Friston is one of the most highly cited living scientists[11] and in 2016 was ranked No. 1 by Semantic Scholar in the list of top 10 most influential neuroscientists.[12]
Education
Karl Friston attended the Ellesmere Port Grammar School, later renamed Whitby Comprehensive, from 1970 to 1977. Friston studied natural sciences (physics and psychology) at the University of Cambridge in 1980, and completed his medical studies at King's College Hospital, London.[3]
Career
Friston subsequently qualified under the Oxford University Rotational Training Scheme in Psychiatry, and is now a professor of neuroscience at University College London.[13] He was a Wellcome Trust Principal Fellow and is currently Scientific Director of the Wellcome Trust Centre for Neuroimaging.[14] He also holds an honorary consultant post at the National Hospital for Neurology and Neurosurgery. He invented statistical parametric mapping: SPM is an international standard for analysing imaging data and rests on the general linear model and random field theory (developed with Keith Worsley). In 1994 his group developed voxel-based morphometry.[15] VBM detects differences in neuroanatomy and is used clinically and as a surrogate in genetic studies.
These technical contributions were motivated by schizophrenia research and theoretical studies of value-learning (with Gerry Edelman). In 1995, this work was formulated as the dysconnection hypothesis of schizophrenia (with Chris Frith). In 2003, he invented dynamic causal modelling (DCM), which is used to infer the architecture of distributed systems like the brain. Mathematical contributions include Variational Laplace[16] and Generalized filtering, which use variational Bayesian methods for time-series analysis. Friston is principally known for models of functional integration in the human brain and the principles that underlie neuronal interactions. His main contribution to theoretical neurobiology is a variational free energy principle[17] (Active inference in the Bayesian brain[18]). According to Google Scholar, Friston's h-index is 263.[2]
In 2024, Friston appeared on StarTalk, the podcast from Neil deGrasse Tyson.
Awards and achievements
In 1996, Friston received the first Young Investigators Award in Human Brain Mapping, and was elected a Fellow of the Academy of Medical Sciences (1999) in recognition of contributions to the bio-medical sciences. In 2000 he was President of the international Organization for Human Brain Mapping. In 2003 he was awarded the Minerva Golden Brain Award and was elected a Fellow of the Royal Society in 2006 and received a Collège de France Medal in 2008. His nomination for the Royal Society reads
Karl Friston pioneered and developed the single most powerful technique for analysing the results of brain imaging studies and unravelling the patterns of cortical activity and the relationship of different cortical areas to one another. Currently over 90% of papers published in brain imaging use his method (SPM or Statistical Parametric Mapping) and this approach is now finding more diverse applications, for example, in the analysis of EEG and MEG data. His method has revolutionised studies of the human brain and given us profound insights into its operations. None has had as major an influence as Friston on the development of human brain studies in the past twenty-five years.[1]
He became a Fellow of the Royal Society of Biology in 2012, received the Weldon Memorial Prize and Medal in 2013 for contributions to mathematical biology and was elected as a member of EMBO in 2014 and the Academia Europaea in 2015. He was the 2016 recipient of the Charles Branch Award for unparalleled breakthroughs in Brain Research and the Glass Brain Award from the Organization for Human Brain Mapping. He holds Honorary Doctorates from the universities of York, Zurich, Liège and Radboud University.
^ abc"FRISTON, Prof. Karl John". Who's Who 2014, A & C Black, an imprint of Bloomsbury Publishing plc, 2014; online edn, Oxford University Press.(subscription required)
^Wright, I.C. (1995). "A Voxel-Based Method for the Statistical Analysis of Gray and White Matter Density Applied to Schizophrenia". NeuroImage. 2 (4): 244–252. doi:10.1006/nimg.1995.1032. PMID9343609. S2CID45664559.