Frequency-Dependent Relationship Between Resting-State fMRI and Glucose Metabolism in the Elderly [PDF]
Frontiers in Neurology, 2019 Both glucose metabolism and resting-state fMRI (RS-fMRI) signal reflect hemodynamic features. The objective of this study was to investigate their relationship in the resting-state in healthy elderly participants (n = 18).
Fangyang Jiao +16 more
doaj +3 more sources
Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRI [PDF]
, 2023 Proceedings of the 2023 International Conference on Neural Information Processing (ICONIP)
Xiatian Zhang 0001 +6 more
core +5 more sources
Seizure-onset zone lateralization in temporal lobe epilepsy using 7T rs-fMRI: Direct comparison with 3T rs-fMRI. [PDF]
EpilepsiaAbstractObjectiveResting‐state functional magnetic resonance imaging (rs‐fMRI) at ultra‐high field strengths (≥7T) is known to provide superior signal‐to‐noise to comparable acquisitions at lower field strengths. In this study, we provide a direct comparison of the seizure onset‐zone (SOZ) lateralizing ability of 7T rs‐fMRI and 3T rs‐fMRI.MethodsWe ...
Lucas A +8 more
europepmc +3 more sources
Depression in multiple sclerosis: RS-FMRI research [PDF]
European Psychiatry, 2021 Introduction Multiple sclerosis (MS) is a demyelinating and neurodegenerative disorder of the CNS, which incapacitates people of working age. Due to progressive disability, the quality of life decreases, adding a number of other diseases to the main one.
A. Temniy +5 more
openaire +2 more sources
The Application of rs-fMRI in Vascular Cognitive Impairment [PDF]
Frontiers in Neurology, 2020 The incidence of vascular cognitive impairment (VCI) has been increasing for years and has become a major disabling factor in middle-aged and elderly populations. The pathogenesis of VCI is unclear, and there are no standard diagnostic criteria. Resting-state functional magnetic resonance imaging (rs-fMRI) can be used to detect spontaneous brain ...
Ran Wang +7 more
openaire +3 more sources
Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures [PDF]
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021 We propose to apply non-linear representation learning to voxelwise rs-fMRI data. Learning the non-linear representations is done using a variational autoencoder (VAE). The VAE is trained on voxelwise rs-fMRI data and performs non-linear dimensionality reduction that retains meaningful information.
Eloy Geenjaar +2 more
openaire +2 more sources
Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy regression [PDF]
, 2022 Nowadays, many people worldwide suffer from brain disorders, and their health is in danger. So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and attention deficit hyperactivity disorder (ADHD), among which functional ...
Shoeibi, Afshin +11 more
core +1 more source
Simultaneous DTI and rs-fMRI using the navigated diffusion sequence [PDF]
, 2016 Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) experiments are normally performed separately. The idea of extracting inherently co-registered activation/connectivity maps and diffusion parameters has resulted in efforts to develop methods for simultaneous fMRI and DTI data ...
Mofya, Mwape
core +3 more sources
Bayesian recurrent state space model for rs-fMRI
CoRR, 2020 Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended ...
Arunesh Mittal +3 more
openaire +2 more sources
rs-fMRI of a healthy volunteer.
, 2021 Three-dimensional MNI surface renders and mean T1 weighted image of rs-fMRI.
Hasyma Abu Hassan (11462539) +10 more
core +1 more source