John Ashburner
Affiliations: | University College London, London, United Kingdom |
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Publications
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| Ing A, Sämann PG, Chu C, et al. (2019) Identification of neurobehavioural symptom groups based on shared brain mechanisms. Nature Human Behaviour |
| Callaghan MF, Lutti A, Ashburner J, et al. (2019) Example dataset for the hMRI toolbox. Data in Brief. 25: 104132 |
| Tabelow K, Balteau E, Ashburner J, et al. (2019) hMRI - A toolbox for quantitative MRI in neuroscience and clinical research. Neuroimage |
| Freund P, Thompson A, Curt A, et al. (2018) Author response: Progressive neurodegeneration following spinal cord injury: Implications for clinical trials. Neurology. 91: 985 |
| Ziegler G, Grabher P, Thompson A, et al. (2018) Progressive neurodegeneration following spinal cord injury: Implications for clinical trials. Neurology |
| Koush Y, Ashburner J, Prilepin E, et al. (2017) Real-time fMRI data for testing OpenNFT functionality. Data in Brief. 14: 344-347 |
| Koush Y, Ashburner J, Prilepin E, et al. (2017) OpenNFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis. Neuroimage |
| Ziegler G, Ridgway GR, Blakemore SJ, et al. (2016) Multivariate Dynamical Modelling of Structural Change during Development. Neuroimage |
| Freund P, Friston K, Thompson AJ, et al. (2016) Embodied neurology: an integrative framework for neurological disorders. Brain : a Journal of Neurology |
| Lorio S, Kherif F, Ruef A, et al. (2016) Neurobiological origin of spurious brain morphological changes: A quantitative MRI study. Human Brain Mapping |