Fig. 6 | Microsystems & Nanoengineering

Fig. 6

From: Microelectrode arrays cultured with in vitro neural networks for motion control tasks: encoding and decoding progress and advances

Fig. 6

Closed-loop experimental workflow for task execution in a neural networks-based motion control system. After MEAs and a bidirectional communication system collect raw neural signals, the signals undergo preprocessing, where complex waveforms are converted into datasets related to firing rates through analog-to-digital conversion, and neuronal firing is classified. The dataset is then input into a decoding model, which maps the neural data to decision-making for the actuator. After executing a decision-driven action, the discrepancy between the performed action and the intended target is computed and subsequently delivered back to the in vitro neural network as electrical stimulation signals. This feedback enables the network to continuously learn and evolve, aligning more closely with the requirements of task execution. (Fig. 6 is created with http://BioRender.com)

Back to article page