Relationship between evoked electrical responses and robotic behavior analyzed by Self-Organization Map

Toward neuroprosthetic technology, it is critical that a simple model system for interaction between brain and electric devices. For this purpose, we developed neurorobot system, Vitroid, equipped with a living neuronal network and a miniature moving robot as a body of the neurorobot. Self-Organization-Map (SOM) was employed as a generator for behavior of Vitroid. SOM was designed to map a high-dimensional feature vector to a 2-dimentional vector as the winner unit in output layer of SOM. Furthermore, neighboring units were assigned to resemble input vectors. Thus, SOM also performs pattern classifying analysis for inputted feature vector of neuronal activity. Cultured neuronal networks on Multi-Electrodes-Array (MEA) dish was alternately stimulated by two different electrodes. SOM mapped patterns induced by electrical stimulation to a 30 × 30 - 2D output layer. Only in the first step of the learning, SOM is forced to select a specific winner unit previously assigned in order to associate specific behaviors. We call this process “Seeding”. After seeding process, the winner-units correspond to the response patterns induced by two different stimuli were separately mapped. We confirmed that response patterns by two different electrical stimuli could be classified and they were almost stable. Furthermore, it revealed that spontaneous activity and evoked response shared the same patterns, suggesting that the internal autonomous activity is not only a noise, but is almost equivalent to a meaningful response. We also succeeded in collision avoidance of Vitroid by SOM-based behavior generator.