Mutual information analysis of the EEG in patients with Alzheimer's disease

• Published in: Clinical neurophysiology Vol. 112; no. 5; pp. 827 - 835
• Main Authors: Jeong, Jaeseung, Gore, John C, Peterson, Bradley S
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Shannon Elsevier Ireland Ltd 01.05.2001; Elsevier Science
• Subjects: Aged; Alzheimer Disease - physiopathology; Alzheimer's disease; Biological and medical sciences; Brain - physiology; Brain - physiopathology; Brain Mapping; Complexity; EEG; Electrodiagnosis. Electric activity recording; Electroencephalography - methods; Female; Functional connectivity; Humans; Information transmission; Investigative techniques, diagnostic techniques (general aspects); Male; Medical sciences; Mutual information; Nerve Net - physiology; Nerve Net - physiopathology; Nervous system; Predictive Value of Tests; Probability; Reference Values; Reproducibility of Results; Functional connectivity; Information transmission; Alzheimer's disease; EEG; Mutual information; Complexity; Human; Nervous system diseases; Cerebral cortex; Corticocortical connection; Alzheimer disease; Electrophysiology; Electroencephalography; Cerebral disorder; Electrodiagnosis; Linearity; Central nervous system disease; Information processing; Nonlinearity; Degenerative disease; Signal analysis

Objective: Mutual information provides a measure of both the linear and nonlinear statistical dependencies between two time series. Cross-mutual information (CMI) is used to quantify the information transmitted from one time series to another, while auto mutual information (AMI) in a time series est...