TemporalPrecisionintheVisualPathwaythroughthe InterplayofExcitationandStimulus-DrivenSuppression
暂无分享,去创建一个
[1] Eero P. Simoncelli,et al. Spatio-temporal correlations and visual signalling in a complete neuronal population , 2008, Nature.
[2] W. Gerstner,et al. Chapter 12 A framework for spiking neuron models: The spike response model , 2001 .
[3] William Bialek,et al. Synergy in a Neural Code , 2000, Neural Computation.
[4] Michael J. Berry,et al. The Neural Code of the Retina , 1999, Neuron.
[5] Michael J. Berry,et al. Selectivity for multiple stimulus features in retinal ganglion cells. , 2006, Journal of neurophysiology.
[6] E J Chichilnisky,et al. A simple white noise analysis of neuronal light responses , 2001, Network.
[7] D. Contreras,et al. Dynamics of excitation and inhibition underlying stimulus selectivity in rat somatosensory cortex , 2005, Nature Neuroscience.
[8] Christopher L Passaglia,et al. Information transmission rates of cat retinal ganglion cells. , 2004, Journal of neurophysiology.
[9] P. McCullagh,et al. Generalized Linear Models , 1992 .
[10] R. Reid,et al. Temporal Coding of Visual Information in the Thalamus , 2000, The Journal of Neuroscience.
[11] M. Carandini,et al. Functional Mechanisms Shaping Lateral Geniculate Responses to Artificial and Natural Stimuli , 2008, Neuron.
[12] Guangying K. Wu,et al. Lateral Sharpening of Cortical Frequency Tuning by Approximately Balanced Inhibition , 2008, Neuron.
[13] Michael J. Berry,et al. Anticipation of moving stimuli by the retina , 1999, Nature.
[14] N. C. Singh,et al. Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli , 2001 .
[15] W. Martin Usrey,et al. Spike Timing and Information Transmission at Retinogeniculate Synapses , 2010, The Journal of Neuroscience.
[16] T. Albright,et al. Efficient Discrimination of Temporal Patterns by Motion-Sensitive Neurons in Primate Visual Cortex , 1998, Neuron.
[17] B. Cleland,et al. Organization of visual inputs to interneurons of lateral geniculate nucleus of the cat. , 1977, Journal of neurophysiology.
[18] Robert Shapley,et al. Linear and nonlinear systems analysis of the visual system: Why does it seem so linear? A review dedicated to the memory of Henk Spekreijse , 2009, Vision Research.
[19] Lawrence C. Sincich,et al. Preserving Information in Neural Transmission , 2009, The Journal of Neuroscience.
[20] Matteo Carandini,et al. Thalamic filtering of retinal spike trains by postsynaptic summation. , 2007, Journal of vision.
[21] J D Victor,et al. How the contrast gain control modifies the frequency responses of cat retinal ganglion cells. , 1981, The Journal of physiology.
[22] J. B. Demb,et al. Disinhibition Combines with Excitation to Extend the Operating Range of the OFF Visual Pathway in Daylight , 2008, The Journal of Neuroscience.
[23] Nicholas J. Priebe,et al. Mechanisms underlying cross-orientation suppression in cat visual cortex , 2006, Nature Neuroscience.
[24] John P. Miller,et al. Temporal encoding in nervous systems: A rigorous definition , 1995, Journal of Computational Neuroscience.
[25] Eero P. Simoncelli,et al. Natural signal statistics and sensory gain control , 2001, Nature Neuroscience.
[26] Jessica A. Cardin,et al. Stimulus Feature Selectivity in Excitatory and Inhibitory Neurons in Primary Visual Cortex , 2007, The Journal of Neuroscience.
[27] Xin Wang,et al. Recoding of Sensory Information across the Retinothalamic Synapse , 2010, The Journal of Neuroscience.
[28] Matteo Carandini,et al. Somatosensory Integration Controlled by Dynamic Thalamocortical Feed-Forward Inhibition , 2005, Neuron.
[29] E. Chichilnisky,et al. Adaptation to Temporal Contrast in Primate and Salamander Retina , 2001, The Journal of Neuroscience.
[30] Alexander Borst,et al. Information theory and neural coding , 1999, Nature Neuroscience.
[31] Pamela Reinagel,et al. Contrast adaptation in a nonadapting LGN model. , 2007, Journal of neurophysiology.
[32] L. Paninski,et al. Inferring input nonlinearities in neural encoding models , 2008, Network.
[33] Konrad Paul Kording,et al. Processing of complex stimuli and natural scenes in the visual cortex , 2004, Current Opinion in Neurobiology.
[34] R. Shapley,et al. The receptive field organization of X-cells in the cat: Spatiotemporal coupling and asymmetry , 1984, Vision Research.
[35] David R. Brillinger,et al. Nerve Cell Spike Train Data Analysis: A Progression of Technique , 1992 .
[36] Garrett B Stanley,et al. Decoupling functional mechanisms of adaptive encoding , 2006, Network.
[37] L. Paninski. Maximum likelihood estimation of cascade point-process neural encoding models , 2004, Network.
[38] P. McCullagh,et al. Generalized Linear Models , 1984 .
[39] Romesh D Kumbhani,et al. Precision, reliability, and information-theoretic analysis of visual thalamocortical neurons. , 2007, Journal of neurophysiology.
[40] T. Sharpee,et al. Estimating linear–nonlinear models using Rényi divergences , 2009, Network.
[41] J. B. Demb,et al. Contrast Adaptation in Subthreshold and Spiking Responses of Mammalian Y-Type Retinal Ganglion Cells , 2005, The Journal of Neuroscience.
[42] Fred Rieke,et al. Network Variability Limits Stimulus-Evoked Spike Timing Precision in Retinal Ganglion Cells , 2006, Neuron.
[43] Wade G. Regehr,et al. Timing and Specificity of Feed-Forward Inhibition within the LGN , 2005, Neuron.
[44] Garrett B Stanley,et al. Timing Precision in Population Coding of Natural Scenes in the Early Visual System , 2008, PLoS biology.
[45] Uri T Eden,et al. A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects. , 2005, Journal of neurophysiology.
[46] Brian Lau,et al. Computational subunits of visual cortical neurons revealed by artificial neural networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[47] Liam Paninski,et al. Convergence properties of three spike-triggered analysis techniques , 2003, NIPS.
[48] Youping Xiao,et al. A simple model of retina-LGN transmission , 2008, Journal of Computational Neuroscience.
[49] Ryan J. Prenger,et al. Nonlinear V1 responses to natural scenes revealed by neural network analysis , 2004, Neural Networks.
[50] Elena A Allen,et al. Dynamic Spatial Processing Originates in Early Visual Pathways , 2006, The Journal of Neuroscience.
[51] M J Korenberg,et al. Dissection of the neuron network in the catfish inner retina. III. Interpretation of spike kernels. , 1989, Journal of neurophysiology.
[52] Michael Okun,et al. Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities , 2008, Nature Neuroscience.
[53] Chun-I Yeh,et al. Receptive field size and response latency are correlated within the cat visual thalamus. , 2005, Journal of neurophysiology.
[54] Kamiar Rahnama Rad,et al. Efficient, adaptive estimation of two-dimensional firing rate surfaces via Gaussian process methods , 2010, Network.
[55] William Bialek,et al. Real-time performance of a movement-sensitive neuron in the blowfly visual system: coding and information transfer in short spike sequences , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[56] Nicole C. Rust,et al. Do We Know What the Early Visual System Does? , 2005, The Journal of Neuroscience.
[57] W. Martin Usrey,et al. Origin and Dynamics of Extraclassical Suppression in the Lateral Geniculate Nucleus of the Macaque Monkey , 2008, Neuron.
[58] Wei Wu,et al. A new look at state-space models for neural data , 2010, Journal of Computational Neuroscience.
[59] Chun-I Yeh,et al. Temporal precision in the neural code and the timescales of natural vision , 2007, Nature.
[60] Eero P. Simoncelli,et al. To appear in: The New Cognitive Neurosciences, 3rd edition Editor: M. Gazzaniga. MIT Press, 2004. Characterization of Neural Responses with Stochastic Stimuli , 2022 .
[61] Liam Paninski,et al. Statistical models for neural encoding, decoding, and optimal stimulus design. , 2007, Progress in brain research.
[62] Eero P. Simoncelli,et al. Dimensionality reduction in neural models: an information-theoretic generalization of spike-triggered average and covariance analysis. , 2006, Journal of vision.
[63] Xin Wang,et al. Thalamic interneurons and relay cells use complementary synaptic mechanisms for visual processing , 2010, Nature Neuroscience.
[64] Robert C. Liu,et al. Variability and information in a neural code of the cat lateral geniculate nucleus. , 2001, Journal of neurophysiology.
[65] William Bialek,et al. Analyzing Neural Responses to Natural Signals: Maximally Informative Dimensions , 2002, Neural Computation.
[66] R. Reid,et al. Predicting Every Spike A Model for the Responses of Visual Neurons , 2001, Neuron.
[67] Garrett B Stanley,et al. The episodic nature of spike trains in the early visual pathway. , 2010, Journal of neurophysiology.
[68] J. Gallant,et al. Complete functional characterization of sensory neurons by system identification. , 2006, Annual review of neuroscience.
[69] R. Shapley,et al. The effect of contrast on the transfer properties of cat retinal ganglion cells. , 1978, The Journal of physiology.