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mini-mental-state-examination
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Multiclass classification of patients during different stages of Alzheimer's disease using fMRI time-series
, Article Biomedical Physics and Engineering Express ; Volume 6, Issue 5 , 2020 ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
IOP Publishing Ltd
2020
Abstract
Alzheimer's Disease (AD) begins several years before the symptoms develop. It starts with Mild Cognitive Impairment (MCI) which can be separated into Early MCI and Late MCI (EMCI and LMCI). Functional connectivity analysis and classification are done among the different stages of illness with Functional Magnetic Resonance Imaging (fMRI). In this study, in addition to the four stages including healthy, EMCI, LMCI, and AD, the patients have been tracked for a year. Indeed, the classification has been done among 7 groups to analyze the functional connectivity changes in one year in different stages. After generating the functional connectivity graphs for eliminating the weak links, three...
Deep sparse graph functional connectivity analysis in AD patients using fMRI data
, Article Computer Methods and Programs in Biomedicine ; Volume 201 , 2021 ; 01692607 (ISSN) ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
Elsevier Ireland Ltd
2021
Abstract
Functional magnetic resonance imaging (fMRI) is a non-invasive method that helps to analyze brain function based on BOLD signal fluctuations. Functional Connectivity (FC) catches the transient relationship between various brain regions usually measured by correlation analysis. The elements of the correlation matrix are between -1 to 1. Some of them are very small values usually related to weak and spurious correlations due to noises and artifacts. They can not be concluded as real strong correlations between brain regions and their existence could make a misconception and leads to fake results. It is crucial to make a conclusion based on reliable and informative correlations. In order to...
Deep sparse graph functional connectivity analysis in AD patients using fMRI data
, Article Computer Methods and Programs in Biomedicine ; Volume 201 , 2021 ; 01692607 (ISSN) ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
Elsevier Ireland Ltd
2021
Abstract
Functional magnetic resonance imaging (fMRI) is a non-invasive method that helps to analyze brain function based on BOLD signal fluctuations. Functional Connectivity (FC) catches the transient relationship between various brain regions usually measured by correlation analysis. The elements of the correlation matrix are between -1 to 1. Some of them are very small values usually related to weak and spurious correlations due to noises and artifacts. They can not be concluded as real strong correlations between brain regions and their existence could make a misconception and leads to fake results. It is crucial to make a conclusion based on reliable and informative correlations. In order to...
Apathy exacerbates postural control impairments in stroke survivors: The potential effects of cognitive dual-task for improving postural control
, Article Neuropsychologia ; Volume 174 , 2022 ; 00283932 (ISSN) ; Mehdizadeh, H ; Azad, A ; Cheraghifard, M ; Jamali, S ; Davoudi, M ; Shokouhyan, S. M ; Taghizadeh, G ; Sharif University of Technology
Elsevier Ltd
2022
Abstract
Apathy is a stressor and debilitating common condition for both stroke survivors and their caregivers. However, its effects on the postural control of these patients have not yet been investigated. Improved postural stability through withdrawing attention from postural control by concurrent cognitive task (i.e. dual-task condition) has been reported previously, but the effect of apathy, as a confounding factor, remains unknown. This study aimed to examine the effects of apathy and dual-task condition on postural control of chronic stroke survivors from biomechanical and neurophysiological perspectives. Twenty non-apathetic stroke survivors, 20 apathetic stroke survivors, and 20 sex-, age-,...
Behavior of olfactory-related frontal lobe oscillations in Alzheimer's disease and MCI: A pilot study
, Article International Journal of Psychophysiology ; Volume 175 , 2022 , Pages 43-53 ; 01678760 (ISSN) ; Aghajan, H ; Vahabi, Z ; Afzal, A ; Sedghizadeh, M. J ; Sharif University of Technology
Elsevier B.V
2022
Abstract
Slow-gamma (35-45 Hz) phase synchronization and the coupling between slow-gamma and low-frequency theta oscillations (4–8 Hz) are closely related to memory retrieval and cognitive functions. In this pilot study, we assess the Phase Amplitude Coupling (PAC) between theta and slow-gamma oscillatory bands and the quality of synchronization in slow-gamma oscillations using Phase Locking Value (PLV) on EEG data from healthy individuals and patients diagnosed with amnestic Mild Cognitive Impairment (aMCI) and Alzheimer's Disease (AD) during an oddball olfactory task. Our study indicates noticeable differences between the PLV and PAC values corresponding to olfactory stimulation in the three groups...