Publications

Journal Publications

1. Jahn, L., Flügge, S., Zhang, D., Poustka, L., Bölte, S., Wörgötter, F., Marchik, P. B., and Kulvicius, T. (2025). Comparison of marker-less 2D image-based methods for infant pose estimation. Scientific Reports, 15, 12148. DOI:10.1038/s41598-025-96206-0. Springer Nature Link
2. Kulvicius, T., Zhang, D., Poustka, L., Bölte, S., Jahn, L., Flügge, S., Kraft, M., Zweckstetter, M., Nielsen-Saines, K., Wörgötter, F., and Marschik, P. B. (2025). Deep learning empowered sensor fusion boosts infant movement classification. Communications Medicine, 5(16). DOI:10.1038/s43856-024-00701-w. Springer Nature Link
3. Jahn, L., Wörgötter, F. and Kulvicius, T. (2025). Comparison of motion encoding frameworks on human manipulation actions. Robotics and Autonomous Systems, 94, 1-11. DOI:10.1016/j.robot.2024.104869. ScienceDirect Link
4. Pomp, J., Garlichs, A. Kulvicius, T., Tamosiunaite, M., Wurm, M. F., Zahedi, A., Wörgötter, F., and Schubotz, R. I. (2024). Action Segmentation in the Brain: The Role of Object–Action Associations. Journal of Cognitive Neuroscience. DOI:10.1162/jocn_a_02210. MIT Press Direct Link
5. Kulvicius, T., Tamosiunaite, M., and Wörgötter, F. (2023). Combining Optimal Path Search With Task-Dependent Learning in a Neural Network. IEEE Transactions on Neural Networks and Learning Systems. DOI:10.1109/TNNLS.2023.3327103. IEEE Xplore Link
6. Li, S., Kulvicius, T., Tamosiunaite, M., and Wörgötter, F. (2023). Simulated mental imagery for robotic task planning. Frontiers in Neurorobotics, 17. DOI:10.3389/fnbot.2023.1218977. Frontiers Link
7. Kulvicius, T., Zhang, D., Nielsen-Saines, K., Bölte, S., Kraft, M., Einspieler, C., Poustka, L., Wörgötter, F., and Marschik, P. B. (2023). Infant movement classification through pressure distribution analysis. Communications Medicine, 3(112). DOI:10.1038/s43856-023-00342-5. Springer Nature Link
8. Marschik, P. B., Kulvicius, T., Flügge, S., Widmann, C., Nielsen-Saines, K., Schulte-Rüther, M., Hüning, B., Bölte, S., Poustka, L., Sigafoos, J., Wörgötter, F., and Einspieler, C., and Zhang, D. (2023). Open Video Data Sharing in Developmental and Behavioural Science. iScience, 26(4), 106348. DOI:10.1016/j.isci.2023.106348. ScienceDirect Link
9. Marschik, P. B., Widmann, C. A. A., Lang, S., Kulvicius, T., Boterberg, S., Nielsen-Saines, K., Bölte, S., Esposito, G., Nordahl-Hansen, A., Roeyers, H., Wörgötter, F., Einspieler, C., Poustka, L, and Zhang, D. (2022). Emerging Verbal Functions in Early Infancy: Lessons from Observational and Computational Approaches on Typical Development and Neurodevelopmental Disorders. Advances in Neurodevelopmental Disorders. DOI:10.1007/s41252-022-00300-7. Springer Link
10. Schulte-Rüther, M., Kulvicius, T., Stroth, S., Wolff, N., Roessner, V., Marschik, P. B., Kamp-Becker, I. and Poustka, L. (2022). Using machine learning to improve diagnostic assessment of ASD in the light of specific differential and co-occurring diagnoses. Journal of Child Psychology and Psychiatry. DOI:10.1111/jcpp.13650. Wiley Link
11. Tamosiunaite, M., Kulvicius, T. and Wörgötter, F. (2022). Bootstrapping Concept Formation in Small Neural Networks. IEEE Transactions on Cognitive and Developmental Systems. DOI:10.1109/TCDS.2022.3163022. IEEE Xplore Link
12. Pomp, J., Heins, N., Trempler, I., Kulvicius, T., Tamosiunaite, M., Mecklenbrauck, F., Wurm,M. F., Wörgötter, F., and Schubotz, R. I. Touching events predict human action segmentation in brain and behavior. NeuroImage, 243, 118534 (2021). DOI:10.1016/j.neuroimage.2021.118534. ScienceDirect Link
13. Kulvicius, T., Herzog, S., T., Tamosiunaite, M., and Wörgötter, F. (2021). Finding Optimal Paths Using Networks Without Learning--Unifying Classical Approaches. IEEE Transactions on Neural Networks and Learning Systems. DOI:10.1109/TNNLS.2021.3089023. IEEE Xplore Link
14. Reich, S., Zhang, D., Kulvicius, T., Bölte, S., Nielsen-Saines, K, Pokorny, F. B., Peharz, R., Poustka, L., Wörgötter, F., Einspieler, C. and Marschik, P. B. (2021). Novel AI driven approach to classify infant motor functions. Scientific Reports, 11, 9888 (2021). DOI:10.1038/s41598-021-89347-5 . Springer Nature Link
15. Silva, N., Zhang, D., Kulvicius, T., Gail, A., Barreiros, C., Lindstaedt, S., Kraft, M., Bölte, S., Poustka, L., Nielsen-Saines, K., Wörgötter, F., Einspieler, C., and Marschik, P. B. (2021). The future of General Movement Assessment: The role of computer vision and machine learning – A scoping review. Research in Developmental Disabilities. DOI:10.1016/j.ridd.2021.103854. ScienceDirect Link
16. Kulvicius, T., Herzog, S., Lüddecke, T., Tamosiunaite, M., and Wörgötter, F. (2021). One-Shot Multi-Path Planning Using Fully Convolutional Networks in a Comparison to Other Algorithms. Frontiers in Neurorobotics. DOI:10.3389/fnbot.2020.600984. Frontiers Link
17. Thor, M., Kulvicius, T., and Manoonpong, P. (2020). Generic neural locomotion control framework for legged robots. IEEE Transactions on Neural Networks and Learning Systems. DOI:10.1109/TNNLS.2020.3016523. IEEE Xplore Link
18. Wörgötter, F., Ziaeetabar, F., Pfeiffer, S., Kaya, O., Kulvicius, T. and Tamosiunaite, M. (2020). Humans Predict Action using Grammar-like Structures. Scientific Reports, 10, 3999 (2020). DOI:10.1038/s41598-020-60923-5. Springer Nature Link
19. Tamosiunaite, M., Aein, M. J., Braun, J. M., Kulvicius, M., Markievicz, I., Kapociute-Dzikiene, J., Valteryte, R., Haidu, A., Crysostomou, D., Ridge, B., Krilavicius, T., Vitkute-Adzgauskiene, D., Beetz, M., Madsen, O., Ude, A., Krüger, N., and Wörgötter, F. (2019). Cut & recombine: Reuse of robot action components based on simple language instructions. The International Journal of Robotics Research. DOI:10.1177/0278364919865594. SagePub Link
20. Lüdecke, T., Kulvicius, T., and Wörgötter, F. (2019). Context-based affordance segmentation from 2D images for robot actions. Robotics and Autonomous Systems, 119, 92-107. DOI:10.1016/j.robot.2019.05.005. ScienceDirect Link
21. Ziaeetabar, F., Kulvicius, T., Tamosiunaite, M. and Wörgötter, F. (2018). Recognition and prediction of manipulation actions using Enriched Semantic Event Chains. Robotics and Autonomous Systems, 110, 173-188. DOI:10.1016/j.robot.2018.10.005. ScienceDirect Link
22. Herzog, S., Wörgötter, F. and Kulvicius, T. (2017). Generation of movements with boundary conditions based on optimal control theory. Robotics and Autonomous Systems, 94, 1-11. DOI:10.1016/j.robot.2017.04.006. ScienceDirect Link
23. Li, Y., Kulvicius, T. and Tetzlaff, C. (2016). Induction and consolidation of calcium-based homo- and heterosynaptic potentiation and depression. PLoS ONE, 11(8): e0161679. DOI:10.1371/journal.pone.0161679. PLoS Link
24. Tetzlaff, C., Dasgupta, S. Kulvicius, T. and Wörgötter, F. (2015). The use of Hebbian cell assemblies for nonlinear computation. Scientific Reports, 5. DOI: 10.1038/srep12866. Springer Nature Link
25. Kulvicius, T., Biehl, M., Aein, M. J., Tamosiunaite, M. and Wörgötter, F. (2013). Interaction learning for dynamic movement primitives used in cooperative robotic tasks. Robotics and Autonomous Systems, 61(12), 1450-1459. ScienceDirect Link
26. Ning, K.J., Kulvicius, T., Tamosiunaite, M. and Wörgötter, F. (2012). A Novel Trajectory Generation Method for Robot Control. Journal of Intelligent & Robotic Systems, 68(2), 165-184. Springer Link
27. Kulvicius, T., Ning, K.J., Tamosiunaite, M. and Wörgötter, F. (2012). Joining movement sequences: Modified dynamic movement primitives for robotics applications exemplified on handwriting. IEEE Transactions on Robotics, 28(1), 145-157. IEEE Xplore Link
28. Kulvicius, T., Kolodziejski, C., Tamosiunaite, M., Porr, B. and Wörgötter, F. (2010). Behavioral analysis of differential hebbian learning in closed-loop systems. Biological Cybernetics, 103(4), 255-271. Springer Link
29. Kulvicius, T., Tamosiunaite, M., Ainge, J., Dudchenko, P. and Wörgötter, F. (2008). Odor supported place cell model and goal navigation in rodents. Journal of Computational Neuroscience, 25(3), 481-500. Springer Link
30. Tamosiunaite, M., Ainge, J., Kulvicius, T., Porr, B., Dudchenko, P. and Wörgötter, F. (2008). Path-finding in real and simulated rats: Assessing the influence of path characteristics on navigation learning. Journal of Computational Neuroscience, 25(3), 562-582. Springer Link
31. Kulvicius, T., Porr, B. and Wörgötter, F. (2007). Chained learning architectures in a simple closed-loop behavioural context. Biological Cybernetics, 97(5), 363-378. Springer Link
32. Manoonpong, P., Geng, T., Kulvicius, T., Porr, B. and Wörgötter, F. (2007). Adaptive, fast walking in a biped robot under neuronal control and learning. PLoS Computational Biology, 3(7), e134. DOI:10.1371/journal.pcbi.0030134. PLoS Link
33. Kulvicius, T., Porr, B. and Wörgötter, F. (2007). Development of receptive fields in a closed-loop behavioural system. Neurocomputing, 70(10-12), 2046-2049. ScienceDirect Link
34. Porr, B., Kulvicius, T. and Wörgötter, F. (2007). Improved stability and convergence with three factor learning. Neurocomputing, 70(10-12), 2005-2008. ScienceDirect Link
35. Kulvicius T., Tamosiunate, M. and Vaisnys, R. (2005). T Wave Alternans Features for Automated Detection. Informatica, 16(4), 587-602. IOS Press Link

Conference Publications

1. Jahn, L., Wörgötter, F., Marschik, P. B., and Kulvicius, T. (2024). Comparison of Motion Encoding Frameworks for Generalization to Human-like Trajectories. In Proceedings of 8th International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM 2024), Sep 18-20, 2024, Kyoto, Japan. Best poster award.
2. Kulvicius, T., M. Tamosiunaite, and Wörgötter, F. (2023). Adaptive Optimal Path Search with a Neural Network using Hebbian Learning . In Proceedings of 28th International Symposium on Artificial Life and Robotics (AROB 2023), Jan 25-27, 2023, Beppu, Japan. arXiv Link
3. Wolnitza, M., Kaya, O., Kulvicius, T., Wörgötter, F., and Dellen, B. (2022). 6D pose estimation and 3D object reconstruction from 2D shape for robotic grasping of objects. In Proceedings of IEEE International Conference on Robotic Computing, 2022, Naples, Italy . IEEE Xplore Link
4. Kulvicius, T., Herzog, S., Lüddecke, T., Tamosiunaite, M. and Wörgötter, F. (2020). One-shot multi-path planning for robotic applications using fully convolutional networks. In Proceedings of IEEE 2020 International Conference on Robotics and Automation, 2020, Paris, France, pp. 1460-1466. IEEE Xplore Link
5. Kulvicius, T., Herzog, S., Lüddecke, T. Tamosiunaite, M. and Wörgötter, F. (2019). One-shot Path Planning for Multi-agent Systems Using Fully Convolutional Neural Network. The 3rd International Symposium on Swarm Behavior and Bioinspired Robotics (SWARM 2019), November 20-22, Okinawa, Japan. Best paper award. arXiv Link
6. Pitchai, M., Xiong, X., Thor, M., Billeschou, P., Mailänder, P. L., Leung, B., Kulvicius, T. and Manoonpong, P. (2019). CPG driven RBF network control with reinforcement learning for gait optimization of a dung beetle-like robot. In Proceedings of 28th International Conference on Artificial Neural Networks, ICANN2019, September 17-19, 2019, Munich, Germany, pp. 698-710. Springer Link
7. Ziaeetabar, F., Kulvicius, T., Tamosiunaite, M. and Wörgötter F. (2018). Prediction of manipulation action classes using semantic spatial reasoning. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, October 1-5, 2018, Madrid, Spain, pp. 3350-3357. IEEE Xplore Link
8. Nielsen, J., Sørensen, A. S., Christensen, T. S., Savarimuthu, T. R. and Kulvicius, T. (2017). Individualised and adaptive upper limb rehabilitation with industrial robot using dynamic movement primitives. In Proceedings of ICRA 2017 Workshop on Advances and challenges on the development, testing and assessment of assistive and rehabilitation robots: Experiences from engineering and human science research, Vol. 1, p. 40. SemanticScholar Link
9. Herzog, S., Wörgötter F., and Kulvicius, T. (2016). Optimal trajectory generation for generalization of discrete movements with boundary conditions. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, October 9-14, 2016, Daejeon, Korea, pp. 3143-3149. IEEE Xplore Link
10. Schoeler M., Wörgötter F., Kulvicius, T. and Papon, J. (2015). Unsupervised generation of context-relevant training-sets for visual object recognition employing multilinguality. In Proceedings of IEEE Winter Conference on Applications of Computer Vision, January 6-9, 2015, Waikoloa Beach, HI, pp. 805-8012. IEEE Xplore Link
11. Schoeler M., Wörgötter F., Aein, M. J. and Kulvicius, T. (2014). Automated generation of training sets for object recognition in robotic applications. In Proceedings of 23rd International Conference on Robotics in Alpe-Adria Danube Region (RAAD2014), September 3-5, 2014, Smolenice, Slovakia, pp. 1-7. IEEE Xplore Link
12. Stein S. C., Wörgötter F., Schoeler M., Papon, J. and Kulvicius, T. (2014). Convexity based object partitioning for robot applications. In Proceedings of 24th International Conference on Robotics and Automation, May 31 - June 5, 2014, Hong Kong, China. IEEE Xplore Link
13. Kulvicius T., Markelic, I., Tamosiunaite, M. and Wörgötter F. (2013). Semantic image search for robotic applications. In Proceedings of 22nd International Workshop on Robotics in Alpe-Adria-Danube Region (RAAD2013), September 11-13, 2013, Portoroz, Slovenia, pp. 1-8. arXiv Link
14. Papon, J., Kulvicius T., Aksoy, E. E. and Wörgötter F. (2013). Point cloud video object segmentation using a persistent supervoxel world-model. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, November 3-7, 2013, Tokyo, Japan, pp. 3712-3718. IEEE Xplore Link
15. Tamosiunaite, M., Markelic, I., Kulvicius T., and Wörgötter F. (2011). Generalizing objects by analyzing language. In Proceedings of 11th IEEE-RAS International Conference on Humanoid Robots, October 26-28, 2011, Bled, Slovenia, pp. 557-563. IEEE Xplore Link
16. Manoonpong, P., Kulvicius, T., Wörgötter, F., Kunze, L., Renjewski, D., and Seyfarth, A. (2011). Compliant ankles and flat feet for improved self-stabilization and passive dynamics of the biped robot “RunBot”. In Proceedings of 11th IEEE-RAS International Conference on Humanoid Robots, October 26-28, 2011, Bled, Slovenia, pp. 276 - 281. IEEE Xplore Link
17. Kulvicius T., Ning, K.J., Tamosiunaite, M. and Wörgötter F. (2011). Modified dynamic movement primitives for joining movement sequences. In Proceedings of 2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai, China, pp. 2275-2280. IEEE Xplore Link
18. Ning, K.J., Kulvicius T., Tamosiunaite, M. and Wörgötter F. (2011). Accurate position and velocity control for trajectories based on dynamic movement primitives. In Proceedings of 2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai, China, pp. 5006-5011. IEEE Xplore Link
19. Abramov A., Kulvicius T., Wörgötter F. and Dellen B. (2010). Real-time image segmentation on a GPU. Lecture Notes in Computer Science: Facing the Multicore-Challenge Conference, 131-142. Springer Link
20. Markelic, I., Kulvicius, T., Tamosiunaite, M., and Wörgötter, F. (2009). Anticipatory Driving for a Robot-Car Based on Supervised Learning. Lecture Notes in Computer Science: Anticipatory Behavior in Adaptive Learning Systems, 267-282. Springer Link
21. Tamosiunaite M., Vaisnys R., Kulvicius T., Urbonaviciene G., Kaminskiene S. and Bluzaite I. (2002). Search for T Wave Alternans by Multiplicative Factor Method. In Analysis of Biomedical Signals and Images: Proceedings of 16-th International EURASIP Conference on Biosignal Analysis, June, 26-28, 2002, Brno, Czech Republic, pp. 103-105.
22. Tamosiunaite M., Vaisnys R., Jogminas D., Kulvicius T., Urbonaviciene G., Plisiene J. and Bluzas J. (2001). Problems of T Wave Alternans Detection in Rest ECG. In Biomedical Engineering: Proceedings of the International Conference on Biomedical Engineering, October 18-19, 2001, Kaunas, Lithuania, pp. 11-14.

PhD Thesis

- Kulvicius, T. (2010). Modelling closed-loop receptive fields: On the formation and utility of receptive fields in closed-loop behavioural systems. Published in Elektronische Dissertationen der Georg-August-Universität Göttingen

Abstracts

1. Kulvicius, T., Zhang, D., Poustka, L., Jahn, L., Wörgötter, F., and Marschik, P. B. (2025). Multi-sensor approach for infant movement classification. Heidelberg Spring Symposium Medical Informatics (HSSMI), 28 May 2025, Heidelberg, Germany.
2. Kulvicius, T., Zhang, D., Poustka, L., Jahn, L., Bölte, S., Wörgötter, F., and Marschik, P. B. (2025). AI empowered multi-sensor fusion for classifying infant motor functions: a new avenue for neurodevelopmental research? Scientific Conference Autism Spectrum (WTAS), 6-8 March 2025, Heidelberg, Germany. Best poster award.
3. Dasgupta, S., Tetzlaff, C., Kulvicius, T. and Wörgötter F. (2015). Self-organization of computation in neural systems by interaction between homeostatic and synaptic plasticity. BMC Neurosci 16, O5 (2015). DOI:10.1186/1471-2202-16-S1-O5
4. Kulvicius T., Kolodziejski C., Tamosiunaite M., Porr B. and Wörgötter F. (2009). On the analysis of differential hebbian learning in closed-loop behavioral systems. Frontiers in Computational Neuroscience. Conference Abstract: Bernstein Conference on Computational Neuroscience. DOI: 10.3389/conf.neuro.10.2009.14.122
5. Kulvicius, T., Kolodziejski C., Tamosiunaite, M., di Prodi, P., Porr, B. and Wörgötter, F. (2008). On the analysis and evaluation of closed loop learning systems. Frontiers in Computational Neuroscience. Conference Abstract: Berstein Symposium 2008. DOI: 10.3389/conf.neuro.10.2008.01.078
6. Kulvicius, T., Tamosiunaite, M. and Wörgötter, F. (2007). Biologically inspired path-finding algorithms on simulated place cell system. In the 3rd Bernstein Symposium for Computational Neuroscience, September 2007, Göttingen.
7. Kulvicius, T., Tamosiunaite, M. and Wörgötter, F. (2007). Development of place cells by a simple model in a closed loop context. BMC Neuroscience. Conference Abstract: The 16th Annual Computational Neuroscience meeting (CNS), July 2007, Toronto. DOI:10.1186/1471-2202-8-S2-P106
8. Geng, T., Kulvicius, T., Porr, B. and Wörgötter, F. (2006). Neural Control and Synaptic Plasticity in a Planar Biped Walking Robot. In the 15th Annual Computational Neuroscience meeting (CNS), July 2006, Edinburgh.
9. Kulvicius, T., Geng, T., Porr, B., and Wörgötter, F. (2006). Speed Optimization of a 2D Walking Robot through STDP. In Dynamical principles for neuroscience and intelligent biomimetic devices: EPFL LATSIS Symposium 2006, 8-10 March 2006, EPFL Campus, Lausanne, Switzerland, pp. 99-100 (ISBN-978-2-8399-0134-5).

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