Gaussian process methods for estimating cortical maps
暂无分享,去创建一个
Matthias Bethge | Matthias Kaschube | Jakob H. Macke | Leonard E. White | Sebastian Gerwinn | M. Bethge | J. Macke | L. White | M. Kaschube | S. Gerwinn
[1] S. Levay,et al. Ocular dominance columns and their development in layer IV of the cat's visual cortex: A quantitative study , 1978, The Journal of comparative neurology.
[2] Brian Everitt,et al. An Introduction to Latent Variable Models , 1984 .
[3] G. Blasdel,et al. Voltage-sensitive dyes reveal a modular organization in monkey striate cortex , 1986, Nature.
[4] M. Cynader,et al. Surface organization of orientation and direction selectivity in cat area 18 , 1987, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[5] Amiram Grinvald,et al. Iso-orientation domains in cat visual cortex are arranged in pinwheel-like patterns , 1991, Nature.
[6] G. Blasdel,et al. Orientation selectivity, preference, and continuity in monkey striate cortex , 1992, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[7] Lawrence Sirovich,et al. Management and Analysis of Large Scientific Datasets , 1992 .
[8] Noel A Cressie,et al. Statistics for Spatial Data. , 1992 .
[9] T. Bonhoeffer,et al. Optimal Smoothness of Orientation Preference Maps , 1994 .
[10] Klaus Schulten,et al. Models of Orientation and Ocular Dominance Columns in the Visual Cortex: A Critical Comparison , 1995, Neural Computation.
[11] D. Fitzpatrick,et al. A systematic map of direction preference in primary visual cortex , 1996, Nature.
[12] Lawrence Sirovich,et al. Separating spatially distributed response to stimulation from background. I. Optical imaging , 1997, Biological Cybernetics.
[13] A. Grinvald,et al. Spatial Relationships among Three Columnar Systems in Cat Area 17 , 1997, The Journal of Neuroscience.
[14] F. Wolf,et al. Spontaneous pinwheel annihilation during visual development , 1998, Nature.
[15] D. Fitzpatrick,et al. Unequal representation of cardinal and oblique contours in ferret visual cortex. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[16] Nicholas V. Swindale,et al. Orientation tuning curves: empirical description and estimation of parameters , 1998, Biological Cybernetics.
[17] S. M. Williams,et al. Maps of Central Visual Space in Ferret V1 and V2 Lack Matching Inputs from the Two Eyes , 1999, The Journal of Neuroscience.
[18] A Shmuel,et al. Coexistence of linear zones and pinwheels within orientation maps in cat visual cortex. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[19] Christopher K. I. Williams,et al. Using the Nyström Method to Speed Up Kernel Machines , 2000, NIPS.
[20] E. Kaplan,et al. A Principal Components-Based Method for the Detection of Neuronal Activity Maps: Application to Optical Imaging , 2000, NeuroImage.
[21] K. Obermayer,et al. Principal Component Analysis and Blind Separation of Sources for Optical Imaging of Intrinsic Signals , 2000, NeuroImage.
[22] M. Stryker,et al. Spatial Frequency Maps in Cat Visual Cortex , 2000, The Journal of Neuroscience.
[23] L. Sirovich,et al. An Optimization Approach to Signal Extraction from Noisy Multivariate Data , 2001, NeuroImage.
[24] Dan Cornford,et al. Online Approximations for Wind-Field Models , 2001, ICANN.
[25] W H Bosking,et al. Consistent mapping of orientation preference across irregular functional domains in ferret visual cortex , 2001, Visual Neuroscience.
[26] Karl J. Friston,et al. Bayesian Estimation of Dynamical Systems: An Application to fMRI , 2002, NeuroImage.
[27] A. Sornborger,et al. Spatiotemporal analysis of optical imaging data , 2003, NeuroImage.
[28] Michael P. Stryker,et al. New Paradigm for Optical Imaging Temporally Encoded Maps of Intrinsic Signal , 2003, Neuron.
[29] Michael I. Jordan,et al. Kernel independent component analysis , 2003 .
[30] Andrew McCallum,et al. Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data , 2004, J. Mach. Learn. Res..
[31] E. L. Schwartz,et al. Cat and monkey cortical columnar patterns modeled by bandpass-filtered 2D white noise , 1990, Biological Cybernetics.
[32] L. Sirovich,et al. The organization of orientation and spatial frequency in primary visual cortex. , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[33] Neil D. Lawrence,et al. Learning to learn with the informative vector machine , 2004, ICML.
[34] M. Opper,et al. inverse problems: some new approaches , 2022 .
[35] M. A. Carreira-Perpiñán,et al. Influence of lateral connections on the structure of cortical maps. , 2004, Journal of neurophysiology.
[36] D. Chklovskii,et al. Maps in the brain: what can we learn from them? , 2004, Annual review of neuroscience.
[37] Christopher K. I. Williams,et al. Using the Equivalent Kernel to Understand Gaussian Process Regression , 2004, NIPS.
[38] F. Tong,et al. Decoding the visual and subjective contents of the human brain , 2005, Nature Neuroscience.
[39] L. Sirovich,et al. Extraction of the average and differential dynamical response in stimulus-locked experimental data , 2005, Journal of Neuroscience Methods.
[40] Sooyoung Chung,et al. Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex , 2005, Nature.
[41] E. Schwartz,et al. Physical limits to spatial resolution of optical recording: clarifying the spatial structure of cortical hypercolumns. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[42] Karl J. Friston,et al. Bayesian fMRI time series analysis with spatial priors , 2005, NeuroImage.
[43] Yee Whye Teh,et al. Semiparametric latent factor models , 2005, AISTATS.
[44] Seong-Gi Kim,et al. Mapping Iso-Orientation Columns by Contrast Agent-Enhanced Functional Magnetic Resonance Imaging: Reproducibility, Specificity, and Evaluation by Optical Imaging of Intrinsic Signal , 2006, The Journal of Neuroscience.
[45] G. Rees,et al. Neuroimaging: Decoding mental states from brain activity in humans , 2006, Nature Reviews Neuroscience.
[46] Donald Robertson,et al. Maximum likelihood factor analysis with rank-deficient sample covariance matrices , 2007 .
[47] Andrew McCallum,et al. Piecewise pseudolikelihood for efficient training of conditional random fields , 2007, ICML '07.
[48] G. Goodhill. Contributions of Theoretical Modeling to the Understanding of Neural Map Development , 2007, Neuron.
[49] Wolfram Burgard,et al. Most likely heteroscedastic Gaussian process regression , 2007, ICML '07.
[50] Essa Yacoub,et al. High-field fMRI unveils orientation columns in humans , 2008, Proceedings of the National Academy of Sciences.
[51] Stephen D. Van Hooser,et al. Experience with moving visual stimuli drives the early development of cortical direction selectivity , 2008, Nature.
[52] M. Carandini,et al. Neuronal Selectivity and Local Map Structure in Visual Cortex , 2008, Neuron.
[53] F. Wolf,et al. Self-organization and the selection of pinwheel density in visual cortical development , 2008, 0801.3651.
[54] N. Cressie,et al. Fixed rank kriging for very large spatial data sets , 2008 .
[55] John P. Cunningham,et al. Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity , 2008, NIPS.
[56] Ari Rosenberg,et al. Models and measurements of functional maps in V1. , 2008, Journal of neurophysiology.
[57] Huajin Tang,et al. Natural scene statistics and the structure of orientation maps in the visual cortex , 2009, NeuroImage.
[58] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[59] Matthias W. Seeger,et al. Convex variational Bayesian inference for large scale generalized linear models , 2009, ICML '09.
[60] Matthias Bethge,et al. Bayesian estimation of orientation preference maps , 2009, NIPS.
[61] P. Kara,et al. A micro-architecture for binocular disparity and ocular dominance in visual cortex , 2009, Nature.
[62] Karl J. Friston,et al. Topological FDR for neuroimaging , 2010, NeuroImage.
[63] Kamiar Rahnama Rad,et al. Efficient, adaptive estimation of two-dimensional firing rate surfaces via Gaussian process methods , 2010, Network.