Rate region analysis of multi-terminal neuronal nanoscale molecular communication channel

Abstract

In this paper, we investigate the communication channel capacity among hippocampal pyramidal neurons. To this aim, we study the processes included in this communication and model them with realistic communication system components based on the existing reports in the physiology literature. We consider the communication between two neurons and reveal the effects of the existence of multiple terminals between these neurons on the achievable rate per spike. To this objective, we derive the power spectral density (PSD) of the signal in the output neuron and utilize it to calculate the rate region of the channel. Moreover, we evaluate the impacts of vesicle availability on the achievable rate by deriving the expected number of available vesicles in input neuron using a realistic vesicle release model. Simulation results show that number of available vesicles for release does not affect the achievable rate of neuro-spike communication with univesicular release model. However, in neurons that multiple vesicles can release from each synaptic terminal, achievable rate is significantly affected by depletion of vesicles. Moreover, we show that increasing the number of synaptic terminals between two neurons makes the synaptic connection stronger. Hence, it is an important factor in learning and memory, which occur in the hippocampal region of the brain based on the synaptic connectivity. I. INTRODUCTION Nanomachines have limited capabilities in computing, data storing, sensing and actuation as a result of their size. Hence, they need to establish networks with each other to become capable for more complex tasks. Among the proposed paradigms for nanonetworks, molecular communication, in which molecules are used to encode, transmit and receive information, is the most promising paradigm since this communication exists in the structure of any living organism and is a biocompatible and biostable solution [1]. One of the significant mechanisms for molecular communication inside the human body is the ultra-large scale network of nerve cells, i.e., neurons, which is known as nanoscale neuro-spike communication [2]. Realistically modeling, analyzing and understanding communication theoretical capabilities of the neuro-spike communication channel contribute to the development of bio-inspired solutions for nanonetworks and ICTinspired solutions for neural diseases caused by dysfunction H. Ramezani and C. Koca are with the Next-generation and Wireless Communications Laboratory (NWCL),

Sum Rate of MISO Neuro-Spike Communication Channel With Constant Spiking Threshold

“…3(b). Either increasing λ or M increases the number of spikes at the input, which in turn increases the average required metabolic energy, w p , based on (5). Moreover, the metabolic energy required to maintain resting potential also increases for higher values of M .…”

“…In [3], Hodgkin-Huxley (HH) model is used to calculate information capacity. In [4], the information transfer rate for single-input single-output (SISO) system is calculated using a probabilistic model, which is extended in [5] to find the information rate in a SISO model with multiple synaptic terminals between two neurons. In [6], the upper bound of the capacity for a SISO synaptic communication is derived using Bernoulli distribution to model diffusion process.…”

An information theoretical analysis of multi-terminal neuro-spike communication network in spinal cord

“…Inputs and outputs of the channel are utilized in finding the bound on the total rate of information flow across the network. For point-to-point links in the network, we use existing neuro-spike channel blocks in the literature [6,17,19,[28][29][30][31] that are applicable to the spinal cord synapses.…”

“…Deployment of replacementnanomachines as an ICT-based solution to SCI requires understanding of healthy and interrupted neural connections from ICT perspective. To this end, extensive research effort has focused on the modeling and analysis of neuro-spike communication [6,17,19,[28][29][30][31] and other physical and conceptual communication models for neural communication [1,7,9,35,37].…”

Speech features for telemonitoring of Parkinson's disease symptoms

“…Dopamine is information carrier for communication among nerve cells responsible for relaying messages that control body movement [1]. Lower amount of available dopamine for release decreases the achievable rate of this communication [2]. Hence, this disease mainly affects the motor system with reducing range of movements and its symptoms include tremor, rigidity and loss of muscle control.…”