467 citations
- University College LondonGB27 papers
- King's College LondonGB7 papers
- Wellcome Centre for Human NeuroimagingGB6 papers
- Queen Mary University of LondonGB5 papers
- UCL Queen Square Institute of NeurologyGB5 papers
- Sorbonne UniversitéFR4 papers
- Wellcome / EPSRC Centre for Interventional and Surgical SciencesGB4 papers
- Assistance Publique – Hôpitaux de ParisFR3 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- InsermFR3 papers
- University of CambridgeGB3 papers
- Cambridge University Hospitals NHS Foundation TrustGB2 papers
28 papers
Parallelism in Neurodegenerative Biomarker Tests: Hidden Errors and the Risk of Misconduct
Axel Petzold, Joachim Pum, David P Crabb
Biomarkers are critical tools in the diagnosis and monitoring of neurodegenerative diseases. Reliable quantification depends on assay validity, especially the demonstration of para…
Dissociating model architectures from inference computations
Noor Sajid, Johan Medrano
Parr et al., 2025 examines how auto-regressive and deep temporal models differ in their treatment of non-Markovian sequence modelling. Building on this, we highlight the need for d…
KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation
L Cif, D Demailly, JP Lin +112
Heterozygous mutations in KMT2B are associated with an early-onset, progressive, and often complex dystonia (DYT28). Key characteristics of typical disease include focal motor feat…
VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI
James K Ruffle, Samia Mohinta, Kelly Pegoretti Baruteau +5
The VASARI MRI feature set is a quantitative system designed to standardise glioma imaging descriptions. Though effective, deriving VASARI is time-consuming and seldom used in clin…
Bayesian sparsification for deep neural networks with Bayesian model reduction
Dimitrije Marković, Karl J. Friston, Stefan J. Kiebel
Deep learning's immense capabilities are often constrained by the complexity of its models, leading to an increasing demand for effective sparsification techniques. Bayesian sparsi…
Compressed representation of brain genetic transcription
James K Ruffle, Henry Watkins, Robert J Gray +3
The architecture of the brain is too complex to be intuitively surveyable without the use of compressed representations that project its variation into a compact, navigable space.…