A new photosensitive neuron model and its dynamics
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Frontiers of Information Technology & Electronic Engineering www.jzus.zju.edu.cn; engineering.cae.cn; www.springerlink.com ISSN 2095-9184 (print); ISSN 2095-9230 (online) E-mail: [email protected]
A new photosensitive neuron model and its dynamics* Yong LIU1, Wan-jiang XU1, Jun MA†‡2,3, Faris ALZAHRANI4, Aatef HOBINY4 1
School of Mathematics and Statistics, Yancheng Teachers University, Yancheng 224002, China 2
Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China
3
School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, China
4
NAAM-Research Group, Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia †
E-mail: [email protected]; [email protected]
Received Nov. 9, 2019; Revision accepted Jan. 25, 2020; Crosschecked Mar. 31, 2020
Abstract: Biological neurons can receive inputs and capture a variety of external stimuli, which can be encoded and transmitted as different electric signals. Thus, the membrane potential is adjusted to activate the appropriate firing modes. Indeed, reliable neuron models should take intrinsic biophysical effects and functional encoding into consideration. One fascinating and important question is the physical mechanism for the transcription of external signals. External signals can be transmitted as a transmembrane current or a signal voltage for generating action potentials. We present a photosensitive neuron model to estimate the nonlinear encoding and responses of neurons driven by external optical signals. In the model, a photocell (phototube) is used to activate a simple FitzHugh-Nagumo (FHN) neuron, and then external optical signals (illumination) are imposed to excite the photocell for generating a time-varying current/voltage source. The photocell-coupled FHN neuron can therefore capture and encode external optical signals, similar to artificial eyes. We also present detailed bifurcation analysis for estimating the mode transition and firing pattern selection of neuronal electrical activities. The sampled time series can reproduce the main characteristics of biological neurons (quiescent, spiking, bursting, and even chaotic behaviors) by activating the photocell in the neural circuit. These results could be helpful in giving possible guidance for studying neurodynamics and applying neural circuits to detect optical signals. Key words: Photosensitive neuron; Neuron model; Bifurcation; Bursting; Photocell https://doi.org/10.1631/FITEE.1900606 CLC number: TN710; O59
1 Introduction The nervous system consists of many functional units that process signals and encode information. To carry out their function, neurons must be sensitive to different stimuli and respond appropriately and rapidly. In generic neuron models (Gu and Pan, 2015; Hu et al., 2016; Mondal and Upadhyay, 2018; Hu and Liu, 2019; Wang YH et al., 2019), external forcing includes physical current forcing, acoustical signals, ‡
Corresponding author Project supported by the National Natural Science Foundation of China (N
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