Hiratani N, Fukai T. (2018). Redundancy in synaptic connections enables neurons to learn optimally. Proceedings of the National Academy of Sciences of the United States of America. 115 [PubMed]

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References and models cited by this paper

Amari S, Park H, Ozeki T. (2006). Singularities affect dynamics of learning in neuromanifolds. Neural computation. 18 [PubMed]

Bartol TM et al. (2015). Nanoconnectomic upper bound on the variability of synaptic plasticity. eLife. 4 [PubMed]

Behrens TE, Woolrich MW, Walton ME, Rushworth MF. (2007). Learning the value of information in an uncertain world. Nature neuroscience. 10 [PubMed]

Bittner KC et al. (2015). Conjunctive input processing drives feature selectivity in hippocampal CA1 neurons. Nature neuroscience. 18 [PubMed]

Bonin V, Histed MH, Yurgenson S, Reid RC. (2011). Local diversity and fine-scale organization of receptive fields in mouse visual cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 31 [PubMed]

Branco T, Staras K. (2009). The probability of neurotransmitter release: variability and feedback control at single synapses. Nature reviews. Neuroscience. 10 [PubMed]

Casella G, Robert C. (2013). Monte Carlo Statistical Methods.

Cash S, Yuste R. (1999). Linear summation of excitatory inputs by CA1 pyramidal neurons. Neuron. 22 [PubMed]

Costa RP et al. (2017). Synaptic Transmission Optimization Predicts Expression Loci of Long-Term Plasticity. Neuron. 96 [PubMed]

Courville AC, Daw ND, Touretzky DS. (2006). Bayesian theories of conditioning in a changing world. Trends in cognitive sciences. 10 [PubMed]

Deuchars J, West DC, Thomson AM. (1994). Relationships between morphology and physiology of pyramid-pyramid single axon connections in rat neocortex in vitro. The Journal of physiology. 478 Pt 3 [PubMed]

Feldmeyer D, Egger V, Lubke J, Sakmann B. (1999). Reliable synaptic connections between pairs of excitatory layer 4 neurones within a single 'barrel' of developing rat somatosensory cortex. The Journal of physiology. 521 Pt 1 [PubMed]

Froemke RC. (2015). Plasticity of cortical excitatory-inhibitory balance. Annual review of neuroscience. 38 [PubMed]

Gal E et al. (2017). Rich cell-type-specific network topology in neocortical microcircuitry. Nature neuroscience. 20 [PubMed]

Geisler WS, Perry JS, Super BJ, Gallogly DP. (2001). Edge co-occurrence in natural images predicts contour grouping performance. Vision research. 41 [PubMed]

Graupner M, Brunel N. (2012). Calcium-based plasticity model explains sensitivity of synaptic changes to spike pattern, rate, and dendritic location. Proceedings of the National Academy of Sciences of the United States of America. 109 [PubMed]

Griffiths TL, Shi L. (2015). Neural implementation of hierarchical Bayesian inference by importance sampling Arxiv.

Gütig R. (2016). Spiking neurons can discover predictive features by aggregate-label learning. Science (New York, N.Y.). 351 [PubMed]

Han B, Zhu Y, Comaniciu D, Davis LS. (2009). Visual tracking by continuous density propagation in sequential bayesian filtering framework. IEEE transactions on pattern analysis and machine intelligence. 31 [PubMed]

Hao J, Wang XD, Dan Y, Poo MM, Zhang XH. (2009). An arithmetic rule for spatial summation of excitatory and inhibitory inputs in pyramidal neurons. Proceedings of the National Academy of Sciences of the United States of America. 106 [PubMed]

Harris KM, Stevens JK. (1989). Dendritic spines of CA 1 pyramidal cells in the rat hippocampus: serial electron microscopy with reference to their biophysical characteristics. The Journal of neuroscience : the official journal of the Society for Neuroscience. 9 [PubMed]

Hines ML, Carnevale NT. (1997). The NEURON simulation environment. Neural computation. 9 [PubMed]

Hiratani N, Fukai T. (2016). Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity. Frontiers in neural circuits. 10 [PubMed]

Holtmaat A, Svoboda K. (2009). Experience-dependent structural synaptic plasticity in the mammalian brain. Nature reviews. Neuroscience. 10 [PubMed]

Iacaruso MF, Gasler IT, Hofer SB. (2017). Synaptic organization of visual space in primary visual cortex. Nature. 547 [PubMed]

Jia H, Rochefort NL, Chen X, Konnerth A. (2010). Dendritic organization of sensory input to cortical neurons in vivo. Nature. 464 [PubMed]

Kasthuri N et al. (2015). Saturated Reconstruction of a Volume of Neocortex. Cell. 162 [PubMed]

Knill DC, Pouget A. (2004). The Bayesian brain: the role of uncertainty in neural coding and computation. Trends in neurosciences. 27 [PubMed]

Ko H et al. (2013). The emergence of functional microcircuits in visual cortex. Nature. 496 [PubMed]

Körding KP, Wolpert DM. (2006). Bayesian decision theory in sensorimotor control. Trends in cognitive sciences. 10 [PubMed]

Lake BM, Salakhutdinov R, Tenenbaum JB. (2015). Human-level concept learning through probabilistic program induction. Science (New York, N.Y.). 350 [PubMed]

Latham PE, Aitchison L. (2014). Bayesian synaptic plasticity makes predictions about plasticity experiments in vivo arXiv.

Latham PE, Aitchison L. (2015). Synaptic sampling: A connection between PSP variability and uncertainty explains neurophysiological observations arXiv, arXiv:1505.04544v2.

Lee WC et al. (2016). Anatomy and function of an excitatory network in the visual cortex. Nature. 532 [PubMed]

Letzkus JJ, Kampa BM, Stuart GJ. (2006). Learning rules for spike timing-dependent plasticity depend on dendritic synapse location. The Journal of neuroscience : the official journal of the Society for Neuroscience. 26 [PubMed]

Loebel A, Le Bé JV, Richardson MJ, Markram H, Herz AV. (2013). Matched pre- and post-synaptic changes underlie synaptic plasticity over long time scales. The Journal of neuroscience : the official journal of the Society for Neuroscience. 33 [PubMed]

Madarasz TJ et al. (2016). Evaluation of ambiguous associations in the amygdala by learning the structure of the environment. Nature neuroscience. 19 [PubMed]

Manita S et al. (2015). A Top-Down Cortical Circuit for Accurate Sensory Perception. Neuron. 86 [PubMed]

Markram H, Lübke J, Frotscher M, Roth A, Sakmann B. (1997). Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. The Journal of physiology. 500 ( Pt 2) [PubMed]

Markram H et al. (2015). Reconstruction and Simulation of Neocortical Microcircuitry. Cell. 163 [PubMed]

Matsuzaki M, Honkura N, Ellis-Davies GC, Kasai H. (2004). Structural basis of long-term potentiation in single dendritic spines. Nature. 429 [PubMed]

Moreno-Bote R. (2014). Poisson-like spiking in circuits with probabilistic synapses. PLoS computational biology. 10 [PubMed]

Moulines E, Douc R, Cappe O. (2005). Comparison of Resampling Schemes for Particle Filtering Image and Signal Processing and Analysis, ISPA 2005 Proceedings of the 4th International Symposium on..

Nessler B, Pfeiffer M, Buesing L, Maass W. (2013). Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity. PLoS computational biology. 9 [PubMed]

Orbán G, Berkes P, Fiser J, Lengyel M. (2016). Neural Variability and Sampling-Based Probabilistic Representations in the Visual Cortex. Neuron. 92 [PubMed]

Pfister JP, Toyoizumi T, Barber D, Gerstner W. (2006). Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning. Neural computation. 18 [PubMed]

Schmidt H et al. (2017). Axonal synapse sorting in medial entorhinal cortex. Nature. 549 [PubMed]

Scholl B, Wilson DE, Fitzpatrick D. (2017). Local Order within Global Disorder: Synaptic Architecture of Visual Space. Neuron. 96 [PubMed]

Segev I, London M. (2000). Untangling dendrites with quantitative models. Science (New York, N.Y.). 290 [PubMed]

Simoncelli EP, Olshausen BA. (2001). Natural image statistics and neural representation. Annual review of neuroscience. 24 [PubMed]

Sjöström PJ, Häusser M. (2006). A cooperative switch determines the sign of synaptic plasticity in distal dendrites of neocortical pyramidal neurons. Neuron. 51 [PubMed]

Smith SL, Smith IT, Branco T, Häusser M. (2013). Dendritic spikes enhance stimulus selectivity in cortical neurons in vivo. Nature. 503 [PubMed]

Soltani A, Wang XJ. (2010). Synaptic computation underlying probabilistic inference. Nature neuroscience. 13 [PubMed]

Staras K et al. (2010). A vesicle superpool spans multiple presynaptic terminals in hippocampal neurons. Neuron. 66 [PubMed]

Stuart G, Spruston N. (1998). Determinants of voltage attenuation in neocortical pyramidal neuron dendrites. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]

Ujfalussy BB, Makara JK, Branco T, Lengyel M. (2015). Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits. eLife. 4 [PubMed]

Urbanczik R, Senn W. (2014). Learning by the dendritic prediction of somatic spiking. Neuron. 81 [PubMed]

Watanabe S. (2001). Algebraic analysis for nonidentifiable learning machines. Neural computation. 13 [PubMed]

Williams SR, Stuart GJ. (2003). Role of dendritic synapse location in the control of action potential output. Trends in neurosciences. 26 [PubMed]

Yang G et al. (2014). Sleep promotes branch-specific formation of dendritic spines after learning. Science (New York, N.Y.). 344 [PubMed]

de Freitas JF, M Niranjan M, Gee AH, doucet A. (2000). Sequential monte carlo methods To train neural network models Neural computation. 12 [PubMed]

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