Prof. Dr. Sen Cheng

Institut für Neuroinformatik
Ruhr-Universität Bochum
Universitätsstraße 150
Building NB, Room NB 3/33
D-44801 Bochum
Germany
Computational Neuroscience

Groups

My research group investigates the neural mechanisms underlying learning and memory. We are primarily interested in the hippocampus, the brain region that is mainly involved in episodic memory, as well as in the learning and memory of sequences. Our research focuses on the dynamics of these processes, which has received relatively little attention to date.

We employ two complementary approaches. Our first approach is modeling, including mathematic models as well as computer simulation of complex networks. While all models are simplified, we aim to build biologically realistic models that capture the essence of the neural circuit mechanism underlying learning and memory. Our second approach is data-mining. We develop methods for model-based data analysis and apply such methods to experimental data. These data include electrophysiological and EEG recordings as well as behavioral data. We collaborate closely with neuroscientists on the RUB campus and at other universities in Germany and abroad.

Cheng, S. (2017). Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung. In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze . Diskurse des Transhumanismus. (p. invited contribution). Bielefeld: transcript Verlag.
Cheng, S. (2017). Consolidation of Episodic Memory: An Epiphenomenon of Semantic Learning. In N. Axmacher & Rasch, B. (Eds.), Cognitive Neuroscience of Memory Consolidation (pp. 57–72). Cham, Switzerland: Springer International Publishing. http://doi.org/10.1007/978-3-319-45066-7_4
Werning, M., & Cheng, S.. (2017). Taxonomy and Unity of Memory. In S. Bernecker & Michaelian, K. (Eds.), The Routledge Handbook of Philosophy of Memory (p. forthcoming). London: Routledge.
Babichev, A., Cheng, S., & Dabaghian, Y. A. (2016). Topological Schemas of Cognitive Maps and Spatial Learning. Frontiers in Computational Neuroscience, 10, 18. http://doi.org/10.3389/fncom.2016.00018
Cheng, S., & Werning, M. (2016). What is episodic memory if it is a natural kind? Synthese, 193(5), 1345–1385. http://doi.org/10.1007/s11229-014-0628-6
Cheng, S., Werning, M., & Suddendorf, T. (2016). Dissociating memory traces and scenario construction in mental time travel. Neuroscience & Biobehavioral Reviews, 60, 82–89. http://doi.org/10.1016/j.neubiorev.2015.11.011
Bayati, M., Valizadeh, A., Abbassian, A., & Cheng, S.. (2015). Self-organization of synchronous activity propagation in neuronal networks driven by local excitation. Frontiers in Computational Neuroscience, 9, 69. http://doi.org/10.3389/fncom.2015.00069
Demic, S., & Cheng, S.. (2014). Modeling the Dynamics of Disease States in Depression. PLOS ONE, 9(10), 1–14. http://doi.org/10.1371/journal.pone.0110358
Azizi, A. H., Schieferstein, N., & Cheng, S.. (2014). The transformation from grid cells to place cells is robust to noise in the grid pattern. Hippocampus, 24(8), 912–919. http://doi.org/10.1002/hipo.22306
Pyka, M., Klatt, S., & Cheng, S.. (2014). Parametric Anatomical Modeling: a method for modeling the anatomical layout of neurons and their projections. Frontiers in Neuroanatomy, 8, 91. http://doi.org/10.3389/fnana.2014.00091
Werning, M., & Cheng, S.. (2014). Is Episodic Memory a Natural Kind?-A Defense of the Sequence Analysis. In P. Bello, Guarini, M., McShane, M., & Scassellati, B. (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (Vol. 2, pp. 964–69). Austin, TX: Cognitive Science Society. Retrieved from https://mindmodeling.org/cogsci2014/papers/173/paper173.pdf http://www.ruhr-uni-bochum.de/mam/phil-lang/content/cogsci2014_episodic_memory.pdf
Cheng, S., & Werning, M. (2013). Composition and replay of mnemonic sequences: The contributions of REM and slow-wave sleep to episodic memory. Behavioral and Brain Sciences, 36(06), 610–611. http://doi.org/10.1017/s0140525x13001234
Azizi, A. H., Wiskott, L., & Cheng, S.. (2013). A computational model for preplay in the hippocampus. Frontiers in Computational Neuroscience, 7, 161. http://doi.org/10.3389/fncom.2013.00161
Cheng, S. (2013). The CRISP theory of hippocampal function in episodic memory. Frontiers in Neural Circuits, 7, 88. http://doi.org/10.3389/fncir.2013.00088
Helduser, S., Cheng, S., & Güntürkün, O. (2013). Identification of two forebrain structures that mediate execution of memorized sequences in the pigeon. Journal of Neurophysiology, 109(4), 958–968. http://doi.org/10.1152/jn.00763.2012
Crotty, P., Lasker, E., & Cheng, S.. (2012). Constraints on the synchronization of entorhinal cortex stellate cells. Phys. Rev. E, 86(1), 011908. http://doi.org/10.1103/PhysRevE.86.011908
Buhry, L., Azizi, A. H., & Cheng, S.. (2011). Reactivation, Replay, and Preplay: How It Might All Fit Together. Neural Plasticity, 2011, 1–11. http://doi.org/10.1155/2011/203462
Cheng, S., & Frank, L. M. (2011). The structure of networks that produce the transformation from grid cells to place cells . Neuroscience , 197, 293–306. http://doi.org/10.1016/j.neuroscience.2011.09.002
Cheng, S., & Frank, L. M. (2008). New Experiences Enhance Coordinated Neural Activity in the Hippocampus . Neuron , 57(2), 303–313. http://doi.org/10.1016/j.neuron.2007.11.035
Cheng, S., & Sabes, P. N. (2007). Calibration of Visually Guided Reaching Is Driven by Error-Corrective Learning and Internal Dynamics. Journal of Neurophysiology, 97(4), 3057–3069. http://doi.org/10.1152/jn.00897.2006
Cheng, S., & Sabes, P. N. (2006). Modeling Sensorimotor Learning with Linear Dynamical Systems. Neural Computation, 18(4), 760–793. http://doi.org/10.1162/neco.2006.18.4.760
Cheng, S., Petriconi, S., Pratt, S., Skoby, M., Gale, C., Jeon, S., et al. (2004). Statistical and dynamic models of charge balance functions. Phys. Rev. C, 69(5), 054906. http://doi.org/10.1103/PhysRevC.69.054906
Pratt, S., & Cheng, S.. (2003). Removing distortions from charge balance functions. Phys. Rev. C, 68(1), 014907. http://doi.org/10.1103/PhysRevC.68.014907
Cheng, S., & Pratt, S. (2003). Isospin fluctuations from a thermally equilibrated hadron gas. Phys. Rev. C, 67(4), 044904. http://doi.org/10.1103/PhysRevC.67.044904
Cheng, S. (2002). Statistical physics in a finite volume with absolute conservation laws.
Cheng, S. (2002). Modeling Relativistic Heavy Ion Collisions.
Cheng, S., Pratt, S., Csizmadia, P., Nara, Y., Molnár, D., Gyulassy, M., et al. (2002). Effect of finite-range interactions in classical transport theory. Phys. Rev. C, 65(2), 024901. http://doi.org/10.1103/PhysRevC.65.024901
Cheng, S., & Pratt, S. (2001). Quantum corrections for pion correlations involving resonance decays. Phys. Rev. C, 63(5), 054904. http://doi.org/10.1103/PhysRevC.63.054904