Visual Cortex
Our goal is to understand the development and function of the visual cortex through computational modeling. The main idea is that the visual cortex is a continuously-adapting structure in a dynamic equilibrium with the external environment, and that lateral connections and synchronization of spiking activity are crucial to its behavior.
People
     [Expand to show all 16][Minimize]
James A. Bednar Postdoctoral Alumni jbednar [at] inf ed ac uk
Yoonsuck Choe Ph.D. Alumni choe [at] tamu edu
Judah De Paula Ph.D. Alumni
Igor Farkas Postdoctoral Alumni farkas [at] fmph uniba sk
Wilson S. Geisler Formerly affiliated Collaborator geisler [at] psy utexas edu
Andrea Haessly Masters Alumni
Stefanie Jegelka Formerly affiliated Visitor stefje [at] eecs berkeley edu
Amol Kelkar Masters Alumni
Risto Miikkulainen Faculty risto [at] cs utexas edu
Enrique Muro Formerly affiliated Visitor
Jefferson Provost Ph.D. Alumni jefferson provost [at] gmail com
Jefferson Provost Ph.D. Alumni jefferson provost [at] gmail com
Eyal Seidemann Formerly affiliated Collaborator eyal [at] mail cps utexas edu
Joseph Sirosh Ph.D. Alumni joseph sirosh [at] gmail com
Yiu Fai Sit Ph.D. Alumni yfsit [at] cs utexas edu
Tal Tversky Ph.D. Alumni tal [at] cs utexas edu
Publications
     [Expand to show all 54][Minimize]
A Population Gain Control Model of Spatiotemporal Responses in the Visual Cortex 2009
Yiu Fai Sit, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. Technical Report AI09-06.
Complex Dynamics of V1 Population Responses Explained by a Simple Gain-Control Model 2009
Yiu Fai Sit, Yuzhi Chen, Wilson S. Geisler, Risto Miikkulainen, and Eyal Seidemann, Neuron, Vol. 64 (2009), pp. 943-956.
Computational Predictions on the Receptive Fields and Organization of V2 for Shape Processing 2009
Yiu Fai Sit and Risto Miikkulainen, Neural Computation, Vol. 21, 3 (2009), pp. 762--785.
A Computational Model of the Signals in Optical Imaging with Voltage-Sensitive Dyes 2007
Yiu Fai Sit and Risto Miikkulainen, Neurocomputing (2007), pp. 1853-1857.
Developing Complex Systems Using Evolved Pattern Generators 2007
Vinod K. Valsalam, James A. Bednar and Risto Miikkulainen, IEEE Transactions on Evolutionary Computation (2007), pp. 181-198.
Modeling the self-organization of color selectivity in the visual cortex 2007
Judah Ben De Paula, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Converting RGB Images to LMS Cone Activations 2006
Judah B. De Paula, Technical Report, Department of Computer Sciences, The University of Texas at Austin. Technical Report 06-49.
Establishing an Appropriate Learning Bias Through Development 2006
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen, In Proceedings of the Fifth International Conference on Development and Learning (ICDL-2006) 2006.
Joint Maps for Orientation, Eye, and Direction Preference in a Self-Organizing Model of V1 2006
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1272--1276.
Prenatal Development of Ocular Dominance and Orientation Maps in a Self-Organizing Model of V1 2006
Stefanie Jegelka, James A. Bednar, and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1291--1296.
Self-Organization of Hierarchical Visual Maps with Feedback Connections 2006
Yiu Fai Sit and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1309-1312.
Constructing Good Learners Using Evolved Pattern Generators 2005
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2005, H.-G. Beyer and others (Eds.), pp. 11-18 2005.
Constructing Visual Function Through Prenatal and Postnatal Learning 2005
James A. Bednar and Risto Miikkulainen, In Neuroconstructivism, Vol. 2: Perspectives and Prospects, Denis Mareschal and Mark H. Johnson and Sylvain Sirois and Michael Spratling and Michael S. C. Thomas and Gert Westermann (Eds.), pp....
Self-organization of color opponent receptive fields and laterally connected orientation maps 2005
James A. Bednar, Judah B. De Paula, and Risto Miikkulainen, Neurocomputing, Vol. 65--66 (2005), pp. 69-76.
Contour Integration and Segmentation with Self-Organized Lateral Connections 2004
Yoonsuck Choe and Risto Miikkulainen, Biological Cybernetics 90:75-88
Modeling Cortical Maps with Topographica 2004
James A. Bednar, Yoonsuck Choe, Judah De Paula, Risto Miikkulainen, Jefferson Provost, and Tal Tversky, Neurocomputing (2004), pp. 1129-1135.
Prenatal and Postnatal Development of Laterally Connected Orientation Maps 2004
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 58-60 (2004), pp. 985-992.
Learning Innate Face Preferences 2003
James A. Bednar and Risto Miikkulainen, Neural Computation, Vol. 15, 7 (2003), pp. 1525-1557.
Self-Organization of Spatiotemporal Receptive Fields and Laterally Connected Direction and Orientation Maps 2003
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 52--54 (2003), pp. 473-480.
The Role of Internally Generated Neural Activity in Newborn and Infant Face Preferences 2003
James A. Bednar, In Face Perception in Infancy and Early Childhood, Olivier Pascalis and Alan Slater (Eds.), pp. 133-142, New York 2003. NOVA Science Publishers.
Learning to See: Genetic and Environmental Influences on Visual Development 2002
James A. Bednar, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Also Technical Report AI-TR-02-294.
Modeling Directional Selectivity Using Self-Organizing Delay-Adaptation Maps 2002
Tal Tversky and Risto Miikkulainen, Neurocomputing, Vol. 44--46 (2002), pp. 679--684. Also in J. M. Bower (editor), Computational Neuroscience: Trends in Research, 2002 (CNS*01, Pacific Grove, CA). New York: Elsevier.
Modeling Large Cortical Networks With Growing Self-Organizing Maps 2002
James A. Bednar, Amol Kelkar, and Risto Miikkulainen, Neurocomputing, Vol. 44--46 (2002), pp. 315-321.
Neonatal Learning Of Faces: Environmental And Genetic Influences 2002
James A. Bednar and Risto Miikkulainen, In Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 107-112 2002.
Perceptual Grouping In A Self-Organizing Map Of Spiking Neurons 2001
Yoonsuck Choe, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 133. Technical Report AI01-292.
Scaling Self-Organizing Maps To Model Large Cortical Networks 2001
James A. Bednar, Amol Kelkar, and Risto Miikkulainen, Neuroinformatics (2001), pp. 275-302.
A Self-Organizing Neural Network For Contour Integration Through Synchronized Firing 2000
Yoonsuck Choe and Risto Miikkulainen, Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000, Austin, TX), 123-128. Cambridge, MA: MIT Press, 2000
Effects Of Presynaptic And Postsynaptic Resource Redistribution In Hebbian Weight Adaptation 2000
Yoonsuck Choe, Risto Miikkulainen, and Lawrence K. Cormack, Neurocomputing, Vol. 32--33 (2000), pp. 77-82.
Internally-Generated Activity, Non-Episodic Memory, and Emotional Salience in Sleep 2000
James A. Bednar, Behavioral and Brain SciencesS. Harnad and E. Pace-Schott and M. Blagrove and M. Solms (Eds.) (2000), pp. 119-120. Cambridge University Press. Commentary on the 'Sleep and Dreaming' issue..
Self-Organization Of Innate Face Preferences: Could Genetics Be Expressed Through Learning? 2000
James A. Bednar and Risto Miikkulainen, In Proceedings of the 17th National Conference on Artificial Intelligence and the 12th Annual Conference on Innovative Applications of Artificial Intelligence, pp. 117-122 2000.
Tilt Aftereffects In A Self-Organizing Model Of The Primary Visual Cortex 2000
James A. Bednar and Risto Miikkulainen, Neural Computation, Vol. 12 (2000), pp. 1721-1740.
Modeling The Self-Organization Of Directional Selectivity In The Primary Visual Cortex 1999
Igor Farkas and Risto Miikkulainen, In Proceedings of the Ninth International Conference on Artificial Neural Networks, Erkki Oja and Samuel Kaski (Eds.), pp. 251-256, Amsterdam 1999. Elsevier.
Pattern-Generator-Driven Development In Self-Organizing Models 1998
James A. Bednar and Risto Miikkulainen, In Computational Neuroscience: Trends in Research, 1998, pp. 317-323 1998.
Self-Organization And Segmentation In A Laterally Connected Orientation Map Of Spiking Neurons 1998
Yoonsuck Choe and Risto Miikkulainen, Neurocomputing (1998), pp. 139-157.
Self-Organization And Segmentation With Laterally Connected Spiking Neurons 1997
Yoonsuck Choe and Risto Miikkulainen, In Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97), pp. 1120-1125, Nagoya, Japan 1997. San Francisco: Kaufmann.
Self-Organization, Plasticity, and Low-Level Visual Phenomena in a Laterally Connected Map Model of the Primary Visual Cortex 1997
Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh, In Perceptual Learning, R. L. Goldstone and P. G. Schyns and D. L. Medin (Eds.), pp. 257-308 1997.
Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex 1997
James A. Bednar, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI97-259.
A Neural Network Model of Topographic Reorganization Following Cortical Lesions 1996
Joseph Sirosh and Risto Miikkulainen, In Computational Medicine, Public Health and Biotechnology: Building a Man in the Machine - Proceedings of the First World Congress Part II, M. Witten (Eds.), pp. 887-901, 1996. Teaneck, NJ: ...
Introduction: The Emerging Understanding of Lateral Interactions in the Cortex 1996
Risto Miikkulainen and Joseph Sirosh, In Lateral Interactions in the Cortex: Structure and Function, Sirosh, J., Miikkulainen, R., and Choe, Y. (Eds.) 1996. Electronic book, http://nn.cs.utexas.edu/web-pubs/htmlbook96.
Lateral Interactions In The Cortex: Structure And Function 1996
Joseph Sirosh, Risto Miikkulainen, and Yoonsuck Choe (editors), Electronic book, ISBN 0-9647060-0-8, http://nn.cs.utexas.edu/web-pubs/htmlbook96/. Austin, TX: The UTCS Neural Networks Research Group
Laterally Interconnected Self-Organizing Maps In Hand-Written Digit Recognition 1996
Yoonsuck Choe, Joseph Sirosh, and Risto Miikkulainen, In Advances in Neural Information Processing Systems 8, David S. Touretzky and Michael C. Mozer and Michael E. Hasselmo (Eds.), pp. 736-742 1996. Cambridge, MA: MIT Press.
Self-Organization and Functional Role of Lateral Connections and Multisize Receptive Fields in the Primary Visual Cortex 1996
Joseph Sirosh and Risto Miikkulainen, Neural Processing Letters, Vol. 3 (1996), pp. 39-48.
Self-Organization of Orientation Maps, Lateral Connections, and Dynamic Receptive Fields in the Primary Visual Cortex 1996
Joseph Sirosh, Risto Miikkulainen and James A. Bednar, In {P}roceedings of the {I}nternational {C}onference {on} {A}rtificial {N}eural {N}etworks, Joseph Sirosh and Risto Miikkulainen and Yoonsuck Choe (Eds.), pp. 1147-1152, Berlin 1996. Springer...
Topographic Receptive Fields and Patterned Lateral Interaction in a Self-Organizing Model of the Primary Visual Cortex 1996
Joseph Sirosh and Risto Miikkulainen, Neural Computation, Vol. 9 (1996), pp. 577-594.
A Model Of Visually Guided Plasticity Of The Auditory Spatial Map In The Barn Owl 1995
Andrea Haessly, Joseph Sirosh and Risto Miikkulainen, In Proceedings of the 17th Annual Conference of the Cognitive Science Society, pp. 154-158 1995. Hillsdale, NJ: Erlbaum.
A Self-Organizing Neural Network Model Of The Primary Visual Cortex 1995
Joseph Sirosh, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI95-237.
Laterally Interconnected Self-Organizing Feature Map In Handwritten Digit Recognition 1995
Yoonsuck Choe, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 65. Technical Report AI95-236.
Modeling Cortical Plasticity Based On Adapting Lateral Interaction 1995
Joseph Sirosh and Risto Miikkulainen, In The Neurobiology of Computation: {T}he Proceedings of the Third Annual Computation and Neural Systems Conference, James M. Bower (Eds.), pp. 305-310 1995.
Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex 1995
Joseph Sirosh and Risto Miikkulainen, In Advances in Neural Information Processing Systems 7, Gerald Tesauro and David S. Touretzky and Todd K. Leen (Eds.), pp. 109-116 1995. Cambridge, MA: MIT Press.
Cooperative Self-Organization Of Afferent And Lateral Connections In Cortical Maps 1994
Joseph Sirosh and Risto Miikkulainen, Biological Cybernetics (1994), pp. 66-78.
Self-Organizing Feature Maps With Lateral Connections: Modeling Ocular Dominance 1994
Joseph Sirosh and Risto Miikkulainen, In Proceedings of the 1993 Connectionist Models Summer School, M. C. Mozer and P. Smolensky and D. S. Touretzky and J. L. Elman and A. S. Weigend (Eds.), pp. 31-38 1994.
How Lateral Interaction Develops In A Self-Organizing Feature Map 1993
Joseph Sirosh and Risto Miikkulainen, In Proceedings of the IEEE International Conference on Neural Networks (San Francisco, CA), pp. 1360-1365 1993. Piscataway, NJ: IEEE.
A Neural Network For Attentional Spotlight 1991
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the International Joint Conference on Neural Networks (Singapore), AI91-165, pp. 436-441 1991. Piscataway, NJ: IEEE.
Self-Organizing Process Based On Lateral Inhibition And Synaptic Resource Redistribution 1991
Risto Miikkulainen, In Proceedings of the 1991 International Conference on Artificial Neural Networks, Teuvo Kohonen and Kai M{"a}kisara and Olli Simula and Jari Kangas (Eds.), pp. 415-420 1991. Amsterdam: North-H...
Projects
Trichromatic LISSOM 2005 - 2007
Developing Complex Systems Using Evolved Pattern Generators 2004 - 2006
Self-Organization of Directional Selectivity 1999 - 2002
PGLISSOM: Perceptual Grouping in a Self-Organizing Map of Spiking Neurons 1999 - Present
GLISSOM: Modeling Large Cortical Maps 1999 - 2001
Segmentation and Binding: the SLISSOM Model 1998 - 2002
Self-Organization Driven by Internally-Generated Patterns 1997 - 2002
Tilt Aftereffects in the RF-LISSOM Model 1996 - 2000
Orientation Perception in the RF-LISSOM Model 1995 - 2000
Self-Organization in the Primary Visual Cortex: The RF-LISSOM Model 1995 - 1997
Software/Data
LISSOM

The LISSOM package contains the C++, Python, and Scheme source code and examples for training and testing firing-rate...

2004
PGLISSOM This package is a simulator for the PGLISSOM model of perceptual grouping and self-organization in the visual cortex. Th... 2002
Demos
Handwritten Digit Recognition Utilizing Evolved Pattern GeneratorsVinod Valsalam2007
Labs
Neural Networks