Energy model for synaptic channel in neuro-spike communication
Introduction
Nanonetworks have important applications which are being considered in biomedical, industrial and environmental areas [1], [2], [3]. In particular, molecular communication (MC) [4], where the information is transmitted, propagated and received in a biological environment by the exchange of molecules, is a promising communication technique to realize nanonetworks [5]. One of the most attractive fields in MC is neuro-spike communication (NSC) [6], which is inspired from signal transmission between neurons. In NSC, electrochemical impulses and neurotransmitters are used for information transmission from the transmitter neuron to the receiver neuron [7]. Generally, the NSC system plays a significant role in transporting information in the body nervous system [8].
In recent years, there have been growing interests and research efforts dedicated to NSC. Many researchers focused on the performance of the NSC system on the basis of the NSC channel model [9], [10]. Akan et al. [11] evaluated the throughput and delay performance of the mobile ad hoc molecular nanonetworks by modeling the NSC channel. In [12], Maham designed the optimum binary detector and derived the probability of error at the receiver neuron for the NSC system. In [13], the authors considered a point-to-point NSC model and investigated the effects on the error probability of the NSC channel. Lee and Cho [14] studied the capacity of NSC system based on the process of the information transmission including the axon propagation, vesicle release and neurotransmitter diffusion. Ramezani and Akan [15] provided a realistic NSC model and evaluated the impacts of availability of vesicles on the channel capacity.
The energy consumption requirements constitute the limits on the performance of the MC system. In [16], Schreiber et al. investigated how the factors influenced the energy efficiency of signaling mechanisms. In [17], an energy model for the diffusion-based MC system was proposed and two optimization problems were set up. In [18], the authors proposed and modeled an energy efficient MC system with a simultaneous molecular information and energy transfer relay. Guo et al. [19] analyzed the information delivery energy efficiency of bacteria mobile relays. In [20], an energy model for active transport MC was presented to show that the energy consumption was important in the engineering of this MC system. Ramezani et al. [21] and evaluated the effects of metabolic energy constraints on the sum rate of the multiple-input single-output (MISO) NSC system. However, the metabolic energy is only considered to be consumed by opening and closing of numerous ionic channels on the cell membrane. In this paper, an energy model combination with the whole communication process of the NSC system is proposed, which can be used to provide the guidelines for designing energy efficient NSC systems. The main contributions of our paper are summarized as follows:
(1) An energy model for the synaptic channel in a point-to-point NSC system is proposed based on the communication process of one spike transmission.
(2) On the basis of this energy model, the energy efficiency which is the channel capacity per unit energy consumption for one spike transmission is formulated.
(3) The numerical results show that the main parameters, such as the vesicle release probability, the optimal threshold, the number of the neurotransmitters contained in one vesicle and the side length of the region in which the receptors are located have different effects on the total energy consumption and channel capacity. In particular, the vesicle release probability is the key factor of energy efficiency.
The remainder of this paper is organized as follows. Section 2 describes the NSC system model. In Section 3, an energy model for the synaptic channel in the point-to-point NSC system is presented and the energy efficiency is analyzed. Numerical results are given in Section 4. Finally, this paper is concluded in Section 5.
Section snippets
The NSC system model
In this section, we introduce the point-to-point NSC system model between two neurons. In the NSC system model, the transmission of information from the transmitter neuron to the receiver neuron is mediated by the electrochemical impulses called spikes. The whole communication process of the NSC system involves three steps including the axonal transmission, the synaptic transmission and the spike generation. The structure of the NSC system model is shown in Fig. 1.
(1) The axonal transmission.
Energy model for the synaptic channel in NSC system
In this section, we first propose the energy model and obtain the mathematical expression of the total energy consumption for one spike transmission, then the channel capacity and energy efficiency of this NSC system with synaptic channel is analyzed.
Numerical results
In this section, we use MATLAB to obtain the numerical results of analyzing the total energy consumption, channel capacity and energy efficiency for one spike transmission. The aim is to investigate how the different parameters including the vesicle release probability , the optimal threshold , the time t, the number of neurotransmitters released in one vesicle and the length of the region on the PSD have impacts on the performance of NSC system. The default parameters used to make
Conclusions
The objective of our paper is to make analysis of the total energy consumption, channel capacity and energy efficiency for one spike transmission for the synaptic channel in NSC system. The energy model for the synaptic channel in the point-to-point NSC system is first proposed. Then the energy efficiency of this energy model is analyzed. The numerical results show that how the different system parameters including the vesicle release probability , the time t, the optimal threshold , the
Acknowledgments
This work was supported by National Natural Science Foundation of China (Grant Nos. 61472367, 61432015) and Zhejiang Provincial Natural Science Foundation of China (Grant Nos. LY19F020029).
Zhen Cheng received B.S. degree from Huanggang Normal University, Hubei, China, in 2004, and received M.S. and Ph.D. degrees from Huazhong University of Science and Technology, Hubei, China, in 2007 and 2010 respectively. She is currently an associate professor in the School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China. Her current research interests include nanonetworks, molecular communication, wireless networks. She has published more than 30
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Zhen Cheng received B.S. degree from Huanggang Normal University, Hubei, China, in 2004, and received M.S. and Ph.D. degrees from Huazhong University of Science and Technology, Hubei, China, in 2007 and 2010 respectively. She is currently an associate professor in the School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China. Her current research interests include nanonetworks, molecular communication, wireless networks. She has published more than 30 technical papers in international proceedings and journals.