The neural marketplace

[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).