Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning

[1]  Peter Bossaerts,et al.  The Neural Representation of Unexpected Uncertainty during Value-Based Decision Making , 2013, Neuron.

[2]  Carlos Diuk,et al.  Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia , 2013, The Journal of Neuroscience.

[3]  Martin Sarter,et al.  Leveraging the cortical cholinergic system to enhance attention , 2013, Neuropharmacology.

[4]  Angela J. Yu,et al.  Bayesian Prediction and Evaluation in the Anterior Cingulate Cortex , 2013, The Journal of Neuroscience.

[5]  Mathieu d'Acremont,et al.  Activity in Inferior Parietal and Medial Prefrontal Cortex Signals the Accumulation of Evidence in a Probability Learning Task , 2013, PLoS Comput. Biol..

[6]  Karl J. Friston,et al.  Action-Specific Value Signals in Reward-Related Regions of the Human Brain , 2012, The Journal of Neuroscience.

[7]  P. Dayan.  Twenty-Five Lessons from Computational Neuromodulation , 2012, Neuron.

[8]  Raymond J. Dolan,et al.  Dopamine, Affordance and Active Inference , 2012, PLoS Comput. Biol..

[9]  Timothy E. J. Behrens,et al.  Dissociable Reward and Timing Signals in Human Midbrain and Ventral Striatum , 2011, Neuron.

[10]  Daeyeol Lee,et al.  Ubiquity and Specificity of Reinforcement Signals throughout the Human Brain , 2011, Neuron.

[11]  Mkael Symmonds,et al.  Hedging Your Bets by Learning Reward Correlations in the Human Brain , 2011, Neuron.

[12]  Karl J. Friston,et al.  An In Vivo Assay of Synaptic Function Mediating Human Cognition , 2011, Current Biology.

[13]  Janneke F. M. Jehee,et al.  Attention Reverses the Effect of Prediction in Silencing Sensory Signals , 2011, Cerebral cortex.

[14]  M. Hariz,et al.  Targeting of the pedunculopontine nucleus by an MRI-guided approach: a cadaver study , 2011, Journal of Neural Transmission.

[15]  M. Frank,et al.  From reinforcement learning models to psychiatric and neurological disorders , 2011, Nature Neuroscience.

[16]  Jim M. Monti,et al.  Expectation and Surprise Determine Neural Population Responses in the Ventral Visual Stream , 2010, The Journal of Neuroscience.

[17]  P. Dayan,et al.  States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning , 2010, Neuron.

[18]  Karl J. Friston,et al.  Comparing Families of Dynamic Causal Models , 2010, PLoS Comput. Biol..

[19]  P. Dayan,et al.  A common mechanism for adaptive scaling of reward and novelty , 2010, Human brain mapping.

[20]  Nathaniel D. Daw,et al.  Selective impairment of prediction error signaling in human dorsolateral but not ventral striatum in Parkinson's disease patients: evidence from a model-based fMRI study , 2010, NeuroImage.

[21]  Karl J. Friston.  The free-energy principle: a rough guide to the brain? , 2009, Trends in Cognitive Sciences.

[22]  N Weiskopf,et al.  Cardiac artefact correction for human brainstem fMRI at 7T , 2009, NeuroImage.

[23]  Karl J. Friston,et al.  Bayesian model selection for group studies , 2009, NeuroImage.

[24]  P. Tobler,et al.  Functional imaging of the human dopaminergic midbrain , 2009, Trends in Neurosciences.

[25]  S. Kollias,et al.  Duvernoy's Atlas of the Human Brain Stem and Cerebellum , 2009, American Journal of Neuroradiology.

[26]  C. Law,et al.  Reinforcement learning can account for associative and perceptual learning on a visual decision task , 2009, Nature Neuroscience.

[27]  Karl J. Friston,et al.  A Dual Role for Prediction Error in Associative Learning , 2008, Cerebral cortex.

[28]  Katrin Amunts,et al.  Stereotaxic probabilistic maps of the magnocellular cell groups in human basal forebrain , 2008, NeuroImage.

[29]  C. Summerfield,et al.  A Neural Representation of Prior Information during Perceptual Inference , 2008, Neuron.

[30]  N. Logothetis.  What we can do and what we cannot do with fMRI , 2008, Nature.

[31]  J. Bolam,et al.  Stereological estimates of dopaminergic, GABAergic and glutamatergic neurons in the ventral tegmental area, substantia nigra and retrorubral field in the rat , 2008, Neuroscience.

[32]  E T Bullmore,et al.  Substantia nigra/ventral tegmental reward prediction error disruption in psychosis , 2008, Molecular Psychiatry.

[33]  Samuel M. McClure,et al.  BOLD Responses Reflecting Dopaminergic Signals in the Human Ventral Tegmental Area , 2008, Science.

[34]  Timothy E. J. Behrens,et al.  Learning the value of information in an uncertain world , 2007, Nature Neuroscience.

[35]  K. Preuschoff,et al.  Adding Prediction Risk to the Theory of Reward Learning , 2007, Annals of the New York Academy of Sciences.

[36]  Karl J. Friston,et al.  Extra-classical receptive field effects measured in striate cortex with fMRI , 2007, NeuroImage.

[37]  Rajesh P. N. Rao,et al.  Bayesian brain : probabilistic approaches to neural coding , 2006 .

[38]  M. Hasselmo.  The role of acetylcholine in learning and memory , 2006, Current Opinion in Neurobiology.

[39]  P. Redgrave,et al.  The short-latency dopamine signal: a role in discovering novel actions? , 2006, Nature Reviews Neuroscience.

[40]  R. Dolan,et al.  Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans , 2006, Nature.

[41]  N. Bunzeck,et al.  Absolute Coding of Stimulus Novelty in the Human Substantia Nigra/VTA , 2006, Neuron.

[42]  Karl J. Friston,et al.  A free energy principle for the brain , 2006, Journal of Physiology-Paris.

[43]  Karl J. Friston,et al.  Synaptic Plasticity and Dysconnection in Schizophrenia , 2006, Biological Psychiatry.

[44]  K. Doya,et al.  The computational neurobiology of learning and reward , 2006, Current Opinion in Neurobiology.

[45]  Angela J. Yu,et al.  Uncertainty, Neuromodulation, and Attention , 2005, Neuron.

[46]  Simon B. Eickhoff,et al.  A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data , 2005, NeuroImage.

[47]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[48]  Jesper Andersson,et al.  Valid conjunction inference with the minimum statistic , 2005, NeuroImage.

[49]  W. Schultz,et al.  Adaptive Coding of Reward Value by Dopamine Neurons , 2005, Science.

[50]  D. Knill,et al.  The Bayesian brain: the role of uncertainty in neural coding and computation , 2004, Trends in Neurosciences.

[51]  Jonathan D. Cohen,et al.  Computational roles for dopamine in behavioural control , 2004, Nature.

[52]  Karl J. Friston,et al.  Comparing dynamic causal models , 2004, NeuroImage.

[53]  J. Maunsell.  Neuronal representations of cognitive state: reward or attention? , 2004, Trends in Cognitive Sciences.

[54]  Samuel M. McClure,et al.  Temporal Prediction Errors in a Passive Learning Task Activate Human Striatum , 2003, Neuron.

[55]  Karl J. Friston,et al.  Temporal Difference Models and Reward-Related Learning in the Human Brain , 2003, Neuron.

[56]  Peter Dayan,et al.  Acetylcholine in cortical inference , 2002, Neural Networks.

[57]  Kenji Doya,et al.  Metalearning and neuromodulation , 2002, Neural Networks.

[58]  J. M. Anderson,et al.  Responses of human frontal cortex to surprising events are predicted by formal associative learning theory , 2001, Nature Neuroscience.

[59]  G H Glover,et al.  Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR , 2000, Magnetic resonance in medicine.

[60]  J. Horvitz.  Mesolimbocortical and nigrostriatal dopamine responses to salient non-reward events , 2000, Neuroscience.

[61]  W. Schultz.  Predictive reward signal of dopamine neurons. , 1998, Journal of neurophysiology.

[62]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[63]  Geoffrey E. Hinton,et al.  The Helmholtz Machine , 1995, Neural Computation.

[64]  David J. C. MacKay,et al.  Bayesian Interpolation , 1992, Neural Computation.

[65]  W. Ashby,et al.  Design for a Brain. , 1953 .

[66]  Karl J. Friston,et al.  Behavioral / Systems / Cognitive Striatal Prediction Error Modulates Cortical Coupling , 2010 .

[67]  R. Sutton.  Gain Adaptation Beats Least Squares , 2006 .

[68]  Rajesh P. N. Rao,et al.  Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. , 1999 .

[69]  Karl J. Friston,et al.  A unified statistical approach for determining significant signals in images of cerebral activation , 1996, Human brain mapping.

[70]  J. Daunizeau,et al.  Human Neuroscience , 2022 .

[71]  Konrad Paul Kording,et al.  Review TRENDS in Cognitive Sciences Vol.10 No.7 July 2006 Special Issue: Probabilistic models of cognition Bayesian decision theory in sensorimotor control , 2022 .