Karl J. Friston

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Karl Friston
Born
Karl John Friston

(1959-07-12) 12 July 1959 (age 61)[1]
York, England
NationalityBritish
Alma materGonville and Caius College, Cambridge (BA, 1980)
Known forStatistical parametric mapping, Voxel-based morphometry, Dynamic causal modelling, Free energy principle
Spouse(s)Ann Elisabeth Leonard[1]
Awards
Scientific career
FieldsNeuroscience
InstitutionsUniversity College London[3]
InfluencesGeoffrey Hinton[citation needed], Donald O. Hebb
Websitewww.fil.ion.ucl.ac.uk/~karl

Karl John Friston FRS, FMedSci, FRSB, is a British neuroscientist at University College London and an authority on brain imaging.[3][4][5][6][7][8][9][10]

Education[edit]

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.[1]

Career[edit]

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.[14] 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). 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 maximisation (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[15] (active inference in the Bayesian brain[16]). According to Google Scholar Karl Friston's h-index is 232.[3]

Awards and achievements[edit]

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 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.[2]

In 2016 he was ranked No. 1 by Semantic Scholar in the list of top 10 most influential neuroscientists.[17]

References[edit]

  1. ^ a b c "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. ^ a b "EC/2006/16: Friston, Karl John". London: The Royal Society. Archived from the original on 19 July 2014.
  3. ^ a b c Karl J. Friston publications indexed by Google Scholar
  4. ^ Friston, K (2003). "Learning and inference in the brain". Neural Networks. 16 (9): 1325–52. CiteSeerX 10.1.1.160.2313. 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. (subscription required)
  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. open access
  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". University College London. Retrieved 20 July 2014.
  12. ^ "Professor Karl Friston – Selected papers". Cite journal requires |journal= (help)
  13. ^ Brown, Harriet (2012). "Free-Energy and Illusions: The Cornsweet Effect". Frontiers in Psychology. 3: 43. doi:10.3389/fpsyg.2012.00043. PMC 3289982. PMID 22393327.
  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. PMID 9343609.
  15. ^ Raviv, Shaun (13 November 2018). "The Genius Neuroscientist Who Might Hold the Key to True AI". WIRED. Retrieved 16 November 2018.
  16. ^ Friston, Karl (2018). "Of woodlice and men: A Bayesian account of cognition, life and consciousness. An interview with Karl Friston (by Martin Fortier & Daniel Friedman)". ALIUS Bulletin. 2: 17–43.
  17. ^ Bohannon, John (11 November 2016). "A computer program just ranked the most influential brain scientists of the modern era". sciencemag.org. Retrieved 5 January 2017.

External links[edit]