Memory and Markov Blankets
暂无分享,去创建一个
Thomas Parr | Lancelot Da Costa | Conor Heins | Maxwell James D. Ramstead | Karl J. Friston | Thomas Parr | K. Friston | M. Ramstead | Conor Heins
[1] L. Squire,et al. Episodic memory, semantic memory, and amnesia , 1998, Hippocampus.
[2] M. Ledoux,et al. Analysis and Geometry of Markov Diffusion Operators , 2013 .
[3] D. Thouless,et al. Structure of stochastic dynamics near fixed points. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[4] Karl J. Friston. A free energy principle for a particular physics , 2019, 1906.10184.
[5] A. Nobre,et al. Spatial Selection of Features within Perceived and Remembered Objects , 2009, NeuroImage.
[6] S. Amari. Information geometry , 2021, Japanese Journal of Mathematics.
[7] Thomas Parr,et al. Deep Active Inference and Scene Construction , 2020, Frontiers in Artificial Intelligence.
[8] Ramón Huerta,et al. Reproducible sequence generation in random neural ensembles. , 2004, Physical review letters.
[9] Gavin E Crooks,et al. Measuring thermodynamic length. , 2007, Physical review letters.
[10] H. Risken. The Fokker-Planck equation : methods of solution and applications , 1985 .
[11] Karl J. Friston,et al. A Hierarchy of Time-Scales and the Brain , 2008, PLoS Comput. Biol..
[12] Judea Pearl,et al. Graphical Models for Probabilistic and Causal Reasoning , 1997, The Computer Science and Engineering Handbook.
[13] Karl J. Friston,et al. Action understanding and active inference , 2011, Biological Cybernetics.
[14] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[15] W. Cannon. ORGANIZATION FOR PHYSIOLOGICAL HOMEOSTASIS , 1929 .
[16] Karl J. Friston,et al. Neural Dynamics under Active Inference: Plausibility and Efficiency of Information Processing , 2020, Entropy.
[17] R. A. Leibler,et al. On Information and Sufficiency , 1951 .
[18] Mark Girolami,et al. A Unifying and Canonical Description of Measure-Preserving Diffusions , 2021, 2105.02845.
[19] Karl J. Friston,et al. Active inference, communication and hermeneutics , 2015, Cortex.
[20] Eun-Jin Kim,et al. Investigating Information Geometry in Classical and Quantum Systems through Information Length , 2018, Entropy.
[21] 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.
[22] H. Eichenbaum. Time cells in the hippocampus: a new dimension for mapping memories , 2014, Nature Reviews Neuroscience.
[23] John Duchi,et al. Derivations for Linear Algebra and Optimization , 2016 .
[24] Kai Ueltzhöffer,et al. Stochastic Chaos and Markov Blankets , 2021, Entropy.
[25] A. Baddeley. Working memory: looking back and looking forward , 2003, Nature Reviews Neuroscience.
[26] W Grodd,et al. Impaired procedural learning after damage to the left supplementary motor area (SMA). , 1996, Journal of neurology, neurosurgery, and psychiatry.
[27] Michela Ottobre,et al. Markov Chain Monte Carlo and Irreversibility , 2016 .
[28] Adeel Razi,et al. Parcels and particles: Markov blankets in the brain , 2020, Network Neuroscience.
[29] Raymond J. Dolan,et al. The anatomy of choice: dopamine and decision-making , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.
[30] Karl J. Friston,et al. Free-energy minimization in joint agent-environment systems: A niche construction perspective , 2018, Journal of theoretical biology.
[31] Karl J. Friston,et al. Variational ecology and the physics of sentient systems , 2019, Physics of life reviews.
[32] Karl J. Friston,et al. Deep temporal models and active inference , 2017, Neuroscience and biobehavioral reviews.
[33] Shun-ichi Amari,et al. Differential-geometrical methods in statistics , 1985 .
[34] F. Opitz. Information geometry and its applications , 2012, 2012 9th European Radar Conference.
[35] S. Cavanagh,et al. A Diversity of Intrinsic Timescales Underlie Neural Computations , 2020, Frontiers in Neural Circuits.
[36] K. Spiliopoulos,et al. Irreversible Langevin samplers and variance reduction: a large deviations approach , 2014, 1404.0105.
[37] J. Luck,et al. Characterising the nonequilibrium stationary states of Ornstein–Uhlenbeck processes , 2018, Journal of Physics A: Mathematical and Theoretical.
[38] H. Risken. Fokker-Planck Equation , 1996 .
[39] R. Knight,et al. Prefrontal modulation of visual processing in humans , 2000, Nature Neuroscience.
[40] Tianqi Chen,et al. Dynamical Decomposition of Markov Processes without Detailed Balance , 2013 .
[41] P. Goldman-Rakic,et al. Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. , 1989, Journal of neurophysiology.
[42] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[43] Irving H. Shames,et al. Introduction to Solid Mechanics , 1975 .
[44] J. Krakauer,et al. Sensory prediction errors drive cerebellum-dependent adaptation of reaching. , 2007, Journal of neurophysiology.
[45] John M. Franchak,et al. The development of motor behavior. , 2017, Wiley interdisciplinary reviews. Cognitive science.
[46] J. Fuster. Upper processing stages of the perception–action cycle , 2004, Trends in Cognitive Sciences.
[47] Fuzhen Zhang. The Schur complement and its applications , 2005 .
[48] J. Fuster. Unit activity in prefrontal cortex during delayed-response performance: neuronal correlates of transient memory. , 1973, Journal of neurophysiology.
[49] Karl J. Friston,et al. The computational neurology of movement under active inference , 2021, Brain : a journal of neurology.
[50] D. Heeger,et al. A Hierarchy of Temporal Receptive Windows in Human Cortex , 2008, The Journal of Neuroscience.
[51] A. Nobre,et al. Modulation of working-memory maintenance by directed attention , 2011, Neuropsychologia.
[52] U. Seifert. Stochastic thermodynamics, fluctuation theorems and molecular machines , 2012, Reports on progress in physics. Physical Society.
[53] L. Squire. Memory systems of the brain: A brief history and current perspective , 2004, Neurobiology of Learning and Memory.
[54] Karl J. Friston,et al. Deep Active Inference and Scene Construction , 2020, bioRxiv.
[55] Adrian-Josue Guel-Cortez,et al. Information Length Analysis of Linear Autonomous Stochastic Processes , 2020, Entropy.
[56] C. Marsden,et al. PROCEDURAL MEMORY AND NEUROLOGICAL DISEASE , 1992 .
[57] Karl J. Friston. Life as we know it , 2013, Journal of The Royal Society Interface.
[58] Grigorios A. Pavliotis,et al. Bayesian mechanics for stationary processes , 2021, Proceedings of the Royal Society A.
[59] J. O'Keefe,et al. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. , 1971, Brain research.
[60] G. Pavliotis. Stochastic Processes and Applications: Diffusion Processes, the Fokker-Planck and Langevin Equations , 2014 .
[61] T. Bliss,et al. Long‐lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path , 1973, The Journal of physiology.
[62] Kai Ueltzhöffer,et al. Deep active inference , 2017, Biological Cybernetics.
[63] A. Nobre,et al. Attentional modulation of object representations in working memory. , 2007, Cerebral cortex.
[64] Karl J. Friston,et al. Population dynamics under the Laplace assumption , 2009, NeuroImage.
[65] Christopher M. Bishop,et al. Pattern Recognition and Machine Learning (Information Science and Statistics) , 2006 .
[66] Karl J. Friston,et al. Prefrontal Computation as Active Inference , 2019, Cerebral cortex.
[67] Karl J. Friston,et al. Markov blankets, information geometry and stochastic thermodynamics , 2019, Philosophical Transactions of the Royal Society A.
[68] Karl J. Friston,et al. Working memory, attention, and salience in active inference , 2017, Scientific Reports.
[69] PascucciValerio,et al. The Helmholtz-Hodge Decomposition—A Survey , 2013 .
[70] M. Molinari,et al. Cerebellum and procedural learning: evidence from focal cerebellar lesions. , 1997, Brain : a journal of neurology.
[71] Karl J. Friston,et al. Active Inference and Learning in the Cerebellum , 2016, Neural Computation.
[72] Karl J. Friston,et al. The computational pharmacology of oculomotion , 2019, Psychopharmacology.