PUBLICATIONS BY TOPICS (click on links below)



1.     sensory encoding (receptive field, tuning, map, etc)

2.     visual perception (binding, object segregation, motion, etc)



1.     stimulus-response compatibility (Fitts, Simon, Erikson, Hedge-Marsh, etc)

2.     decision” process (sensory-motor locus of neuron, stimulus/response components in ERP)



1.     reinforcement learning (dopamine, TD learning, action policy, etc)

2.     classification and regularized learning (reproducing kernels, feature map, etc)



1.     theory-of-mind recursive reasoning (“I think you think I think …”)

2.     game theory (prisoner’s dilemma, meta-game, rationality, etc)



1.     divergence function, convex duality 

2.     non-parametric information geometry (Fisher metric and affine connections)

3.     alpha-curvature

4.     arbitrary (rho-tau) embedding

5.     affine coordinates

6.     symplectic structure, Kahler structure

7.     reference-representation bidualtiy




1.     signal detection theory

2.     individual and social choice

3.     dynamical system

4.     probability theory










Zhang, J. and Miller, J.P. (1989). A model for resolution enhancement (hyperacuity) in sensory representation. In Touretzky, D. (Ed.) Advances in Neural Network Information Processing System. I. pp.444-450. Morgan-Kaufmann Publishers, San Mateo, CA.


Zhang, J. (1990). How to unconfound orientational and directional information in visual neuron's response. Biological Cybernetics, 63: 135-142.


Zhang, J. (1990). Dynamical self-organization and formation of cortical maps. In Proceedings of International Joint Conference on Neural Networks, San Diego, 1990, Vol. III, pp. 487-492.


Zhang, J. and Miller, J.P. (1991). A mathematical model for hyperacuity in sensory systems. Biological Cybernetics, 64: 357-364.


Zhang, J. (1991). Dynamics and formation of self-organizing maps. Neural Computation, 3: 54-66.


Skottun, B., Zhang, J. and Grosof, D. (1994). On the direction selectivity of cortical neurons to drifting dot patterns. Visual Neuroscience, 11: 885-897.


Zhang, J. (2005). A method to unconfound orientation and direction tunings in neuronal response to moving bars and gratings. Journal of Optical Society of America A. 22: 2246-2256.


Yenduri, P.K., Zhang, J., and Gilbert, A. (2012). Integrate-and-fire neuron modeled as a low-rate sparse time-encoding device. Proceedings of the Third International Conference on Intelligent Control and Information Processing, ICICIP 2012, pp 507-512.  





Zhang, J. and Wu, S. (1990). Structure of visual perception. Proceedings of National Academy of Sciences, USA. 87: 7819-7823.


Zhang, J., Yeh, S.-L. and De Valois, K.K. (1993). Motion contrast and motion integration. Vision Research, 33: 2721-2732.


Zhang, J. (1994) Image representation using affine covariant coordinates. In O, Y.-L., Toet, A., Foster, D., Heijmans, H.J.A.M., and Meer, P. (Eds.) Shape in Picture: Mathematical Description of Shape in Grey-Level Images, Springer-Verlag, Berlin (pp.353-362).


Zhang, J. (1995). Motion detectors and motion segregation. Spatial Vision, 9: 261-273.


Zhang, J. (2005). Object oneness: the essence of the topological approach to perception. Visual Cognition, 12: 683-690.


Zhou, T., Zhang, J. and Chen, L. (2008). Neural correlation of “global-first” topological perception: Anterior temporal lobe. Brain Imaging and Behavior, 2: 309-317.


He, L., Zhang, J., Zhou, T. and Chen, L. (2009). Connectedness affects dot numerosity judgment: implications for configural processing. Psychonomic Bulletin and Review, 16: 509-517.





Zhang, H., Kornblum, S. and Zhang, J. (1995). Utilization of stimulus-response and stimulus-stimulus compatibility principles in machine design. In K. Cox, J. Marsh, and B. Anderson (Eds.) Proceedings of the First International Cognitive Technology Conference, Hong Kong: City University of Hong Kong (pp. 151-157).


Zhang, J. and Kornblum, S. (1997). Distributional analysis, and De Jong et al.'s (1994) dual process model of the "Simon effect". Journal of Experimental Psychology: Human Perception and Performance, 23: 1543-1551.


Zhang, H., Zhang, J. and Kornblum, S. (1999). An interactive activation model of stimulus-stimulus and stimulus-response compatibility. Cognitive Psychology, 38: 386-432.


Zhang, J. (2001). Dimension overlap and S-S and S-R compatibility: A structural model. In L. Chen and Y. Zhuo (Eds.) Proceedings of the Third International Conference on Cognitive Science (ICCS2001), Heifei, China: Press of University of Science and Technology of China. pp 377-381.





Zhang, J., Riehle, A., Requin, J. and Kornblum, S. (1997). Dynamics of single neuron activity in primary motor cortex related to sensorimotor transformation. Journal of Neuroscience, 17: 2227-2246.


Zhang, J., Riehle, A. and Requin, J. (1997). Locus of a neural process in stimulus-response association tasks. Journal of Mathematical Psychology, 41: 219-236.


Zhang, J. (1998). Decomposing stimulus and response component waveforms in ERP. Journal of Neuroscience Methods, 80: 49-63.


Yin, G., Zhang, J., Tian, Y. and Yao, D-Z. (2009). A multi-component decomposition algorithm for event-related potentials. Journal of Neuroscience Methods, 178: 219-227.


Stern, E., Liu, Y., Gehring, W., Lister, J., Yin, G., Zhang, J., Fitzgerald, K., Himle, J., Abelson, J., and Taylor, S. (2010). Chronic medication does not affect hyperactive error responses in obsessive-compulsive disorder. Psychophysiology. 47: 913-920.


Park, J and Zhang, J. (2010). Sensorimotor locus of the buildup activity in monkey LIP neurons. Journal of Neurophysiology. 103: 2664-2674.


Yin, G. and Zhang J. (2011). On decomposing stimulus and response waveforms in event-related potentials (ERP) recordings. IEEE Transactions on Biomedical Research, 58: 1534-1545.


Zhang, J. and Yin, G. (2013). A method to decompose stimulus and response components in event-related potential (ERP) recordings.  In Z. Lu and Y. Luo (Eds). Progress in Cognitive Science: From Cellular Mechanisms to Computational Theories. Peking University Press.





Zhang, J. (1999). A game-theoretic analysis of the political situation across Taiwan Strait. In J. Zhang and Y. Yu (Eds), Taiwan in the 21st Century: the Mainland Chinese Scholars Looking Ahead, Global Publishing Co., River Edge, New Jersey. pp 217-236 (in Chinese with English summary).


Zhang, J. (1999). A note on Lefebvre's reflexive function. In V.A. Lefebvre (Ed.) Proceedings of the Workshop on Multi-Reflexive Models of Agent Behavior, ARL-SR-64, U.S. Army Research Lab (pp.109-110).


Hedden, T. and Zhang, J. (2002). What do you think I think you think? Theory of mind and strategic reasoning in matrix games. Cognition, 85: 1-36.


Zhang, J. and Hedden, T. (2003). Two paradigms for depth of strategic reasoning in games: Response to Colman. Trends in Cognitive Sciences, 7: 4-5.


Jones, M. and Zhang, J. (2003). Which is to blame: Instrumental rationality or common knowledge? Comments to "Cooperation, psychological games theory, and limitations of rationality in social interaction" by A. Colman. Brain and Behavioral Science, 26: 166-167.


Jones, M. and Zhang, J. (2004). Rationality and bounded information in repeated games, with application to the Iterated Prisoner's Dilemma. Journal of Mathematical Psychology, 48: 334-354.


Chavez, A. and Zhang, J. (2008). Metagame strategies of nation-states, with application to Cross-Strait relations. In Liu, H., Salerno, J. and Young, M. (Eds.) Social computing, behavioral modeling, and prediction. Springer.


Zhang, J., Hedden, T and Chai, A. (2012). Perspective-taking and depth of theory of mind reasoning in sequential-move games. Cognitive Science, 36: 560-573.





Tindell, A.J., Berridge, K.C., Zhang, J., Pecińa, S., and Aldridge, J.W. (2005). Ventral pallidal neurons code incentive motivation: Effects of mesolimbic activation. European Journal of Neuroscience, 22: 2617-2634.


Zhang, J. (2009). Adaptive learning via selectionism and Bayesianism. Part I: A connection. Neural Networks, 22: 220-228.


Zhang, J. (2009). Adaptive learning via selectionism and Bayesianism Part II: The sequential case. Neural Networks, 22: 229-236.


Zhang, J. Tindell, A.J., Berridge, K.C., Zhang, J., and Aldridge, J.W. (2009). A neural computational model of incentive salience. PLoS Computational Biology, 5: 1-14.


Zhang, J., Berridge, K., Tindell, A., and Aldridge, J.A. (2011). Computational models of incentive-sensitization in addiction: Dynamic limbic transformation of learning into motivation. In Gutkin, B. and Ahmed, S.H. (Eds.) Computational Neuroscience of Drug Addition, Springer (pp.189-203).





Zhang, H., Xu, Y., and Zhang, J. (2009). Reproducing kernel Banach spaces for machine learning. Journal of Machine Learning Research 10: 2741-2775.


Zhang, H. and Zhang, J. (2010). Generalized semi-inner products with application to regularized learning. Journal of Mathematical Analysis and Application. 372: 181-196.


Zhang, H. and Zhang, J. (2011). Frames, Riesz bases, and sampling expansions in Banach spaces via semi-inner products. Applied and Computational Harmonic Analysis, 31: 1-25.


Zhang, H. and Zhang, J. (2012). Regularized learning in Banach space as an optimization problem: Representer theorems. Journal of Global Optimization, 54: 235-250 (e-print published 11 July 2010).


Zhang, H. and Zhang, J. (2013). Vector-valued Reproducing Kernel Banach Spaces with applications to multi-task learning. Journal of Complexity, 29: 195-215.





Zhang, J. (2004). Divergence function, duality, and convex analysis. Neural Computation, 16: 159-195.


Zhang, J. (2004). Dual scaling between comparison and reference stimuli in multidimensional psychological space. Journal of Mathematical Psychology, 48: 409-424.


Zhang, J. (2005). Referential duality and representational duality on statistical manifolds. Proceedings of the Second International Symposium on Information Geometry and Its Applications, Tokyo (pp 58-67).


Zhang, J. and Hasto, P. (2006). Statistical manifold as an affine space: A functional equation approach. Journal of Mathematical Psychology, 50: 60-65.


Zhang, J. (2006). Referential duality and representational duality in the scaling of multi-dimensional and infinite-dimensional stimulus space. In Dzhafarov, E. and Colonius, H. (Eds.) Measurement and representation of sensations: Recent progress in psychological theory. Lawrence Erlbaum Associates, Mahwah, NJ (pp131-157).


Zhang J. (2007). A note on curvature of a-connections of a statistical manifold. Annals of the Institute of Statistical Mathematics, 59: 161-170.


Calin, O., Matsuzoe, H., and Zhang, J. (2009). Generalization of conjugate connections. Proceedings of 9th International Workshop on Complex Structures, Integrability, and Vector Fields. 


Zhang, J. and Matsuzuo, H. (2009). Dualistic differential geometry associated with a convex function. In Gao D.Y. and Sherali, H.D. (Eds) Advances in Applied Mathematics and Global Optimization (Dedicated to Gilbert Strang on the Occasion of His 70th Birthday), Advances in Mechanics and Mathematics, Vol. III, Chapter 13, Springer (pp 437-464).


Zhang, J. (2013). Nonparametric information geometry: From divergence function to referential-representational biduality on statistical manifolds. Entropy, 15: 5384-5418.


Zhang, J. and Li, F. (2013). Symplectic and Kahler structures on statistical manifolds induced from divergence functions. Proceedings of the First International Conference on Geometric Science of Information GSI2013, Nielson, F. and Barbaresco, F. (Eds), (pp. 595-603).


Zhang, J. (2014) Divergence functions and geometric structures they induce on a manifold. In F. Nielsen (Ed). Geometric Theory of Information, Springer (pp 1-30).


Zhang, J. (2014). Reference duality and representation duality in information geometry. In Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt2014), Vol. 1641 (pp130-146). AIP Publishing.


Zhang, J. (2015). On monotone embedding in information geometry. Entropy, 17: 4485-4489.


Tao, J. and Zhang, J. (2015). Transformation and coupling of relations for affine connections. In Nielson, F. and Barbaresco, F. (Eds), Geometric Science of Information, 2nd International Conference GSI2015, LNCS 9389, Springer (pp. 326-339).








Zhang, J. and Mueller, S. (2005). A note on ROC analysis and non-parametric estimation of sensitivity. Psychometrika. 70: 203-212.


Mueller, S. and Zhang, J. (2006). Upper and lower bounds of area under ROC curves and index of discriminability of classifier performance. Proceedings of ICML2006 Workshop on ROC Analysis in Machine Learning, Pittsurgh, PA, 2006, (pp. 41-46).




Jones, M., Zhang, J. and Simpson, G. (2003). Aggregation of utility and social choice: A topological characterization. Journal of Mathematical Psychology, 47: 545-556.


Zhang, J. (2004). Binary choice, subset choice, random utility, and ranking: A unified perspective using the permutahedron. Journal of Mathematical Psychology, 48: 107-134.




Wei, H., Zhang, J., Cousseau, F., Ozeki, T., and Amari, S. (2007). Dynamics of learning near singularities in layered network. Neural Computation, 20: 813-843.


Stevens, G. and Zhang, J (2009). A dynamic systems model of infant attachment. IEEE Transaction of Autonomous Mental Development. 1: 196-207.


Ilin, R., Zhang, J., Perlovsky, L., and Kozma, R. (2014). Vague-to-crisp dynamics of percept formation modeled as operant (selectionist) process. Cognitive Neurodynamics, 8: 71-80.





Zhang, J. (2011). Model selection with informative normalized maximal likelihood: Data prior and model prior (book chapter).  In Dzhafarov, E.N and Perry, L. (Eds) Descriptive and Normative Approaches to Human Behavior, World Scientific, New Jersey (pp. 303-319).


Ilin, R. and Zhang, J. (2014). Information fusion with uncertainty modeled on topological event spaces. Proceedings of IEEE Symposium on Foundation of Computation Intelligence (FOCI 2014).


Ilin, R. and Zhang, J. (2015). Information fusion with topological event spaces. In Proceedings of International Conference on Information Fusion FUSION’2015, IEEE (pp. 2092-2099).