Deep temporal models and active inference

[1]  David Janssen,et al.  Cerebral responses to local and global auditory novelty under general anesthesia , 2016, NeuroImage.

[2]  J. Mattingley,et al.  A hierarchy of timescales explains distinct effects of local inhibition of primary visual cortex and frontal eye fields , 2016, eLife.

[3]  Karl J. Friston,et al.  Neuroscience and Biobehavioral Reviews , 2022 .

[4]  Alberto Testolin,et al.  Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions , 2016, Front. Comput. Neurosci..

[5]  Karl J. Friston,et al.  The Functional Anatomy of Time: What and When in the Brain , 2016, Trends in Cognitive Sciences.

[6]  Karl J. Friston,et al.  Scene Construction, Visual Foraging, and Active Inference , 2016, Front. Comput. Neurosci..

[7]  J. Rothwell,et al.  A fronto–striato–subthalamic–pallidal network for goal-directed and habitual inhibition , 2015, Nature Reviews Neuroscience.

[8]  Karl J. Friston,et al.  Evidence for surprise minimization over value maximization in choice behavior , 2015, Scientific Reports.

[9]  Raymond J. Dolan,et al.  Dopamine, reward learning, and active inference , 2015, Front. Comput. Neurosci..

[10]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[11]  Michael F. Green,et al.  Validation of mismatch negativity and P3a for use in multi-site studies of schizophrenia: Characterization of demographic, clinical, cognitive, and functional correlates in COGS-2 , 2015, Schizophrenia Research.

[12]  S. Dehaene,et al.  Disruption of hierarchical predictive coding during sleep , 2015, Proceedings of the National Academy of Sciences.

[13]  Karl J. Friston,et al.  Active inference and epistemic value , 2015, Cognitive neuroscience.

[14]  Raymond J. Dolan,et al.  Precision and neuronal dynamics in the human posterior parietal cortex during evidence accumulation , 2015, NeuroImage.

[15]  Raymond J. Dolan,et al.  Active Inference, Evidence Accumulation, and the Urn Task , 2015, Neural Computation.

[16]  Karl J. Friston,et al.  Optimal inference with suboptimal models: Addiction and active Bayesian inference , 2015, Medical hypotheses.

[17]  Karl J. Friston,et al.  The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes , 2014, Cerebral cortex.

[18]  Raymond J. Dolan,et al.  The anatomy of choice: dopamine and decision-making , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[19]  David J. Freedman,et al.  A hierarchy of intrinsic timescales across primate cortex , 2014, Nature Neuroscience.

[20]  Shintaro Funahashi,et al.  Saccade-related activity in the prefrontal cortex: its role in eye movement control and cognitive functions , 2014, Front. Integr. Neurosci..

[21]  Raymond J. Dolan,et al.  Model averaging, optimal inference, and habit formation , 2014, Front. Hum. Neurosci..

[22]  Karl J. Friston,et al.  A formal model of interpersonal inference , 2014, Front. Hum. Neurosci..

[23]  Xiao-Jing Wang,et al.  Computational Psychiatry , 2014, Neuron.

[24]  Dominique Morlet,et al.  MMN and Novelty P3 in Coma and Other Altered States of Consciousness: A Review , 2013, Brain Topography.

[25]  Henry Kennedy,et al.  Cortical High-Density Counterstream Architectures , 2013, Science.

[26]  Miles A. Whittington,et al.  Top-Down Beta Rhythms Support Selective Attention via Interlaminar Interaction: A Model , 2013, PLoS Comput. Biol..

[27]  Joshua B. Tenenbaum,et al.  Learning with Hierarchical-Deep Models , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Alberto Testolin,et al.  Modeling language and cognition with deep unsupervised learning: a tutorial overview , 2013, Front. Psychol..

[29]  Daniel A. Braun,et al.  Thermodynamics as a theory of decision-making with information-processing costs , 2012, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[30]  Anne G E Collins,et al.  Cognitive control over learning: creating, clustering, and generalizing task-set structure. , 2013, Psychological review.

[31]  Omar J. Ahmed,et al.  Thalamic Control of Layer 1 Circuits in Prefrontal Cortex , 2012, The Journal of Neuroscience.

[32]  Karl J. Friston,et al.  Canonical Microcircuits for Predictive Coding , 2012, Neuron.

[33]  Karl J. Friston,et al.  What is value—accumulated reward or evidence? , 2012, Front. Neurorobot..

[34]  Karl J. Friston,et al.  Active inference and agency: optimal control without cost functions , 2012, Biological Cybernetics.

[35]  M. Botvinick,et al.  Planning as inference , 2012, Trends in Cognitive Sciences.

[36]  H. B. Barlow,et al.  Possible Principles Underlying the Transformations of Sensory Messages , 2012 .

[37]  Karl J. Friston,et al.  Computational psychiatry , 2012, Trends in Cognitive Sciences.

[38]  Vicenç Gómez,et al.  Optimal control as a graphical model inference problem , 2009, Machine Learning.

[39]  Doina Precup,et al.  An information-theoretic approach to curiosity-driven reinforcement learning , 2012, Theory in Biosciences.

[40]  Stefan Schaal,et al.  Path integral control and bounded rationality , 2011, 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).

[41]  Asohan Amarasingham,et al.  Hippocampus Internally Generated Cell Assembly Sequences in the Rat , 2011 .

[42]  Hilbert J. Kappen,et al.  Risk Sensitive Path Integral Control , 2010, UAI.

[43]  Y. Niv,et al.  Learning latent structure: carving nature at its joints , 2010, Current Opinion in Neurobiology.

[44]  Marcello Ferro,et al.  Neurorobotics Original Research Article , 2022 .

[45]  Dileep George,et al.  Towards a Mathematical Theory of Cortical Micro-circuits , 2009, PLoS Comput. Biol..

[46]  K. Deisseroth,et al.  Parvalbumin neurons and gamma rhythms enhance cortical circuit performance , 2009, Nature.

[47]  Karl J. Friston,et al.  Frontiers in Neuroinformatics , 2022 .

[48]  Pierre Baldi,et al.  Bayesian surprise attracts human attention , 2005, Vision Research.

[49]  Karl J. Friston,et al.  A Hierarchy of Time-Scales and the Brain , 2008, PLoS Comput. Biol..

[50]  Asohan Amarasingham,et al.  Internally Generated Cell Assembly Sequences in the Rat Hippocampus , 2008, Science.

[51]  D. Heeger,et al.  A Hierarchy of Temporal Receptive Windows in Human Cortex , 2008, The Journal of Neuroscience.

[52]  H. Haken,et al.  Intentionality in non-equilibrium systems? The functional aspects of self-organized pattern formation , 2007 .

[53]  Wolfgang Maass,et al.  Cerebral Cortex Advance Access published February 15, 2006 A Statistical Analysis of Information- Processing Properties of Lamina-Specific , 2022 .

[54]  B. Wyble,et al.  The simultaneous type, serial token model of temporal attention and working memory. , 2007, Psychological review.

[55]  Mark Johnson,et al.  Nonparametric bayesian models of lexical acquisition , 2007 .

[56]  M. Sigman,et al.  Functional organization of perisylvian activation during presentation of sentences in preverbal infants , 2006, Proceedings of the National Academy of Sciences.

[57]  Matthew M Botvinick,et al.  Short-term memory for serial order: a recurrent neural network model. , 2006, Psychological review.

[58]  Sarah J. White,et al.  Raeding Wrods With Jubmled Lettres , 2006, Psychological science.

[59]  Chrystopher L. Nehaniv,et al.  Empowerment: a universal agent-centric measure of control , 2005, 2005 IEEE Congress on Evolutionary Computation.

[60]  D. Umbricht,et al.  Mismatch negativity in schizophrenia: a meta-analysis , 2005, Schizophrenia Research.

[61]  John Field,et al.  Language and the mind , 1968 .

[62]  Michael J. Frank,et al.  Dynamic Dopamine Modulation in the Basal Ganglia: A Neurocomputational Account of Cognitive Deficits in Medicated and Nonmedicated Parkinsonism , 2005, Journal of Cognitive Neuroscience.

[63]  K. Rayner Eye movements in reading: Models and data , 2003, Behavioral and Brain Sciences.

[64]  Steven F. Kalik,et al.  Analysis of perisaccadic field potentials in the occipitotemporal pathway during active vision. , 2003, Journal of neurophysiology.

[65]  A. Thomson,et al.  Interlaminar connections in the neocortex. , 2003, Cerebral cortex.

[66]  Matthew J. Beal Variational algorithms for approximate Bayesian inference , 2003 .

[67]  S. Pinker,et al.  The past and future of the past tense , 2002, Trends in Cognitive Sciences.

[68]  Kevin P. Murphy,et al.  Dynamic Bayesian Networks for Audio-Visual Speech Recognition , 2002, EURASIP J. Adv. Signal Process..

[69]  S. Laughlin Efficiency and complexity in neural coding. , 2008, Novartis Foundation symposium.

[70]  Dominique Morlet,et al.  Mismatch Negativity and N100 in Comatose Patients , 2000, Audiology and Neurotology.

[71]  G D Brown,et al.  Oscillator-based memory for serial order. , 2000, Psychological review.

[72]  N. Burgess,et al.  Memory for serial order: A network model of the phonological loop and its timing , 1999 .

[73]  D. Norris,et al.  The primacy model: a new model of immediate serial recall. , 1998, Psychological review.

[74]  R. Henson Short-Term Memory for Serial Order: The Start-End Model , 1998, Cognitive Psychology.

[75]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

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

[77]  David J. C. MacKay,et al.  A hierarchical Dirichlet language model , 1995, Natural Language Engineering.

[78]  Jürgen Schmidhuber,et al.  Curious model-building control systems , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.

[79]  F. D. Silva Neural mechanisms underlying brain waves: from neural membranes to networks. , 1991 .

[80]  F. H. Lopes da Silva Neural mechanisms underlying brain waves: from neural membranes to networks. , 1991, Electroencephalography and clinical neurophysiology.

[81]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[82]  R Linsker,et al.  Perceptual neural organization: some approaches based on network models and information theory. , 1990, Annual review of neuroscience.

[83]  E. Donchin,et al.  Is the P300 component a manifestation of context updating? , 1988, Behavioral and Brain Sciences.

[84]  J. Fodor,et al.  Connectionism and cognitive architecture: A critical analysis , 1988, Cognition.

[85]  N. Kanwisher Repetition blindness: Type recognition without token individuation , 1987, Cognition.

[86]  K. Kubota,et al.  The organization of prefrontocaudate projections and their laminar origin in the macaque monkey: A retrograde study using HRP‐gel , 1986, The Journal of comparative neurology.

[87]  P. Goldman-Rakic,et al.  Delay-related activity of prefrontal neurons in rhesus monkeys performing delayed response , 1982, Brain Research.

[88]  K. Rayner Eye movements in reading and information processing. , 1978, Psychological bulletin.

[89]  H. Barlow Inductive Inference, Coding, Perception, and Language , 1974, Perception.

[90]  Ronald A. Howard,et al.  Information Value Theory , 1966, IEEE Trans. Syst. Sci. Cybern..

[91]  K. Lashley The problem of serial order in behavior , 1951 .