title: Toward Building Hybrid Biological/in silico Neural Networks for Motor Neuroprosthetic Control.
abstract: In this article, we introduce the Bioinspired Neuroprosthetic Design Environment (BNDE) as a practical platform for the development of novel brain-machine interface (BMI) controllers, which are based on spiking model neurons. We built the BNDE around a hard real-time system so that it is capable of creating simulated synapses from extracellularly recorded neurons to model neurons. In order to evaluate the practicality of the BNDE for neuroprosthetic control experiments, a novel, adaptive BMI controller was developed and tested using real-time closed-loop simulations. The present controller consists of two in silico medium spiny neurons, which receive simulated synaptic inputs from recorded motor cortical neurons. In the closed-loop simulations, the recordings from the cortical neurons were imitated using an external, hardware-based neural signal synthesizer. By implementing a reward-modulated spike timing-dependent plasticity rule, the controller achieved perfect target reach accuracy for a two-target reaching task in one-dimensional space. The BNDE combines the flexibility of software-based spiking neural network (SNN) simulations with powerful online data visualization tools and is a low-cost, PC-based, and all-in-one solution for developing neurally inspired BMI controllers. We believe that the BNDE is the first implementation, which is capable of creating hybrid biological/in silico neural networks for motor neuroprosthetic control and utilizes multiple CPU cores for computationally intensive real-time SNN simulations.
authors: Institute of Biomedical Engineering, Bogazici University , Istanbul , Turkey ; Department of Biomedical Engineering, Istanbul Medipol University , Istanbul , Turkey.
authors: Mehmet
authors: M
authors: Kocaturk
authors: Institute of Biomedical Engineering, Bogazici University , Istanbul , Turkey.
authors: Halil Ozcan
authors: HO
authors: Gulcur
authors: Department of Psychology, Bogazici University , Istanbul , Turkey.
authors: Resit
authors: R
authors: Canbeyli
keywords: brain–machine interface; motor cortex; neuroprosthetics; spike timing-dependent plasticity; spiking neuron models