Abstract
Abstract
Different real-world cognitive tasks evolve on different relevant timescales. Processing these tasks requires memory mechanisms able to match their specific time constants. In particular, the working memory (WM) utilizes mechanisms that span orders of magnitudes of timescales, from milliseconds to seconds or even minutes. This plentitude of timescales is an essential ingredient of WM tasks like visual or language processing. This degree of flexibility is challenging in analog computing hardware because it requires the integration of several reconfigurable capacitors of different size. Emerging volatile memristive devices present a compact and appealing solution to reproduce reconfigurable temporal dynamics in a neuromorphic network. We present a demonstration of WM using a silver-based memristive device whose key parameters, retention time and switching probability, can be electrically tuned and adapted to the task at hand. First, we demonstrate the principles of WM in a small scale hardware to execute an associative memory task. Then, we use the experimental data in two larger scale simulations, the first featuring WM in a biological environment, the second demonstrating associative symbolic WM.
Funder
Bundesministerium für Bildung und Forschung
European Research Council
Deutsche Forschungsgemeinschaft
H2020 Future and Emerging Technologies
Subject
Psychiatry and Mental health,Neuropsychology and Physiological Psychology
Cited by
1 articles.
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