Choe et al.'s Publications (2002-Current): By Topic

Table of contents Note: Some papers may be listed in multiple categories.

Action and Neural Semantics of Perception
Evolutionary Perspectives on Brain Function
Temporal Aspects of Brain Function
Biologically Inspired Vision and Cortical Maps
Thalamocortical Function
Neural Synchrony and Perceptual Grouping
Pattern Recognition
Neuroinformatics and Computational Neuroanatomy
System Biology
Theses and Dissertations (by students)

Note:

Some papers belong to multiple categories, and they may be redundantly listed.
Technical reports that are published subsequently in journals or conference proceedings are not listed: See the listing by medium page for a complete listing.
Choe and Miikkulainen (2004) is reprinted from Biological Cybernetics 90(2). The original publication is available at springerlink.com. The copyright holder for this article is Springer.
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Student theses and dissertations are also listed within each topic, and separately as a category of its own.

Action and Neural Semantics of Perception

Yoonsuck Choe and Huei-Fang Yang. Decoding spikes without stimulus information: Its implications on receptive-field learning. In Proceedings of the 5th Computational and Systems Neuroscience Meeting (COSYNE 2008 Abstracts), page 267, 2008.
Yoonsuck Choe, Huei-Fang Yang, and Navendu Misra. Motor system's role in grounding, receptive field development, and shape recognition. In Proceedings of the Seventh International Conference on Development and Learning, pages 67-72. IEEE, 2008.
Yoonsuck Choe, Huei-Fang Yang, and Daniel Chern-Yeow Eng. Autonomous learning of the semantics of internal sensory states based on motor exploration. International Journal of Humanoid Robotics, 4:211-243, 2007.
Navendu Misra and Yoonsuck Choe. Shape recognition through dynamic motor representations. In Robert Kozma and Leonid Perlovsky, editors, Neurodynamics of Higher-Level Cognition and Consciousness, pages 185-210. Springer, Berlin, 2007.
Huei-Fang Yang and Yoonsuck Choe. Co-development of visual receptive fields and their motor-primitive-based decoding scheme. In Proceedings of the International Joint Conference on Neural Networks 2007 Post conference Workshop on Biologically-inspired Computational Vision (BCV) 2007, 2007. [Online] url https://umdrive.memphis.edu/iftekhar/public/IJCNN/BCV.htm.
Yoonsuck Choe and Noah H. Smith. Motion-based autonomous grounding: Inferring external world properties from internal sensory states alone. In Yolanda Gil and Raymond Mooney, editors, Proceedings of the 21st National Conference on Artificial Intelligence, 2006. 936-941.
Yoonsuck Choe and Huei-Fang Yang. Co-development of visual receptive fields and their motor primitive-based decoding scheme. In Society for Neuroscience Abstracts. Washington, DC: Society for Neuroscience, 2006. Program No. 734.6. Online.
Yoonsuck Choe. A deeper semantic role for the mirror system. Behavioral and Brain Sciences, 28, 2005. (On-line supplemental commentary on Arbib (2005) Behavioral and Brain Sciences, 28:105-167. URL: http://www.bbsonline.org/Preprints/Arbib-05012002/Supplemental.) 1 page.
Navendu Misra. Comparison of motor-based versus visual representations in object recognition tasks. Master's thesis, Department of Computer Science, Texas A&M University, College Station, Texas, 2005.
S. Kumar Bhamidipati. Sensory invariance driven action (SIDA) framework for understanding the meaning of neural spikes. Master's thesis, Department of Computer Science, Texas A&M University, 2004.
Yoonsuck Choe and S. Kumar Bhamidipati. Autonomous acquisition of the meaning of sensory states through sensory-invariance driven action. In A. J. Ijspeert, M. Murata, and N. Wakamiya, editors, Biologically Inspired Approaches to Advanced Information Technology, Lecture Notes in Computer Science 3141, pages 176-188, Berlin, 2004. Springer.
Yoonsuck Choe and S. Kumar Bhamidipati. Learning the meaning of neural spikes through sensory-invariance driven action. Technical Report 2003-8-3, Department of Computer Science, Texas A&M University, 2003.

Evolutionary Perspectives on Brain Function

Ji Ryang Chung, Jaerock Kwon, and Yoonsuck Choe. Evolution of recollection and prediction in neural networks. In Proceedings of the International Joint Conference on Neural Networks, Piscataway, NJ, 2009. IEEE Press. In press.
Jaerock Kwon and Yoonsuck Choe. Facilitating neural dynamics for delay compensation: A road to predictive neural dynamics? Neural Networks, 22:xxx-xxx, 2009.
Jaerock Kwon and Yoonsuck Choe. Internal state predictability as an evolutionary precursor of self-awareness and agency. In Proceedings of the Seventh International Conference on Development and Learning, pages 109-114. IEEE, 2008.
Jaerock Kwon and Yoonsuck Choe. Enhanced facilitatory neuronal dynamics for delay compensation. In Proceedings of the International Joint Conference on Neural Networks, pages 2040-2045, Piscataway, NJ, 2007. IEEE Press.
Heejin Lim and Yoonsuck Choe. Compensating for neural transmission delay using extrapolatory neural activation in evolutionary neural networks. Neural Information Processing-Letters and Reviews, 10:147-161, 2006.
Heejin Lim and Yoonsuck Choe. Facilitating neural dynamics for delay compensation and prediction in evolutionary neural networks. In Maarten Keijzer, editor, Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation, GECCO-2006, pages 167-174, 2006. Nominated for Best Paper Award.

Temporal Aspects of Brain Function

Ji Ryang Chung, Jaerock Kwon, and Yoonsuck Choe. Evolution of recollection and prediction in neural networks. In Proceedings of the International Joint Conference on Neural Networks, Piscataway, NJ, 2009. IEEE Press. In press.
Jaerock Kwon and Yoonsuck Choe. Facilitating neural dynamics for delay compensation: A road to predictive neural dynamics? Neural Networks, 22:xxx-xxx, 2009.
Bum Soon Jang, Timothy Mann, and Yoonsuck Choe. Effects of varying the delay distribution in random, scale-free, and small-world networks. In Proceedings of the 2008 IEEE International Conference on Granular Computing, pages 316-321, 2008.
Jaerock Kwon and Yoonsuck Choe. Internal state predictability as an evolutionary precursor of self-awareness and agency. In Proceedings of the Seventh International Conference on Development and Learning, pages 109-114. IEEE, 2008.
Heejin Lim and Yoonsuck Choe. Delay compensation through facilitating synapses and its relation to the flash-lag effect. IEEE Transactions on Neural Networks, 19:1678-1688, 2008.
Bum Soon Jang. Effect of varying the delay distribution in different classes of networks: Random, scale-free, and small-world. Master's thesis, Department of Computer Science, Texas A&M University, 2007.
Jaerock Kwon and Yoonsuck Choe. Enhanced facilitatory neuronal dynamics for delay compensation. In Proceedings of the International Joint Conference on Neural Networks, pages 2040-2045, Piscataway, NJ, 2007. IEEE Press.
Heejin Lim. Facilitatory Neural Dynamics for Extrapolatory Prediction. PhD thesis, Department of Computer Science, Texas A&M University, 2006.
Heejin Lim and Yoonsuck Choe. Compensating for neural transmission delay using extrapolatory neural activation in evolutionary neural networks. Neural Information Processing-Letters and Reviews, 10:147-161, 2006.
Heejin Lim and Yoonsuck Choe. Delay compensation through facilitating synapses and STDP: A neural basis for orientation flash-lag effect. In Proceedings of the International Joint Conference on Neural Networks, pages 8385-8392, Piscataway, NJ, 2006. IEEE Press.
Heejin Lim and Yoonsuck Choe. Facilitating neural dynamics for delay compensation and prediction in evolutionary neural networks. In Maarten Keijzer, editor, Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation, GECCO-2006, pages 167-174, 2006. Nominated for Best Paper Award.
Heejin Lim and Yoonsuck Choe. Extrapolative role of facilitating synapses in the compensation of neural delay. In Society for Neuroscience Abstracts. Washington, DC: Society for Neuroscience, 2005. Program No. 41.19. Online.
Heejin Lim and Yoonsuck Choe. Facilitatory neural activity compensating for neural delays as a potential cause of the flash-lag effect. In Proceedings of the International Joint Conference on Neural Networks, pages 268-273, Piscataway, NJ, 2005. IEEE Press.
Yoonsuck Choe. The role of temporal parameters in a thalamocortical model of analogy. IEEE Transactions on Neural Networks, 15:1071-1082, 2004.
Yoonsuck Choe and Risto Miikkulainen. Contour integration and segmentation in a self-organizing map of spiking neurons. Biological Cybernetics, 90:75-88, 2004.

Biologically Inspired Vision and Cortical Maps

Choonseog Park, Yoon H. Bai, and Yoonsuck Choe. Tactile of visual?: Stimulus characteristics determine receptive field type in a self-organizing map model of cortical development. In Proceedings of the 2009 IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, 2009.
Yoon H. Bai, Choonseog Park, and Yoonsuck Choe. Relative advantage of touch over vision in the exploration of texture. In Proceedings of the 19th International Conference on Pattern Recognition, 2008. In press. Best Scientific Paper Award.
Heeyoul Choi, Seungjin Choi, and Yoonsuck Choe. Manifold integration with markov random walks. In Proceedings of the 23rd National Conference on Artificial Intelligence, pages 424-429, 2008.
Yingwei Yu and Yoonsuck Choe. Neural model of disinhibitory interactions in modified Poggendorff illusion. Biological Cybernetics, 98:75-85, 2008.
Sejong Oh and Yoonsuck Choe. Segmentation of textures defined on flat vs. layered surfaces using neural networks: Comparison of 2D vs. 3D representations. Neurocomputing, 70:2245-2255, 2007.
Subramonia Sarma and Yoonsuck Choe. Salience in orientation-filter response measured as suspicious coincidence in natural images. In Yolanda Gil and Raymond Mooney, editors, Proceedings of the 21st National Conference on Artificial Intelligence, 2006. 193-198.
Yingwei Yu. Computational Role of Disinhibition in Brain Function. PhD thesis, Department of Computer Science, Texas A&M University, 2006.
Yingwei Yu and Yoonsuck Choe. A neural model of the scintillating grid illusion: Disinhibition and self-inhibition in early vision. Neural Computation, 18:521-544, 2006.
Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh. Computational Maps in the Visual Cortex. Springer, Berlin, 2005. URL: http://www.computationalmaps.org.
Yoonsuck Choe and Risto Miikkulainen. Contour integration and segmentation in a self-organizing map of spiking neurons. Biological Cybernetics, 90:75-88, 2004.
Risto Miikkulainen, James A. Bednar, and Yoonsuck Choe. Sparse, redundancy-reduced visual coding through self-organized lateral connections. In Society for Neuroscience Abstracts. Washington, DC: Society for Neuroscience, 2004. Program No. 490.3. Online.
Sejong Oh. Learning to segment texture in 2D vs. 3D: A comparative study. Master's thesis, Department of Computer Science, Texas A&M University, 2004.
Sejong Oh and Yoonsuck Choe. Texture segmentation in 2D vs. 3D: Did 3D developmentally precede 2D?. In J. Triesh and T. Jebara, editors, Proceedings of the 2004 International Conference on Development and Learning [electronic], pages 175-182. UCSD Institute for Neural Computation, 2004.
Yingwei Yu and Yoonsuck Choe. Angular disinhibition effect in a modified Poggendorff illusion. In Kenneth D. Forbus, Dedre Gentner, and Terry Regier, editors, Proceedings of the 26th Annual Conference of the Cognitive Science Society, pages 1500-1505, 2004.
Yingwei Yu, Takashi Yamauchi, and Yoonsuck Choe. Explaining low-level brightness-contrast illusions using disinhibition. In A. J. Ijspeert, M. Murata, and N. Wakamiya, editors, Biologically Inspired Approaches to Advanced Information Technology, Lecture Notes in Computer Science 3141, pages 166-175, Berlin, 2004. Springer.
Yoonsuck Choe and Subramonia Sarma. Relationship between suspicious coincidence in natural images and oriented filter response distributions. Technical Report 2003-8-4, Department of Computer Science, Texas A&M University, 2003.
Hyeon-Cheol Lee and Yoonsuck Choe. Detecting salient contours using orientation energy distribution. In Proceedings of the International Joint Conference on Neural Networks, pages 206-211. IEEE, 2003.
Yingwei Yu and Yoonsuck Choe. Modeling disinhibition in the early visual pathway. Technical Report 2003-8-6, Department of Computer Science, Texas A&M University, 2003.

Thalamocortical Function

Yingwei Yu. Computational Role of Disinhibition in Brain Function. PhD thesis, Department of Computer Science, Texas A&M University, 2006.
Yingwei Yu and Yoonsuck Choe. Selective attention in time: An extended model of stimulus onset asynchrony (SOA) in Stroop effect. In Proceedings of the Fifth International Conference on Development and Learning ICDL 2006 [electronic], Bloomington, IN, 2006. Department of Psychological and Brain Sciences, Indiana University.
Yoonsuck Choe. How neural is the neural blackboard architecture?. Behavioral and Brain Sciences, 29:72-73, 2005. (Commentary on van der Velde and de Kamps (2006) Behavioral and Brain Sciences, 29:37-108.) 2 pages.
Yingwei Yu and Yoonsuck Choe. Asymptotic stability analysis of the thalamocortical circuit. In Society for Neuroscience Abstracts. Washington, DC: Society for Neuroscience, 2005. Program No. 274.23. Online.
Yoonsuck Choe. The role of temporal parameters in a thalamocortical model of analogy. IEEE Transactions on Neural Networks, 15:1071-1082, 2004.
Yoonsuck Choe. Analogical cascade: A theory on the role of the thalamo-cortical loop in brain function. Neurocomputing, 52-54:713-719, 2003.
Yoonsuck Choe. Processing of analogy in the thalamocortical circuit. In Proceedings of the International Joint Conference on Neural Networks, pages 1480-1485. IEEE, 2003.
Yoonsuck Choe. Active representations: A primitive for analogical computing in the brain. Technical Report 2002-1-3, Department of Computer Science, Texas A&M University, 2002. 6 pages.
Yoonsuck Choe. Second order isomorphism: A reinterpretation and its implications in brain and cognitive sciences. In Wayne D. Gray and Christian D. Schunn, editors, Proceedings of the 24th Annual Conference of the Cognitive Science Society, pages 190-195. Erlbaum, 2002.

Neural Synchrony and Perceptual Grouping

Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh. Computational Maps in the Visual Cortex. Springer, Berlin, 2005. URL: http://www.computationalmaps.org.
Yoonsuck Choe and Risto Miikkulainen. The role of postsynaptic potential decay rate in neural synchrony. Neurocomputing, 52-54:707-712, 2003.

Pattern Recognition

Heeyoul Choi, Seungjin Choi, and Yoonsuck Choe. Manifold integration with markov random walks. In Proceedings of the 23rd National Conference on Artificial Intelligence, pages 424-429, 2008.
Heeyoul Choi, Ricardo Gutierrez-Osuna, Seungjin Choi, and Yoonsuck Choe. Kernel oriented discriminant analysis for speaker-independent phoneme spaces. In Proceedings of the 19th International Conference on Pattern Recognition, 2008. In press.
Yingwei Yu, Yoonsuck Choe, and Ricardo Gutierrez-Osuna. Preserving class discriminatory information by context-sensitive intra-class clustering algorithm. Technical Report 2005-2-3, Department of Computer Science, Texas A&M University, 2005.

Neuroinformatics and Computational Neuroanatomy

Donghyeop Han, Heeyoul Choi, Choonseog Park, and Yoonsuck Choe. Fast and accurate retinal vasculature tracing and kernel-isomap-based feature selection. In Proceedings of the International Joint Conference on Neural Networks, Piscataway, NJ, 2009. IEEE Press. In press.
Donghyeop Han, John Keyser, and Yoonsuck Choe. A local maximum intensity projection tracing of vasculature in Knife-Edge Scanning Microscope volume data. In Proceedings of the IEEE International Symposium on Biomedical Imaging, 2009.
Huei-Fang Yang and Yoonsuck Choe. 3D volume extraction of densely packed cells in EM data stack by forward and backward graph cuts. In Proceedings of the 2009 IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing, 2009.
Huei-Fang Yang and Yoonsuck Choe. Cell tracking and segmentation in electron microscopy images using graph cuts. In Proceedings of the IEEE International Symposium on Biomedical Imaging, 2009.
Yoonsuck Choe, Louise C. Abbott, Donghyeop Han, Pei-San Huang, John Keyser, Jaerock Kwon, David Mayerich, Zeki Melek, and Bruce H. McCormick. Knife-edge scanning microscopy: High-throughput imaging and analysis of massive volumes of biological microstructures. In A. Ravi Rao and Guillermo Cecchi, editors, High-Throughput Image Reconstruction and Analysis: Intelligent Microscopy Applications. Artech House, Boston, MA, 2008. In press.
Daniel Chern-Yeow Eng and Yoonsuck Choe. Stereo pseudo 3D rendering for web-based display of scientific volumetric data. In Proceedings of the IEEE/EG International Symposium on Volume Graphics, 2008. In press.
Jaerock Kwon, David Mayerich, Yoonsuck Choe, and Bruce H. McCormick. Lateral sectioning for knife-edge scanning microscopy. In Proceedings of the IEEE International Symposium on Biomedical Imaging, pages 1371-1374, 2008.
D. Mayerich, J. Kwon, Y. Choe, L. Abbott, and J. Keyser. Constructing high-resolution microvascular models. In Proceedings of the 3rd International Workshop on Microscopic Image Analysis with Applications in Biology (MIAAB 2008), 2008. In press.
Y. Choe, L. C. Abbott, J. Keyser, J. Kwon, D. M. Mayerich, Zeki Melek, and B. H. McCormick. Enhanced microvascular staining and tracing in large volumes of mouse brain tissue. In Neuroscience Meeting Planner, San Diego, CA: Society for Neuroscience, 2007. Program No. 845.14. Online.
Jyothi S. Guntupalli. Physical sectioning in 3D biological microscopy. Master's thesis, Department of Computer Science, Texas A&M University, 2007.
D. M. Mayerich, L. C. Abbott, Y. Choe, D. Han, J. Keyser, Zeki Melek, and B. H. McCormick. Efficient methods for tracing and visualization of neural morphology in microscopy image stacks. In Neuroscience Meeting Planner, San Diego, CA: Society for Neuroscience, 2007. Program No. 845.2. Online.
B. H. McCormick, L. C. Abbott, D. M. Mayerich, , J. Keyser, Jaerock Kwon, Zeki Melek, and Y. Choe. Full-scale submicron neuroanatomy of the mouse brain. In Society for Neuroscience Abstracts. Washington, DC: Society for Neuroscience, 2006. Program No. 694.5. Online.
J. A. Bednar, Y. Choe, J. De Paula, R. Miikkulainen, and J. Provost. Modeling the visual cortex using the topographica cortical map simulator. In Society for Neuroscience Abstracts. Washington, DC: Society for Neuroscience, 2005. Program No. 508.1.
B. H. McCormick, B. L. Busse, D. M. Mayerich, L. C. Abbott, Y. Choe, J. Keyser, S. J. Smith, and W. Denk. Biologically accurate modeling of mouse brain requires biologically accurate networks. Microscopy and Microanalysis, 11 (Supplement 2):66-67, 2005.
B. H. McCormick, D. M. Mayerich, B. L. Busse, Z. Melek, W. Koh, L. C. Abbott, Y. Choe, and E.-J. Kim. The whole mouse brain: The spatial distribution and morphology of its neurons. Microscopy and Microanalysis, 11 (Supplement 2):640-641, 2005.
James A. Bednar, Yoonsuck Choe, Judah De Paula, Risto Miikkulainen, Jefferson Provost, and Tal Tversky. Modeling cortical maps with Topographica. Neurocomputing, 58-60:1129-1135, 2004.
B. H. McCormick, Y. Choe, W. Koh, L. C. Abbott, J. Keyser, Z. Melek, P. Doddapaneni, and D. Mayerich. Construction of anatomically correct models of mouse brain networks. Neurocomputing, 58-60:379-386, 2004.

System Biology

Hao Xiong and Yoonsuck Choe. Dynamic pathway analysis. BMC Systems Biology, 2:9, 2008. 17 pages (online open-access journal).
Hao Xiong and Yoonsuck Choe. Structural systems identification of genetic regulatory networks. Bioinformatics, 24:553-560, 2008.
Hao Xiong and Yoonsuck Choe. Constrained estimation of genetic networks. In BIOCOMP'07, Proceedings of the 2007 International Conference on Bioinformatics and Computational Biology, pages 51-57, 2007.
Hao Xiong and Yoonsuck Choe. Significantly different dynamic behaviors of biological networks between normal and abnormal cells in response to perturbation of environmental stressors and drugs. In Engineering Principles in Biological Systems (Cold Spring Harbor Laboratory, New York, December 3-6, 2006), page 52, 2006.

Theses and Dissertations (by students)

Jyothi S. Guntupalli. Physical sectioning in 3D biological microscopy. Master's thesis, Department of Computer Science, Texas A&M University, 2007.
Bum Soon Jang. Effect of varying the delay distribution in different classes of networks: Random, scale-free, and small-world. Master's thesis, Department of Computer Science, Texas A&M University, 2007.
Heejin Lim. Facilitatory Neural Dynamics for Extrapolatory Prediction. PhD thesis, Department of Computer Science, Texas A&M University, 2006.
Hari Shankar Muddana. Integrated biomechanical model of cells embedded in extracellular matrix. Master's thesis, Department of Computer Science, Texas A&M University, 2006.
Yingwei Yu. Computational Role of Disinhibition in Brain Function. PhD thesis, Department of Computer Science, Texas A&M University, 2006.
Navendu Misra. Comparison of motor-based versus visual representations in object recognition tasks. Master's thesis, Department of Computer Science, Texas A&M University, College Station, Texas, 2005.
S. Kumar Bhamidipati. Sensory invariance driven action (SIDA) framework for understanding the meaning of neural spikes. Master's thesis, Department of Computer Science, Texas A&M University, 2004.
Sejong Oh. Learning to segment texture in 2D vs. 3D: A comparative study. Master's thesis, Department of Computer Science, Texas A&M University, 2004.
Subramonia P. Sarma. Relationship between suspicious coincidence in natural images and contour-salience in oriented filter responses. Master's thesis, Department of Computer Science, Texas A&M University, 2003.

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