Prof. Dr. Sen Cheng

RUB
INI
People
Prof. Dr. Sen Cheng

Computational Neuroscience

Ruhr-Universität Bochum
Institut für Neuroinformatik
Universitätsstraße 150
Building NB, Room NB 3/33

D-44801 Bochum, Germany

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.

Selected Publications

2023

A map of spatial navigation for neuroscience
Parra-Barrero, E., Vijayabaskaran, S., Seabrook, E., Wiskott, L., & Cheng, S.
Neuroscience & Biobehavioral Reviews, 152, 105200

A map of spatial navigation for neuroscience

@article{Parra-BarreroVijayabaskaranSeabrookEtAl2023, author = {Parra-Barrero, Eloy and Vijayabaskaran, Sandhiya and Seabrook, Eddie and Wiskott, Laurenz and Cheng, Sen}, title = {A map of spatial navigation for neuroscience}, journal = {Neuroscience & Biobehavioral Reviews}, volume = {152}, pages = {105200}, month = {September}, year = {2023}, doi = {10.1016/j.neubiorev.2023.105200}, }

Parra-Barrero, E., Vijayabaskaran, S., Seabrook, E., Wiskott, L., & Cheng, S.. (2023). A map of spatial navigation for neuroscience. Neuroscience & Biobehavioral Reviews, 152, 105200. http://doi.org/10.1016/j.neubiorev.2023.105200
Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3
de Jong, L. W., Nejad, M. M., Yoon, E., Cheng, S., & Diba, K.
Current Biology, 33(9), 1689–1703.e5

Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3 Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3- SupplementaryMaterial

@article{de JongNejadYoonEtAl2023, author = {de Jong, Laurel Watkins and Nejad, Mohammadreza Mohagheghi and Yoon, Euisik and Cheng, Sen and Diba, Kamran}, title = {Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3}, journal = {Current Biology}, volume = {33}, number = {9}, pages = {1689–1703.e5}, month = {May}, year = {2023}, doi = {10.1016/j.cub.2023.03.032}, }

de Jong, L. W., Nejad, M. M., Yoon, E., Cheng, S., & Diba, K. (2023). Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3. Current Biology, 33(9), 1689–1703.e5. http://doi.org/10.1016/j.cub.2023.03.032
A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning
Diekmann, N., & Cheng, S.
eLife, 12, e82301

A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning

@article{DiekmannCheng2023, author = {Diekmann, Nicolas and Cheng, Sen}, title = {A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning}, journal = {eLife}, volume = {12}, pages = {e82301}, month = {March}, year = {2023}, doi = {10.7554/eLife.82301}, }

Diekmann, N., & Cheng, S.. (2023). A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning. eLife, 12, e82301. http://doi.org/10.7554/eLife.82301

2022

The cerebellum contributes to context-effects during fear extinction learning: A 7T fMRI study

Batsikadze, G., Diekmann, N., Ernst, T. M., Klein, M., Maderwald, S., Deuschl, C., et al.

NeuroImage, 253, 119080

@article{BatsikadzeDiekmannErnstEtAl2022,
	author		=	{Batsikadze, Giorgi and Diekmann, Nicolas and Ernst, Thomas Michael and Klein, Michael and Maderwald, Stefan and Deuschl, Cornelius and Merz, Christian Josef and Cheng, Sen and Quick, Harald H. and Timmann, Dagmar},
	title		=	{The cerebellum contributes to context-effects during fear extinction learning: A 7T fMRI study},
	journal		=	{NeuroImage},
	volume		=	{253},
	pages		=	{119080},
	month		=	{June},
	year		=	{2022},
	doi		=	{10.1016/j.neuroimage.2022.119080},
}

2021

Neuronal Sequences during Theta Rely on Behavior-Dependent Spatial Maps
Parra-Barrero, E., Diba, K., & Cheng, S.
eLife, 10, e70296

@article{Parra-BarreroDibaCheng2021, author = {Parra-Barrero, Eloy and Diba, Kamran and Cheng, Sen}, title = {Neuronal Sequences during Theta Rely on Behavior-Dependent Spatial Maps}, journal = {eLife}, volume = {10}, pages = {e70296}, year = {2021}, doi = {10.7554/eLife.70296}, }

Parra-Barrero, E., Diba, K., & Cheng, S.. (2021). Neuronal Sequences during Theta Rely on Behavior-Dependent Spatial Maps. eLife, 10, e70296. http://doi.org/10.7554/eLife.70296

2019

Hippocampal Reactivation Extends for Several Hours Following Novel Experience
Giri, B., Miyawaki, H., Mizuseki, K., Cheng, S., & Diba, K.
The Journal of Neuroscience, 39(5), 866–875

link

@article{GiriMiyawakiMizusekiEtAl2019, author = {Giri, Bapun and Miyawaki, Hiroyuki and Mizuseki, Kenji and Cheng, Sen and Diba, Kamran}, title = {Hippocampal Reactivation Extends for Several Hours Following Novel Experience}, journal = {The Journal of Neuroscience}, volume = {39}, number = {5}, pages = {866–875}, month = {December}, year = {2019}, doi = {10.1523/jneurosci.1950-18.2018}, }

Giri, B., Miyawaki, H., Mizuseki, K., Cheng, S., & Diba, K. (2019). Hippocampal Reactivation Extends for Several Hours Following Novel Experience. The Journal of Neuroscience, 39(5), 866–875. http://doi.org/10.1523/jneurosci.1950-18.2018

2016

What is episodic memory if it is a natural kind?

Cheng, S., & Werning, M.

Synthese, 193(5), 1345–1385

@article{ChengWerning2016,
	author		=	{Cheng, Sen and Werning, Markus},
	title		=	{What is episodic memory if it is a natural kind?},
	journal		=	{Synthese},
	volume		=	{193},
	number		=	{5},
	pages		=	{1345–1385},
	year		=	{2016},
	doi		=	{10.1007/s11229-014-0628-6},
}

Dissociating memory traces and scenario construction in mental time travel
Cheng, S., Werning, M., & Suddendorf, T.
Neuroscience & Biobehavioral Reviews, 60, 82–89

@article{ChengWerningSuddendorf2016, author = {Cheng, Sen and Werning, Markus and Suddendorf, Thomas}, title = {Dissociating memory traces and scenario construction in mental time travel}, journal = {Neuroscience & Biobehavioral Reviews}, volume = {60}, pages = {82–89}, month = {January}, year = {2016}, doi = {10.1016/j.neubiorev.2015.11.011}, }

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

2008

New Experiences Enhance Coordinated Neural Activity in the Hippocampus
Cheng, S., & Frank, L. M.
Neuron , 57(2), 303–313

@article{ChengFrank2008, author = {Cheng, Sen and Frank, Loren M.}, title = {New Experiences Enhance Coordinated Neural Activity in the Hippocampus }, journal = {Neuron }, volume = {57}, number = {2}, pages = {303–313}, year = {2008}, doi = {10.1016/j.neuron.2007.11.035}, }

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

in press

Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung
Cheng, S.
In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze "Mensch". Diskurse des Transhumanismus. Bielefeld: transcript Verlag

@incollection{Cheng0, author = {Cheng, Sen}, title = {Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung}, booktitle = {Die Grenze "Mensch". Diskurse des Transhumanismus.}, editor = {Hüttemann, Felix and Liggieri, Kevin}, publisher = {transcript Verlag}, address = {Bielefeld}, year = {in press}, }

Cheng, S. (in press). Gedächtnisverbesserung: Möglichkeiten und kritische Betrachtung. In F. Hüttemann & Liggieri, K. (Eds.), Die Grenze "Mensch". Diskurse des Transhumanismus.. Bielefeld: transcript Verlag.

2025

Appetitive and aversive classical conditioning: Self-reports and physiological responses

Petrenko, M., Coenen, L., Doubliez, A., Ernst, T. M., Nio, E., Diekmann, N., et al.

Behavioural Brain Research, 484, 115509

@article{PetrenkoCoenenDoubliezEtAl2025,
	author		=	{Petrenko, Mykola and Coenen, Lena and Doubliez, Alice and Ernst, Thomas M. and Nio, Enzo and Diekmann, Nicolas and Uengoer, Metin and Cheng, Sen and Merz, Christian J. and Timmann, Dagmar and Batsikadze, Giorgi},
	title		=	{Appetitive and aversive classical conditioning: Self-reports and physiological responses},
	journal		=	{Behavioural Brain Research},
	volume		=	{484},
	pages		=	{115509},
	month		=	{April},
	year		=	{2025},
	doi		=	{10.1016/j.bbr.2025.115509},
}

A Taxonomy of Spatial Navigation in Mammals: Insights from Computational Modeling
Vijayabaskaran, S., Zeng, X., Ghazinouri, B., Wiskott, L., & Cheng, S.
Center for Open Science

link

@misc{VijayabaskaranZengGhazinouriEtAl2025, author = {Vijayabaskaran, Sandhiya and Zeng, Xiangshuai and Ghazinouri, Behnam and Wiskott, Laurenz and Cheng, Sen}, title = {A Taxonomy of Spatial Navigation in Mammals: Insights from Computational Modeling}, month = {March}, year = {2025}, doi = {10.31219/osf.io/g9sfd_v1}, }

Vijayabaskaran, S., Zeng, X., Ghazinouri, B., Wiskott, L., & Cheng, S.. (2025, March). A Taxonomy of Spatial Navigation in Mammals: Insights from Computational Modeling. Center for Open Science. http://doi.org/10.31219/osf.io/g9sfd_v1
What is the nature of cache memory in Parids? A comment on Chettih et al. 2024
Smulders, T. V., & Cheng, S.
Animal Cognition, 28(1)

@article{SmuldersCheng2025, author = {Smulders, Tom V. and Cheng, Sen}, title = {What is the nature of cache memory in Parids? A comment on Chettih et al. 2024}, journal = {Animal Cognition}, volume = {28}, number = {1}, month = {February}, year = {2025}, doi = {10.1007/s10071-025-01932-7}, }

Smulders, T. V., & Cheng, S.. (2025). What is the nature of cache memory in Parids? A comment on Chettih et al. 2024. Animal Cognition, 28(1). http://doi.org/10.1007/s10071-025-01932-7
The Cost of Behavioral Flexibility: Reversal Learning Driven by a Spiking Neural Network
Ghazinouri, B., & Cheng, S.
In O. Brock & Krichmar, J. (Eds.), From Animals to Animats 17 (pp. 39–50) Cham: Springer Nature Switzerland

@inproceedings{GhazinouriCheng2025, author = {Ghazinouri, Behnam and Cheng, Sen}, title = {The Cost of Behavioral Flexibility: Reversal Learning Driven by a Spiking Neural Network}, booktitle = {From Animals to Animats 17}, editor = {Brock, Oliver and Krichmar, Jeffrey}, pages = {39–50}, publisher = {Springer Nature Switzerland}, address = {Cham}, year = {2025}, }

Ghazinouri, B., & Cheng, S.. (2025). The Cost of Behavioral Flexibility: Reversal Learning Driven by a Spiking Neural Network. In O. Brock & Krichmar, J. (Eds.), From Animals to Animats 17 (pp. 39–50). Cham: Springer Nature Switzerland.
Global remapping emerges as the mechanism for renewal of context-dependent behavior in a reinforcement learning model
Kappel, D., & Cheng, S.
Frontiers in Computational Neuroscience, 18

@article{KappelCheng2025, author = {Kappel, David and Cheng, Sen}, title = {Global remapping emerges as the mechanism for renewal of context-dependent behavior in a reinforcement learning model}, journal = {Frontiers in Computational Neuroscience}, volume = {18}, month = {January}, year = {2025}, doi = {10.3389/fncom.2024.1462110}, }

Kappel, D., & Cheng, S.. (2025). Global remapping emerges as the mechanism for renewal of context-dependent behavior in a reinforcement learning model. Frontiers in Computational Neuroscience, 18. http://doi.org/10.3389/fncom.2024.1462110

Human cerebellum and ventral tegmental area interact during extinction of learned fear

Nio, E., Pereira, P. P., Diekmann, N., Petrenko, M., Doubliez, A., Ernst, T. M., et al.

@article{NioPereiraDiekmannEtAl2025,
	author		=	{Nio, Enzo and Pereira, Patrick Pais and Diekmann, Nicolas and Petrenko, Mykola and Doubliez, Alice and Ernst, Thomas M and Batsikadze, Giorgi and Maderwald, Stefan and Deuschl, Cornelius and Üngör, Metin and Cheng, Sen and Merz, Christian J and Quick, Harald H and Timmann, Dagmar},
	title		=	{Human cerebellum and ventral tegmental area interact during extinction of learned fear},
	month		=	{January},
	year		=	{2025},
	doi		=	{10.7554/elife.105399.1},
}

2024

Gain control of sensory input across polysynaptic circuitries in mouse visual cortex by a single G protein-coupled receptor type (5-HT2A)

Barzan, R., Bozkurt, B., Nejad, M. M., Süß, S. T., Surdin, T., Böke, H., et al.

Nature Communications, 15(1)

@article{BarzanBozkurtNejadEtAl2024,
	author		=	{Barzan, Ruxandra and Bozkurt, Beyza and Nejad, Mohammadreza M. and Süß, Sandra T. and Surdin, Tatjana and Böke, Hanna and Spoida, Katharina and Azimi, Zohre and Grömmke, Michelle and Eickelbeck, Dennis and Mark, Melanie D. and Rohr, Lennard and Siveke, Ida and Cheng, Sen and Herlitze, Stefan and Jancke, Dirk},
	title		=	{Gain control of sensory input across polysynaptic circuitries in mouse visual cortex by a single G protein-coupled receptor type (5-HT2A)},
	journal		=	{Nature Communications},
	volume		=	{15},
	number		=	{1},
	month		=	{September},
	year		=	{2024},
	doi		=	{10.1038/s41467-024-51861-1},
}

Distinct mechanisms and functions of episodic memory
Cheng, S.
Philosophical Transactions of the Royal Society B: Biological Sciences, 379(1913)

@article{Cheng2024, author = {Cheng, Sen}, title = {Distinct mechanisms and functions of episodic memory}, journal = {Philosophical Transactions of the Royal Society B: Biological Sciences}, volume = {379}, number = {1913}, month = {September}, year = {2024}, doi = {10.1098/rstb.2023.0411}, }

Cheng, S. (2024). Distinct mechanisms and functions of episodic memory. Philosophical Transactions of the Royal Society B: Biological Sciences, 379(1913). http://doi.org/10.1098/rstb.2023.0411
A neural network model for online one-shot storage of pattern sequences
Melchior, J., Altamimi, A., Bayati, M., Cheng, S., & Wiskott, L.
PLOS ONE, 19(6), 1–28

link

@article{MelchiorAltamimiBayatiEtAl2024, author = {Melchior, Jan and Altamimi, Aya and Bayati, Mehdi and Cheng, Sen and Wiskott, Laurenz}, title = {A neural network model for online one-shot storage of pattern sequences}, journal = {PLOS ONE}, volume = {19}, number = {6}, pages = {1–28}, month = {June}, year = {2024}, doi = {10.1371/journal.pone.0304076}, }

Melchior, J., Altamimi, A., Bayati, M., Cheng, S., & Wiskott, L.. (2024). A neural network model for online one-shot storage of pattern sequences. PLOS ONE, 19(6), 1–28. http://doi.org/10.1371/journal.pone.0304076
Navigation and the efficiency of spatial coding: insights from closed-loop simulations
Ghazinouri, B., Nejad, M. M., & Cheng, S.
Brain Structure and Function, 229(3), 577–592

Navigation and the efficiency of spatial coding: insights from closed-loop simulations

@article{GhazinouriNejadCheng2024, author = {Ghazinouri, Behnam and Nejad, Mohammadreza Mohagheghi and Cheng, Sen}, title = {Navigation and the efficiency of spatial coding: insights from closed-loop simulations}, journal = {Brain Structure and Function}, volume = {229}, number = {3}, pages = {577–592}, year = {2024}, }

Ghazinouri, B., Nejad, M. M., & Cheng, S.. (2024). Navigation and the efficiency of spatial coding: insights from closed-loop simulations. Brain Structure and Function, 229(3), 577–592.

2023

Working memory performance is tied to stimulus complexity
Pusch, R., Packheiser, J., Azizi, A. H., Sevincik, C. S., Rose, J., Cheng, S., et al.
Communications Biology, 6(1)

Working memory performance is tied to stimulus complexity

@article{PuschPackheiserAziziEtAl2023, author = {Pusch, Roland and Packheiser, Julian and Azizi, Amir Hossein and Sevincik, Celil Semih and Rose, Jonas and Cheng, Sen and Stüttgen, Maik C. and Güntürkün, Onur}, title = {Working memory performance is tied to stimulus complexity}, journal = {Communications Biology}, volume = {6}, number = {1}, month = {November}, year = {2023}, doi = {10.1038/s42003-023-05486-7}, }

Pusch, R., Packheiser, J., Azizi, A. H., Sevincik, C. S., Rose, J., Cheng, S., et al. (2023). Working memory performance is tied to stimulus complexity. Communications Biology, 6(1). http://doi.org/10.1038/s42003-023-05486-7
A map of spatial navigation for neuroscience
Parra-Barrero, E., Vijayabaskaran, S., Seabrook, E., Wiskott, L., & Cheng, S.
Neuroscience & Biobehavioral Reviews, 152, 105200

A map of spatial navigation for neuroscience

@article{Parra-BarreroVijayabaskaranSeabrookEtAl2023, author = {Parra-Barrero, Eloy and Vijayabaskaran, Sandhiya and Seabrook, Eddie and Wiskott, Laurenz and Cheng, Sen}, title = {A map of spatial navigation for neuroscience}, journal = {Neuroscience & Biobehavioral Reviews}, volume = {152}, pages = {105200}, month = {September}, year = {2023}, doi = {10.1016/j.neubiorev.2023.105200}, }

Parra-Barrero, E., Vijayabaskaran, S., Seabrook, E., Wiskott, L., & Cheng, S.. (2023). A map of spatial navigation for neuroscience. Neuroscience & Biobehavioral Reviews, 152, 105200. http://doi.org/10.1016/j.neubiorev.2023.105200
A Multisession SLAM Approach for RatSLAM
Menezes, M., Muñoz, M., de Freitas, E. P., Cheng, S., de Almeida Neto, A., Ribeiro, P., & Oliveira, A.
Journal of Intelligent & Robotic Systems, 108(4)

A Multisession SLAM Approach for RatSLAM

@article{MenezesMuñozde FreitasEtAl2023, author = {Menezes, Matheus and Muñoz, Mauro and de Freitas, Edison Pignaton and Cheng, Sen and de Almeida Neto, Areolino and Ribeiro, Paulo and Oliveira, Alexandre}, title = {A Multisession SLAM Approach for RatSLAM}, journal = {Journal of Intelligent & Robotic Systems}, volume = {108}, number = {4}, month = {July }, year = {2023}, doi = {10.1007/s10846-023-01816-3}, }

Menezes, M., Muñoz, M., de Freitas, E. P., Cheng, S., de Almeida Neto, A., Ribeiro, P., & Oliveira, A. (2023). A Multisession SLAM Approach for RatSLAM. Journal of Intelligent & Robotic Systems, 108(4). http://doi.org/10.1007/s10846-023-01816-3
Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3
de Jong, L. W., Nejad, M. M., Yoon, E., Cheng, S., & Diba, K.
Current Biology, 33(9), 1689–1703.e5

Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3 Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3- SupplementaryMaterial

@article{de JongNejadYoonEtAl2023, author = {de Jong, Laurel Watkins and Nejad, Mohammadreza Mohagheghi and Yoon, Euisik and Cheng, Sen and Diba, Kamran}, title = {Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3}, journal = {Current Biology}, volume = {33}, number = {9}, pages = {1689–1703.e5}, month = {May}, year = {2023}, doi = {10.1016/j.cub.2023.03.032}, }

de Jong, L. W., Nejad, M. M., Yoon, E., Cheng, S., & Diba, K. (2023). Optogenetics reveals paradoxical network stabilizations in hippocampal CA1 and CA3. Current Biology, 33(9), 1689–1703.e5. http://doi.org/10.1016/j.cub.2023.03.032
Learning to predict future locations with internally generated theta sequences
Parra-Barrero, E., & Cheng, S.
PLOS Computational Biology, 19(5), e1011101

Learning to predict future locations with internally generated theta sequences

@article{Parra-BarreroCheng2023, author = {Parra-Barrero, Eloy and Cheng, Sen}, title = {Learning to predict future locations with internally generated theta sequences}, journal = {PLOS Computational Biology}, volume = {19}, number = {5}, pages = {e1011101}, month = {May}, year = {2023}, doi = {10.1371/journal.pcbi.1011101}, }

Parra-Barrero, E., & Cheng, S.. (2023). Learning to predict future locations with internally generated theta sequences. PLOS Computational Biology, 19(5), e1011101. http://doi.org/10.1371/journal.pcbi.1011101
A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning
Diekmann, N., & Cheng, S.
eLife, 12, e82301

A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning

@article{DiekmannCheng2023, author = {Diekmann, Nicolas and Cheng, Sen}, title = {A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning}, journal = {eLife}, volume = {12}, pages = {e82301}, month = {March}, year = {2023}, doi = {10.7554/eLife.82301}, }

Diekmann, N., & Cheng, S.. (2023). A model of hippocampal replay driven by experience and environmental structure facilitates spatial learning. eLife, 12, e82301. http://doi.org/10.7554/eLife.82301
CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning
Diekmann, N., Vijayabaskaran, S., Zeng, X., Kappel, D., Menezes, M. C., & Cheng, S.
Frontiers in Neuroinformatics, 17

CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning

@article{DiekmannVijayabaskaranZengEtAl2023, author = {Diekmann, Nicolas and Vijayabaskaran, Sandhiya and Zeng, Xiangshuai and Kappel, David and Menezes, Matheus Chaves and Cheng, Sen}, title = {CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning}, journal = {Frontiers in Neuroinformatics}, volume = {17}, month = {March}, year = {2023}, doi = {10.3389/fninf.2023.1134405}, }

Diekmann, N., Vijayabaskaran, S., Zeng, X., Kappel, D., Menezes, M. C., & Cheng, S.. (2023). CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning. Frontiers in Neuroinformatics, 17. http://doi.org/10.3389/fninf.2023.1134405
Solidity Meets Surprise: Cerebral and Behavioral Effects of Learning from Episodic Prediction Errors
Siestrup, S., Jainta, B., Cheng, S., & Schubotz, R. I.
Journal of Cognitive Neuroscience, 35(2), 291–313

Solidity Meets Surprise: Cerebral and Behavioral Effects of Learning from Episodic Prediction Errors

@article{SiestrupJaintaChengEtAl2023, author = {Siestrup, Sophie and Jainta, Benjamin and Cheng, Sen and Schubotz, Ricarda I.}, title = {Solidity Meets Surprise: Cerebral and Behavioral Effects of Learning from Episodic Prediction Errors}, journal = {Journal of Cognitive Neuroscience}, volume = {35}, number = {2}, pages = {291–313}, year = {2023}, doi = {10.1162/jocn_a_01948}, }

Siestrup, S., Jainta, B., Cheng, S., & Schubotz, R. I. (2023). Solidity Meets Surprise: Cerebral and Behavioral Effects of Learning from Episodic Prediction Errors. Journal of Cognitive Neuroscience, 35(2), 291–313. http://doi.org/10.1162/jocn_a_01948
Modeling the function of episodic memory in spatial learning
Zeng, X., Diekmann, N., Wiskott, L., & Cheng, S.
Frontiers in Psychology, 14

Modeling the function of episodic memory in spatial learning Modeling the function of episodic memory in spatial learning - SupplementaryMaterial

@article{ZengDiekmannWiskottEtAl2023, author = {Zeng, Xiangshuai and Diekmann, Nicolas and Wiskott, Laurenz and Cheng, Sen}, title = {Modeling the function of episodic memory in spatial learning}, journal = {Frontiers in Psychology}, volume = {14}, year = {2023}, doi = {10.3389/fpsyg.2023.1160648}, }

Zeng, X., Diekmann, N., Wiskott, L., & Cheng, S.. (2023). Modeling the function of episodic memory in spatial learning. Frontiers in Psychology, 14. http://doi.org/10.3389/fpsyg.2023.1160648

2022

xRatSLAM: An Extensible RatSLAM Computational Framework

de Souza Muñoz, M. E., Menezes, M. C., de Freitas, E. P., Cheng, S., de Almeida Ribeiro, P. R., de Almeida Neto, A., & de Oliveira, A. C. M.

Sensors, 22(21), 8305

@article{de Souza MuñozMenezesde FreitasEtAl2022,
	author		=	{de Souza Muñoz, Mauro Enrique and Menezes, Matheus Chaves and de Freitas, Edison Pignaton and Cheng, Sen and de Almeida Ribeiro, Paulo Rogério and de Almeida Neto, Areolino and de Oliveira, Alexandre César Muniz},
	title		=	{xRatSLAM: An Extensible RatSLAM Computational Framework},
	journal		=	{Sensors},
	volume		=	{22},
	number		=	{21},
	pages		=	{8305},
	month		=	{October},
	year		=	{2022},
	doi		=	{10.3390/s22218305},
}

Navigation task and action space drive the emergence of egocentric and allocentric spatial representations
Vijayabaskaran, S., & Cheng, S.
PLOS Computational Biology, 18(10), e1010320

@article{VijayabaskaranCheng2022, author = {Vijayabaskaran, Sandhiya and Cheng, Sen}, title = {Navigation task and action space drive the emergence of egocentric and allocentric spatial representations}, journal = {PLOS Computational Biology}, volume = {18}, number = {10}, pages = {e1010320}, month = {October}, year = {2022}, doi = {10.1371/journal.pcbi.1010320}, }

Vijayabaskaran, S., & Cheng, S.. (2022). Navigation task and action space drive the emergence of egocentric and allocentric spatial representations. PLOS Computational Biology, 18(10), e1010320. http://doi.org/10.1371/journal.pcbi.1010320
Where was the toaster? A systematic investigation of semantic construction in a new virtual episodic memory paradigm
Zöllner, C., Klein, N., Cheng, S., Schubotz, R. I., Axmacher, N., & Wolf, O. T.
Quarterly Journal of Experimental Psychology, 174702182211166

@article{ZöllnerKleinChengEtAl2022, author = {Zöllner, Carina and Klein, Nicole and Cheng, Sen and Schubotz, Ricarda I and Axmacher, Nikolai and Wolf, Oliver T}, title = {Where was the toaster? A systematic investigation of semantic construction in a new virtual episodic memory paradigm}, journal = {Quarterly Journal of Experimental Psychology}, pages = {174702182211166}, month = {September}, year = {2022}, doi = {10.1177/17470218221116610}, }

Zöllner, C., Klein, N., Cheng, S., Schubotz, R. I., Axmacher, N., & Wolf, O. T. (2022). Where was the toaster? A systematic investigation of semantic construction in a new virtual episodic memory paradigm. Quarterly Journal of Experimental Psychology, 174702182211166. http://doi.org/10.1177/17470218221116610
A Model of Semantic Completion in Generative Episodic Memory
Fayyaz, Z., Altamimi, A., Zoellner, C., Klein, N., Wolf, O. T., Cheng, S., & Wiskott, L.
Neural Computation, 34(9), 1841–1870

@article{FayyazAltamimiZoellnerEtAl2022, author = {Fayyaz, Zahra and Altamimi, Aya and Zoellner, Carina and Klein, Nicole and Wolf, Oliver T. and Cheng, Sen and Wiskott, Laurenz}, title = {A Model of Semantic Completion in Generative Episodic Memory}, journal = {Neural Computation}, volume = {34}, number = {9}, pages = {1841–1870}, month = {August}, year = {2022}, doi = {10.1162/neco_a_01520}, }

Fayyaz, Z., Altamimi, A., Zoellner, C., Klein, N., Wolf, O. T., Cheng, S., & Wiskott, L.. (2022). A Model of Semantic Completion in Generative Episodic Memory. Neural Computation, 34(9), 1841–1870. http://doi.org/10.1162/neco_a_01520
Learning shifts the preferred theta phase of gamma oscillations in CA1
Rayan, A., Donoso, J. R., Mendez-Couz, M., Dolón, L., Cheng, S., & Manahan-Vaughan, D.
Hippocampus, 32(9), 695–704

@article{RayanDonosoMendez-CouzEtAl2022, author = {Rayan, Abdelrahman and Donoso, José R. and Mendez-Couz, Marta and Dolón, Laura and Cheng, Sen and Manahan-Vaughan, Denise}, title = {Learning shifts the preferred theta phase of gamma oscillations in CA1}, journal = {Hippocampus}, volume = {32}, number = {9}, pages = {695–704}, month = {August}, year = {2022}, doi = {10.1002/hipo.23460}, }

Rayan, A., Donoso, J. R., Mendez-Couz, M., Dolón, L., Cheng, S., & Manahan-Vaughan, D. (2022). Learning shifts the preferred theta phase of gamma oscillations in CA1. Hippocampus, 32(9), 695–704. http://doi.org/10.1002/hipo.23460

The cerebellum contributes to context-effects during fear extinction learning: A 7T fMRI study

Batsikadze, G., Diekmann, N., Ernst, T. M., Klein, M., Maderwald, S., Deuschl, C., et al.

NeuroImage, 253, 119080

@article{BatsikadzeDiekmannErnstEtAl2022,
	author		=	{Batsikadze, Giorgi and Diekmann, Nicolas and Ernst, Thomas Michael and Klein, Michael and Maderwald, Stefan and Deuschl, Cornelius and Merz, Christian Josef and Cheng, Sen and Quick, Harald H. and Timmann, Dagmar},
	title		=	{The cerebellum contributes to context-effects during fear extinction learning: A 7T fMRI study},
	journal		=	{NeuroImage},
	volume		=	{253},
	pages		=	{119080},
	month		=	{June},
	year		=	{2022},
	doi		=	{10.1016/j.neuroimage.2022.119080},
}

What Happened When? Cerebral Processing of Modified Structure and Content in Episodic Cueing
Siestrup, S., Jainta, B., El-Sourani, N., Trempler, I., Wurm, M. F., Wolf, O. T., et al.
Journal of Cognitive Neuroscience, 34(7), 1287–1305

@article{SiestrupJaintaEl-SouraniEtAl2022, author = {Siestrup, Sophie and Jainta, Benjamin and El-Sourani, Nadiya and Trempler, Ima and Wurm, Moritz F. and Wolf, Oliver T. and Cheng, Sen and Schubotz, Ricarda I.}, title = {What Happened When? Cerebral Processing of Modified Structure and Content in Episodic Cueing}, journal = {Journal of Cognitive Neuroscience}, volume = {34}, number = {7}, pages = {1287–1305}, year = {2022}, doi = {10.1162/jocn_a_01862}, }

Siestrup, S., Jainta, B., El-Sourani, N., Trempler, I., Wurm, M. F., Wolf, O. T., et al. (2022). What Happened When? Cerebral Processing of Modified Structure and Content in Episodic Cueing. Journal of Cognitive Neuroscience, 34(7), 1287–1305. http://doi.org/10.1162/jocn_a_01862
Learning Cognitive Map Representations for Navigation by Sensory–Motor Integration
Zhao, D., Zhang, Z., Lu, H., Cheng, S., Si, B., & Feng, X.
IEEE Transactions on Cybernetics, 52(1), 508–521

@article{ZhaoZhangLuEtAl2022, author = {Zhao, Dongye and Zhang, Zheng and Lu, Hong and Cheng, Sen and Si, Bailu and Feng, Xisheng}, title = {Learning Cognitive Map Representations for Navigation by Sensory–Motor Integration}, journal = {IEEE Transactions on Cybernetics}, volume = {52}, number = {1}, pages = {508–521}, month = {January}, year = {2022}, doi = {10.1109/tcyb.2020.2977999}, }

Zhao, D., Zhang, Z., Lu, H., Cheng, S., Si, B., & Feng, X. (2022). Learning Cognitive Map Representations for Navigation by Sensory–Motor Integration. IEEE Transactions on Cybernetics, 52(1), 508–521. http://doi.org/10.1109/tcyb.2020.2977999

2021

A multistage retrieval account of associative recognition ROC curves

Hakobyan, O., & Cheng, S.

Learning and Memory, 28(11), 400–404

@article{HakobyanCheng2021b,
	author		=	{Hakobyan, Olya and Cheng, Sen},
	title		=	{A multistage retrieval account of associative recognition ROC curves},
	journal		=	{Learning and Memory},
	volume		=	{28},
	number		=	{11},
	pages		=	{400–404},
	month		=	{October},
	year		=	{2021},
	doi		=	{10.1101/lm.053432.121},
}

Emergence of complex dynamics of choice due to repeated exposures to extinction learning

Donoso, J. R., Packheiser, J., Pusch, R., Lederer, Z., Walther, T., Uengoer, M., et al.

Animal Cognition, 24(6), 1279–1297

@article{DonosoPackheiserPuschEtAl2021,
	author		=	{Donoso, José R. and Packheiser, Julian and Pusch, Roland and Lederer, Zhiyin and Walther, Thomas and Uengoer, Metin and Lachnit, Harald and Güntürkün, Onur and Cheng, Sen},
	title		=	{Emergence of complex dynamics of choice due to repeated exposures to extinction learning},
	journal		=	{Animal Cognition},
	volume		=	{24},
	number		=	{6},
	pages		=	{1279–1297},
	month		=	{May},
	year		=	{2021},
	doi		=	{10.1007/s10071-021-01521-4},
}

Recognition Receiver Operating Characteristic Curves: The Complex Influence of Input Statistics, Memory, and Decision-making
Hakobyan, O., & Cheng, S.
Journal of Cognitive Neuroscience, 33(6), 1032–1055

@article{HakobyanCheng2021, author = {Hakobyan, Olya and Cheng, Sen}, title = {Recognition Receiver Operating Characteristic Curves: The Complex Influence of Input Statistics, Memory, and Decision-making}, journal = {Journal of Cognitive Neuroscience}, volume = {33}, number = {6}, pages = {1032–1055}, month = {May}, year = {2021}, doi = {10.1162/jocn_a_01697}, }

Hakobyan, O., & Cheng, S.. (2021). Recognition Receiver Operating Characteristic Curves: The Complex Influence of Input Statistics, Memory, and Decision-making. Journal of Cognitive Neuroscience, 33(6), 1032–1055. http://doi.org/10.1162/jocn_a_01697
Self-referential false associations: A self-enhanced constructive effect for verbal but not pictorial stimuli
Wang, J., Otgaar, H., Howe, M. L., & Cheng, S.
Quarterly Journal of Experimental Psychology, 74(9), 1512–1524

@article{WangOtgaarHoweEtAl2021, author = {Wang, Jianqin and Otgaar, Henry and Howe, Mark L and Cheng, Sen}, title = {Self-referential false associations: A self-enhanced constructive effect for verbal but not pictorial stimuli}, journal = {Quarterly Journal of Experimental Psychology}, volume = {74}, number = {9}, pages = {1512–1524}, month = {April}, year = {2021}, doi = {10.1177/17470218211009772}, }

Wang, J., Otgaar, H., Howe, M. L., & Cheng, S.. (2021). Self-referential false associations: A self-enhanced constructive effect for verbal but not pictorial stimuli. Quarterly Journal of Experimental Psychology, 74(9), 1512–1524. http://doi.org/10.1177/17470218211009772
Trial-by-trial dynamics of reward prediction error-associated signals during extinction learning and renewal
Packheiser, J., Donoso, J. R., Cheng, S., Güntürkün, O., & Pusch, R.
Progress in Neurobiology, 197, 101901

@article{PackheiserDonosoChengEtAl2021, author = {Packheiser, Julian and Donoso, José R. and Cheng, Sen and Güntürkün, Onur and Pusch, Roland}, title = {Trial-by-trial dynamics of reward prediction error-associated signals during extinction learning and renewal}, journal = {Progress in Neurobiology}, volume = {197}, pages = {101901}, month = {February}, year = {2021}, doi = {10.1016/j.pneurobio.2020.101901}, }

Packheiser, J., Donoso, J. R., Cheng, S., Güntürkün, O., & Pusch, R. (2021). Trial-by-trial dynamics of reward prediction error-associated signals during extinction learning and renewal. Progress in Neurobiology, 197, 101901. http://doi.org/10.1016/j.pneurobio.2020.101901
Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach
Walther, T., Diekmann, N., Vijayabaskaran, S., Donoso, J. R., Manahan-Vaughan, D., Wiskott, L., & Cheng, S.
Scientific Reports, 11(1)

@article{WaltherDiekmannVijayabaskaranEtAl2021, author = {Walther, Thomas and Diekmann, Nicolas and Vijayabaskaran, Sandhiya and Donoso, José R. and Manahan-Vaughan, Denise and Wiskott, Laurenz and Cheng, Sen}, title = {Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach}, journal = {Scientific Reports}, volume = {11}, number = {1}, month = {February}, year = {2021}, doi = {10.1038/s41598-021-81157-z}, }

Walther, T., Diekmann, N., Vijayabaskaran, S., Donoso, J. R., Manahan-Vaughan, D., Wiskott, L., & Cheng, S.. (2021). Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach. Scientific Reports, 11(1). http://doi.org/10.1038/s41598-021-81157-z
Neuronal Sequences during Theta Rely on Behavior-Dependent Spatial Maps
Parra-Barrero, E., Diba, K., & Cheng, S.
eLife, 10, e70296

@article{Parra-BarreroDibaCheng2021, author = {Parra-Barrero, Eloy and Diba, Kamran and Cheng, Sen}, title = {Neuronal Sequences during Theta Rely on Behavior-Dependent Spatial Maps}, journal = {eLife}, volume = {10}, pages = {e70296}, year = {2021}, doi = {10.7554/eLife.70296}, }

Parra-Barrero, E., Diba, K., & Cheng, S.. (2021). Neuronal Sequences during Theta Rely on Behavior-Dependent Spatial Maps. eLife, 10, e70296. http://doi.org/10.7554/eLife.70296

2020

Improving sensory representations using episodic memory

Görler, R., Wiskott, L., & Cheng, S.

Hippocampus, 30(6), 638–656

@article{GörlerWiskottCheng2020,
	author		=	{Görler, Richard and Wiskott, Laurenz and Cheng, Sen},
	title		=	{Improving sensory representations using episodic memory},
	journal		=	{Hippocampus},
	volume		=	{30},
	number		=	{6},
	pages		=	{638–656},
	month		=	{December},
	year		=	{2020},
	doi		=	{10.1002/hipo.23186},
}

Automatic Tuning of RatSLAM′s Parameters by Irace and Iterative Closest Point
Menezes, M. C., Muñoz, M. E. S., Freitas, E. P., Cheng, S., Walther, T., Neto, A. A., et al.
In IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society (pp. 562–568)

@inproceedings{MenezesMuñozFreitasEtAl2020, author = {Menezes, M. C. and Muñoz, M. E. S. and Freitas, E. P. and Cheng, S. and Walther, T. and Neto, A. A. and Ribeiro, P. R. A. and Oliveira, A. C. M.}, title = {Automatic Tuning of RatSLAM′s Parameters by Irace and Iterative Closest Point}, booktitle = {IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society}, pages = {562–568}, month = {October}, year = {2020}, doi = {10.1109/IECON43393.2020.9254718}, }

Menezes, M. C., Muñoz, M. E. S., Freitas, E. P., Cheng, S., Walther, T., Neto, A. A., et al. (2020). Automatic Tuning of RatSLAM′s Parameters by Irace and Iterative Closest Point. In IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society (pp. 562–568). http://doi.org/10.1109/IECON43393.2020.9254718

2019

Hippocampal Reactivation Extends for Several Hours Following Novel Experience
Giri, B., Miyawaki, H., Mizuseki, K., Cheng, S., & Diba, K.
The Journal of Neuroscience, 39(5), 866–875

link

@article{GiriMiyawakiMizusekiEtAl2019, author = {Giri, Bapun and Miyawaki, Hiroyuki and Mizuseki, Kenji and Cheng, Sen and Diba, Kamran}, title = {Hippocampal Reactivation Extends for Several Hours Following Novel Experience}, journal = {The Journal of Neuroscience}, volume = {39}, number = {5}, pages = {866–875}, month = {December}, year = {2019}, doi = {10.1523/jneurosci.1950-18.2018}, }

Giri, B., Miyawaki, H., Mizuseki, K., Cheng, S., & Diba, K. (2019). Hippocampal Reactivation Extends for Several Hours Following Novel Experience. The Journal of Neuroscience, 39(5), 866–875. http://doi.org/10.1523/jneurosci.1950-18.2018

Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia)

Azizi, A. H., Pusch, R., Koenen, C., Klatt, S., Bröcker, F., Thiele, S., et al.

Behavioural Brain Research, 356, 423–434

@article{AziziPuschKoenenEtAl2019,
	author		=	{Azizi, Amir Hossein and Pusch, Roland and Koenen, Charlotte and Klatt, Sebastian and Bröcker, Franziska and Thiele, Samuel and Kellermann, Janosch and Güntürkün, Onur and Cheng, Sen},
	title		=	{Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia)},
	journal		=	{Behavioural Brain Research},
	volume		=	{356},
	pages		=	{423–434},
	month		=	{January},
	year		=	{2019},
	doi		=	{10.1016/j.bbr.2018.05.014},
}

A Parallel RatSlam C++ Library Implementation
de Souza Muñoz, M. E., Menezes, M. C., de Freitas, E. P., Cheng, S., de Almeida Neto, A., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R.
In Communications in Computer and Information Science (pp. 173–183) Springer International Publishing

@incollection{de Souza MuñozMenezesde FreitasEtAl2019, author = {de Souza Muñoz, Mauro Enrique and Menezes, Matheus Chaves and de Freitas, Edison Pignaton and Cheng, Sen and de Almeida Neto, Areolino and de Oliveira, Alexandre César Muniz and de Almeida Ribeiro, Paulo Rogério}, title = {A Parallel RatSlam C++ Library Implementation}, booktitle = {Communications in Computer and Information Science}, pages = {173–183}, publisher = {Springer International Publishing}, year = {2019}, doi = {10.1007/978-3-030-36636-0_13}, }

de Souza Muñoz, M. E., Menezes, M. C., de Freitas, E. P., Cheng, S., de Almeida Neto, A., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R. (2019). A Parallel RatSlam C++ Library Implementation. In Communications in Computer and Information Science (pp. 173–183). Springer International Publishing. http://doi.org/10.1007/978-3-030-36636-0_13
Deep reinforcement learning in a spatial navigation task: Multiple contexts and their representation
Diekmann, N., Walther, T., Vijayabaskaran, S., & Cheng, S.
In 2019 Conference on Cognitive Computational Neuroscience Berlin, Germany: Cognitive Computational Neuroscience

@inproceedings{DiekmannWaltherVijayabaskaranEtAl2019, author = {Diekmann, Nicolas and Walther, Thomas and Vijayabaskaran, Sandhiya and Cheng, Sen}, title = {Deep reinforcement learning in a spatial navigation task: Multiple contexts and their representation}, booktitle = {2019 Conference on Cognitive Computational Neuroscience}, publisher = {Cognitive Computational Neuroscience}, address = {Berlin, Germany}, year = {2019}, doi = {10.32470/CCN.2019.1151-0}, }

Diekmann, N., Walther, T., Vijayabaskaran, S., & Cheng, S.. (2019). Deep reinforcement learning in a spatial navigation task: Multiple contexts and their representation. In 2019 Conference on Cognitive Computational Neuroscience. Berlin, Germany: Cognitive Computational Neuroscience. http://doi.org/10.32470/CCN.2019.1151-0
How do memory modules differentially contribute to familiarity and recollection?
Hakobyan, O., & Cheng, S.
Behavioral and Brain Sciences, 42, e288

@article{HakobyanCheng2019, author = {Hakobyan, Olya and Cheng, Sen}, title = {How do memory modules differentially contribute to familiarity and recollection?}, journal = {Behavioral and Brain Sciences}, volume = {42}, pages = {e288}, year = {2019}, doi = {10.1017/S0140525X19001833}, }

Hakobyan, O., & Cheng, S.. (2019). How do memory modules differentially contribute to familiarity and recollection? Behavioral and Brain Sciences, 42, e288. http://doi.org/10.1017/S0140525X19001833
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences
Melchior, J., Bayati, M., Azizi, A., Cheng, S., & Wiskott, L.
CoRR e-print arXiv:1905.12937

@misc{MelchiorBayatiAziziEtAl2019, author = {Melchior, Jan and Bayati, Mehdi and Azizi, Amir and Cheng, Sen and Wiskott, Laurenz}, title = {A Hippocampus Model for Online One-Shot Storage of Pattern Sequences}, howpublished = {e-print arXiv:1905.12937}, year = {2019}, }

Melchior, J., Bayati, M., Azizi, A., Cheng, S., & Wiskott, L.. (2019). A Hippocampus Model for Online One-Shot Storage of Pattern Sequences. CoRR. e-print arXiv:1905.12937. Retrieved from https://arxiv.org/abs/1905.12937

2018

A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems
Menezes, M. C., de Freitas, E. P., Cheng, S., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R.
In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) IEEE

@inproceedings{Menezesde FreitasChengEtAl2018, author = {Menezes, Matheus Chaves and de Freitas, Edison Pignaton and Cheng, Sen and de Oliveira, Alexandre Cesar Muniz and de Almeida Ribeiro, Paulo Rogerio}, title = {A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems}, booktitle = {2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)}, publisher = {IEEE}, month = {November}, year = {2018}, doi = {10.1109/icarcv.2018.8581270}, }

Menezes, M. C., de Freitas, E. P., Cheng, S., de Oliveira, A. C. M., & de Almeida Ribeiro, P. R. (2018). A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems. In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE. http://doi.org/10.1109/icarcv.2018.8581270
Autonomous Exploration Guided by Optimisation Metaheuristic
Santos, R. G., de Freitas, E. P., Cheng, S., de Almeida Ribeiro, P. R., & de Oliveira, A. C. M.
In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) IEEE

@inproceedings{Santosde FreitasChengEtAl2018, author = {Santos, Raphael Gomes and de Freitas, Edison Pignaton and Cheng, Sen and de Almeida Ribeiro, Paulo Rogerio and de Oliveira, Alexandre Cesar Muniz}, title = {Autonomous Exploration Guided by Optimisation Metaheuristic}, booktitle = {2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)}, publisher = {IEEE}, month = {November}, year = {2018}, doi = {10.1109/icarcv.2018.8581136}, }

Santos, R. G., de Freitas, E. P., Cheng, S., de Almeida Ribeiro, P. R., & de Oliveira, A. C. M. (2018). Autonomous Exploration Guided by Optimisation Metaheuristic. In 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE. http://doi.org/10.1109/icarcv.2018.8581136

Storage fidelity for sequence memory in the hippocampal circuit

Bayati, M., Neher, T., Melchior, J., Diba, K., Wiskott, L., & Cheng, S.

PLOS ONE, 13(10), e0204685

@article{BayatiNeherMelchiorEtAl2018,
	author		=	{Bayati, Mehdi and Neher, Torsten and Melchior, Jan and Diba, Kamran and Wiskott, Laurenz and Cheng, Sen},
	title		=	{Storage fidelity for sequence memory in the hippocampal circuit},
	journal		=	{PLOS ONE},
	volume		=	{13},
	number		=	{10},
	pages		=	{e0204685},
	month		=	{October},
	year		=	{2018},
	doi		=	{10.1371/journal.pone.0204685},
}

The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory
Fang, J., Demic, S., & Cheng, S.
PLOS ONE, 13(6), e0198406

@article{FangDemicCheng2018, author = {Fang, Jing and Demic, Selver and Cheng, Sen}, title = {The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory}, journal = {PLOS ONE}, volume = {13}, number = {6}, pages = {e0198406}, month = {June}, year = {2018}, doi = {10.1371/journal.pone.0198406}, }

Fang, J., Demic, S., & Cheng, S.. (2018). The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory. PLOS ONE, 13(6), e0198406. http://doi.org/10.1371/journal.pone.0198406

The Interaction between Semantic Representation and Episodic Memory

Fang, J., Rüther, N., Bellebaum, C., Wiskott, L., & Cheng, S.

Neural Computation, 30(2), 293–332

@article{FangRütherBellebaumEtAl2018,
	author		=	{Fang, Jing and Rüther, Naima and Bellebaum, Christian and Wiskott, Laurenz and Cheng, Sen},
	title		=	{The Interaction between Semantic Representation and Episodic Memory},
	journal		=	{Neural Computation},
	volume		=	{30},
	number		=	{2},
	pages		=	{293–332},
	month		=	{February},
	year		=	{2018},
	doi		=	{10.1162/neco_a_01044},
}

Doing without metarepresentation: Scenario construction explains the epistemic generativity and privileged status of episodic memory
Werning, M., & Cheng, S.
Behavioral and Brain Sciences, 41, e34

@article{WerningCheng2018, author = {Werning, Markus and Cheng, Sen}, title = {Doing without metarepresentation: Scenario construction explains the epistemic generativity and privileged status of episodic memory}, journal = {Behavioral and Brain Sciences}, volume = {41}, pages = {e34}, year = {2018}, doi = {10.1017/s0140525x17001534}, }

Werning, M., & Cheng, S.. (2018). Doing without metarepresentation: Scenario construction explains the epistemic generativity and privileged status of episodic memory. Behavioral and Brain Sciences, 41, e34. http://doi.org/10.1017/s0140525x17001534

2017

Generating sequences in recurrent neural networks for storing and retrieving episodic memories
Bayati, M., Melchior, J., Wiskott, L., & Cheng, S.
In Proc. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2

@inproceedings{BayatiMelchiorWiskottEtAl2017, author = {Bayati, Mehdi and Melchior, Jan and Wiskott, Laurenz and Cheng, Sen}, title = {Generating sequences in recurrent neural networks for storing and retrieving episodic memories}, booktitle = {Proc. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2}, year = {2017}, }

Bayati, M., Melchior, J., Wiskott, L., & Cheng, S.. (2017). Generating sequences in recurrent neural networks for storing and retrieving episodic memories. In Proc. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2. Retrieved from http://europepmc.org/articles/PMC5592442
Consolidation of Episodic Memory: An Epiphenomenon of Semantic Learning
Cheng, S.
In N. Axmacher & Rasch, B. (Eds.), Cognitive Neuroscience of Memory Consolidation (pp. 57–72) Cham, Switzerland: Springer International Publishing

@incollection{Cheng2017, author = {Cheng, Sen}, title = {Consolidation of Episodic Memory: An Epiphenomenon of Semantic Learning}, booktitle = {Cognitive Neuroscience of Memory Consolidation}, editor = {Axmacher, Nikolai and Rasch, Björn}, pages = {57–72}, publisher = {Springer International Publishing}, chapter = {4}, address = {Cham, Switzerland}, year = {2017}, doi = {10.1007/978-3-319-45066-7_4}, }

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

From grid cells to place cells with realistic field sizes

Neher, T., Azizi, A. H., & Cheng, S.

PLoS ONE, 12(7), e0181618

@article{NeherAziziCheng2017,
	author		=	{Neher, Torsten and Azizi, Amir H and Cheng, Sen},
	title		=	{From grid cells to place cells with realistic field sizes},
	journal		=	{PLoS ONE},
	volume		=	{12},
	number		=	{7},
	pages		=	{e0181618},
	year		=	{2017},
	doi		=	{10.1371/JOURNAL.PONE.0181618},
}

Taxonomy and Unity of Memory
Werning, M., & Cheng, S.
In S. Bernecker & Michaelian, K. (Eds.), The Routledge Handbook of Philosophy of Memory (pp. 7–20) New York: Routledge

@incollection{WerningCheng2017, author = {Werning, Markus and Cheng, Sen}, title = {Taxonomy and Unity of Memory}, booktitle = {The Routledge Handbook of Philosophy of Memory}, editor = {Bernecker, Sven and Michaelian, Kourken}, pages = {7–20}, publisher = {Routledge}, chapter = {1}, address = {New York}, year = {2017}, }

Werning, M., & Cheng, S.. (2017). Taxonomy and Unity of Memory. In S. Bernecker & Michaelian, K. (Eds.), The Routledge Handbook of Philosophy of Memory (pp. 7–20). New York: Routledge.

2016

Topological Schemas of Cognitive Maps and Spatial Learning
Babichev, A., Cheng, S., & Dabaghian, Y. A.
Frontiers in Computational Neuroscience, 10, 18

@article{BabichevChengDabaghian2016, author = {Babichev, Andrey and Cheng, Sen and Dabaghian, Yuri A.}, title = {Topological Schemas of Cognitive Maps and Spatial Learning}, journal = {Frontiers in Computational Neuroscience}, volume = {10}, pages = {18}, year = {2016}, doi = {10.3389/fncom.2016.00018}, }

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

What is episodic memory if it is a natural kind?

Cheng, S., & Werning, M.

Synthese, 193(5), 1345–1385

@article{ChengWerning2016,
	author		=	{Cheng, Sen and Werning, Markus},
	title		=	{What is episodic memory if it is a natural kind?},
	journal		=	{Synthese},
	volume		=	{193},
	number		=	{5},
	pages		=	{1345–1385},
	year		=	{2016},
	doi		=	{10.1007/s11229-014-0628-6},
}

Dissociating memory traces and scenario construction in mental time travel
Cheng, S., Werning, M., & Suddendorf, T.
Neuroscience & Biobehavioral Reviews, 60, 82–89

@article{ChengWerningSuddendorf2016, author = {Cheng, Sen and Werning, Markus and Suddendorf, Thomas}, title = {Dissociating memory traces and scenario construction in mental time travel}, journal = {Neuroscience & Biobehavioral Reviews}, volume = {60}, pages = {82–89}, month = {January}, year = {2016}, doi = {10.1016/j.neubiorev.2015.11.011}, }

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

2015

Self-organization of synchronous activity propagation in neuronal networks driven by local excitation
Bayati, M., Valizadeh, A., Abbassian, A., & Cheng, S.
Frontiers in Computational Neuroscience, 9, 69

@article{BayatiValizadehAbbassianEtAl2015, author = {Bayati, Mehdi and Valizadeh, Alireza and Abbassian, Abdolhossein and Cheng, Sen}, title = {Self-organization of synchronous activity propagation in neuronal networks driven by local excitation}, journal = {Frontiers in Computational Neuroscience}, volume = {9}, pages = {69}, year = {2015}, doi = {10.3389/fncom.2015.00069}, }

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
Memory Storage Fidelity in the Hippocampal Circuit: The Role of Subregions and Input Statistics
Neher, T., Cheng, S., & Wiskott, L.
PLoS Computational Biology, 11(5), e1004250

Journal's article page

@article{NeherChengWiskott2015, author = {Neher, Torsten and Cheng, Sen and Wiskott, Laurenz}, title = {Memory Storage Fidelity in the Hippocampal Circuit: The Role of Subregions and Input Statistics}, journal = {PLoS Computational Biology}, volume = {11}, number = {5}, pages = {e1004250}, year = {2015}, doi = {10.1371/journal.pcbi.1004250}, }

Neher, T., Cheng, S., & Wiskott, L.. (2015). Memory Storage Fidelity in the Hippocampal Circuit: The Role of Subregions and Input Statistics. PLoS Computational Biology, 11(5), e1004250. http://doi.org/10.1371/journal.pcbi.1004250

2014

Modeling the Dynamics of Disease States in Depression

Demic, S., & Cheng, S.

PLOS ONE, 9(10), 1–14

@article{DemicCheng2014,
	author		=	{Demic, Selver and Cheng, Sen},
	title		=	{Modeling the Dynamics of Disease States in Depression},
	journal		=	{PLOS ONE},
	volume		=	{9},
	number		=	{10},
	pages		=	{1–14},
	month		=	{October},
	year		=	{2014},
	doi		=	{10.1371/journal.pone.0110358},
}

The transformation from grid cells to place cells is robust to noise in the grid pattern
Azizi, A. H., Schieferstein, N., & Cheng, S.
Hippocampus, 24(8), 912–919

@article{AziziSchiefersteinCheng2014, author = {Azizi, Amir H. and Schieferstein, Natalie and Cheng, Sen}, title = {The transformation from grid cells to place cells is robust to noise in the grid pattern}, journal = {Hippocampus}, volume = {24}, number = {8}, pages = {912–919}, year = {2014}, doi = {10.1002/hipo.22306}, }

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
Parametric Anatomical Modeling: a method for modeling the anatomical layout of neurons and their projections
Pyka, M., Klatt, S., & Cheng, S.
Frontiers in Neuroanatomy, 8, 91

@article{PykaKlattCheng2014, author = {Pyka, Martin and Klatt, Sebastian and Cheng, Sen}, title = {Parametric Anatomical Modeling: a method for modeling the anatomical layout of neurons and their projections}, journal = {Frontiers in Neuroanatomy}, volume = {8}, pages = {91}, year = {2014}, doi = {10.3389/fnana.2014.00091}, }

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
Is Episodic Memory a Natural Kind?-A Defense of the Sequence Analysis
Werning, M., & Cheng, S.
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

Is Episodic Memory a Natural Kind? - A Defense of the Sequence Analysis

@inproceedings{WerningCheng2014, author = {Werning, Markus and Cheng, Sen}, title = {Is Episodic Memory a Natural Kind?-A Defense of the Sequence Analysis}, booktitle = {Proceedings of the 36th Annual Conference of the Cognitive Science Society}, editor = {Bello, P and Guarini, M and McShane, M and Scassellati, B}, pages = {964–69}, publisher = {Cognitive Science Society}, volume = {2}, address = {Austin, TX}, year = {2014}, }

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

2013

Composition and replay of mnemonic sequences: The contributions of REM and slow-wave sleep to episodic memory
Cheng, S., & Werning, M.
Behavioral and Brain Sciences, 36(06), 610–611

@article{ChengWerning2013, author = {Cheng, Sen and Werning, Markus}, title = {Composition and replay of mnemonic sequences: The contributions of REM and slow-wave sleep to episodic memory}, journal = {Behavioral and Brain Sciences}, volume = {36}, number = {06}, pages = {610–611}, month = {November}, year = {2013}, doi = {10.1017/s0140525x13001234}, }

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
A computational model for preplay in the hippocampus
Azizi, A. H., Wiskott, L., & Cheng, S.
Frontiers in Computational Neuroscience, 7, 161

@article{AziziWiskottCheng2013, author = {Azizi, Amir Hossein and Wiskott, Laurenz and Cheng, Sen}, title = {A computational model for preplay in the hippocampus}, journal = {Frontiers in Computational Neuroscience}, volume = {7}, pages = {161}, year = {2013}, doi = {10.3389/fncom.2013.00161}, }

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
The CRISP theory of hippocampal function in episodic memory
Cheng, S.
Frontiers in Neural Circuits, 7, 88

@article{Cheng2013, author = {Cheng, Sen}, title = {The CRISP theory of hippocampal function in episodic memory}, journal = {Frontiers in Neural Circuits}, volume = {7}, pages = {88}, year = {2013}, doi = {10.3389/fncir.2013.00088}, }

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
Identification of two forebrain structures that mediate execution of memorized sequences in the pigeon
Helduser, S., Cheng, S., & Güntürkün, O.
Journal of Neurophysiology, 109(4), 958–968

@article{HelduserChengGüntürkün2013, author = {Helduser, Sascha and Cheng, Sen and Güntürkün, Onur}, title = {Identification of two forebrain structures that mediate execution of memorized sequences in the pigeon}, journal = {Journal of Neurophysiology}, volume = {109}, number = {4}, pages = {958–968}, year = {2013}, doi = {10.1152/jn.00763.2012}, }

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

2012

Constraints on the synchronization of entorhinal cortex stellate cells
Crotty, P., Lasker, E., & Cheng, S.
Phys. Rev. E, 86(1), 011908

@article{CrottyLaskerCheng2012, author = {Crotty, Patrick and Lasker, Eric and Cheng, Sen}, title = {Constraints on the synchronization of entorhinal cortex stellate cells}, journal = {Phys. Rev. E}, volume = {86}, pages = {011908}, month = {July }, year = {2012}, doi = {10.1103/PhysRevE.86.011908}, }

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

2011

Reactivation, Replay, and Preplay: How It Might All Fit Together
Buhry, L., Azizi, A. H., & Cheng, S.
Neural Plasticity, 2011, 1–11

@article{BuhryAziziCheng2011, author = {Buhry, Laure and Azizi, Amir H. and Cheng, Sen}, title = {Reactivation, Replay, and Preplay: How It Might All Fit Together}, journal = {Neural Plasticity}, volume = {2011}, pages = {1–11}, year = {2011}, doi = {10.1155/2011/203462}, }

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
The structure of networks that produce the transformation from grid cells to place cells
Cheng, S., & Frank, L. M.
Neuroscience , 197, 293–306

@article{ChengFrank2011, author = {Cheng, S. and Frank, L.M.}, title = {The structure of networks that produce the transformation from grid cells to place cells }, journal = {Neuroscience }, volume = {197}, pages = {293–306}, year = {2011}, doi = {10.1016/j.neuroscience.2011.09.002}, }

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

2008

New Experiences Enhance Coordinated Neural Activity in the Hippocampus
Cheng, S., & Frank, L. M.
Neuron , 57(2), 303–313

@article{ChengFrank2008, author = {Cheng, Sen and Frank, Loren M.}, title = {New Experiences Enhance Coordinated Neural Activity in the Hippocampus }, journal = {Neuron }, volume = {57}, number = {2}, pages = {303–313}, year = {2008}, doi = {10.1016/j.neuron.2007.11.035}, }

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

2007

Calibration of Visually Guided Reaching Is Driven by Error-Corrective Learning and Internal Dynamics
Cheng, S., & Sabes, P. N.
Journal of Neurophysiology, 97(4), 3057–3069

Cheng, Sabes - 2007

@article{ChengSabes2007, author = {Cheng, Sen and Sabes, Philip N.}, title = {Calibration of Visually Guided Reaching Is Driven by Error-Corrective Learning and Internal Dynamics}, journal = {Journal of Neurophysiology}, volume = {97}, number = {4}, pages = {3057–3069}, year = {2007}, doi = {10.1152/jn.00897.2006}, }

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

2006

Modeling Sensorimotor Learning with Linear Dynamical Systems
Cheng, S., & Sabes, P. N.
Neural Computation, 18(4), 760–793

Cheng, Sabes 2006

@article{ChengSabes2006, author = {Cheng, Sen and Sabes, Philip N.}, title = {Modeling Sensorimotor Learning with Linear Dynamical Systems}, journal = {Neural Computation}, volume = {18}, number = {4}, pages = {760–793}, month = {April}, year = {2006}, doi = {10.1162/neco.2006.18.4.760}, }

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

2004

Statistical and dynamic models of charge balance functions

Cheng, S., Petriconi, S., Pratt, S., Skoby, M., Gale, C., Jeon, S., et al.

Phys. Rev. C, 69(5), 054906

@article{ChengPetriconiPrattEtAl2004,
	author		=	{Cheng, Sen and Petriconi, Silvio and Pratt, Scott and Skoby, Michael and Gale, Charles and Jeon, Sangyong and Topor Pop, Vasile and Zhang, Qing-Hui},
	title		=	{Statistical and dynamic models of charge balance functions},
	journal		=	{Phys. Rev. C},
	volume		=	{69},
	pages		=	{054906},
	month		=	{May},
	year		=	{2004},
	doi		=	{10.1103/PhysRevC.69.054906},
}

2003

Removing distortions from charge balance functions

Pratt, S., & Cheng, S.

Phys. Rev. C, 68(1), 014907

@article{PrattCheng2003,
	author		=	{Pratt, Scott and Cheng, Sen},
	title		=	{Removing distortions from charge balance functions},
	journal		=	{Phys. Rev. C},
	volume		=	{68},
	pages		=	{014907},
	month		=	{July },
	year		=	{2003},
	doi		=	{10.1103/PhysRevC.68.014907},
}

Isospin fluctuations from a thermally equilibrated hadron gas

Cheng, S., & Pratt, S.

Phys. Rev. C, 67(4), 044904

@article{ChengPratt2003,
	author		=	{Cheng, Sen and Pratt, Scott},
	title		=	{Isospin fluctuations from a thermally equilibrated hadron gas},
	journal		=	{Phys. Rev. C},
	volume		=	{67},
	pages		=	{044904},
	month		=	{April},
	year		=	{2003},
	doi		=	{10.1103/PhysRevC.67.044904},
}

2002

Statistical physics in a finite volume with absolute conservation laws
Cheng, S.

Statistical Physics in a Finite Volume with Absolute Conservation Laws

@article{Cheng2002, author = {Cheng, Sen}, title = {Statistical physics in a finite volume with absolute conservation laws}, year = {2002}, }

Cheng, S. (2002). Statistical physics in a finite volume with absolute conservation laws.
Modeling Relativistic Heavy Ion Collisions
Cheng, S.

MODELING RELATIVISTIC HEAVY ION COLLISIONS

@article{Cheng2002b, author = {Cheng, Sen}, title = {Modeling Relativistic Heavy Ion Collisions}, year = {2002}, }

Cheng, S. (2002). Modeling Relativistic Heavy Ion Collisions.

Effect of finite-range interactions in classical transport theory

Cheng, S., Pratt, S., Csizmadia, P., Nara, Y., Molnár, D., Gyulassy, M., et al.

Phys. Rev. C, 65(2), 024901

@article{ChengPrattCsizmadiaEtAl2002,
	author		=	{Cheng, Sen and Pratt, Scott and Csizmadia, Peter and Nara, Yasushi and Molnár, Dénes and Gyulassy, Miklos and Vance, Stephen E. and Zhang, Bin},
	title		=	{Effect of finite-range interactions in classical transport theory},
	journal		=	{Phys. Rev. C},
	volume		=	{65},
	pages		=	{024901},
	month		=	{January},
	year		=	{2002},
	doi		=	{10.1103/PhysRevC.65.024901},
}

2001

Quantum corrections for pion correlations involving resonance decays
Cheng, S., & Pratt, S.
Phys. Rev. C, 63(5), 054904

@article{ChengPratt2001, author = {Cheng, Sen and Pratt, Scott}, title = {Quantum corrections for pion correlations involving resonance decays}, journal = {Phys. Rev. C}, volume = {63}, pages = {054904}, month = {April}, year = {2001}, doi = {10.1103/PhysRevC.63.054904}, }

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

Summer Term 2025

Seminars	Colloquium: Brains in Space: An Interdisciplinary Research Colloquium on Spatial Navigation
Lectures	Introduction to Computational Neuroscience
Seminars	Journal Club "Learning and Memory"
Seminars	Seminar Computational Neuroscience
Seminars	Seminar From Biological to Artificial Neural Networks

Winter Term 2024/2025

Seminars

Colloquium: Brains in Space: An Interdisciplinary Research Colloquium on Spatial Navigation

Summer Term 2024

Seminars	Colloquium: Brains in Space: An Interdisciplinary Research Colloquium on Spatial Navigation
Lectures	Introduction to Artificial Intelligence
Lectures	Introduction to Computational Neuroscience
Seminars	Journal Club "Learning and Memory"
Seminars	Seminar Computational Neuroscience
Seminars	Seminar From Biological to Artificial Neural Networks

Winter Term 2023/2024

Lectures	Artificial Neural Networks
Seminars	Journal Club: Learning and Memory
Seminars	Research Colloquium: Interdisciplinary Perspectives on Episodic Memory

Summer Term 2023

Lectures	Introduction to Computational Neuroscience
Seminars	Journal Club "Learning and Memory"
Seminars	Seminar Computational Neuroscience
Seminars	Seminar From Biological to Artificial Neural Networks

Winter Term 2022/2023

Lectures	Artificial Neural Networks
Seminars	Journal Club: Learning and Memory
Seminars	Research Colloquium: Interdisciplinary Perspectives on Episodic Memory

Summer Term 2022

Lectures	Introduction to Computational Neuroscience
Seminars	Journal Club "Learning and Memory"
Seminars	Research Colloquium: Interdisciplinary Perspectives on Episodic Memory

Winter Term 2021/2022

Lectures	Artificial Neural Networks
Seminars	Journal Club: Learning and Memory
Seminars	Research Colloquium: Interdisciplinary Perspectives on Episodic Memory

Summer Term 2021

Lectures	Introduction to Computational Neuroscience
Seminars	Journal Club "Learning and Memory"
Seminars	Research Colloquium: Interdisciplinary Perspectives on Episodic Memory

Winter Term 2020/2021

Lectures	Artificial Neural Networks
Seminars	Journal Club: Learning and Memory

Summer Term 2020

Seminars

Journal Club "Learning and Memory"

Winter Term 2019/2020

Lectures	Artificial Neural Networks
Seminars	Journal Club: Learning and Memory

Summer Term 2019

Seminars	Journal Club "Learning and Memory"
Lectures	Mathematical Psychology

Winter Term 2018/2019

Seminars	Computational Cognitive Modeling
Lectures	Introduction to Perception
Seminars	Journal Club: Learning and Memory
Seminars	The Neural Basis of Vision

Summer Term 2018

Seminars	Discourse in Episodic Memory
Seminars	Journal Club "Learning and Memory"
Lectures	Mathematical Psychology

Winter Term 2017/2018

Seminars	Colloquium: Learning and Memory
Seminars	Computational Cognitive Modeling
Lectures	Introduction to Perception

Summer Term 2017

Seminars	Discourse in Episodic Memory
Seminars	Journal Club "Learning and Memory"
Lectures	Mathematical Psychology

Winter Term 2016/2017

Seminars	Colloquium: Learning and Memory
Seminars	Computational Cognitive Modeling
Lectures	Introduction to Perception
Seminars	The Neural Basis of Vision

Summer Term 2016

Seminars	S Discourse in Episodic Memory
Seminars	S Journal Club "Learning and Memory"
Seminars	S Mathematical Psychology

Summer Term 2025

Lectures

Introduction to Artificial Intelligence

Summer Term 2023

Lectures

Introduction to Artificial Intelligence

Summer Term 2022

Lectures

Introduction to Artificial Intelligence

Summer Term 2021

Lectures

Introduction to Artificial Intelligence

2024

Sequential Replay and Network Instability in Deep Reinforcement Learning
Jentgens, S.
Bachelor's thesis, Computer Science, Free University of Berlin, Germany

@bachelorthesis{Jentgens2024, author = {Jentgens, Sebastian}, title = {Sequential Replay and Network Instability in Deep Reinforcement Learning}, school = {Computer Science, Free University of Berlin, Germany}, month = {November}, year = {2024}, }

Jentgens, S. (2024, November). Sequential Replay and Network Instability in Deep Reinforcement Learning. Bachelor's thesis, Computer Science, Free University of Berlin, Germany.
Reinforced learning model of biases in behavior and replay due to motivational state
Plavnik, T.
Bachelor's thesis, Computer Science, Ruhr University Bochum, Germany

@bachelorthesis{Plavnik2024, author = {Plavnik, Timur}, title = {Reinforced learning model of biases in behavior and replay due to motivational state}, school = {Computer Science, Ruhr University Bochum, Germany}, month = {November}, year = {2024}, }

Plavnik, T. (2024, November). Reinforced learning model of biases in behavior and replay due to motivational state. Bachelor's thesis, Computer Science, Ruhr University Bochum, Germany.

2023

Injecting noise into a spiking neural network model of spatial learning to induce exploration
Buhaiev, A.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Buhaiev2023, author = {Buhaiev, Artem}, title = {Injecting noise into a spiking neural network model of spatial learning to induce exploration}, year = {2023}, }

Buhaiev, A. (2023, October). Injecting noise into a spiking neural network model of spatial learning to induce exploration. Applied Computer Science, Ruhr University Bochum, Germany.
Modeling the targeted manipulation of behavior with reinforcement learning
Gerecke, J. T.
Bachelor's thesis, IT Security, Ruhr University Bochum, Germany

@bachelorthesis{Gerecke2023, author = {Gerecke, Julius Tim}, title = {Modeling the targeted manipulation of behavior with reinforcement learning}, school = {IT Security, Ruhr University Bochum, Germany}, month = {September}, year = {2023}, }

Gerecke, J. T. (2023, September). Modeling the targeted manipulation of behavior with reinforcement learning. Bachelor's thesis, IT Security, Ruhr University Bochum, Germany.
Comparing recurrent and feed-forward reinforcement learning agents in a spatial working memory task
Forchap, W.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Forchap2023, author = {Forchap, William}, title = {Comparing recurrent and feed-forward reinforcement learning agents in a spatial working memory task}, year = {2023}, }

Forchap, W. (2023, June). Comparing recurrent and feed-forward reinforcement learning agents in a spatial working memory task. Applied Computer Science, Ruhr University Bochum, Germany.
Comparison of Monte Carlo tree search with a MiniMax algorithm in perfect information games
Kröcker, B.
Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Kröcker2023, author = {Kröcker, Benjamin}, title = {Comparison of Monte Carlo tree search with a MiniMax algorithm in perfect information games}, year = {2023}, }

Kröcker, B. (2023, March). Comparison of Monte Carlo tree search with a MiniMax algorithm in perfect information games. Computer Science, Ruhr University Bochum, Germany.
Studying the role of grid cell properties in spatial navigation with spiking neural networks
Boughedda, I.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Boughedda2023, author = {Boughedda, Issam}, title = {Studying the role of grid cell properties in spatial navigation with spiking neural networks}, year = {2023}, }

Boughedda, I. (2023, January). Studying the role of grid cell properties in spatial navigation with spiking neural networks. Applied Computer Science, Ruhr University Bochum, Germany.

2022

Analyses of emerging representations in Supervised Learning of spatial tasks with Convolutional Neural Networks
Mousavi, S.
Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany

@mastersthesis{Mousavi2022, author = {Mousavi, Seyed}, title = {Analyses of emerging representations in Supervised Learning of spatial tasks with Convolutional Neural Networks}, school = {Applied Computer Science, Ruhr University Bochum, Germany}, month = {December}, year = {2022}, }

Mousavi, S. (2022, December). Analyses of emerging representations in Supervised Learning of spatial tasks with Convolutional Neural Networks. Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany.
Learning hippocampal theta sequences with behavioral timescale synaptic plasticity
Kerscher, M.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Kerscher2022, author = {Kerscher, Marvin}, title = {Learning hippocampal theta sequences with behavioral timescale synaptic plasticity}, year = {2022}, }

Kerscher, M. (2022, August). Learning hippocampal theta sequences with behavioral timescale synaptic plasticity. Applied Computer Science, Ruhr University Bochum, Germany.
A model of hippocampal theta sequences based on phase precession and behavioral time scale plasticity
Tomashevskaya, A.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Tomashevskaya2022, author = {Tomashevskaya, Anna}, title = {A model of hippocampal theta sequences based on phase precession and behavioral time scale plasticity}, year = {2022}, }

Tomashevskaya, A. (2022, August). A model of hippocampal theta sequences based on phase precession and behavioral time scale plasticity. Applied Computer Science, Ruhr University Bochum, Germany.
The Influence of Stimulus Representations on Recognition Memory
Pronoza, J.
Master’s thesis, Medical Physics, TU Dortmund, Germany

@mastersthesis{Pronoza2022, author = {Pronoza, Julia}, title = {The Influence of Stimulus Representations on Recognition Memory}, school = {Medical Physics, TU Dortmund, Germany}, month = {June}, year = {2022}, }

Pronoza, J. (2022, June). The Influence of Stimulus Representations on Recognition Memory. Master’s thesis, Medical Physics, TU Dortmund, Germany.
Anwendung eines Objektalgorithmus auf Textblöcken
Markl, S.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Markl2022, author = {Markl, Susanne}, title = {Anwendung eines Objektalgorithmus auf Textblöcken}, year = {2022}, }

Markl, S. (2022, March). Anwendung eines Objektalgorithmus auf Textblöcken. Applied Computer Science, Ruhr University Bochum, Germany.

2021

Spatial Representations in an Egocentric Navigation Task using Deep Reinforcement Learning
Al-Dilaimi, S.
Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany

@mastersthesis{Al-Dilaimi2021, author = {Al-Dilaimi, Saif}, title = {Spatial Representations in an Egocentric Navigation Task using Deep Reinforcement Learning}, school = {Applied Computer Science, Ruhr University Bochum, Germany}, month = {November}, year = {2021}, }

Al-Dilaimi, S. (2021, November). Spatial Representations in an Egocentric Navigation Task using Deep Reinforcement Learning. Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany.
Training a deep reinforcement learning agent with prioritized experience replay on navigation tasks
Kellermann, N.
Bachelor's thesis, Applied Computer Science, Ruhr University Bochum, Germany

@bachelorthesis{Kellermann2021, author = {Kellermann, Nick}, title = {Training a deep reinforcement learning agent with prioritized experience replay on navigation tasks }, school = {Applied Computer Science, Ruhr University Bochum, Germany}, month = {September}, year = {2021}, }

Kellermann, N. (2021, September). Training a deep reinforcement learning agent with prioritized experience replay on navigation tasks . Bachelor's thesis, Applied Computer Science, Ruhr University Bochum, Germany.
Understanding the effects of place field size in spatial navigation using a spiking neural network
Sens, Y.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Sens2021, author = {Sens, Yorick}, title = {Understanding the effects of place field size in spatial navigation using a spiking neural network}, year = {2021}, }

Sens, Y. (2021, September). Understanding the effects of place field size in spatial navigation using a spiking neural network. Applied Computer Science, Ruhr University Bochum, Germany.
Simulation of Spatial Behaviour using Spiking Neural Network
Murugan, K. V.
Master’s thesis, Computational Engineering, Ruhr University Bochum, Germany

@mastersthesis{Murugan2021, author = {Murugan, Kaarthik Vellore}, title = {Simulation of Spatial Behaviour using Spiking Neural Network }, school = {Computational Engineering, Ruhr University Bochum, Germany}, month = {July }, year = {2021}, }

Murugan, K. V. (2021, July). Simulation of Spatial Behaviour using Spiking Neural Network . Master’s thesis, Computational Engineering, Ruhr University Bochum, Germany.
Training State-Transition and Reward Models in Deep Neural Networks for Reinforcement Learning
Altamimi, A.
Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany

@mastersthesis{Altamimi2021, author = {Altamimi, Aya}, title = {Training State-Transition and Reward Models in Deep Neural Networks for Reinforcement Learning}, school = {Applied Computer Science, Ruhr University Bochum, Germany}, month = {January}, year = {2021}, }

Altamimi, A. (2021, January). Training State-Transition and Reward Models in Deep Neural Networks for Reinforcement Learning. Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany.
Generative effects of extinction learning emerging from an embodied associative network
Lazarova, S.
Master’s thesis, Cognitive Science, Ruhr University Bochum, Germany

@mastersthesis{Lazarova2021, author = {Lazarova, Sofia}, title = {Generative effects of extinction learning emerging from an embodied associative network}, school = {Cognitive Science, Ruhr University Bochum, Germany}, month = {January}, year = {2021}, }

Lazarova, S. (2021, January). Generative effects of extinction learning emerging from an embodied associative network. Master’s thesis, Cognitive Science, Ruhr University Bochum, Germany.

2020

Comparing Deep Reinforcement Learning Algorithms in Discrete and Continuous Environments
De Stefano, G.
Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany

@mastersthesis{De Stefano2020, author = {De Stefano, Gianluca}, title = {Comparing Deep Reinforcement Learning Algorithms in Discrete and Continuous Environments}, school = {Applied Computer Science, Ruhr University Bochum, Germany}, month = {December}, year = {2020}, }

De Stefano, G. (2020, December). Comparing Deep Reinforcement Learning Algorithms in Discrete and Continuous Environments. Master’s thesis, Applied Computer Science, Ruhr University Bochum, Germany.
Dynamical decoding of oscillatory neural activity during extinction learning using artificial neural networks
Ghazinouri, B.
Master’s thesis, Physics, Ruhr University Bochum, Germany

@mastersthesis{Ghazinouri2020, author = {Ghazinouri, Behnam}, title = {Dynamical decoding of oscillatory neural activity during extinction learning using artificial neural networks}, school = {Physics, Ruhr University Bochum, Germany}, month = {November}, year = {2020}, }

Ghazinouri, B. (2020, November). Dynamical decoding of oscillatory neural activity during extinction learning using artificial neural networks. Master’s thesis, Physics, Ruhr University Bochum, Germany.
Deep Reinforcement Learning in Virtual Reality Environments Driven by Physics Simulation
Woltersdorf, P.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Woltersdorf2020, author = {Woltersdorf, Philip}, title = {Deep Reinforcement Learning in Virtual Reality Environments Driven by Physics Simulation}, year = {2020}, }

Woltersdorf, P. (2020, October). Deep Reinforcement Learning in Virtual Reality Environments Driven by Physics Simulation. Applied Computer Science, Ruhr University Bochum, Germany.
Exploration of a continuous attractor model of grid cells with aligned conjunctive cells.
Atak, M.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Atak2020, author = {Atak, Mehmet}, title = {Exploration of a continuous attractor model of grid cells with aligned conjunctive cells.}, year = {2020}, }

Atak, M. (2020, May). Exploration of a continuous attractor model of grid cells with aligned conjunctive cells. Applied Computer Science, Ruhr University Bochum, Germany.
Spiking Network Model Of Hippocampus To Store And Recall Individual Patterns
Bharadwai, M.
Master’s thesis, Cognitive Systems, University of Ulm, Germany

@mastersthesis{Bharadwai2020, author = {Bharadwai, Maryada}, title = {Spiking Network Model Of Hippocampus To Store And Recall Individual Patterns}, school = {Cognitive Systems, University of Ulm, Germany}, month = {May}, year = {2020}, }

Bharadwai, M. (2020, May). Spiking Network Model Of Hippocampus To Store And Recall Individual Patterns. Master’s thesis, Cognitive Systems, University of Ulm, Germany.
Representational similarity of naturalistic stimuli from different categories in a deep neural network
Simon, R.
Applied Computer Science, Ruhr University Bochum, Germany

@bachelorsthesis{Simon2020, author = {Simon, Robin}, title = {Representational similarity of naturalistic stimuli from different categories in a deep neural network}, year = {2020}, }

Simon, R. (2020, January). Representational similarity of naturalistic stimuli from different categories in a deep neural network. Applied Computer Science, Ruhr University Bochum, Germany.
Learning pose-invariant object representations using Power-SFA
van Wickern, J.
Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany

@bachelorthesis{van Wickern2020, author = {van Wickern, Jan}, title = {Learning pose-invariant object representations using Power-SFA}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {January}, year = {2020}, }

van Wickern, J. (2020, January). Learning pose-invariant object representations using Power-SFA. Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany.

2019

Modeling extinction learning in Pigeons using a deep Q network
Fischer, L.
Bachelor's thesis, Applied Computer Science, Ruhr University Bochum, Germany

@bachelorthesis{Fischer2019, author = {Fischer, Lennard}, title = {Modeling extinction learning in Pigeons using a deep Q network}, school = {Applied Computer Science, Ruhr University Bochum, Germany}, month = {September}, year = {2019}, }

Fischer, L. (2019, September). Modeling extinction learning in Pigeons using a deep Q network. Bachelor's thesis, Applied Computer Science, Ruhr University Bochum, Germany.
Differential Visual Discrimination Performance Dependent on Stimulus Category in a Deep Neural Network Model of the Visual Cortex
Boschuk, V.
Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany

@bachelorthesis{Boschuk2019, author = {Boschuk, Volker}, title = {Differential Visual Discrimination Performance Dependent on Stimulus Category in a Deep Neural Network Model of the Visual Cortex}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {August}, year = {2019}, }

Boschuk, V. (2019, August). Differential Visual Discrimination Performance Dependent on Stimulus Category in a Deep Neural Network Model of the Visual Cortex. Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany.
Simulating the effects of the balance between excitatory and inhibitory neurons on the dynamics of spiking neural networks
Droßel, A.
Master’s thesis, Physics, TU Dortmund, Germany

@mastersthesis{Droßel2019, author = {Droßel, Alexander}, title = {Simulating the effects of the balance between excitatory and inhibitory neurons on the dynamics of spiking neural networks}, school = {Physics, TU Dortmund, Germany}, month = {May}, year = {2019}, }

Droßel, A. (2019, May). Simulating the effects of the balance between excitatory and inhibitory neurons on the dynamics of spiking neural networks. Master’s thesis, Physics, TU Dortmund, Germany.
Reinforcement learning in multiple contexts: How does the network represent the learned information?
Diekmann, N.
Master’s thesis, Applied Informatics, Univ. of Bochum, Germany

@mastersthesis{Diekmann2019, author = {Diekmann, Nicolas}, title = {Reinforcement learning in multiple contexts: How does the network represent the learned information?}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {April}, year = {2019}, }

Diekmann, N. (2019, April). Reinforcement learning in multiple contexts: How does the network represent the learned information?. Master’s thesis, Applied Informatics, Univ. of Bochum, Germany.
Transfer of Learned Associations in a Reinforcement Learning Context
Vijayabaskaran, S.
Master’s thesis, Computational Engineering, Univ. of Bochum, Germany

@mastersthesis{Vijayabaskaran2019, author = {Vijayabaskaran, Sandhiya}, title = {Transfer of Learned Associations in a Reinforcement Learning Context}, school = {Computational Engineering, Univ. of Bochum, Germany}, month = {April}, year = {2019}, }

Vijayabaskaran, S. (2019, April). Transfer of Learned Associations in a Reinforcement Learning Context. Master’s thesis, Computational Engineering, Univ. of Bochum, Germany.
Driving network oscillations in ING and PING models with realistic spiking inputs
Sowade, J.
Master’s thesis, Applied Informatics, Univ. of Bochum, Germany

@mastersthesis{Sowade2019, author = {Sowade, Jan}, title = {Driving network oscillations in ING and PING models with realistic spiking inputs}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {February}, year = {2019}, }

Sowade, J. (2019, February). Driving network oscillations in ING and PING models with realistic spiking inputs. Master’s thesis, Applied Informatics, Univ. of Bochum, Germany.

2018

Storing and retrieving neural sequences in a network model of the hippocampus with spiking neurons and STDP
Dyck, S.
Master’s thesis, Cognitive Science, Univ. of Bochum, Germany

@mastersthesis{Dyck2018, author = {Dyck, Susanne}, title = {Storing and retrieving neural sequences in a network model of the hippocampus with spiking neurons and STDP}, school = {Cognitive Science, Univ. of Bochum, Germany}, month = {October}, year = {2018}, }

Dyck, S. (2018, October). Storing and retrieving neural sequences in a network model of the hippocampus with spiking neurons and STDP. Master’s thesis, Cognitive Science, Univ. of Bochum, Germany.
Spontaneous sequence generation in a neural network model of the hippocampus
Matzke, S.
Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany

@bachelorthesis{Matzke2018, author = {Matzke, Stephan}, title = {Spontaneous sequence generation in a neural network model of the hippocampus}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {August}, year = {2018}, }

Matzke, S. (2018, August). Spontaneous sequence generation in a neural network model of the hippocampus. Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany.

2017

Generating Neural Network Connectivity from a Visual Representation
Herbers, P.
Master’s thesis, Applied Informatics, Univ. of Bochum, Germany

pdf

@mastersthesis{Herbers2017, author = {Herbers, Patrick}, title = {Generating Neural Network Connectivity from a Visual Representation}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {November}, year = {2017}, }

Herbers, P. (2017, November). Generating Neural Network Connectivity from a Visual Representation. Master’s thesis, Applied Informatics, Univ. of Bochum, Germany.

2016

Propagation of sequential activity in feedforward neural networks
Hakobyan, O.
Master’s thesis, Cognitive Science, Univ. of Bochum, Germany

@mastersthesis{Hakobyan2016, author = {Hakobyan, Olya}, title = {Propagation of sequential activity in feedforward neural networks}, school = {Cognitive Science, Univ. of Bochum, Germany}, month = {September}, year = {2016}, }

Hakobyan, O. (2016, September). Propagation of sequential activity in feedforward neural networks. Master’s thesis, Cognitive Science, Univ. of Bochum, Germany.
Uncovering the representation of visual categories in neural ensembles
Klatt, S.
Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany

@bachelorthesis{Klatt2016, author = {Klatt, Sebastian}, title = {Uncovering the representation of visual categories in neural ensembles}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {September}, year = {2016}, }

Klatt, S. (2016, September). Uncovering the representation of visual categories in neural ensembles. Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany.
Modeling the effect of depression on mortality.
Ogiermann, D.
Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany

@bachelorthesis{Ogiermann2016, author = {Ogiermann, Dennis}, title = {Modeling the effect of depression on mortality.}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {September}, year = {2016}, }

Ogiermann, D. (2016, September). Modeling the effect of depression on mortality. Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany.
Using Kalman filtering to combine path integration and external spatial information in a mobile robot
Diekmann, N.
Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany

@bachelorthesis{Diekmann2016, author = {Diekmann, Nicolas}, title = {Using Kalman filtering to combine path integration and external spatial information in a mobile robot}, school = {Applied Informatics, Univ. of Bochum, Germany}, month = {August}, year = {2016}, }

Diekmann, N. (2016, August). Using Kalman filtering to combine path integration and external spatial information in a mobile robot. Bachelor's thesis, Applied Informatics, Univ. of Bochum, Germany.

2019

Computational modeling of generative episodic memory

Dynamics of extinction learning in behavior and neural activity

How does learning unfold over time? This question can be studied in experimental data and with computational modeling. We analyze behavioral and neural activity data that was collected by collaborating labs. In our theoretical work, we employ simple associative models as well as deep reinforcement learning, which allows us to study the emerging representations and to correlate them to experimental data.

Emergent behavior and neural representations in spatial learning

Spatial navigation might appear to be a simple behavior, but closer inspection reveals that it is the complex result of many interacting sub-processes. We use deep reinforcement learning to understand how goal-directed behavior emerges in an artificial agent, how the deep neural network represents spatial information, and how the model's representations are related to neural codes for space in the hippocampus.

Episodic memory interactions with sensory and semantic systems

We study, on the one hand, how episodic memories are stored and retrieved in interaction with the sensory and semantic systems. On the other hand, we investigate how episodic memories influence these sensory and semantic systems.

Nature and function of episodic memory

There is still great uncertainty as to what episodic memory is and what function it might serve. Within the research unit FOR 2812, we are working on an interdisciplinary framework for episodic memory.

Neural mechanisms underlying spatial navigation

A large number of cell types in the mammalian brain code for various types of spatial information, e.g., head direction cells, place cells, and grid cells. We study how networks of these cell types could support spatial navigation by combining computational modeling and data analysis.

Sequence memory in the hippocampus

The CRISP theory suggests that episodic memories are best represented by neuronal sequences and specific mechanisms by which sequences are stored and retrieved from the hippocampal circuit. Using neural network models, we investigate under which conditions the hippocampal circuit can perform the hypothesized functions reliably and robustly.

About the INI

The Institut für Neuroinformatik (INI) is a interdisciplinary research unit of the Ruhr-Universität Bochum. We aim to understand fundamental principles that characterize how organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by insights into natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology, theoretical approaches from physics, mathematics, and computer science, including, in particular, machine learning, artificial intelligence, autonomous robotics, and computer vision.

Contact

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210

sekretariat@ini.rub.de
www.ini.rub.de

Prof. Dr. Sen Cheng

Computational Neuroscience

Ruhr-Universität Bochum Institut für Neuroinformatik Universitätsstraße 150 Building NB, Room NB 3/33

D-44801 Bochum, Germany

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Ruhr-Universität Bochum
Institut für Neuroinformatik
Universitätsstraße 150
Building NB, Room NB 3/33