Professor STAMATIOS SOTIROPOULOS's Outputs (4)

Denoising Diffusion MRI: Considerations and implications for analysis (2023)
Journal Article
Manzano-Patron, J.-P., Moeller, S., Andersson, J. L. R., Ugurbil, K., Yacoub, E., & Sotiropoulos, S. N. (2024). Denoising Diffusion MRI: Considerations and implications for analysis. Imaging Neuroscience, 2, 1-29. https://doi.org/10.1101/2023.07.24.550348

Development of diffusion MRI (dMRI) denoising approaches has experienced considerable growth over the last years. As noise can inherently reduce accuracy and precision in measurements, its effects have been well characterised both in terms of uncerta... Read More about Denoising Diffusion MRI: Considerations and implications for analysis.

A resource for development and comparison of multimodal brain 3T MRI harmonisation approaches (2023)
Journal Article
Warrington, S., Ntata, A., Mougin, O., Campbell, J., Torchi, A., Craig, M., Alfaro-Almagro, F., Miller, K. L., Morgan, P. S., Jenkinson, M., & Sotiropoulos, S. N. (2023). A resource for development and comparison of multimodal brain 3T MRI harmonisation approaches. Imaging Neuroscience, 1(2023), 1-27. https://doi.org/10.1162/imag_a_00042

Despite the huge potential of magnetic resonance imaging (MRI) in mapping and exploring the brain, MRI measures can often be limited in their consistency, reproducibility and accuracy which subsequently restricts their quantifiability. Nuisance nonbi... Read More about A resource for development and comparison of multimodal brain 3T MRI harmonisation approaches.

Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data (2023)
Journal Article
Tewarie, P. K., Hindriks, R., Lai, Y. M., Sotiropoulos, S. N., Kringelbach, M., & Deco, G. (2023). Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data. NeuroImage, 276, Article 120186. https://doi.org/10.1016/j.neuroimage.2023.120186

Characterising brain states during tasks is common practice for many neuroscientific experiments using electrophysiological modalities such as electroencephalography (EEG) and magnetoencephalography (MEG). Brain states are often described in terms of... Read More about Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data.

QuNex – An Integrative Platform for Reproducible Neuroimaging Analytics (2023)
Journal Article
Ji, J. L., Demšar, J., Fonteneau, C., Tamayo, Z., Pan, L., Kraljič, A., Matkovič, A., Purg, N., Helmer, M., Warrington, S., Winkler, A., Zerbi, V., Coalson, T. S., Glasser, M. F., Harms, M. P., Sotiropoulos, S. N., Murray, J. D., Anticevic, A., & Repovš, G. (2023). QuNex – An Integrative Platform for Reproducible Neuroimaging Analytics. Frontiers in Neuroinformatics, 17, Article 1104508. https://doi.org/10.1101/2022.06.03.494750

Introduction: Neuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces chall... Read More about QuNex – An Integrative Platform for Reproducible Neuroimaging Analytics.