Inhibitory cells enable sparse coding in V1 model (King et al. 2013)


King PD, Zylberberg J, DeWeese MR. (2013). Inhibitory interneurons decorrelate excitatory cells to drive sparse code formation in a spiking model of V1. The Journal of neuroscience : the official journal of the Society for Neuroscience. 33 [PubMed]

See more from authors: King PD · Zylberberg J · DeWeese MR

References and models cited by this paper

ATTNEAVE F. (1954). Some informational aspects of visual perception. Psychological review. 61 [PubMed]

Abbott LF, Nelson SB. (2000). Synaptic plasticity: taming the beast. Nature neuroscience. 3 Suppl [PubMed]

Ali AB, Bannister AP, Thomson AM. (2007). Robust correlations between action potential duration and the properties of synaptic connections in layer 4 interneurones in neocortical slices from juvenile rats and adult rat and cat. The Journal of physiology. 580 [PubMed]

Alitto HJ, Dan Y. (2010). Function of inhibition in visual cortical processing. Current opinion in neurobiology. 20 [PubMed]

Anderson JS, Carandini M, Ferster D. (2000). Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. Journal of neurophysiology. 84 [PubMed]

Atick JJ, Redlich AN. (1992). What does the Retina Know about Natural Scenes? Neural Comput. 4

BARLOW HB. (1961). Possible principles underlying the transformations of sensory messages Sensory Communication.

Bell AJ, Sejnowski TJ. (1997). The "independent components" of natural scenes are edge filters. Vision research. 37 [PubMed]

Bi GQ, Poo MM. (1998). Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]

Bourgeois JP, Rakic P. (1993). Changes of synaptic density in the primary visual cortex of the macaque monkey from fetal to adult stage. The Journal of neuroscience : the official journal of the Society for Neuroscience. 13 [PubMed]

Carlson NL, Ming VL, Deweese MR. (2012). Sparse codes for speech predict spectrotemporal receptive fields in the inferior colliculus. PLoS computational biology. 8 [PubMed]

Clopath C, Büsing L, Vasilaki E, Gerstner W. (2010). Connectivity reflects coding: a model of voltage-based STDP with homeostasis. Nature neuroscience. 13 [PubMed]

Dan Y, Atick JJ, Reid RC. (1996). Efficient coding of natural scenes in the lateral geniculate nucleus: experimental test of a computational theory. The Journal of neuroscience : the official journal of the Society for Neuroscience. 16 [PubMed]

Dan Y, Poo MM. (2004). Spike timing-dependent plasticity of neural circuits. Neuron. 44 [PubMed]

DeWeese MR, Wehr M, Zador AM. (2003). Binary spiking in auditory cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 23 [PubMed]

Eccles J. (1976). From electrical to chemical transmission in the central nervous system. Notes and records of the Royal Society of London. 30 [PubMed]

Ecker AS et al. (2010). Decorrelated neuronal firing in cortical microcircuits. Science (New York, N.Y.). 327 [PubMed]

Espinosa JS, Stryker MP. (2012). Development and plasticity of the primary visual cortex. Neuron. 75 [PubMed]

Evans BD, Stringer SM. (2012). Transformation-invariant visual representations in self-organizing spiking neural networks. Frontiers in computational neuroscience. 6 [PubMed]

Feldman DE. (2009). Synaptic mechanisms for plasticity in neocortex. Annual review of neuroscience. 32 [PubMed]

Ferster D. (1986). Orientation selectivity of synaptic potentials in neurons of cat primary visual cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 6 [PubMed]

Ferster D, Miller KD. (2000). Neural mechanisms of orientation selectivity in the visual cortex. Annual review of neuroscience. 23 [PubMed]

Földiák P. (1990). Forming sparse representations by local anti-Hebbian learning. Biological cybernetics. 64 [PubMed]

Gonchar Y, Burkhalter A. (1999). Connectivity of GABAergic calretinin-immunoreactive neurons in rat primary visual cortex. Cerebral cortex (New York, N.Y. : 1991). 9 [PubMed]

Haider B et al. (2010). Synaptic and network mechanisms of sparse and reliable visual cortical activity during nonclassical receptive field stimulation. Neuron. 65 [PubMed]

Hebb DO. (1949). The Organization Of Behavior.

Heeger DJ. (1992). Normalization of cell responses in cat striate cortex. Visual neuroscience. 9 [PubMed]

Hensch TK. (2005). Critical period plasticity in local cortical circuits. Nature reviews. Neuroscience. 6 [PubMed]

Hirsch JA et al. (2003). Functionally distinct inhibitory neurons at the first stage of visual cortical processing. Nature neuroscience. 6 [PubMed]

Hromádka T, Deweese MR, Zador AM. (2008). Sparse representation of sounds in the unanesthetized auditory cortex. PLoS biology. 6 [PubMed]

Isaacson JS, Scanziani M. (2011). How inhibition shapes cortical activity. Neuron. 72 [PubMed]

Kerlin AM, Andermann ML, Berezovskii VK, Reid RC. (2010). Broadly tuned response properties of diverse inhibitory neuron subtypes in mouse visual cortex. Neuron. 67 [PubMed]

Kording KP, Klein DJ, Konig PK. (2003). Sparse spectrotemporal coding of sounds EURASIP J Appl Sig Proc. 2003

Laughlin S. (1981). A simple coding procedure enhances a neuron's information capacity. Zeitschrift fur Naturforschung. Section C, Biosciences. 36 [PubMed]

Laughlin SB. (2001). Energy as a constraint on the coding and processing of sensory information. Current opinion in neurobiology. 11 [PubMed]

Lennie P. (2003). The cost of cortical computation. Current biology : CB. 13 [PubMed]

Liu BH et al. (2011). Broad inhibition sharpens orientation selectivity by expanding input dynamic range in mouse simple cells. Neuron. 71 [PubMed]

Lochmann T, Deneve S. (2011). Neural processing as causal inference. Current opinion in neurobiology. 21 [PubMed]

Lochmann T, Ernst UA, Denève S. (2012). Perceptual inference predicts contextual modulations of sensory responses. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]

Maffei A, Nataraj K, Nelson SB, Turrigiano GG. (2006). Potentiation of cortical inhibition by visual deprivation. Nature. 443 [PubMed]

Markram H et al. (2004). Interneurons of the neocortical inhibitory system. Nature reviews. Neuroscience. 5 [PubMed]

Masquelier T. (2012). Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model. Journal of computational neuroscience. 32 [PubMed]

Masquelier T, Guyonneau R, Thorpe SJ. (2009). Competitive STDP-based spike pattern learning. Neural computation. 21 [PubMed]

McLaughlin D, Shapley R, Shelley M, Wielaard DJ. (2000). A neuronal network model of macaque primary visual cortex (V1): orientation selectivity and dynamics in the input layer 4Calpha. Proceedings of the National Academy of Sciences of the United States of America. 97 [PubMed]

Oja E. (1982). A simplified neuron model as a principal component analyzer. Journal of mathematical biology. 15 [PubMed]

Olshausen BA, Field DJ. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature. 381 [PubMed]

Olshausen BA, Field DJ. (1997). Sparse coding with an overcomplete basis set: a strategy employed by V1? Vision research. 37 [PubMed]

Perrinet LU. (2010). Role of homeostasis in learning sparse representations. Neural computation. 22 [PubMed]

Rao RP, Ballard DH. (1999). Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nature neuroscience. 2 [PubMed]

Rehn M, Sommer FT. (2007). A network that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. Journal of computational neuroscience. 22 [PubMed]

Rieke F, Warland D, de Ruyter van Steveninck, R, Bialek B. (1997). Spikes: Exploring The Neural Code.

Rozell CJ, Johnson DH, Baraniuk RG, Olshausen BA. (2008). Sparse coding via thresholding and local competition in neural circuits. Neural computation. 20 [PubMed]

Sakata S, Harris KD. (2009). Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex. Neuron. 64 [PubMed]

Salinas E, Abbott LF. (1994). Vector reconstruction from firing rates. Journal of computational neuroscience. 1 [PubMed]

Savin C, Joshi P, Triesch J. (2010). Independent component analysis in spiking neurons. PLoS computational biology. 6 [PubMed]

Smith EC, Lewicki MS. (2006). Efficient auditory coding. Nature. 439 [PubMed]

Somogyi P, Kisvárday ZF, Martin KA, Whitteridge D. (1983). Synaptic connections of morphologically identified and physiologically characterized large basket cells in the striate cortex of cat. Neuroscience. 10 [PubMed]

Spratling MW. (2010). Predictive coding as a model of response properties in cortical area V1. The Journal of neuroscience : the official journal of the Society for Neuroscience. 30 [PubMed]

Tamás G, Somogyi P, Buhl EH. (1998). Differentially interconnected networks of GABAergic interneurons in the visual cortex of the cat. The Journal of neuroscience : the official journal of the Society for Neuroscience. 18 [PubMed]

Thomson AM, Lamy C. (2007). Functional maps of neocortical local circuitry. Frontiers in neuroscience. 1 [PubMed]

Tolhurst DJ, Smyth D, Thompson ID. (2009). The sparseness of neuronal responses in ferret primary visual cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience. 29 [PubMed]

Turrigiano G. (2011). Too many cooks? Intrinsic and synaptic homeostatic mechanisms in cortical circuit refinement. Annual review of neuroscience. 34 [PubMed]

Vinje WE, Gallant JL. (2000). Sparse coding and decorrelation in primary visual cortex during natural vision. Science (New York, N.Y.). 287 [PubMed]

Vinje WE, Gallant JL. (2002). Natural stimulation of the nonclassical receptive field increases information transmission efficiency in V1. The Journal of neuroscience : the official journal of the Society for Neuroscience. 22 [PubMed]

Yoshimura Y, Dantzker JL, Callaway EM. (2005). Excitatory cortical neurons form fine-scale functional networks. Nature. 433 [PubMed]

Zhao L, Zhaoping L. (2011). Understanding auditory spectro-temporal receptive fields and their changes with input statistics by efficient coding principles. PLoS computational biology. 7 [PubMed]

Zylberberg J, Murphy JT, DeWeese MR. (2011). A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields. PLoS computational biology. 7 [PubMed]

References and models that cite this paper

Cayco-Gajic NA, Clopath C, Silver RA. (2017). Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks. Nature communications. 8 [PubMed]

This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.