AIMC Topic: Default Mode Network
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Neuroimaging and natural language processing-based classification of suicidal thoughts in major depressive disorder.
Translational psychiatry
Jul 4, 2024
Suicide is a growing public health problem around the world. The most important risk factor for suicide is underlying psychiatric illness, especially depression. Detailed classification of suicide in patients with depression can greatly enhance perso...
Alterations in dynamic regional homogeneity within default mode network in patients with thyroid-associated ophthalmopathy.
Neuroreport
Jun 1, 2024
Thyroid-associated ophthalmopathy (TAO) is a significant autoimmune eye disease known for causing exophthalmos and substantial optic nerve damage. Prior investigations have solely focused on static functional MRI (fMRI) scans of the brain in TAO pati...
The divided brain: Functional brain asymmetry underlying self-construal.
NeuroImage
Jul 9, 2021
Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical pri...
Predicting Parkinson's disease trajectory using clinical and neuroimaging baseline measures.
Parkinsonism & related disorders
Mar 7, 2021
INTRODUCTION: Predictive biomarkers of Parkinson's Disease progression are needed to expedite neuroprotective treatment development and facilitate prognoses for patients. This work uses measures derived from resting-state functional magnetic resonanc...
How hot is the hot zone? Computational modelling clarifies the role of parietal and frontoparietal connectivity during anaesthetic-induced loss of consciousness.
NeuroImage
Feb 9, 2021
In recent years, specific cortical networks have been proposed to be crucial for sustaining consciousness, including the posterior hot zone and frontoparietal resting state networks (RSN). Here, we computationally evaluate the relative contributions ...
More stringent criteria are needed for diagnosing internet gaming disorder: Evidence from regional brain features and whole-brain functional connectivity multivariate pattern analyses.
Journal of behavioral addictions
Oct 7, 2020
BACKGROUND: Internet gaming disorder (IGD) is included in the DSM-5 as a provisional diagnosis. Whether IGD should be regarded as a disorder and, if so, how it should be defined and thresholded have generated considerable debate.
Magnetic Resonance Imaging
Internet Addiction Disorder
Image Interpretation, Computer-Assisted
Default Mode Network
Pattern Recognition, Automated
Female
Humans
Connectome
Recreation
Multivariate Analysis
Young Adult
Machine Learning
Nerve Net
Adult
Diagnostic and Statistical Manual of Mental Disorders
Brain
Male
Video Games
Adolescent
Executive Function
Predicting individual improvement in schizophrenia symptom severity at 1-year follow-up: Comparison of connectomic, structural, and clinical predictors.
Human brain mapping
May 29, 2020
In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at bas...
Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.
Human brain mapping
May 4, 2020
Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to ...
Discriminating stress from rest based on resting-state connectivity of the human brain: A supervised machine learning study.
Human brain mapping
Apr 15, 2020
Acute stress induces large-scale neural reorganization with relevance to stress-related psychopathology. Here, we applied a novel supervised machine learning method, combining the strengths of a priori theoretical insights with a data-driven approach...
Test-retest reliability of spatial patterns from resting-state functional MRI using the restricted Boltzmann machine and hierarchically organized spatial patterns from the deep belief network.
Journal of neuroscience methods
Oct 15, 2019
BACKGROUND: Restricted Boltzmann machines (RBMs), including greedy layer-wise trained RBMs as part of a deep belief network (DBN), have the ability to identify spatial patterns (SPs; functional networks) in resting-state fMRI (rfMRI) data. However, t...
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