Disambiguations:
Karl J. Friston [15]Karl Friston [6]
  1. Jakob Hohwy, Andreas Roepstorff & Karl Friston (2008). Predictive Coding Explains Binocular Rivalry: An Epistemological Review. Cognition 108 (3):687-701.
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  2.  34
    P. Read Montague, Raymond J. Dolan, Karl J. Friston & Peter Dayan (2012). Computational Psychiatry. Trends in Cognitive Sciences 16 (1):72-80.
  3.  16
    Karl Friston (2013). Active Inference and Free Energy. Behavioral and Brain Sciences 36 (3):212-213.
    Why do brains have so many connections? The principles exposed by Andy Clark provide answers to questions like this by appealing to the notion that brains distil causal regularities in the sensorium and embody them in models of their world. For example, connections embody the fact that causes have particular consequences. This commentary considers the imperatives for this form of embodiment.
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  4.  71
    Karl J. Friston & Klaas E. Stephan (2007). Free-Energy and the Brain. Synthese 159 (3):417 - 458.
    If one formulates Helmholtz's ideas about perception in terms of modern-day theories one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. Using constructs from statistical physics it can be shown that the problems of inferring what cause our sensory inputs and learning causal regularities in the sensorium can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on (...)
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  5.  34
    Rick A. Adams, Harriet R. Brown & Karl J. Friston (2015). Bayesian Inference, Predictive Coding and Delusions. Avant: Trends in Interdisciplinary Studies 3:51-88.
    This paper considers psychotic symptoms in terms of false inferences or beliefs. It is based on the notion that the brain is an organ of inference that actively constructs hypotheses to explain or predict its sensations. This perspective provides a normative account of action and perception that emphasises probabilistic representations; in particular, the confidence or precision of beliefs about the world. We consider sensory attenuation deficits, catatonia and delusions as various expressions of the same core pathology: namely, an aberrant encoding (...)
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  6.  7
    Karl J. Friston & Cathy J. Price (2003). Degeneracy and Redundancy in Cognitive Anatomy. Trends in Cognitive Sciences 7 (4):151-152.
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  7.  8
    Michael Moutoussis, Pasco Fearon, Wael El-Deredy, Raymond J. Dolan & Karl J. Friston (2014). Bayesian Inferences About the Self : A Review. Consciousness and Cognition 25 (1):67-76.
    Viewing the brain as an organ of approximate Bayesian inference can help us understand how it represents the self. We suggest that inferred representations of the self have a normative function: to predict and optimise the likely outcomes of social interactions. Technically, we cast this predict-and-optimise as maximising the chance of favourable outcomes through active inference. Here the utility of outcomes can be conceptualised as prior beliefs about final states. Actions based on interpersonal representations can therefore be understood as minimising (...)
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  8.  23
    Karl J. Friston (1998). Modes or Models: A Critique on Independent Component Analysis for fMRI. Trends in Cognitive Sciences 2 (10):373-375.
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  9.  6
    Karl J. Friston, Rebecca Lawson & Chris D. Frith (2013). On Hyperpriors and Hypopriors: Comment on Pellicano and Burr. Trends in Cognitive Sciences 17 (1):1.
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  10.  35
    Karl J. Friston (2005). Hallucinations and Perceptual Inference. Behavioral and Brain Sciences 28 (6):764-766.
    This commentary takes a closer look at how “constructive models of subjective perception,” referred to by Collerton et al. (sect. 2), might contribute to the Perception and Attention Deficit (PAD) model. It focuses on the neuronal mechanisms that could mediate hallucinations, or false inference – in particular, the role of cholinergic systems in encoding uncertainty in the context of hierarchical Bayesian models of perceptual inference (Friston 2002b; Yu & Dayan 2002).
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  11.  6
    Karl Friston & Christopher Frith (2015). A Duet for One. Consciousness and Cognition 36:390-405.
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  12.  6
    P. Read Montague, Raymond J. Dolan, Karl J. Friston & Peter Dayan (2012). Erratum: Computational Psychiatry. Trends in Cognitive Sciences 16 (5):306.
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  13.  14
    Frances Abell, Michael Krams, John Ashburner, Richard Passingham, Karl Friston, Richard Frackowiak, Francesca HappeÂ, Chris Frith & Uta FrithCA (1999). Cognitive Neuroscience NeuroReport. Cognition 10 (1647):1647-1651.
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  14.  3
    Giovanni Pezzulo, Laura Barca & Karl J. Friston (2015). Active Inference and Cognitive-Emotional Interactions in the Brain. Behavioral and Brain Sciences 38.
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  15.  16
    Karl J. Friston (2012). What Does Functional MRI Measure? Two Complementary Perspectives. Trends in Cognitive Sciences 16 (10):491-492.
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  16.  8
    Karl Friston (2010). Some Free-Energy Puzzles Resolved: Response to Thornton. Trends in Cognitive Sciences 14 (2):54-55.
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  17.  17
    Karl J. Friston (1999). Modularity, Segregation, and Interactions. Behavioral and Brain Sciences 22 (1):99-100.
    This commentary considers how far one can go in making inferences about functional modularity or segregation, based on the sorts of analyses used by Caplan & Waters in relation to the underlying neuronal infrastructure. Specifically, an attempt is made to relate the “functionalist” approach adopted in the target article to “neuroreductionist” perspectives on the same issue.
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  18.  14
    Michael Breakspear & Karl Friston (2001). Symmetries and Itineracy in Nonlinear Systems with Many Degrees of Freedom. Behavioral and Brain Sciences 24 (5):813-813.
    Tsuda examines the potential contribution of nonlinear dynamical systems, with many degrees of freedom, to understanding brain function. We offer suggestions concerning symmetry and transients to strengthen the physiological motivation and theoretical consistency of this novel research direction: Symmetry plays a fundamental role, theoretically and in relation to real brains. We also highlight a distinction between chaotic “transience” and “itineracy.”.
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  19.  1
    Christopher D. Frith & Karl J. Friston (1997). Studying Brain Function with Neuroimaging. In M. D. Rugg (ed.), Cognitive Neuroscience. MIT Press 169--195.
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  20.  1
    James M. Kilner & Karl J. Friston (2014). Relating the “Mirrorness” of Mirror Neurons to Their Origins. Behavioral and Brain Sciences 37 (2):207-208.
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  21. Wei Ji Ma, Josef Perner, Johannes Roessler, Karl J. Friston, Motomu Katsurakawa, Katsuyuki Sakai, Nathalie Tzourio-Mazoyer, Laure Zago, Martin M. Monti & Lawrence M. Parsons (2012). Forum: Science & Society 489 Brain Network: Social Media and the Cognitive Scientist. Trends in Cognitive Sciences 16:404-406.
     
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