Encoding of configural regularity in the human visual system.
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Johan Wagemans | Jonas Kubilius | Hans P Op de Beeck | J. Wagemans | H. P. Op de Beeck | J. Kubilius
[1] A. O'Toole,et al. Prototype-referenced shape encoding revealed by high-level aftereffects , 2001, Nature Neuroscience.
[2] Johan Wagemans,et al. Development of differential sensitivity for shape changes resulting from linear and nonlinear planar transformations , 2011, i-Perception.
[3] W. R. Garner. The Processing of Information and Structure , 1974 .
[4] Jonas Kubilius,et al. A framework for streamlining research workflow in neuroscience and psychology , 2014, Front. Neuroinform..
[5] I. Biederman,et al. Dynamic binding in a neural network for shape recognition. , 1992, Psychological review.
[6] F. Attneave. Applications of information theory to psychology: A summary of basic concepts, methods, and results. , 1961 .
[7] Maria Alejandra Gonzalez-Perez,et al. Conceptual and Theoretical Foundations , 2014 .
[8] M. Masson,et al. Using confidence intervals in within-subject designs , 1994, Psychonomic bulletin & review.
[9] I. Biederman. Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.
[10] Johan Wagemans,et al. Dynamic prototypicality effects in visual search. , 2011, Journal of experimental psychology. General.
[11] C. Gilbert,et al. On a common circle: natural scenes and Gestalt rules. , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[12] Richard D. Morey,et al. Confidence Intervals from Normalized Data: A correction to Cousineau (2005) , 2008 .
[13] Jacob Feldman,et al. Regularity‐based Perceptual Grouping , 1997, Comput. Intell..
[14] M. Giese,et al. Norm-based face encoding by single neurons in the monkey inferotemporal cortex , 2006, Nature.
[15] Karl J. Friston. The free-energy principle: a rough guide to the brain? , 2009, Trends in Cognitive Sciences.
[16] Jacob Feldman,et al. Perceptual Grouping by Selection of a Logically Minimal Model , 2003, International Journal of Computer Vision.
[17] Jacob Feldman,et al. Formation of visual “objects” in the early computation of spatial relations , 2007, Perception & psychophysics.
[18] R. Andersen,et al. Functional analysis of human MT and related visual cortical areas using magnetic resonance imaging , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[19] Eero P. Simoncelli,et al. Efficient Coding of Spatial Information in the Primate Retina , 2012, The Journal of Neuroscience.
[20] I Biederman,et al. To what extent can matching algorithms based on direct outputs of spatial filters account for human object recognition? , 1996, Spatial vision.
[21] David D. Cox,et al. Opinion TRENDS in Cognitive Sciences Vol.11 No.8 Untangling invariant object recognition , 2022 .
[22] Alexei A. Efros,et al. What makes Paris look like Paris? , 2015, Commun. ACM.
[23] J. Hegdé,et al. A comparative study of shape representation in macaque visual areas v2 and v4. , 2007, Cerebral cortex.
[24] Russell A. Epstein,et al. Decoding the Representation of Multiple Simultaneous Objects in Human Occipitotemporal Cortex , 2009, Current Biology.
[25] G. Rhodes,et al. Adaptive norm-based coding of facial identity , 2006, Vision Research.
[26] Peter A. van der Helm. Simplicity in Vision: A Multidisciplinary Account of Perceptual Organization , 2014 .
[27] Jaakko Hintikka,et al. On the Logic of Perception , 1969 .
[28] Jacob Feldman,et al. Constructing perceptual categories , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[29] J. Feldman,et al. Bayes and the Simplicity Principle in Perception Simplicity versus Likelihood Principles in Perception , 2022 .
[30] H. B. Barlow,et al. Possible Principles Underlying the Transformations of Sensory Messages , 2012 .
[31] Irving Biederman,et al. Greater sensitivity to nonaccidental than metric changes in the relations between simple shapes in the lateral occipital cortex , 2012, NeuroImage.
[32] Emanuel Leeuwenberg,et al. Structural Information Theory: The Simplicity of Visual Form , 2012 .
[33] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[34] Jonathan W. Peirce,et al. PsychoPy—Psychophysics software in Python , 2007, Journal of Neuroscience Methods.
[35] R van Lier,et al. Integrating Global and Local Aspects of Visual Occlusion , 1994, Perception.
[36] Nikolaus Kriegeskorte,et al. Comparison of multivariate classifiers and response normalizations for pattern-information fMRI , 2010, NeuroImage.
[37] Joachim M. Buhmann,et al. Distortion Invariant Object Recognition in the Dynamic Link Architecture , 1993, IEEE Trans. Computers.
[38] J. R. Pomerantz,et al. A century of Gestalt psychology in visual perception: II. Conceptual and theoretical foundations. , 2012, Psychological bulletin.
[39] Stefan Pollmann,et al. PyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data , 2009, Neuroinformatics.
[40] David C. Van Essen,et al. Application of Information Technology: An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex , 2001, J. Am. Medical Informatics Assoc..
[41] Hans Op de Beeck,et al. The role of temporal context in norm-based encoding of faces , 2014 .
[42] Jonathan Westley Peirce,et al. Neuroinformatics Original Research Article Generating Stimuli for Neuroscience Using Psychopy , 2022 .
[43] Denis Cousineau,et al. Confidence intervals in within-subject designs: A simpler solution to Loftus and Masson's method , 2005 .
[44] David D. Cox,et al. What response properties do individual neurons need to underlie position and clutter "invariant" object recognition? , 2009, Journal of neurophysiology.
[45] Johan Wagemans,et al. Asymmetries in Stimulus Comparisons by Monkey and Man , 2003, Current Biology.
[46] Johan Wagemans,et al. Dynamic Norm-based Encoding for Unfamiliar Shapes in Human Visual Cortex , 2011, Journal of Cognitive Neuroscience.
[47] Irving Biederman,et al. The neural basis for shape preferences , 2011, Vision Research.
[48] J L Gallant,et al. Sparse coding and decorrelation in primary visual cortex during natural vision. , 2000, Science.
[49] F. Attneave. Some informational aspects of visual perception. , 1954, Psychological review.
[50] S. Palmer,et al. A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization. , 2012, Psychological bulletin.
[51] S. Edelman,et al. Human Brain Mapping 6:316–328(1998) � A Sequence of Object-Processing Stages Revealed by fMRI in the Human Occipital Lobe , 2022 .
[52] Hans P Op de Beeck,et al. The role of temporal context in norm-based encoding of faces , 2014, Psychonomic bulletin & review.
[53] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[54] Jeffrey S. Perry,et al. Edge co-occurrence in natural images predicts contour grouping performance , 2001, Vision Research.
[55] C. Connor,et al. Neural representations for object perception: structure, category, and adaptive coding. , 2011, Annual review of neuroscience.
[56] I. Biederman,et al. Representation of regular and irregular shapes in macaque inferotemporal cortex. , 2005, Cerebral cortex.
[57] I. Biederman,et al. Inferior Temporal Neurons Show Greater Sensitivity to Nonaccidental than to Metric Shape Differences , 2001, Journal of Cognitive Neuroscience.