| osl-dynamics, a toolbox for modeling fast dynamic brain activity C Gohil, R Huang, E Roberts, MWJ van Es, AJ Quinn, D Vidaurre, ... Elife 12, RP91949, 2024 | 5 | 2024 |
| A generative model of electrophysiological brain responses to stimulation D Vidaurre Elife 12, RP87729, 2024 | | 2024 |
| Toward stability of dynamic FC estimates in neuroimaging and electrophysiology: Solutions and limits S Alonso, D Vidaurre Network Neuroscience 7 (4), 1389-1403, 2023 | 4 | 2023 |
| The Gaussian-Linear Hidden Markov model: a Python package D Vidaurre, NY Larsen, L Masaracchia, LRPT Ruijters, S Alonso, ... arXiv preprint arXiv:2312.07151, 2023 | | 2023 |
| Brain Network Dynamics Following Induced Acute Stress: A Neural Marker of Psychological Vulnerability to Real-Life Chronic Stress A Segal, M Charquero-Ballester, S Vaisvaser, J Cabral, Z Ben-Zion, ... | | 2023 |
| A data-driven network decomposition of the temporal, spatial, and spectral dynamics underpinning visual-verbal working memory processes C Rossi, D Vidaurre, L Costers, F Akbarian, M Woolrich, G Nagels, ... Communications Biology 6 (1), 1079, 2023 | 7* | 2023 |
| Unraveling the milliseconds working memory network dynamics in MS: a magnetoencephalography study C Rossi, D Vidaurre, L Costers, F Akbarian, G Nagels, ... MULTIPLE SCLEROSIS JOURNAL 29, 322-322, 2023 | | 2023 |
| Dissecting unsupervised learning through hidden Markov modeling in electrophysiological data L Masaracchia, F Fredes, MW Woolrich, D Vidaurre Journal of Neurophysiology 130 (2), 364-379, 2023 | 4 | 2023 |
| A data-driven network description of the event-related waves in a working memory task: a magnetoencephalographic study. C Rossi, D Vidaurre, L Costers, F Akbarian, M Woolrich, G Nagels, ... Organization for Computational Neurosciences, 2023 | | 2023 |
| Dynamic functional connectivity: why the controversy? D Vidaurre arXiv preprint arXiv:2306.15485, 2023 | 2 | 2023 |
| Differential activity patterns in the upper and lower blade of the dentate gyrus F Fredes, L Masaracchia, M Capogna, D Vidaurre bioRxiv, 2023.06. 07.544044, 2023 | | 2023 |
| Predicting individual traits from models of brain dynamics accurately and reliably using the Fisher kernel C Ahrends, M Woolrich, D Vidaurre Biorxiv, 2023.03. 02.530638, 2023 | 2 | 2023 |
| Dynamic Functional Connectivity C Ahrends, D Vidaurre arXiv preprint arXiv:2301.03408, 2023 | | 2023 |
| The task-evoked network dynamics underlying working memory in RR-MS: a magnetoencephalography study C Rossi, D Vidaurre, L Costers, MB D'Hooghe, F Akbarian, M D'Haeseleer, ... ECTRIMS 2023: MSMilan2023, 2023 | | 2023 |
| Impaired activation of the prefrontal executive network during working memory processing in multiple sclerosis C Rossi, D Vidaurre, L Costers, M D'hooghe, F Akbarian, M D'haeseleer, ... bioRxiv, 2023.12. 22.573051, 2023 | 1 | 2023 |
| Stacking models of brain dynamics improves prediction of subject traits in fMRI B Griffin, C Ahrends, F Alfaro-Almagro, M Woolrich, S Smith, D Vidaurre bioRxiv, 2023.11. 08.566196, 2023 | | 2023 |
| Predicting subject traits from brain spectral signatures: an application to brain ageing CG Jarne, B Griffin, D Vidaurre bioRxiv, 2023.11. 02.565261, 2023 | | 2023 |
| Spontaneous network transitions predict somatosensory perception A Sharma, J Lange, D Vidaurre, E Florin bioRxiv, 2023.10. 19.563130, 2023 | | 2023 |
| Large-scale cortical networks are organized in structured cycles MWJ van Es, C Higgins, C Gohil, AJ Quinn, D Vidaurre, MW Woolrich bioRxiv, 2023.07. 25.550338, 2023 | 1 | 2023 |
| The relationship between frequency content and representational dynamics in the decoding of neurophysiological data C Higgins, MWJ van Es, AJ Quinn, D Vidaurre, MW Woolrich NeuroImage 260, 119462, 2022 | 5 | 2022 |
Mark WoolrichHead of Analysis, OHBA, University of OxfordVerified email at ohba.ox.ac.uk
