Neural and phenotypic representation under the free-energy principle

[1]  Adeel Razi,et al.  Parcels and particles: Markov blankets in the brain , 2020, Network Neuroscience.

[2]  Karl J. Friston,et al.  Is the Free-Energy Principle a Formal Theory of Semantics? From Variational Density Dynamics to Neural and Phenotypic Representations , 2020, Entropy.

[3]  Karl J. Friston,et al.  Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological systems. , 2020, Physics of life reviews.

[4]  Karl J. Friston,et al.  Markov blankets in the brain , 2020, Neuroscience & Biobehavioral Reviews.

[5]  Alex B. Kiefer Psychophysical identity and free energy , 2020, Journal of the Royal Society Interface.

[6]  Karl J. Friston,et al.  Modules or Mean-Fields? , 2020, Entropy.

[7]  Karl J. Friston,et al.  Sentience and the Origins of Consciousness: From Cartesian Duality to Markovian Monism , 2020, Entropy.

[8]  Karl J. Friston,et al.  Markov blankets, information geometry and stochastic thermodynamics , 2019, Philosophical Transactions of the Royal Society A.

[9]  Karl J. Friston,et al.  Variational ecology and the physics of sentient systems , 2019, Physics of life reviews.

[10]  Adeel Razi,et al.  On Markov blankets and hierarchical self-organisation , 2019, Journal of theoretical biology.

[11]  Ines Hipolito,et al.  A simple theory of every 'thing'. , 2019, Physics of life reviews.

[12]  Karl J. Friston,et al.  A tale of two densities: active inference is enactive inference , 2019, Adapt. Behav..

[13]  Karl J. Friston A free energy principle for a particular physics , 2019, 1906.10184.

[14]  Karl J. Friston,et al.  Choosing a Markov blanket , 2019, Behavioral and Brain Sciences.

[15]  Karl J. Friston,et al.  The emergence of synchrony in networks of mutually inferring neurons , 2019, Scientific Reports.

[16]  Yan M. Yufik,et al.  The Understanding Capacity and Information Dynamics in the Human Brain , 2019, Entropy.

[17]  Karl J. Friston,et al.  The Anatomy of Inference: Generative Models and Brain Structure , 2018, Front. Comput. Neurosci..

[18]  Frances Egan,et al.  The nature and function of content in computational models , 2018, The Routledge Handbook of the Computational Mind.

[19]  J. Hohwy,et al.  Content and misrepresentation in hierarchical generative models , 2018, Synthese.

[20]  Karl J. Friston,et al.  In vitro neural networks minimise variational free energy , 2018, Scientific Reports.

[21]  Karl J. Friston,et al.  A variational approach to niche construction , 2018, Journal of The Royal Society Interface.

[22]  Maxwell J. D. Ramstead,et al.  Embodiment and Enactment in Cultural Psychiatry , 2018 .

[23]  Yan M. Yufik,et al.  Virtual Associative Networks: A Framework for Cognitive Modeling , 2018 .

[24]  Karl J. Friston,et al.  The Markov blankets of life: autonomy, active inference and the free energy principle , 2018, Journal of The Royal Society Interface.

[25]  Karl J. Friston,et al.  The graphical brain: Belief propagation and active inference , 2017, Network Neuroscience.

[26]  Deborah M. Gordon,et al.  A distributed algorithm to maintain and repair the trail networks of arboreal ants , 2017, Scientific Reports.

[27]  Karl J. Friston,et al.  Active Inference, Curiosity and Insight , 2017, Neural Computation.

[28]  Karl J. Friston,et al.  Predicting green: really radical (plant) predictive processing , 2017, Journal of The Royal Society Interface.

[29]  Karl J. Friston,et al.  Answering Schrödinger's question: A free-energy formulation , 2017, Physics of life reviews.

[30]  Karl J. Friston,et al.  Life and Understanding: The Origins of “Understanding” in Self-Organizing Nervous Systems , 2016, Front. Syst. Neurosci..

[31]  M. Ramstead,et al.  Cultural Affordances: Scaffolding Local Worlds Through Shared Intentionality and Regimes of Attention , 2016, Front. Psychol..

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

[33]  Carolyn Parkinson,et al.  Reason for optimism: How a shifting focus on neural population codes is moving cognitive neuroscience beyond phrenology , 2016, Behavioral and Brain Sciences.

[34]  J. Hohwy The self-evidencing brain , 2016 .

[35]  Karl J. Friston,et al.  Knowing one's place: a free-energy approach to pattern regulation , 2015, Journal of The Royal Society Interface.

[36]  F. Quevedo,et al.  Theory for Development , 2014 .

[37]  Karl J. Friston,et al.  Structural and Functional Brain Networks: From Connections to Cognition , 2013, Science.

[38]  Karl J. Friston Life as we know it , 2013, Journal of The Royal Society Interface.

[39]  A. Pouget,et al.  Probabilistic brains: knowns and unknowns , 2013, Nature Neuroscience.

[40]  Karl J. Friston,et al.  A Free Energy Principle for Biological Systems. , 2012, Entropy.

[41]  A. Dussutour,et al.  Slime mold uses an externalized spatial “memory” to navigate in complex environments , 2012, Proceedings of the National Academy of Sciences.

[42]  Karl J. Friston,et al.  Free Energy and Dendritic Self-Organization , 2011, Front. Syst. Neurosci..

[43]  György Buzsáki,et al.  Neural Syntax: Cell Assemblies, Synapsembles, and Readers , 2010, Neuron.

[44]  Ernst Strüngmann Forum,et al.  Dynamic coordination in the brain : from neurons to mind , 2010 .

[45]  Karl J. Friston The free-energy principle: a unified brain theory? , 2010, Nature Reviews Neuroscience.

[46]  Miguel A. L. Nicolelis,et al.  Principles of neural ensemble physiology underlying the operation of brain–machine interfaces , 2009, Nature Reviews Neuroscience.

[47]  Timothy D. Hanks,et al.  Probabilistic Population Codes for Bayesian Decision Making , 2008, Neuron.

[48]  M. Sur,et al.  Patterning and Plasticity of the Cerebral Cortex , 2005, Science.

[49]  S. Zeki The Ferrier Lecture 1995 Behind the Seen: The functional specialization of the brain in space and time , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[50]  F. Ratnieks,et al.  Trail geometry gives polarity to ant foraging networks , 2004, Nature.

[51]  E. S. Ruthazer,et al.  Dendrite growth increased by visual activity requires NMDA receptor and Rho GTPases , 2002, Nature.

[52]  George L. Gerstein,et al.  Neural assemblies: technical issues, analysis, and modeling , 2001, Neural Networks.

[53]  R. Zemel,et al.  Information processing with population codes , 2000, Nature Reviews Neuroscience.

[54]  D. Rice,et al.  Critical periods of vulnerability for the developing nervous system: evidence from humans and animal models. , 2000, Environmental health perspectives.

[55]  M. Sur,et al.  Visual behaviour mediated by retinal projections directed to the auditory pathway , 2000, Nature.

[56]  Alexander Borst,et al.  Information theory and neural coding , 1999, Nature Neuroscience.

[57]  W. Bair Spike timing in the mammalian visual system , 1999, Current Opinion in Neurobiology.

[58]  Shimon Edelman Representation is representation of similarities , 1998, Behavioral and Brain Sciences.

[59]  H. Thoenen Neurotrophins and Neuronal Plasticity , 1995, Science.

[60]  G. Edelman Neural Darwinism: Selection and reentrant signaling in higher brain function , 1993, Neuron.

[61]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[62]  S. Zeki,et al.  Modular Connections between Areas V2 and V4 of Macaque Monkey Visual Cortex , 1989, The European journal of neuroscience.

[63]  M. Sur,et al.  Experimentally induced visual projections into auditory thalamus and cortex. , 1988, Science.

[64]  J. Movshon,et al.  The statistical reliability of signals in single neurons in cat and monkey visual cortex , 1983, Vision Research.

[65]  D C Van Essen,et al.  Functional properties of neurons in middle temporal visual area of the macaque monkey. I. Selectivity for stimulus direction, speed, and orientation. , 1983, Journal of neurophysiology.

[66]  E. Bienenstock,et al.  Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[67]  W. Singer,et al.  Restriction of visual experience to a single orientation affects the organization of orientation columns in cat visual cortex , 1981, Experimental Brain Research.

[68]  D E Mitchell,et al.  Visual Resolution and Experience: Acuity Deficits in Cats Following Early Selective Visual Deprivation , 1973, Science.

[69]  G. F. Cooper,et al.  Development of the Brain depends on the Visual Environment , 1970, Nature.

[70]  C. Sherrington Integrative Action of the Nervous System , 1907 .

[71]  Jakob Hohwy,et al.  Representation in the Prediction Error Minimization Framework , 2019, The Routledge Companion to Philosophy of Psychology.

[72]  T. Fuchs,et al.  Embodiment, Enaction, and Culture: Investigating the Constitution of the Shared World , 2017 .

[73]  Wei Ji Ma,et al.  Probabilistic brains: knowns and , 2013 .

[74]  R. Zemel,et al.  To appear in : Neural Computation , 10 ( 2 ) , 403-430 Probabilistic Interpretation of Population Codes , 2007 .

[75]  V. Mountcastle REVIEW ARTICLE The , 2004 .

[76]  E. Huang,et al.  Neurotrophins: roles in neuronal development and function. , 2001, Annual review of neuroscience.

[77]  R. Reid,et al.  Synchronous activity in the visual system. , 1999, Annual review of physiology.

[78]  D. Buonomano,et al.  Cortical plasticity: from synapses to maps. , 1998, Annual review of neuroscience.

[79]  Christoph von der Malsburg,et al.  The Correlation Theory of Brain Function , 1994 .

[80]  A. Peters,et al.  Neuronal organization in area 17 of cat visual cortex. , 1993, Cerebral cortex.

[81]  J. Pearl Probabilistic reasoning in intelligent systems - networks of plausible inference , 1989, Morgan Kaufmann series in representation and reasoning.

[82]  D. O. Hebb,et al.  The organization of behavior , 1988 .