Topic: bidirectional microelectrode stimulation

The modern world is increasingly dependent upon artificial intelligence and machine learning. Applications range from decision-making in areas such as health and finance to autonomous vehicle control. However, current deep-learning machines and neural network algorithms have important limitations, namely ineffective learning rules, long training, and high power consumption (1). In the present project, we aim to address these limitations by using the human nervous system itself as a model, which can process external information in a power-efficient way. To accomplish this objective, we utilize