563 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University College LondonGB37 papers
- National Hospital for Neurology and NeurosurgeryGB15 papers
- Newcastle UniversityGB10 papers
- Wellcome Centre for Human NeuroimagingGB8 papers
- King's College LondonGB4 papers
- Queen Mary University of LondonGB4 papers
- Harvard UniversityUS3 papers
- Imperial College LondonGB3 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Humboldt-Universität zu BerlinDE2 papers
- Max Planck Institute for Human Cognitive and Brain SciencesDE2 papers
- National Institute for Health and Care ResearchGB2 papers
5 papers · 1 filter
Reliability and comparability of human brain structural covariance networks
Jona Carmon, Jil Heege, Joe H Necus +5
Structural covariance analysis is a widely used structural MRI analysis method which characterises the co-relations of morphology between brain regions over a group of subjects. To…
Interictal intracranial EEG for predicting surgical success: the importance of space and time
Yujiang Wang, Nishant Sinha, Gabrielle M. Schroeder +8
Predicting post-operative seizure freedom using functional correlation networks derived from interictal intracranial EEG has shown some success. However, there are important challe…
Active inference: demystified and compared
Noor Sajid, Philip J. Ball, Thomas Parr +1
Active inference is a first principle account of how autonomous agents operate in dynamic, non-stationary environments. This problem is also considered in reinforcement learning (R…
Empirical Bayesian Mixture Models for Medical Image Translation
Mikael Brudfors, John Ashburner, Parashkev Nachev +1
Automatically generating one medical imaging modality from another is known as medical image translation, and has numerous interesting applications. This paper presents an interpre…
Grey matter sublayer thickness estimation in themouse cerebellum
Da Ma, Manuel J. Cardoso, Maria A. Zuluaga +7
The cerebellar grey matter morphology is an important feature to study neurodegenerative diseases such as Alzheimer's disease or Down's syndrome. Its volume or thickness is commonl…