NClSilico: A Closed-Loop neuromodulation platform in silico.

• A hardware-in-loop platform of the closed-loop neuromodulation is developed. • The hardware platform is programable, real-time and supports the repeated experiments. • Multithreaded application developed in Python is loaded on the "virtual brain" • Multiple closed-loop neuromodulation algorithms are implemented on our platform. The closed-loop electrophysiology is gradually applied to targeted stimulation of nervous system. According to desired neural biomarkers acquired by biological signal measurement, the stimulus pattern can be automatically adjusted with the suitable closed-loop control algorithms. Moreover, the neural computing uses the numerical computing models to simulate the structures, functions and relations of the neurons and the neural networks, as the substitute of biological brain. As the prevalence of the hardware-in-loop (HIL), the HIL closed-loop electrophysiology not only bypasses the problem of biological experiments but also makes up for the insufficient efficiency and real-time performance of software digital simulation. This paper proposes a hardware experiment platform mainly made up of TMS320F28377D digital signal processor (DSP) and AMD Ryzen 5 5600X 6-Core Processor (CPU) for closed-loop electrophysiological research. The hardware platform is programable, portable, real-time and supports the repeated experiments. Closed-loop electrophysiological experiments with different kinds of control algorithms, stimulation waveforms, feedback variables or neuron models can be implemented on the platform, it may promote the development of researches in the field of closed-loop neuroscience and biomedical engineering. [ABSTRACT FROM AUTHOR]