Dipl.-Psych. Jonas Lins

Institut für Neuroinformatik
Ruhr-Universität Bochum
Universitätsstraße 150
Building NB, Room NB 02/75
D-44801 Bochum
Theory of Cognitive Systems




Research Interests

My work is concerned with the neural realization of higher cognitive functionality, in particular relational reasoning. A central test case so far has been cognition about spatial relations in the visual world, but by extension the topic also includes the construction and representation of mental models involved in solving both concrete and abstract problems.

I am specifically interested in the role sensorimotor representations play in these functions. How are sensorimotor 'concepts' invoked, modified, and combined to form new patterns and insights, and what is the structure of the neural substrate that underlies these functions?

With regard to the above projects, I'm working in close collaboration with Mathis Richter.

The approach taken relies on dynamic models which simulate the evolution of activation patterns in neural populations. The overarching theoretical framework is Dynamic Field Theory (DFT).

I have recently started to complement prior modelling work with empirical tests of model predictions concerning behavioral signatures of the embodied nature of relational processing.

In earlier (but related) work, I have studied how failures of feature binding may arise from coarse attentional selection mechanisms.

Lins, J., & Schöner, G.. (in press). Mouse Tracking Shows Attraction to Alternative Targets While Grounding Spatial Relations. In Proceedings of the 39th Annual Conference of the Cognitive Science Society (to appear). Austin, TX: Cognitive Science Society.
Richter, M., Lins, J., & Schöner, G.. (2017). A neural dynamic model generates descriptions of object-oriented actions. Topics in Cognitive Science, 9(1), 35–47. http://doi.org/10.1111/tops.12240
Reimann, H., Lins, J., & Schöner, G.. (2015). The Dynamics of Neural Activation Variables. Paladyn, Journal of Behavioral Robotics, 6(1), 57–70.
Lins, J., & Schöner, G.. (2014). Neural Fields. In S. Coombes, beim Graben, P., Potthast, R., & , J. W. (Eds.) (pp. 319–339). Springer Berlin Heidelberg.
Richter, M., Lins, J., Schneegans, S., Sandamirskaya, Y., & Schöner, G.. (2014). Autonomous Neural Dynamics to Test Hypotheses in a Model of Spatial Language. In P. Bello, Guarini, M., McShane, M., & Scassellati, B. (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 2847–2852). Austin, TX: Cognitive Science Society.
Richter, M., Lins, J., Schneegans, S., & Schöner, G.. (2014). A neural dynamic architecture resolves phrases about spatial relations in visual scenes. In 24th International Conference on Artificial Neural Networks (ICANN) (pp. 201–208). Heidelberg, Germany: Springer.
Lins, J., Schneegans, S., Spencer, J., & Schöner, G.. (2012). The Function and Fallibility of Visual Feature Integration: A Dynamic Neural Field Model of Illusory Conjunctions. Frontiers in Computational Neuroscience, (128). http://doi.org/10.3389/conf.fncom.2012.55.00128