eSSENCE@LU 4:1 - Method development for analysis and modelling of large scale electrophysiological recordings using deep artificial neural networks
Project: Research › Interdisciplinary research
Aim 1 : To develop plausible systems-level network models that can reproduce observed neurophysiological data and generate testable hypotheses about policy/ value functions Method: To extend and connect existing computational models of cortex and basal ganglia and to enhance them with data on network functional connectivity estimated from electrophysiological measurements.
Aim 2: To evaluate action-based learning in autonomous humanoid robots Method: Humanoid robots learn to control an artificial hand in a skilled reaching task by action-based learning and sensory feedback combining systems for intelligent perception with autonomous robotic systems and direct comparisons to brain processes are made.
|Short title||eSSENCE@LU 4:1|
|Effective start/end date||2017/07/01 → 2020/06/30|
- Christian Balkenius - eSSENCE: The e-Science Collaboration - Cognitive modeling - Cognitive Science (PI)
- Per Petersson - eSSENCE: The e-Science Collaboration - Integrative Neurophysiology (Researcher)
- Karl Åström - Mathematics (Faculty of Engineering) - eSSENCE: The e-Science Collaboration - Mathematical Imaging Group (Researcher)
- Trond Arild Tjöstheim - Cognitive Science (Researcher)
- Birger Johansson - Cognitive modeling - Cognitive Science (Researcher)
- Joel Sjöbom - MultiPark: Multidisciplinary research focused on Parkinson´s disease - Integrative Neurophysiology (Researcher)
Kalle Åström, Jacek Malec, Stefan Larsson, Mattias Ohlsson, Christian Balkenius, Anamaria Dutceac Segesten, Jutta Haider, Robert Willim, Jonas Ledendal, Sonja Aits, Maria Hedlund, Jonas Wisbrant, Einar Heiberg, Elin Anna Topp, Jörn Janneck, Marcus Klang, Ingar Brinck & Olof Sundin
2018/01/01 → …
Project: Network › Interdisciplinary research, Internal collaboration (LU)