Publications
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A Neural Dynamic Model Perceptually Grounds Nested Noun PhrasesSabinasz, D., & Schöner, G.Topics in Cognitive Science
@article{SabinaszSchöner2022b, author = {Sabinasz, Daniel and Schöner, Gregor}, title = {A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases}, journal = {Topics in Cognitive Science}, month = {October}, year = {2022}, doi = {10.1111/tops.12630}, }
Sabinasz, D., & Schöner, G.. (2022). A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases. Topics in Cognitive Science. http://doi.org/10.1111/tops.12630Bridging DFT and DNNs: A neural dynamic process model of scene representation, guided visual search and scene grammar in natural scenesGrieben, R., & Schöner, G.In J. Culbertson, Perfors, A., Rabagliati, H., & Ramenzoni, V. (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society@inproceedings{GriebenSchöner2022, author = {Grieben, Raul and Schöner, Gregor}, title = {Bridging DFT and DNNs: A neural dynamic process model of scene representation, guided visual search and scene grammar in natural scenes}, booktitle = {Proceedings of the 44th Annual Conference of the Cognitive Science Society}, editor = {Culbertson, Jennifer and Perfors, Andrew and Rabagliati, Hugh and Ramenzoni, Veronica}, year = {2022}, }
Grieben, R., & Schöner, G.. (2022). Bridging DFT and DNNs: A neural dynamic process model of scene representation, guided visual search and scene grammar in natural scenes. In J. Culbertson, Perfors, A., Rabagliati, H., & Ramenzoni, V. (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society.A Neural Dynamic Model Perceptually Grounds Nested Noun PhrasesSabinasz, D., & Schöner, G.In J. Culbertson, Perfors, A., Rabagliati, H., & Ramenzoni, V. (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society@inproceedings{SabinaszSchöner2022, author = {Sabinasz, Daniel and Schöner, Gregor}, title = {A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases}, booktitle = {Proceedings of the 44th Annual Conference of the Cognitive Science Society}, editor = {Culbertson, Jennifer and Perfors, Andrew and Rabagliati, Hugh and Ramenzoni, Veronica}, year = {2022}, }
Sabinasz, D., & Schöner, G.. (2022). A Neural Dynamic Model Perceptually Grounds Nested Noun Phrases. In J. Culbertson, Perfors, A., Rabagliati, H., & Ramenzoni, V. (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society.2021
A neural dynamic process model of combined bottom-up and top-down guidance in triple conjunction visual searchGrieben, R., & Schöner, G.In T. Fitch, Lamm, C., Leder, H., & Teßmar-Raible, K. (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society@inproceedings{GriebenSchöner2021, author = {Grieben, Raul and Schöner, Gregor}, title = {A neural dynamic process model of combined bottom-up and top-down guidance in triple conjunction visual search}, booktitle = {Proceedings of the 43rd Annual Conference of the Cognitive Science Society}, editor = {Fitch, Tecumseh and Lamm, Claus and Leder, Helmut and Teßmar-Raible, Kristin}, year = {2021}, }
Grieben, R., & Schöner, G.. (2021). A neural dynamic process model of combined bottom-up and top-down guidance in triple conjunction visual search. In T. Fitch, Lamm, C., Leder, H., & Teßmar-Raible, K. (Eds.), Proceedings of the 43rd Annual Conference of the Cognitive Science Society.2020
Scene memory and spatial inhibition in visual search: A neural dynamic process model and new experimental evidenceGrieben, R., Tekülve, J., Zibner, S. K. U., Lins, J., Schneegans, S., & Schöner, G.Attention, Perception, & Psychophysics@article{GriebenTekülveZibnerEtAl2020, author = {Grieben, Raul and Tekülve, Jan and Zibner, Stephan K.U. and Lins, Jonas and Schneegans, Sebastian and Schöner, Gregor}, title = {Scene memory and spatial inhibition in visual search: A neural dynamic process model and new experimental evidence}, journal = {Attention, Perception, & Psychophysics}, year = {2020}, doi = {10.3758/s13414-019-01898-y}, }
Grieben, R., Tekülve, J., Zibner, S. K. U., Lins, J., Schneegans, S., & Schöner, G.. (2020). Scene memory and spatial inhibition in visual search: A neural dynamic process model and new experimental evidence. Attention, Perception, & Psychophysics. http://doi.org/10.3758/s13414-019-01898-y2019
Computer mouse tracking reveals motor signatures in a cognitive task of spatial language groundingLins, J., & Schöner, G.Attention, Perception, & Psychophysics@article{LinsSchöner2019, author = {Lins, Jonas and Schöner, Gregor}, title = {Computer mouse tracking reveals motor signatures in a cognitive task of spatial language grounding}, journal = {Attention, Perception, & Psychophysics}, month = {September}, year = {2019}, doi = {10.3758/s13414-019-01847-9}, }
Lins, J., & Schöner, G.. (2019). Computer mouse tracking reveals motor signatures in a cognitive task of spatial language grounding. Attention, Perception, & Psychophysics. http://doi.org/10.3758/s13414-019-01847-9The Dynamics of Neural Populations Capture the Laws of the MindSchöner, G.Topics in Cognitive Science, 1–15@article{Schöner2019, author = {Schöner, Gregor}, title = {The Dynamics of Neural Populations Capture the Laws of the Mind}, journal = {Topics in Cognitive Science}, pages = {1–15}, year = {2019}, doi = {10.1111/tops.12453}, }
Schöner, G. (2019). The Dynamics of Neural Populations Capture the Laws of the Mind. Topics in Cognitive Science, 1–15. http://doi.org/10.1111/tops.124532018
Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous timeGrieben, R., Tekülve, J., Zibner, S. K. U., Schneegans, S., & Schöner, G.In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society@inproceedings{GriebenTekülveZibnerEtAl2018, author = {Grieben, R and Tekülve, J. and Zibner, S.K.U. and Schneegans, S. and Schöner, G.}, title = {Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous time}, booktitle = {Proceedings of the 40th Annual Conference of the Cognitive Science Society}, editor = {Rogers, T.T. and Rau, M. and Zhu, X. and Kalish, C. W.}, year = {2018}, }
Grieben, R., Tekülve, J., Zibner, S. K. U., Schneegans, S., & Schöner, G.. (2018). Sequences of discrete attentional shifts emerge from a neural dynamic architecture for conjunctive visual search that operates in continuous time. In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society.A Neural Dynamic Architecture That Autonomously Builds Mental ModelsKounatidou, P., Richter, M., & Schöner, G.In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 643–648)@inproceedings{KounatidouRichterSchöner2018, author = {Kounatidou, P. and Richter, M. and Schöner, G.}, title = {A Neural Dynamic Architecture That Autonomously Builds Mental Models}, booktitle = {Proceedings of the 40th Annual Conference of the Cognitive Science Society}, editor = {Rogers, T.T. and Rau, M. and Zhu, X. and Kalish, C. W.}, pages = {643–648}, year = {2018}, }
Kounatidou, P., Richter, M., & Schöner, G.. (2018). A Neural Dynamic Architecture That Autonomously Builds Mental Models. In T. T. Rogers, Rau, M., Zhu, X., & Kalish, C. W. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 643–648).The Institut für Neuroinformatik (INI) is a research unit of the Faculty of Computer Science at the Ruhr-Universität Bochum. Its scientific goal is to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory and effector systems. Inspired by our insights into such 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 psychology and neurophysiology as well as machine learning, neural artificial intelligence, computer vision, and robotics.
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