Dennis Goldschmidt

Publications

Also on Google Scholar and ORCID.

Journals & pre-prints

  1. Coban B, Harris SN, Guer B, Corrales M, Correia Da Silva AJ, Shevchuk D, Leptien K, Goldschmidt D, Schnaitmann C, Kempf A, Januszewski M, Ceffa N, Clayton M, Henry I, Lee SY, Dulac A, Cardona A, Zlatic M, Felsenberg J (2026). “Olfactory loss enhances visual learning in Drosophila through structural and functional reorganisation”. bioRxiv 2026.06.16.732444. doi: 10.64898/2026.06.16.732444.
  2. Goldschmidt D*, Guo Y, Chitnis SS, Christoforou C, Turner-Evans D, Ribeiro C, Hermundstad A, Jayaraman V, Haberkern H* (2026). “Recent experience and internal state shape local search strategies in flies”. Current Biology 36 (7), 1605-1620.e6. doi: 10.1016/j.cub.2026.02.037. *: equal contribution. codedata
  3. Warnecke C, Schweizer JA, Zattera B, Goldschmidt D, Leptien K, Felsenberg J (2026). “Re-exposure to reward re-evaluates related memories”. Current Biology 36 (3), 565-575.e3. doi: 10.1016/j.cub.2025.11.058.
  4. Goldschmidt D*, Tastekin I*, Münch D, Park JY, Haberkern H, Serra L, Baltazar C, Jayaraman V, Rubin GM, Ribeiro C (2023). “A neuronal substrate for translating nutrient state and resource density estimations into foraging decisions”. bioRxiv 2023.07.19.549514. doi: 10.1101/2023.07.19.549514. *: equal contribution.
  5. Münch D, Goldschmidt D, Ribeiro C (2022). “The neuronal logic of how internal states control food choice”. Nature 607 (7920), 747-755. doi: 10.1038/s41586-022-04909-5.
  6. Moreira JM*, Itskov PM*, Goldschmidt D*, Baltazar C, Steck K, Tastekin I, Walker SJ, Ribeiro C (2019). “optoPAD, a closed-loop optogenetics system to study the circuit basis of feeding behaviors”. eLife 8, e43924. doi: 10.7554/eLife.43924. *: equal contribution.
  7. Walker SJ*, Goldschmidt D*, Ribeiro C (2017). “Craving for the future: The brain as a nutritional prediction system”. Curr Opin Insect Sci. 23, 96–103. doi: 10.1016/j.cois.2017.07.013. *: equal contribution.
  8. Goldschmidt D, Manoonpong P, Dasgupta S (2017). “A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents”. Front. Neurorobot. 11:20. doi: 10.3389/fnbot.2017.00020.
  9. Dasgupta S, Goldschmidt D, Wörgötter F, Manoonpong P (2015). “Distributed Recurrent Neural Forward Models with Synaptic Adaptation and CPG-based control for Complex Behaviors of Walking Robots”. Front. Neurorobot. 9:10. doi: 10.3389/fnbot.2015.00010.
  10. Goldschmidt D, Wörgötter F, Manoonpong P (2014). “Biologically-inspired adaptive obstacle negotiation behavior of hexapod robots”. Front. Neurorobot. 8:3. doi: 10.3389/fnbot.2014.00003.

Conference papers & abstracts

  1. Goldschmidt D, Manoonpong P, Dasgupta S (2016). “Reward-modulated learning of population-encoded vectors for insect-like navigation in embodied agents”. 25th Annual Computational Neuroscience Meeting: CNS-2016, Jeju Island, Korea. BMC Neuroscience 17 (Suppl 1), 54. doi: 10.1186/s12868-016-0283-6.
  2. Goldschmidt D, Dasgupta S, Wörgötter F, Manoonpong P (2015). “A neural path integration mechanism for adaptive vector navigation in autonomous agents”. International Joint Conference on Neural Networks (IJCNN) 2015, pp. 1-8. doi: 10.1109/IJCNN.2015.7280400.
  3. Goldschmidt D, Dasgupta S, Wörgötter F, Manoonpong P (2014). “A Neural Path Integration Mechanism for Adaptive Vector Navigation in Autonomous Robots”. Bernstein Conference 2014, Göttingen, Germany, 02-05 September 2014.
  4. Manoonpong P*, Dasgupta S*, Goldschmidt D, Wörgötter F (2014). “Reservoir-based Online Adaptive Forward Models with Neural Control for Complex Locomotion in a Hexapod Robot”. International Joint Conference on Neural Networks (IJCNN) 2014, pp. 3295-3302. doi: 10.1109/IJCNN.2014.6889405. *: equal contribution.
  5. Goldschmidt D, Wörgötter F, Manoonpong P (2013). “Adaptive Neural Obstacle Negotiation Control for Hexapod Robots”. Bernstein Conference 2013, Tübingen, Germany, 24-27 September 2013.
  6. Manoonpong P, Goldschmidt D, Wörgötter F, Kovalev A, Heepe L, Gorb S (2013). “Using a Biological Material to Improve Locomotion of Hexapod Robots”. Living Machines 2013, London, UK. Lecture Notes in Computer Science, pp. 402-404. doi: 10.1007/978-3-642-39802-5_48.
  7. Zenker S, Erdal Aksoy E, Goldschmidt D, Wörgötter F, Manoonpong P (2013). “Visual Terrain Classification for Selecting Energy Efficient Gaits of a Hexapod Robot”. IEEE/ASME International Conference on Advanced Intelligent Mechatronics 2013, Wollongong, Australia, pp. 577-584. doi: 10.1109/AIM.2013.6584154.
  8. Goldschmidt D, Hesse F, Wörgötter F, Manoonpong P (2012). “Reactive Neural Climbing Control for Hexapod Robots”. Frontiers in Computational Neuroscience, Conference Abstract: Bernstein Conference 2012.
  9. Goldschmidt D, Hesse F, Wörgötter F, Manoonpong P (2012). “Biologically Inspired Reactive Climbing Behavior of Hexapod Robots”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2012, Portugal, pp. 4632-4637. doi: 10.1109/IROS.2012.6386135. Best Paper Award Finalist and Best Student Paper Award Finalist.