Dynamic Exploration of a Controllable Thermosensitive Neuron Model and Its Applications

Abstract

A specific functional electric component is connected to any branch of the neural circuit, which can enhance the corresponding biological function as a smart sensor, whereas the temperature has a significant effect on the firing rhythm of neurons by regulating channel conductance and excitability. So for this paper, a controllable thermosensitive neuron model is established by paralleling two thermistors in the FitzHugh–Nagumo neural circuit. Especially, the thermistors are controlled by two switches, where three working modes can be selected, for which bifurcation diagrams, time response diagrams and spectral entropy (SE) complexity are used to analyze the dynamic behaviors in different operating modes. It is found that any modulation of thermistor can regulate the branch current and output voltage completely under the three working modes. More importantly, the neuronal activities show different mode transitions from periodic to bursts or chaos. The superior dynamic characteristics and rich firing behavior make the new model more suitable for images encryption. For this purpose, we consider switching the three thermosensitive neuron models continuously to obtain more complex chaotic sequences. Next, based on the feature of high pixel correlation among color image components, a 3D projection scrambling algorithm is designed, and then employed in combination with the universal gravitational diffusion method to propose a color image encryption scheme. In addition, the designed algorithm is executed by encrypting and decrypting some color images. The experimental results show that the algorithm cannot only encrypt the color image effectively, but also has no limitation on the size of the test image. It is worth mentioning that the designed encrypted algorithm has satisfactory security performance and considerable robustness against noise attacks and shearing attacks. The exploration of this paper about the thermosensitive neuron model and its application may provide some theoretical guidance and experimental basis in the field of secure communication.