Karl Friston

Karl Friston

Karl Friston is a theoretical neuroscientist and authority on brain imaging. He invented statistical parametric mapping (SPM), voxel-based morphometry (VBM) and dynamic causal modelling (DCM). These contributions were motivated by schizophrenia research and theoretical studies of value-learning, formulated as the dysconnection hypothesis of schizophrenia. Mathematical contributions include variational Laplacian procedures and generalized filtering for hierarchical Bayesian model inversion. 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 free-energy principle for action and perception (active inference).

Collaborative publications

I had the chance to visit the theoretical group of Karl Friston at Wellcome Trust Centre for Neuroimaging (University College London) from November 2010 to February 2012. This led to a collaboration on modelling eye movements using active inference Friston et al, 2012 in persons with or without schizophrenia Adams et al, 2012. Notably, we established a model accounting for sensory-motor delays Perrinet et al, 2014.

**This schematic shows the dependencies among various quantities that are assumed when modeling the exchanges of a self organizing system like the brain with the environment.** The top panel describes the states of the environment and the system or agent in terms of a probabilistic dependency graph, where connections denote directed dependencies. The quantities are described within the nodes of this graph with exemplar forms for their dependencies on other variables (see main text). Here, hidden and internal states are separated by action and sensory states. Both action and internal states encoding a conditional density minimize free energy, while internal states encoding prior beliefs maximize salience. Both free energy and salience are defined in terms of a generative model that is shown as fictive dependency graph in the lower panel. Note that the variables in the real world and the form of their dynamics are different from that assumed by the generative model; this is why external states are in bold. Furthermore, note that action is a state in the model of the brain but is replaced by hidden controls in the brain’s model of its world. This means that the agent is not aware of action but has beliefs about hidden causes in the world that action can fulfill through minimizing free energy. These beliefs correspond to prior expectations that sensory states will be sampled in a way that optimizes conditional confidence or salience.
This schematic shows the dependencies among various quantities that are assumed when modeling the exchanges of a self organizing system like the brain with the environment. The top panel describes the states of the environment and the system or agent in terms of a probabilistic dependency graph, where connections denote directed dependencies. The quantities are described within the nodes of this graph with exemplar forms for their dependencies on other variables (see main text). Here, hidden and internal states are separated by action and sensory states. Both action and internal states encoding a conditional density minimize free energy, while internal states encoding prior beliefs maximize salience. Both free energy and salience are defined in terms of a generative model that is shown as fictive dependency graph in the lower panel. Note that the variables in the real world and the form of their dynamics are different from that assumed by the generative model; this is why external states are in bold. Furthermore, note that action is a state in the model of the brain but is replaced by hidden controls in the brain’s model of its world. This means that the agent is not aware of action but has beliefs about hidden causes in the world that action can fulfill through minimizing free energy. These beliefs correspond to prior expectations that sensory states will be sampled in a way that optimizes conditional confidence or salience.

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