Resting-state dynamic functional connectivity in major depressive disorder: a systematic review
As a novel measure, dynamic functional connectivity (dFC) provides insight into the dynamic
nature of brain networks and their interactions in resting-state, surpassing traditional static …
nature of brain networks and their interactions in resting-state, surpassing traditional static …
Crosstalk between depression and dementia with resting-state fMRI studies and its relationship with cognitive functioning
Alzheimer's disease (AD) is the most common type of dementia, and depression is a risk
factor for develo** AD. Epidemiological studies provide a clinical correlation between late …
factor for develo** AD. Epidemiological studies provide a clinical correlation between late …
Resting state connectivity differences in eyes open versus eyes closed conditions
Functional magnetic resonance imaging data are commonly collected during the resting
state. Resting state functional magnetic resonance imaging (rs‐fMRI) is very practical and …
state. Resting state functional magnetic resonance imaging (rs‐fMRI) is very practical and …
[HTML][HTML] Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent …
J Teeuw, RM Brouwer, JP Guimarães, P Brandner… - NeuroImage, 2019 - Elsevier
The human brain is active during rest and hierarchically organized into intrinsic functional
networks. These functional networks are largely established early in development, with …
networks. These functional networks are largely established early in development, with …
[HTML][HTML] Functional topography of the thalamo-cortical system during development and its relation to cognition
The thalamus has complex connections with the cortex and is involved in various cognitive
processes. However, little is known about the age-related changes of thalamo-cortical …
processes. However, little is known about the age-related changes of thalamo-cortical …
Fused sparse network learning for longitudinal analysis of mild cognitive impairment
Alzheimer's disease (AD) is a neurodegenerative disease with an irreversible and
progressive process. To understand the brain functions and identify the biomarkers of AD …
progressive process. To understand the brain functions and identify the biomarkers of AD …
The identification of Alzheimer's disease using functional connectivity between activity voxels in resting-state fMRI data
Background: Alzheimer's disease (AD) is a common neurodegenerative disease occurring
in the elderly population. The effective and accurate classification of AD symptoms by using …
in the elderly population. The effective and accurate classification of AD symptoms by using …
Multi-scale feature combination of brain functional network for eMCI classification
Z Jiao, Z **
Alzheimer's disease (AD) or another dementia. High prevalence will possibly be reduced if …
Alzheimer's disease (AD) or another dementia. High prevalence will possibly be reduced if …
Automated atrophy assessment for Alzheimer's disease diagnosis from brain MRI images
An inventive scheme for automated tissue segmentation and classification is offered in this
paper using Fast Discrete Wavelet Transform (DWT)/Band Expansion Process (BEP), Kernel …
paper using Fast Discrete Wavelet Transform (DWT)/Band Expansion Process (BEP), Kernel …
A novel joint brain network analysis using longitudinal Alzheimer's disease data
There is well-documented evidence of brain network differences between individuals with
Alzheimer's disease (AD) and healthy controls (HC). To date, imaging studies investigating …
Alzheimer's disease (AD) and healthy controls (HC). To date, imaging studies investigating …