FOR 2093:  Memristive Devices for Neural Systems

• Subject Area: Computer Science, Systems and Electrical Engineering ; Materials Science and Engineering ; Medicine ; Social and Behavioural Sciences
• Term: from 2014 to 2023
• Website: Homepage
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 239767484

The remarkable interaction performance between biological nervous systems and the environment is a result of a million years evolution explained by Darwinism. Exploring the whole signal pathway from sensory transduction, decision making neuron ensembles and the final response via motor neurons and muscles are the challenging task in neuroscience. Yet still, the real benefits of biological information processing when it comes to cognitive tasks or pattern recognition together with extreme power efficiency, are still unattainable in technical pendants. Based on memristive devices as an electrical pendant to biological synapses, we will explore novel neuromorphic circuits taking the fascinating topological structures and dynamical synchronisation mechanisms of the nervous system as a guideline. Our overarching long-term goals are autonomous and energy-efficient cognitive electronics systems to nucleate a paradigm shift in information technology, which may lead to improved system performances in visual pattern recognition, audio real-time signal processing, autonomous robots, internet of things, and green IT. The RU 2093 will tackle the cutting-edge science of memristive devices in neuromorphic circuits by an interdisciplinary team of scientists from electrical engineering, physics, material science, neurobiology and biological psychology.

• DFG Programme: Research Units

Projects

• Coordination Funds (Applicant Kohlstedt, Hermann )
• Electric characterization of memristive devices in basal learning circuits (Applicant Kohlstedt, Hermann )
• Memristive and memsensor devices for filament free sparse CNT networks (Applicants Adelung, Rainer ;  Faupel, Franz )
• Memristive tunnel junctions and CMOS integration (Applicants Kohlstedt, Hermann ;  Wenger, Christian ;  Ziegler, Martin )
• Modeling and simulation of memristive devices and systems (Applicant Mussenbrock, Thomas )
• Modellierung und Simulation memristiver Bauelemente und Systeme (Applicants Mussenbrock, Thomas ;  Ochs, Karlheinz )
• Modelling of memristive learning behaviour and mnemonic similarity tasks (Applicants Bartsch, Thorsten ;  Kaernbach, Christian ;  Ziegler, Martin )
• Neuromorphic Circuits (Applicant Krautschneider, Wolfgang )
• Structural and chemical nanoanalysis on memristive devices (Applicant Kienle, Lorenz )
• Synchronization in memristively pulse-coupled oscillator networks – experiments (Applicants Kohlstedt, Hermann ;  Ziegler, Martin )
• Synchronization of Memristively Couples Oscillator Networks – Theory and Emulation (Applicants Meurer, Thomas ;  Ochs, Karlheinz ;  Schaum, Alexander )

• Spokesperson: Professor Dr. Hermann Kohlstedt