Memristive network controls hippocampal CA1 area activity by adaptive сlose-loop stimulation

Here we present a closed-loop control system for real-time maintenance of hippocampal neuronal activity, integrating artificial neural networks with memristive technologies. The system performs detection of local field potentials (LFP) followed by automatic assessment of their amplitude. Adaptive stimulation, whose parameters are adjusted by a neural network algorithm via a memristive interface, minimizes the difference between current and target LFP amplitudes, ensuring proportional stimulus correction. The developed approach demonstrates a new standard of efficacy and safety for therapeutic interventions through its ability to dynamically adapt stimulation parameters to the changing state of neural networks.