Optoelectronic system for brain neuronal network stimulation

Living-Neuron-Based Autogenerator

We present a novel closed-loop system designed to integrate biological and artificial neurons of the oscillatory type into a unified circuit. The system comprises an electronic circuit based on the FitzHugh-Nagumo model, which provides stimulation to living neurons in acute hippocampal mouse brain slices. The local field potentials generated by the living neurons trigger a transition in the FitzHugh-Nagumo circuit from an excitable state to an oscillatory mode, and in turn, the spikes produced by the electronic circuit synchronize with the living-neuron spikes. The key advantage of this hybrid electrobiological autogenerator lies in its capability to control biological neuron signals, which holds significant promise for diverse neuromorphic applications.

Automatic Adaptation of Model Neurons and Connections to Build Hybrid Circuits with Living Networks

Hybrid circuits built by creating mono- or bi-directional interactions among living cells and model neurons and synapses are an effective way to study neuron, synaptic and neural network dynamics. However, hybrid circuit technology has been largely underused in the context of neuroscience studies mainly because of the inherent difficulty in implementing and tuning this type of interactions. In this paper, we present a set of algorithms for the automatic adaptation of model neurons and connections in the creation of hybrid circuits with living neural networks. The algorithms perform model time and amplitude scaling, real-time drift adaptation, goal-driven synaptic and model tuning/calibration and also automatic parameter mapping. These algorithms have been implemented in RTHybrid, an open-source library that works with hard real-time constraints. We provide validation examples by building hybrid circuits in a central pattern generator. The results of the validation experiments show that the proposed dynamic adaptation facilitates closed-loop communication among living and artificial model neurons and connections, and contributes to characterize system dynamics, achieve control, automate experimental protocols and extend the lifespan of the preparations.

From Novel Technology to Novel Applications: Comment on "An Integrated Brain-Machine Interface Platform With Thousands of Channels" by Elon Musk and Neuralink

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Switch Elements with S-Shaped Current-Voltage Characteristic in Models of Neural Oscillators

In this paper, we present circuit solutions based on a switch element with the S-type I–V characteristic implemented using the classic FitzHugh–Nagumo and FitzHugh–Rinzel models. Using the proposed simplified electrical circuits allows the modeling of the integrate-and-fire neuron and burst oscillation modes with the emulation of the mammalian cold receptor patterns. The circuits were studied using the experimental I–V characteristic of an NbO2 switch with a stable section of negative differential resistance (NDR) and a VO2 switch with an unstable NDR, considering the temperature dependences of the threshold characteristics. The results are relevant for modern neuroelectronics and have practical significance for the introduction of the neurodynamic models in circuit design and the brain–machine interface. The proposed systems of differential equations with the piecewise linear approximation of the S-type I–V characteristic may be of scientific interest for further analytical and numerical research and development of neural networks with artificial intelligence.

Enabling biodegradable functional biomaterials for the management of neurological disorders

An increasing number of patients are being diagnosed with neurological diseases, but are rarely cured because of the lack of curative therapeutic approaches. This situation creates an urgent clinical need to develop effective diagnosis and treatment strategies for repair and regeneration of injured or diseased neural tissues. In this regard, biodegradable functional biomaterials provide promising solutions to meet this demand owing to their unique responsiveness to external stimulation fields, which enable neuro-imaging, neuro-sensing, specific targeting, hyperthermia treatment, controlled drug delivery, and nerve regeneration. This review discusses recent progress in the research and development of biodegradable functional biomaterials including electroactive biomaterials, magnetic materials and photoactive biomaterials for the management of neurological disorders with emphasis on their applications in bioimaging (photoacoustic imaging, MRI and fluorescence imaging), biosensing (electrochemical sensing, magnetic sensing and opical sensing), and therapy strategies (drug delivery, hyperthermia treatment, and tissue engineering). It is expected that this review will provide an insightful discussion on the roles of biodegradable functional biomaterials in the diagnosis and treatment of neurological diseases, and lead to innovations for the design and development of the next generation biodegradable functional biomaterials.