2022 - Research.com Best Scientist Award
2022 - Research.com Neuroscience in United Kingdom Leader Award
2015 - Member of Academia Europaea
2006 - Fellow of the Royal Society, United Kingdom
2003 - Golden Brain Award, Minerva Foundation
Member of the European Molecular Biology Organization (EMBO)
Fellow of The Academy of Medical Sciences, United Kingdom
His primary scientific interests are in Neuroscience, Artificial intelligence, Inference, Brain mapping and Functional magnetic resonance imaging. Many of his studies on Neuroscience apply to Cerebral blood flow as well. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Pattern recognition.
Karl J. Friston studied Inference and Perception that intersect with Cognitive psychology. The Brain mapping study which covers Neuroimaging that intersects with Functional integration. The concepts of his Functional magnetic resonance imaging study are interwoven with issues in Functional imaging, Visual cortex and Electroencephalography.
Karl J. Friston mainly focuses on Neuroscience, Artificial intelligence, Inference, Cognitive psychology and Bayesian inference. Functional magnetic resonance imaging, Brain mapping, Electroencephalography, Visual cortex and Cognition are subfields of Neuroscience in which his conducts study. Karl J. Friston combines topics linked to Prefrontal cortex with his work on Functional magnetic resonance imaging.
His research investigates the connection with Artificial intelligence and areas like Dynamic causal modelling which intersect with concerns in Causal model. His research in Inference focuses on subjects like Perception, which are connected to Sensory system. His biological study spans a wide range of topics, including Context and Prior probability.
His primary areas of study are Inference, Neuroscience, Dynamic causal modelling, Cognitive science and Bayesian inference. His study on Inference is covered under Artificial intelligence. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, State space and Pattern recognition.
He works mostly in the field of Dynamic causal modelling, limiting it down to topics relating to Causal model and, in certain cases, Time series. Karl J. Friston interconnects Consciousness, Cognition and Embodied cognition in the investigation of issues within Cognitive science. The various areas that he examines in his Bayesian inference study include Mortality rate and Prior probability.
Karl J. Friston focuses on Inference, Cognitive psychology, Cognitive science, Neuroscience and Artificial intelligence. His research integrates issues of Perception, Cognition, Bayesian probability, Bayesian inference and Generative grammar in his study of Inference. His Bayes' theorem study in the realm of Bayesian probability interacts with subjects such as Information geometry.
His Cognitive psychology research includes themes of Computational neuroscience, Salient, Metacognition and Conceptualization. His research in the fields of Externalism overlaps with other disciplines such as Message passing. In his work, Parametric statistics is strongly intertwined with Machine learning, which is a subfield of Artificial intelligence.
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Statistical parametric maps in functional imaging: A general linear approach
K. J. Friston;A. P. Holmes;K. J. Worsley;J.-P. Poline.
Human Brain Mapping (1994)
Voxel-Based Morphometry—The Methods
John Ashburner;Karl J. Friston.
A voxel-based morphometric study of ageing in 465 normal adult human brains.
Catriona D. Good;Ingrid S. Johnsrude;John Ashburner;Richard N.A. Henson;Richard N.A. Henson.
The free-energy principle: a unified brain theory?
Karl J. Friston.
Nature Reviews Neuroscience (2010)
Dynamic causal modelling.
Karl J. Friston;Lee M. Harrison;William D. Penny.
Spatial registration and normalization of images
Karl. J. Friston;J. Ashburner;C. D. Frith;J.-B. Poline.
Human Brain Mapping (1995)
Statistical Parametric Mapping: The Analysis of Functional Brain Images
W Penny;K Friston;J Ashburner;S Kiebel.
A theory of cortical responses
Philosophical Transactions of the Royal Society B (2005)
Psychophysiological and modulatory interactions in neuroimaging.
K. J. Friston;C. Buechel;G. R. Fink;J. Morris.
A unified statistical approach for determining significant signals in images of cerebral activation.
K. J. Worsley;S. Marrett;P. Neelin;A. C. Vandal.
Human Brain Mapping (1996)
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