Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks
KA Smitha, K Akhil Raja, KM Arun… - The …, 2017 - journals.sagepub.com
The inquisitiveness about what happens in the brain has been there since the beginning of
humankind. Functional magnetic resonance imaging is a prominent tool which helps in the …
humankind. Functional magnetic resonance imaging is a prominent tool which helps in the …
[HTML][HTML] Applications of generative adversarial networks in neuroimaging and clinical neuroscience
Generative adversarial networks (GANs) are one powerful type of deep learning models that
have been successfully utilized in numerous fields. They belong to the broader family of …
have been successfully utilized in numerous fields. They belong to the broader family of …
DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI
Background Resting state fMRI has emerged as a popular neuroimaging method for
automated recognition and classification of brain disorders. Attention Deficit Hyperactivity …
automated recognition and classification of brain disorders. Attention Deficit Hyperactivity …
BolT: Fused window transformers for fMRI time series analysis
Deep-learning models have enabled performance leaps in analysis of high-dimensional
functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for …
functional MRI (fMRI) data. Yet, many previous methods are suboptimally sensitive for …
Fusion of fMRI and non-imaging data for ADHD classification
Resting state fMRI has emerged as a popular neuroimaging method for automated
recognition and classification of different brain disorders. Attention Deficit Hyperactivity …
recognition and classification of different brain disorders. Attention Deficit Hyperactivity …
Differences in functional connectivity profiles as a predictor of response to anterior thalamic nucleus deep brain stimulation for epilepsy: a hypothesis for the …
EH Middlebrooks, SS Grewal, M Stead… - Neurosurgical …, 2018 - thejns.org
OBJECTIVE Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a
promising therapy for refractory epilepsy. Unfortunately, the variability in outcomes from ANT …
promising therapy for refractory epilepsy. Unfortunately, the variability in outcomes from ANT …
Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach
Purpose Functional magnetic resonance imaging (fMRI) in resting state can be used to
evaluate the functional organization of the human brain in the absence of any task or …
evaluate the functional organization of the human brain in the absence of any task or …
Visual analysis for evaluation of community detection algorithms
Networks are often used to model the structure of interactions between parts of a system.
One important characteristic of a network is the so-called network community structures that …
One important characteristic of a network is the so-called network community structures that …
DS-GCNs: connectome classification using dynamic spectral graph convolution networks with assistant task training
Functional connectivity (FC) matrices measure the regional interactions in the brain and
have been widely used in neurological brain disease classification. A brain network, also …
have been widely used in neurological brain disease classification. A brain network, also …
A novel knowledge distillation-based feature selection for the classification of ADHD
Attention Deficit Hyperactivity Disorder (ADHD) is a brain disorder with characteristics such
as lack of concentration, excessive fidgeting, outbursts of emotions, lack of patience …
as lack of concentration, excessive fidgeting, outbursts of emotions, lack of patience …