Decoding task-based fMRI data with graph neural networks, considering individual differences

M Saeidi, W Karwowski, FV Farahani, K Fiok… - Brain Sciences, 2022 - mdpi.com
Task fMRI provides an opportunity to analyze the working mechanisms of the human brain
during specific experimental paradigms. Deep learning models have increasingly been …

Multitask fMRI data classification via group-wise hybrid temporal and spatial sparse representations

L Song, Y Ren, Y Hou, X He, H Liu - Eneuro, 2022 - eneuro.org
Task-based functional magnetic resonance imaging (tfMRI) has been widely used to induce
functional brain activities corresponding to various cognitive tasks. A relatively under …

Static and Dynamic Connectivity Analysis of Human Brain via Functional Magnetic Resonance Imaging

B Sen - 2020 - search.proquest.com
Functional connectivity of brain refers to statistical dependence of brain functions among
often remote neuronal units. This thesis addresses two novel ways to analyse brain …

Calculation of Sub-bands {1, 2, 5, 6} for 64-Point Complex FFT and Its extension to N (= 2^ N) Point FFT

B Sen - arXiv preprint arXiv:2203.01529, 2022 - arxiv.org
FFT algorithm is one of the most applied algorithmsin digital signal processing. Digital signal
processing hasgradually become important in biomedical application. Herehardware …

Decoding Task-Based fMRI Data Using Graph Neural Networks, Considering Individual Differences

M Saeidi - 2022 - stars.library.ucf.edu
Functional magnetic resonance imaging (fMRI) is a non-invasive technology that provides
high spatial resolution in determining the human brain's responses and measures regional …