Research summary
Statistical parametric mapping was generalized within a single linear-model framework that accommodates most experimental layouts, unifying ANCOVA, correlation coefficients and t-tests as special cases of a general linear model for testing regionally specific effects in neuroimaging data [1]. A theory of cortical responses framed evoked brain activity as inference about the causes of changes in sensory input, expressing Helmholtz's perception ideas in modern statistical terms to derive a model of perceptual inference and learning consistent with a broad range of neurobiological findings [2]. A method to model and remove subject-motion-related effects from fMRI time-series addressed residual artifacts present even after perfect realignment, dividing them into position-dependent and history-dependent components that depend on prior spin excitation in a small volume [3]. A general nonlinear spatial normalization technique simultaneously and explicitly solves for spatial and intensity transformations by least-squares minimization between two images using linearizing devices, applicable in any dimensionality and operating noninteractively and noniteratively [4]. A book on Statistical Parametric Mapping consolidated the conceptual and computational framework for analyzing functional brain images across modalities from fMRI to MEG, providing a unified methodology for understanding functional architecture and dynamics [5].
Recent publications
- Statistical parametric maps in functional imaging: A general linear approachDOI
- Voxel-Based Morphometry鈥擳he MethodsDOI
- The free-energy principle: a unified brain theory?DOI
- Unified segmentationDOI
- A theory of cortical responsesDOI
- Dynamic causal modellingDOI
- A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human BrainsDOI
- Movement鈥怰elated effects in fMRI time鈥恠eriesDOI
- Spatial registration and normalization of imagesDOI
- Statistical Parametric Mapping: The Analysis of Functional Brain Images
The lab page does not clearly state student acceptance status. Email the professor directly to confirm.
How to apply
Email Karl Friston 6-12 months before your application deadline. Read several recent papers and reference specific work in your message. Use our how to email a Japanese professor guide for the proven email structure.
For applications via MEXT scholarship: see our MEXT 2027 complete guide and university-specific University Recommendation track.
External profiles
- ORCID: https://orcid.org/0000-0001-7984-8909
- OpenAlex: openalex.org
Profile compiled from public sources (Researchmap, OpenAlex, Nagoya University faculty directory). Last refreshed 2026-05. Report incorrect information.