2 citations · 4 across the 3 of their papers we have counts for
6 papers
Functional2Structural: Cross-Modality Brain Networks Representation Learning
Haoteng Tang, Xiyao Fu, Lei Guo +7
MRI-based modeling of brain networks has been widely used to understand functional and structural interactions and connections among brain regions, and factors that affect them, su…
TempoCave: Visualizing Dynamic Connectome Datasets to Support Cognitive Behavioral Therapy
Ran Xu, Manu Mathew Thomas, Alex Leow +2
We introduce TempoCave, a novel visualization application for analyzing dynamic brain networks, or connectomes. TempoCave provides a range of functionality to explore metrics relat…
EEG Classification by factoring in Sensor Configuration
Lubna Shibly Mokatren, Rashid Ansari, Ahmet Enis Cetin +4
Electroencephalography (EEG) serves as an effective diagnostic tool for mental disorders and neurological abnormalities. Enhanced analysis and classification of EEG signals can hel…
EEG Classification based on Image Configuration in Social Anxiety Disorder
Lubna Shibly Mokatren, Rashid Ansari, Ahmet Enis Cetin +4
The problem of detecting the presence of Social Anxiety Disorder (SAD) using Electroencephalography (EEG) for classification has seen limited study and is addressed with a new appr…
Sex-by-age differences in the resting-state brain connectivity
Sean D. Conrin, Liang Zhan, Zachery D. Morrissey +6
Recently we developed a novel method for assessing the hierarchical modularity of functional brain networks - the probability associated community estimation(PACE). The PACE algori…
Exploring the Human Connectome Topology in Group Studies
Johnson J. G. Keiriz, Liang Zhan, Morris Chukhman +3
Visually comparing brain networks, or connectomes, is an essential task in the field of neuroscience. Especially relevant to the field of clinical neuroscience, group studies that…