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Karl J. Friston [20]Karl Friston [8]
  1. Thomas H. B. FitzGerald, Raymond J. Dolan & Karl J. Friston (2014). Model Averaging, Optimal Inference, and Habit Formation. Frontiers in Human Neuroscience 8.
  2. Rebecca P. Lawson, Geraint Rees & Karl J. Friston (2014). An Aberrant Precision Account of Autism. Frontiers in Human Neuroscience 8.
  3. Michael Moutoussis, Pasco Fearon, Wael El-Deredy, Raymond J. Dolan & Karl J. Friston (2014). Bayesian Inferences About the Self (and Others): A Review. Consciousness and Cognition 25:67-76.
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  4. Harriet R. Brown & Karl J. Friston (2013). The Functional Anatomy of Attention: A DCM Study. Frontiers in Human Neuroscience 7:784.
    Recent formulations of attention – in terms of predictive coding – associate attentional gain with the expected precision of sensory information. Formal models of the Posner paradigm suggest that validity effects can be explained in a principled (Bayes optimal) fashion in terms of a cue-dependent setting of precision or gain on the sensory channels reporting anticipated target locations, which is subsequently updated by invalid targets. This normative model is equipped with a biologically plausible process theory in the form of predictive (...)
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  5. Vincenzo G. Fiore, Valerio Sperati, Francesco Mannella, Marco Mirolli, Kevin Gurney, Karl Friston, Raymond J. Dolan & Gianluca Baldassarre (2013). Keep Focussing: Striatal Dopamine Multiple Functions Resolved in a Single Mechanism Tested in a Simulated Humanoid Robot. Frontiers in Psychology 4:864.
    The effects of striatal dopamine on behaviour have been widely investigated over the past decades, with “phasic” burst firings considered as the key expression of a reward prediction error responsible for reinforcement learning. Less well studied is tonic dopamine, where putative functions include the idea that it is a regulator of vigour, incentive salience, disposition to exert an effort and a modulator of approach strategies. We present a model combining tonic and phasic dopamine to show how different outflows triggered by (...)
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  6. 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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  7. 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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  8. Harriet Brown & Karl J. Friston (2012). Free-Energy and Illusions: The Cornsweet Effect. Frontiers in Psychology 3.
    In this paper, we review the nature of illusions using the free-energy formulation of Bayesian perception. We reiterate the notion that illusory percepts are, in fact, Bayes-optimal and represent the most likely explanation for ambiguous sensory input. This point is illustrated using perhaps the simplest of visual illusions; namely, the Cornsweet effect. By using plausible prior beliefs about the spatial gradients of luminance and reflectance in the visual world, we show that the Cornsweet effect emerges as a natural consequence of (...)
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  9. Karl J. Friston (2012). What Does Functional MRI Measure? Two Complementary Perspectives. Trends in Cognitive Sciences 16 (10):491-492.
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  10. Karl Friston, Rick A. Adams, Laurent Perrinet & Michael Breakspear (2012). Perceptions as Hypotheses: Saccades as Experiments. Frontiers in Psychology 3 (151).
    If perception corresponds to hypothesis testing (Gregory, 1980); then visual searches might be construed as experiments that generate sensory data. In this work, we explore the idea that saccadic eye movements are optimal experiments, in which data are gathered to test hypotheses or beliefs about how those data are caused. This provides a plausible model of visual search that can be motivated from the basic principles of self-organised behaviour: namely, the imperative to minimise the entropy of hidden states of the (...)
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  11. Baojuan Li, Xiang Wang, Shuqiao Yao, Dewen Hu & Karl Friston (2012). Task-Dependent Modulation of Effective Connectivity Within the Default Mode Network. Frontiers in Psychology 3.
    The default mode network (DMN) has recently attracted widespread interest. Previous studies have found that task-related processing can induce deactivation and changes in the functional connectivity of this network. However, it remains unclear how tasks modulate the underlying effective connectivity within the DMN. Using recent advances in dynamic causal modeling (DCM), we investigated the modulatory effect of (gender judgment) task performance on directed connectivity within the DMN. Sixteen healthy subjects were scanned twice: at rest and while performing a gender judgment (...)
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  12. 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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  13. P. Read Montague, Raymond J. Dolan, Karl J. Friston & Peter Dayan (2012). Computational Psychiatry. Trends in Cognitive Sciences 16 (1):72-80.
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  14. 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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  15. Harriet Brown, Karl J. Friston & Sven Bestmann (2011). Active Inference, Attention, and Motor Preparation. Frontiers in Psychology 2:218.
    Perception is the foundation of cognition and is fundamental to our beliefs and consequent action planning. The Editorial (this issue) asks: “what mechanisms, if any, mediate between perceptual and cognitive processes?” It has recently been argued that attention might furnish such a mechanism. In this paper, we pursue the idea that action planning (motor preparation) is an attentional phenomenon directed towards kinaesthetic signals. This rests on a view of motor control as active inference, where predictions of proprioceptive signals are fulfilled (...)
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  16. Richard N. Henson, Daniel G. Wakeman, Vladimir Litvak & Karl J. Friston (2011). A Parametric Empirical Bayesian Framework for the EEG/MEG Inverse Problem: Generative Models for Multi-Subject and Multi-Modal Integration. Frontiers in Human Neuroscience 5.
  17. Christoph Mathys, Jean Daunizeau, Karl J. Friston & Klaas E. Stephan (2011). A Bayesian Foundation for Individual Learning Under Uncertainty. Frontiers in Human Neuroscience 5.
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  18. Harriet Feldman & Karl J. Friston (2010). Attention, Uncertainty, and Free-Energy. Frontiers in Human Neuroscience 4.
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  19. Karl Friston (2010). Some Free-Energy Puzzles Resolved: Response to Thornton. Trends in Cognitive Sciences 14 (2):54-55.
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  20. Jakob Hohwy, Andreas Roepstorff & Karl Friston (2008). Predictive Coding Explains Binocular Rivalry: An Epistemological Review. Cognition 108 (3):687-701.
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  21. 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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  22. 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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  23. 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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  24. 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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  25. 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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  26. 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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  27. 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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  28. 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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