Molecular Communication-Based Intelligent Dopamine Rate Modulator for Parkinson's Disease Treatment.

Parkinson's disease (PD) is a progressive neurodegenerative disease, and it is caused by the loss of dopaminergic neurons in the basal ganglia (BG). Currently, there is no definite cure for PD, and available treatments mainly aim to alleviate its symptoms. Due to impaired neurotransmitter-based information transmission in PD, molecular communication-based approaches can be employed as potential solutions to address this issue.

N⁴ Sim: The First Nervous NaNoNetwork Simulator With Synaptic Molecular Communications.

The unconventional nature of molecular communication necessitates contributions from a host of scientific fields making the simulator design for such systems to be quite challenging. The nervous system is one of the largest and most important nanonetworks of the body. Several molecular and nano communication simulators exist in literature along with a few neural network simulators, however, most existing simulators are not specific for the nervous system since they ignore the synaptic diffusion because of the computational complexity required to model it.

Fabrication and microfluidic analysis of graphene-based molecular communication receiver for Internet of Nano Things (IoNT).

Bio-inspired molecular communications (MC), where molecules are used to transfer information, is the most promising technique to realise the Internet of Nano Things (IoNT), thanks to its inherent biocompatibility, energy-efficiency, and reliability in physiologically-relevant environments. Despite a substantial body of theoretical work concerning MC, the lack of practical micro/nanoscale MC devices and MC testbeds has led researchers to make overly simplifying assumptions about the implications of the channel conditions and the physical architectures of the practical transceivers in developing theoretical models and devising communication methods for MC. On the other hand, MC imposes unique challenges resulting from the highly complex, nonlinear, time-varying channel properties that cannot be always tackled by conventional information and communication tools and technologies (ICT).

Molecular Communication Theoretical Modeling and Analysis of SARS-CoV2 Transmission in Human Respiratory System.

Severe Acute Respiratory Syndrome-CoronaVirus 2 (SARS-CoV2) caused the ongoing pandemic. This pandemic devastated the world by killing more than a million people, as of October 2020. It is imperative to understand the transmission dynamics of SARS-CoV2 so that novel and interdisciplinary prevention, diagnostic, and therapeutic techniques could be developed.

Information and Communication Theoretical Understanding and Treatment of Spinal Cord Injuries: State-of-The-Art and Research Challenges.

Among the various key networks in the human body, the nervous system occupies central importance. The debilitating effects of spinal cord injuries (SCI) impact a significant number of people throughout the world, and to date, there is no satisfactory method to treat them. In this paper, we review the major treatment techniques for SCI that include promising solutions based on information and communication technology (ICT) and identify the key characteristics of such systems.

Rate of Information Flow Across Layered Neuro-Spike Network in the Spinal Cord.

Spinal Cord Injury (SCI) is a severe condition that can result in loss of motor and sensory functions by disrupting communication among neurons, i.e., neuro-spike communication.

Impact of Long Term Plasticity on Information Transmission Over Neuronal Networks.

The realization of bio-compatible nanomachines would pave the way for developing novel diagnosis and treatment techniques for the dysfunctions of intra-body nanonetworks and revolutionize the traditional healthcare methodologies making them less invasive and more efficient. The network of these nanomachines is aimed to be used for treating neuronal diseases such as developing an implant that bridges over the injured spinal cord to regain its normal functionality. Thus, nanoscale communication paradigms are needed to be investigated to facilitate communication between nanomachines.

Impacts of Spike Shape Variations on Synaptic Communication.

Understanding the communication theoretical capabilities of information transmission among neurons, known as neuro-spike communication, is a significant step in developing bio-inspired solutions for nanonetworking. In this paper, we focus on a part of this communication known as synaptic transmission for pyramidal neurons in the Cornu Ammonis area of the hippocampus location in the brain and propose a communication-based model for it that includes effects of spike shape variation on neural calcium signaling and the vesicle release process downstream of it. For this aim, we find impacts of spike shape variation on opening of voltage-dependent calcium channels, which control the release of vesicles from the pre-synaptic neuron by changing the influx of calcium ions.

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

Communication among neurons, known as neuro-spike communication, is the most promising technique for realization of a bio-inspired nanoscale communication paradigm to achieve biocompatible nanonetworks. In neuro-spike communication, the information, encoded into spike trains, is communicated to various brain regions through neuronal network. An output neuron needs to receive signal from multiple input neurons to generate a spike.

Maximum Likelihood Detection With Ligand Receptors for Diffusion-Based Molecular Communications in Internet of Bio-Nano Things.

Molecular Communication (MC) is a bio-inspired communication technique that uses molecules as a method of information transfer among nanoscale devices. MC receiver is an essential component having profound impact on the communication system performance. However, the interaction of the receiver with information bearing molecules has been usually oversimplified in modeling the reception process and developing signal detection techniques.

D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things.

Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples.

Modeling convection-diffusion-reaction systems for microfluidic molecular communications with surface-based receivers in Internet of Bio-Nano Things.

We consider a microfluidic molecular communication (MC) system, where the concentration-encoded molecular messages are transported via fluid flow-induced convection and diffusion, and detected by a surface-based MC receiver with ligand receptors placed at the bottom of the microfluidic channel. The overall system is a convection-diffusion-reaction system that can only be solved by numerical methods, e.g.

Controlled Information Transfer Through An In Vivo Nervous System.

The nervous system holds a central position among the major in-body networks. It comprises of cells known as neurons that are responsible to carry messages between different parts of the body and make decisions based on those messages. In this work, further to the extensive theoretical studies, we demonstrate the first controlled information transfer through an in vivo nervous system by modulating digital data from macro-scale devices onto the nervous system of common earthworms and conducting successful transmissions.

Speech features for telemonitoring of Parkinson's disease symptoms.

The aim of this paper is tracking Parkinson's disease (PD) progression based on its symptoms on vocal system using Unified Parkinsons Disease Rating Scale (UPDRS). We utilize a standard speech signal feature set, which contains 6373 static features as functionals of low-level descriptor (LLD) contours, and select the most informative ones using the maximal relevance and minimal redundancy based on correlations (mRMR) criteria. Then, we evaluate performance of Gaussian mixture regression (GMR) and support vector regression (SVR) on estimating the third subscale of UPDRS, i.

Importance of vesicle release stochasticity in neuro-spike communication.

Aim of this paper is proposing a stochastic model for vesicle release process, a part of neuro-spike communication. Hence, we study biological events occurring in this process and use microphysiological simulations to observe functionality of these events. Since the most important source of variability in vesicle release probability is opening of voltage dependent calcium channels (VDCCs) followed by influx of calcium ions through these channels, we propose a stochastic model for this event, while using a deterministic model for other variability sources.

An Information Theoretical Analysis of Human Insulin-Glucose System Toward the Internet of Bio-Nano Things.

Molecular communication is an important tool to understand biological communications with many promising applications in Internet of Bio-Nano Things (IoBNT). The insulin-glucose system is of key significance among the major intra-body nanonetworks, since it fulfills metabolic requirements of the body. The study of biological networks from information and communication theoretical (ICT) perspective is necessary for their introduction in the IoBNT framework.

A Fast Algorithm for Analysis of Molecular Communication in Artificial Synapse.

In this paper, we analyze molecular communications (MCs) in a proposed artificial synapse (AS), whose main difference from biological synapses (BSs) is that it is closed, i.e., transmitter molecules cannot diffuse out from AS.

Diffusion-Based Model for Synaptic Molecular Communication Channel.

Computational methods have been extensively used to understand the underlying dynamics of molecular communication methods employed by nature. One very effective and popular approach is to utilize a Monte Carlo simulation. Although it is very reliable, this method can have a very high computational cost, which in some cases renders the simulation impractical.

Theoretical Limits on Multiuser Molecular Communication in Internet of Nano-Bio Things.

In nano-bio networks, multiple transmitter-receiver pairs will operate in the same medium. Both inter-symbol interference and multi-user interference can cause saturation at the receiver side, and this effect may cause an outage. Thus, we propose a tractable framework to calculate the theoretical operating points for fully absorbing receiver.

A Communication Theoretical Modeling of Axonal Propagation in Hippocampal Pyramidal Neurons.

Understanding the fundamentals of communication among neurons, known as neuro-spike communication, leads to reach bio-inspired nanoscale communication paradigms. In this paper, we focus on a part of neuro-spike communication, known as axonal transmission, and propose a realistic model for it. The shape of the spike during axonal transmission varies according to previously applied stimulations to the neuron, and these variations affect the amount of information communicated between neurons.

On the capacity of diffusion-based molecular communications with SiNW FET-based receiver.

Molecular communication (MC) is a bio-inspired communication method based on the exchange of molecules for information transfer among nanoscale devices. Although MC has been extensively studied from various aspects, limitations imposed by the physical design of transceiving units have been largely neglected in the literature. Recently, we have proposed a nanobioelectronic MC receiver architecture based on the nanoscale field effect transistor-based biosensor (bioFET) technology, providing noninvasive and sensitive molecular detection at nanoscale while producing electrical signals at the output.

Fluorescent molecules as transceiver nanoantennas: the first practical and high-rate information transfer over a nanoscale communication channel based on FRET.

Nanocommunications via Förster Resonance Energy Transfer (FRET) is a promising means of realising collaboration between photoactive nanomachines to implement advanced nanotechnology applications. The method is based on exchange of energy levels between fluorescent molecules by the FRET phenomenon which intrinsically provides a virtual nanocommunication link. In this work, further to the extensive theoretical studies, we demonstrate the first information transfer through a FRET-based nanocommunication channel.

FRET-based nanoscale point-to-point and broadcast communications with multi-exciton transmission and channel routing.

Nanoscale communication based on Förster Resonance Energy Transfer (FRET) enables nanoscale single molecular devices to communicate with each other utilizing excitons generated on fluorescent molecules as information carriers. Based on the point-to-point single-exciton FRET-based nanocommunication model, we investigate the multiple-exciton case for point-to-point and broadcast communications following an information theoretical approach and conducting simulations through Monte Carlo approach. We demonstrate that the multi-exciton transmission significantly improves the channel reliability and the range of the communication up to tens of nanometers for immobile nanonodes providing high data transmission rates.

A communication theoretical analysis of FRET-based mobile ad hoc molecular nanonetworks.

Nanonetworks refer to a group of nanosized machines with very basic operational capabilities communicating to each other in order to accomplish more complex tasks such as in-body drug delivery, or chemical defense. Realizing reliable and high-rate communication between these nanomachines is a fundamental problem for the practicality of these nanonetworks. Recently, we have proposed a molecular communication method based on Förster Resonance Energy Transfer (FRET) which is a nonradiative excited state energy transfer phenomenon observed among fluorescent molecules, i.

Nanoscale communication with molecular arrays in nanonetworks.

Molecular communication is a promising nanoscale communication paradigm that enables nanomachines to exchange information by using molecules as communication carrier. Up to now, the molecular communication channel between a transmitter nanomachine (TN) and a receiver nanomachine (RN) has been modeled as either concentration channel or timing channel. However, these channel models necessitate exact time synchronization of the nanomachines and provide a relatively low communication bandwidth.