Simulation of a recurrent neurointerface with sparse electrical connections

With the technical development of multi-electrode arrays, the monitoring of many individual neurons has become feasible. However, for practical use of those arrays as bidirectional neurointerfaces, feedback signals have to be generated in real-time to integrate the electrodes into the existing spatio-temporal context as a new information source. In this modeling study we will introduce a recurrent neurointerface, which uses a biologically plausible artificial neural network to pre-process electrode signals and generate adequate feedback signals to the biological network. The artificial network is more transparent for advanced methods to analyze synchronous firing patterns and reacts more stably to external input signals.

• Type: Conference
• Year: 2008
• Where: ESANN
• Authors: Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana D. de Lima, Thomas B. Voigt
• Keywords: Adequate Feedback Signals, ESANN 2008, External Input Signals, Feedback Signals, Neural Networks