  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 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 working
memory 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 working memory 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 working memory 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 working memory in a biological environment,
the second demonstrating associative symbolic working memory.
