State of the science on mild cognitive impairment (MCI)
ND Anderson - CNS spectrums, 2019 - cambridge.org
Mild cognitive impairment (MCI) represents a transitional stage between healthy aging and
dementia, and affects 10–15% of the population over the age of 65. The failure of drug trials …
dementia, and affects 10–15% of the population over the age of 65. The failure of drug trials …
Axonal energy metabolism, and the effects in aging and neurodegenerative diseases
Human studies consistently identify bioenergetic maladaptations in brains upon aging and
neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's …
neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's …
A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia
Electroencephalographic (EEG) recordings generate an electrical map of the human brain
that are useful for clinical inspection of patients and in biomedical smart Internet-of-Things …
that are useful for clinical inspection of patients and in biomedical smart Internet-of-Things …
Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: recommendations of an expert panel
Abstract The Electrophysiology Professional Interest Area (EPIA) and Global Brain
Consortium endorsed recommendations on candidate electroencephalography (EEG) …
Consortium endorsed recommendations on candidate electroencephalography (EEG) …
What electrophysiology tells us about Alzheimer's disease: a window into the synchronization and connectivity of brain neurons
Electrophysiology provides a real-time readout of neural functions and network capability in
different brain states, on temporal (fractions of milliseconds) and spatial (micro, meso, and …
different brain states, on temporal (fractions of milliseconds) and spatial (micro, meso, and …
Combining EEG signal processing with supervised methods for Alzheimer's patients classification
Abstract Background Alzheimer's Disease (AD) is a neurodegenaritive disorder
characterized by a progressive dementia, for which actually no cure is known. An early …
characterized by a progressive dementia, for which actually no cure is known. An early …
Multivariate multi-scale permutation entropy for complexity analysis of Alzheimer's disease EEG
FC Morabito, D Labate, FL Foresta, A Bramanti… - Entropy, 2012 - mdpi.com
An original multivariate multi-scale methodology for assessing the complexity of
physiological signals is proposed. The technique is able to incorporate the simultaneous …
physiological signals is proposed. The technique is able to incorporate the simultaneous …
Diagnosis of Alzheimer's disease with Electroencephalography in a differential framework
N Houmani, F Vialatte, E Gallego-Jutglà, G Dreyfus… - PloS one, 2018 - journals.plos.org
This study addresses the problem of Alzheimer's disease (AD) diagnosis with
Electroencephalography (EEG). The use of EEG as a tool for AD diagnosis has been widely …
Electroencephalography (EEG). The use of EEG as a tool for AD diagnosis has been widely …
EEG microstate complexity for aiding early diagnosis of Alzheimer's disease
The dynamics of the resting brain exhibit transitions between a small number of discrete
networks, each remaining stable for tens to hundreds of milliseconds. These functional …
networks, each remaining stable for tens to hundreds of milliseconds. These functional …
Deep convolutional neural networks for classification of mild cognitive impaired and Alzheimer's disease patients from scalp EEG recordings
In spite of the worldwide financial and research efforts made, the pathophysiological
mechanism at the basis of Alzheimer's disease (AD) is still poorly understood. Previous …
mechanism at the basis of Alzheimer's disease (AD) is still poorly understood. Previous …