The neural marketplace
暂无分享,去创建一个
[1] Elke Edelmann,et al. Pre- and postsynaptic twists in BDNF secretion and action in synaptic plasticity , 2014, Neuropharmacology.
[2] Kenneth D. Harris,et al. The Neural Marketplace: I. General Formalism and Linear Theory , 2014, bioRxiv.
[3] U. Frey,et al. Synaptic tagging and long-term potentiation , 1997, Nature.
[4] F. Eckenstein,et al. An anatomical study of cholinergic innervation in rat cerebral cortex , 1988, Neuroscience.
[5] Kevin R Jones,et al. Genetic evidence that brain-derived neurotrophic factor mediates competitive interactions between individual cortical neurons , 2012, Proceedings of the National Academy of Sciences.
[6] Walter Senn,et al. A Gradient Learning Rule for the Tempotron , 2009, Neural Computation.
[7] G. Einevoll,et al. From grid cells to place cells: A mathematical model , 2006, Hippocampus.
[8] O. Penrose. Foundations of statistical mechanics , 1969 .
[9] Kenneth D. Harris,et al. The Convallis Rule for Unsupervised Learning in Cortical Networks , 2013, PLoS Comput. Biol..
[10] Henning Sprekeler,et al. Functional Requirements for Reward-Modulated Spike-Timing-Dependent Plasticity , 2010, The Journal of Neuroscience.
[11] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2003, ICTAI.
[12] Mattias P. Karlsson,et al. Network Dynamics Underlying the Formation of Sparse, Informative Representations in the Hippocampus , 2008, The Journal of Neuroscience.
[13] Katherine M. Armstrong,et al. Selective gating of visual signals by microstimulation of frontal cortex , 2003, Nature.
[14] D. Paré,et al. Plastic synaptic networks of the amygdala for the acquisition, expression, and extinction of conditioned fear. , 2010, Physiological reviews.
[15] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[16] Razvan V. Florian,et al. Reinforcement Learning Through Modulation of Spike-Timing-Dependent Synaptic Plasticity , 2007, Neural Computation.
[17] Yann LeCun,et al. Unsupervised Learning of Sparse Features for Scalable Audio Classification , 2011, ISMIR.
[18] W. Gerstner,et al. Connectivity reflects coding: a model of voltage-based STDP with homeostasis , 2010, Nature Neuroscience.
[19] M. Hasselmo. The role of acetylcholine in learning and memory , 2006, Current Opinion in Neurobiology.
[20] P. J. Sjöström,et al. Neocortical LTD via Coincident Activation of Presynaptic NMDA and Cannabinoid Receptors , 2003, Neuron.
[21] Stephen Maren,et al. The Amygdala Is Essential for the Development of Neuronal Plasticity in the Medial Geniculate Nucleus during Auditory Fear Conditioning in Rats , 2001, The Journal of Neuroscience.
[22] K. Stevens,et al. Linguistic experience alters phonetic perception in infants by 6 months of age. , 1992, Science.
[23] Francis Crick,et al. The recent excitement about neural networks , 1989, Nature.
[24] R. Costa. Plastic Corticostriatal Circuits for Action Learning , 2007, Annals of the New York Academy of Sciences.
[25] Stanley J. Wiegand,et al. The neurotrophins BDNF, NT-3, and NGF display distinct patterns of retrograde axonal transport in peripheral and central neurons , 1992, Neuron.
[26] Bernardo L Sabatini,et al. Timing and Location of Synaptic Inputs Determine Modes of Subthreshold Integration in Striatal Medium Spiny Neurons , 2007, The Journal of Neuroscience.
[27] David Balduzzi,et al. Cortical prediction markets , 2014, AAMAS.
[28] C Kentros,et al. Abolition of long-term stability of new hippocampal place cell maps by NMDA receptor blockade. , 1998, Science.
[29] V. Hamburger,et al. The history of the discovery of the nerve growth factor. , 1993, Journal of neurobiology.
[30] Erkki Oja,et al. Independent component analysis by general nonlinear Hebbian-like learning rules , 1998, Signal Process..
[31] C. M. Davenport,et al. Mediation by a CREB family transcription factor of NGF-dependent survival of sympathetic neurons. , 1999, Science.
[32] N. Sigala,et al. Visual categorization shapes feature selectivity in the primate temporal cortex , 2002, Nature.
[33] V. Hamburger,et al. History of the discovery of neuronal death in embryos. , 1992, Journal of neurobiology.
[34] Walter Senn,et al. Spatio-Temporal Credit Assignment in Neuronal Population Learning , 2011, PLoS Comput. Biol..
[35] David J. C. MacKay,et al. A Practical Bayesian Framework for Backpropagation Networks , 1992, Neural Computation.
[36] Charles J. Wilson,et al. Connectivity and Convergence of Single Corticostriatal Axons , 1998, The Journal of Neuroscience.
[37] Nathan Intrator,et al. Theory of Cortical Plasticity , 2004 .
[38] Gernot Riedel,et al. Foreground contextual fear memory consolidation requires two independent phases of hippocampal ERK/CREB activation. , 2006, Learning & memory.
[39] E. Kandel,et al. D1/D5 receptor agonists induce a protein synthesis-dependent late potentiation in the CA1 region of the hippocampus. , 1995, Proceedings of the National Academy of Sciences of the United States of America.
[40] Yoram Singer,et al. The Forgetron: A Kernel-Based Perceptron on a Budget , 2008, SIAM J. Comput..
[41] M. Frank. Computational models of motivated action selection in corticostriatal circuits , 2011, Current Opinion in Neurobiology.
[42] David J. C. MacKay,et al. Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.
[43] Peter Dayan,et al. A Neural Substrate of Prediction and Reward , 1997, Science.
[44] Rosalind A. Segal,et al. Neurotrophins use the Erk5 pathway to mediate a retrograde survival response , 2001, Nature Neuroscience.
[45] Paul J. Werbos,et al. Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.
[46] Denise J. Cai,et al. Synaptic tagging during memory allocation , 2014, Nature Reviews Neuroscience.
[47] Lin Tian,et al. Activity in motor-sensory projections reveals distributed coding in somatosensation , 2012, Nature.
[48] R. Morris,et al. Making memories last: the synaptic tagging and capture hypothesis , 2010, Nature Reviews Neuroscience.
[49] F ROSENBLATT,et al. The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.
[50] A. Riccio,et al. An NGF-TrkA-mediated retrograde signal to transcription factor CREB in sympathetic neurons. , 1997, Science.
[51] E. Thorndike. SOME EXPERIMENTS ON ANIMAL INTELLIGENCE. , 1898, Science.
[52] L. V. D. Heyden,et al. Perturbation bounds for the stationary probabilities of a finite Markov chain , 1984 .
[53] K. Doya,et al. Multiple representations and algorithms for reinforcement learning in the cortico-basal ganglia circuit , 2011, Current Opinion in Neurobiology.
[54] Wulfram Gerstner,et al. Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail , 2009, PLoS Comput. Biol..
[55] B L McNaughton,et al. Dynamics of the hippocampal ensemble code for space. , 1993, Science.
[56] Michael Frotscher,et al. Cholinergic innervation of the rat hippocampus as revealed by choline acetyltransferase immunocytochemistry: A combined light and electron microscopic study , 1985, The Journal of comparative neurology.
[57] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[58] D. Ginty,et al. Functions and mechanisms of retrograde neurotrophin signalling , 2005, Nature Reviews Neuroscience.
[59] E. Thorndike. “Animal Intelligence” , 1898, Nature.
[60] Jürgen Schmidhuber,et al. Market-Based Reinforcement Learning in Partially Observable Worlds , 2001, ICANN.
[61] M. Poo,et al. Propagation of activity-dependent synaptic depression in simple neural networks , 1997, Nature.
[62] Woong Sun,et al. Adaptive roles of programmed cell death during nervous system development. , 2006, Annual review of neuroscience.
[63] J. Wickens. Synaptic plasticity in the basal ganglia , 2009, Behavioural Brain Research.
[64] K. Fox,et al. The role of nitric oxide in pre-synaptic plasticity and homeostasis , 2013, Front. Cell. Neurosci..
[65] U. Frey,et al. Synaptic tagging: implications for late maintenance of hippocampal long-term potentiation , 1998, Trends in Neurosciences.
[66] J. O'Keefe,et al. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. , 1971, Brain research.
[67] D. Purves. Body and Brain: A Trophic Theory of Neural Connections , 1988 .
[68] G. Shepherd,et al. The neocortical circuit: themes and variations , 2015, Nature Neuroscience.
[69] Sen Song,et al. Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits , 2005, PLoS biology.
[70] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[71] R. Oppenheim. Cell death during development of the nervous system. , 1991, Annual review of neuroscience.
[72] L. Abbott,et al. Eigenvalue spectra of random matrices for neural networks. , 2006, Physical review letters.
[73] Claudio Gentile,et al. Tracking the best hyperplane with a simple budget Perceptron , 2006, Machine Learning.
[74] Roland Vollgraf,et al. From grids to places , 2007, Journal of Computational Neuroscience.
[75] David M. Lovinger,et al. Neurotransmitter roles in synaptic modulation, plasticity and learning in the dorsal striatum , 2010, Neuropharmacology.
[76] S. Sajikumar,et al. Late-associativity, synaptic tagging, and the role of dopamine during LTP and LTD , 2004, Neurobiology of Learning and Memory.
[77] Mu-ming Poo,et al. Long-range retrograde spread of LTP and LTD from optic tectum to retina , 2009, Proceedings of the National Academy of Sciences.
[78] Kenneth D. Harris,et al. Top-Down Control of Cortical State , 2013, Neuron.
[79] Doyun Lee,et al. Hippocampal Place Fields Emerge upon Single-Cell Manipulation of Excitability During Behavior , 2012, Science.
[80] E. Kandel,et al. Gene Expression Profiling of Facilitated L-LTP in VP16-CREB Mice Reveals that BDNF Is Critical for the Maintenance of LTP and Its Synaptic Capture , 2005, Neuron.
[81] Henry Markram,et al. Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations , 2002, Neural Computation.
[82] Alcino J. Silva,et al. CREB and memory. , 1998, Annual review of neuroscience.
[83] Anthony W. Harrington,et al. Long-Distance Control of Synapse Assembly by Target-Derived NGF , 2010, Neuron.
[84] M. Bentivoglio,et al. Chapter I The organization and circuits of mesencephalic dopaminergic neurons and the distribution of dopamine receptors in the brain , 2005 .
[85] Sreedharan Sajikumar,et al. Making synapses strong: metaplasticity prolongs associativity of long-term memory by switching synaptic tag mechanisms. , 2014, Cerebral cortex.
[86] Richard Miles,et al. Interneuron Diversity series: Fast in, fast out – temporal and spatial signal processing in hippocampal interneurons , 2004, Trends in Neurosciences.
[87] Geoffrey E. Hinton,et al. Unsupervised learning : foundations of neural computation , 1999 .
[88] Y. Dan,et al. Spike timing-dependent plasticity: a Hebbian learning rule. , 2008, Annual review of neuroscience.
[89] Greg D. Gale,et al. Hippocampus and contextual fear conditioning: Recent controversies and advances , 2001, Hippocampus.
[90] L. Frank,et al. Behavioral/Systems/Cognitive Hippocampal Plasticity across Multiple Days of Exposure to Novel Environments , 2022 .
[91] L. F. Abbott,et al. Generating Coherent Patterns of Activity from Chaotic Neural Networks , 2009, Neuron.
[92] Spartaco Santi,et al. Induction of long-term potentiation and depression is reflected by corresponding changes in secretion of endogenous brain-derived neurotrophic factor. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[93] Cordelia Schmid,et al. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).