, revealing an initial increase in synchrony (MMSE>20) followed by a decrease in later AD stages.
Conclusions:
- Proposed qEEG markers are closely associated with Alzheimer's disease severity.
- The observed ambiguous trend in qEEG synchrony may reflect compensatory brain mechanisms.
- qEEG markers show promise for assisting in the diagnosis of early-stage Alzheimer's disease, despite diagnostic ambiguities.
Related Concept Videos
02:20Correlations
37.1K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
37.1K
01:12Coefficient of Correlation
9.3K
The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
9.3K
00:53Correlation and Regression
4.4K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
4.4K
01:10Calibration Curves: Correlation Coefficient
6.5K
In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
6.5K
01:23Alzheimer Disease ll: Pathophysiology
1
Alzheimer disease involves structural changes in the brain that begin long before symptoms appear. The most distinctive features are extracellular neuritic plaques and intracellular neurofibrillary tangles.Neuritic plaques form in the cerebral cortex and around blood vessels. These plaques contain a dense core of beta-amyloid (Aβ)—a toxic protein fragment that clumps outside neurons. The core is surrounded by damaged neuronal extensions, as well as reactive astrocytes and...
1
01:29Alzheimer Disease l: Introduction
2
Alzheimer disease is a chronic, progressive, and irreversible neurodegenerative disorder and the most common cause of dementia in older adults. It leads to gradual neuronal loss, causing cognitive decline, behavioral changes, and loss of functional independence.Risk Factors and EtiologyThe disease is multifactorial. Age is the strongest risk factor, with prevalence doubling every 5 years after age 65. Genetic factors include mutations in genes such as APP, PSEN1, and PSEN2, which are associated...
2