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Hierarchical Models in the Brain

Friston, K; (2008) Hierarchical Models in the Brain. PLOS COMPUT BIOL , 4 (11) , Article e1000211. 10.1371/journal.pcbi.1000211. Green open access

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Abstract

This paper describes a general model that subsumes many parametric models for continuous data. The model comprises hidden layers of state-space or dynamic causal models, arranged so that the output of one provides input to another. The ensuing hierarchy furnishes a model for many types of data, of arbitrary complexity. Special cases range from the general linear model for static data to generalised convolution models, with system noise, for nonlinear time-series analysis. Crucially, all of these models can be inverted using exactly the same scheme, namely, dynamic expectation maximization. This means that a single model and optimisation scheme can be used to invert a wide range of models. We present the model and a brief review of its inversion to disclose the relationships among, apparently, diverse generative models of empirical data. We then show that this inversion can be formulated as a simple neural network and may provide a useful metaphor for inference and learning in the brain.

Type: Article
Title: Hierarchical Models in the Brain
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pcbi.1000211
Publisher version: http://dx.doi.org/10.1371/journal.pcbi.1000211
Language: English
Additional information: © 2008 Karl Friston. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by the Wellcome Trust.
Keywords: VISUAL-CORTEX, ATTENTIONAL MODULATION, CORTICAL CONNECTIONS, DIFFUSION-PROCESSES, MAXIMUM-LIKELIHOOD, BAYESIAN-INFERENCE, NEURAL MECHANISMS, DYNAMIC-SYSTEMS, FREE-ENERGY, PLASTICITY
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/128289
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