Karl J. Friston

Karl Friston
Born Karl John Friston
(1959-07-12) 12 July 1959[1]
York, UK
Nationality British
Fields Neuroscience
Institutions University College London[2]
Patrons Gonville & Caius College, Cambridge (BA, 1980)
Known for Statistical parametric mapping, Voxel-based morphometry, Dynamic causal modelling, Free energy principle
Notable awards
Spouse Ann Elisabeth Leonard[1]
Website
www.fil.ion.ucl.ac.uk/~karl

Karl John Friston FRS, FMedSci, FSB, is a British neuroscientist and authority on brain imaging.[2][4][5][6][7][8][9][10]

Education

Karl Friston studied Natural Sciences (physics and psychology) at the University of Cambridge and went on to complete his medical studies at King's College Hospital, London.[1]

Career

Friston subsequently qualified under the Oxford University Rotational Training Scheme in Psychiatry, and is now a Professor of Neuroscience at University College London.[11] He is currently a Wellcome Trust Principal Fellow and Scientific Director of the Wellcome Trust Centre for Neuroimaging.[12][13] 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. 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 disconnection hypothesis of schizophrenia (with Chris Frith).[14] 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 (generalised) filtering and dynamic expectation maximization (DEM), which are Variational Bayesian methods for time-series analysis. Friston currently works on 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 (active inference in the Bayesian brain). According to Google Scholar Karl Friston's h-index is 186.[2]

Awards and honours

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. In 2011 he received an Honorary Doctorate from the University of York and became a Fellow of the Society of Biology. 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 revolutionized 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.[3] ”

References

  1. 1 2 3 "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)
  2. 1 2 3 's publications indexed by Google Scholar, a service provided by Google
  3. 1 2 "EC/2006/16: Friston, Karl John". London: The Royal Society. Archived from the original on 2014-07-19.
  4. ↑ Friston, K (2003). "Learning and inference in the brain". Neural Networks 16 (9): 1325–52. doi:10.1016/j.neunet.2003.06.005. PMID 14622888.
  5. ↑ Friston, K (2002). "Functional integration and inference in the brain". Progress in neurobiology 68 (2): 113–43. doi:10.1016/s0301-0082(02)00076-x. PMID 12450490.
  6. ↑ Friston, K (2005). "A theory of cortical responses". Philosophical Transactions of the Royal Society B: Biological Sciences 360 (1456): 815–36. doi:10.1098/rstb.2005.1622. PMC 1569488. PMID 15937014.
  7. ↑ Karl J. Friston's publications indexed by the Scopus bibliographic database, a service provided by Elsevier.
  8. ↑ Penny, W; Ghahramani, Z; Friston, K (2005). "Bilinear dynamical systems". Philosophical transactions of the Royal Society of London. Series B, Biological sciences 360 (1457): 983–93. doi:10.1098/rstb.2005.1642. PMC 1854926. PMID 16087442.
  9. ↑ Harrison, L. M.; David, O; Friston, K. J. (2005). "Stochastic models of neuronal dynamics". Philosophical transactions of the Royal Society of London. Series B, Biological sciences 360 (1457): 1075–91. doi:10.1098/rstb.2005.1648. PMC 1854931. PMID 16087449.
  10. ↑ David, O; Harrison, L; Friston, K. J. (2005). "Modelling event-related responses in the brain". NeuroImage 25 (3): 756–70. doi:10.1016/j.neuroimage.2004.12.030. PMID 15808977.
  11. ↑ "Iris View Profile". Iris.ucl.ac.uk. Retrieved 2014-07-20.
  12. ↑ "Professor Karl Friston – Selected papers".
  13. ↑ Brown, Harriet (2012). "Free-Energy and Illusions: The Cornsweet Effect". Frontiers in Psychology 3. doi:10.3389/fpsyg.2012.00043.
  14. ↑ 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.

External links

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