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. Moreover, we derive the structure of the optimum receiver based on the Neyman-Pearson detection method to find the effects of spike shape variations on the functionality of neuro-spike communication. Numerical results depict that changes in both spike width and amplitude affect the error detection probability. Moreover, these two factors do not control the performance of the system independently. Hence, a proper model for neuro-spike communication should contain effects of spike shape variations during axonal transmission on both synaptic propagation and spike generation mechanisms to enable us to accurately explain the performance of this communication paradigm

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. To capture the stochasticity of calcium influx to pre-synaptic neuron in our model, we study its statistics and find that it can be modeled by a distribution defined based on Normal and Logistic distributions.This work was supported in part by ERC project MINERVA (ERC-2013- CoG #616922), EU project CIRCLE (EU-H2020-FET-Open #665564), and TU˘ BI˙TAK graduate scholarship program (BIDEB-2215). 1MCell development is supported by the NIGMS-funded (P41GM103712) National Center for Multiscale Modeling of Biological Systems (MMBioS)

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. Hence, in this paper, we aim to quantify the information transmitted through the multiple-input single-output (MISO) neuro-spike communication channel by considering models for axonal propagation, synaptic transmission, and spike generation. Moreover, the spike generation and propagation in each neuron requires opening and closing of numerous ionic channels on the cell membrane, which consumes considerable amount of ATP molecules called metabolic energy. Thus, we evaluate how applying a constraint on available metabolic energy affects the maximum achievable mutual information of this system. To this aim, we derive a closed form equation for the sum rate of the MISO neuro-spike communication channel and analyze it under the metabolic cost constraints. Finally, we discuss the impacts of changes in number of pre-synaptic neurons on the achievable rate and quantify the tradeoff between maximum achievable sum rate and the consumed metabolic energy

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. Hence, to reach an accurate model for neuro-spike communication, the memory of axon and its effect on the axonal transmission should be considered, which are not studied in the existing literature. In this paper, we extract the important factors on the memory of axon and define memory states based on these factors. We also describe the transition among these states and the properties of axonal transmission in each of them. Finally, we demonstrate that the proposed model can follow changes in the axonal functionality properly by simulating the proposed model and reporting the root mean square error between simulation results and experimental data

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 (mRMRC) criteria. Then, we evaluate performance of Gaussian mixture regression (GMR) and support vector regression (SVR) on estimating the third subscale of UPDRS, i.e., UPDRS: motor subscale (UPDRS-III). Among the most informative features, a list of features are selected after redundancy reduction. The selected features depict that LLDs providing information about spectrum flatness, spectral distribution of energy, and hoarseness of voice are the most important ones for estimating UPDRS-III. Moreover, the most informative statistical functions are related to range, maximum, minimum and standard deviation of LLDs, which is an evidence of the muscle weakness due to the PD. Furthermore, GMR outperforms SVR on compact feature sets while the performance of SVR improves by increasing number of features

A Study on Exploring the Variables Influenced by Utilization of “Radio-Frequency Identification (RFID)” Technology in Iran

The purpose of this paper is to introduce one of the leading new technologies, “Radio-frequency identification (RFID)”, and investigate the effects of applying this technology on target environment in Iran. The variables, affected by application of RFID technology in various environments, were extracted through the review of literature then a research was carried out in this field, and the obtained variables were localized by consulting with the experts in this area. A questionnaire was developed through using these variables and distributed among a sample of RFID technology providers and users after testing its the reliability and validity. Finally, the statistical tests on the obtained results from the research led to the discovery of components. The findings of this paper would be discovered components, which are affected by application of RFID technology, are as follows:Tracking quality, decision-making improvement, error control, warehouse management, cost leadership, level of assurance, inventory data, speed of provided service, data monitoring and order management. Considering the prevalent use of RFID technology in various industries around the world, the need for this technology and its benefits becomes obvious to everyone. This paper has created a proper vision of RFID for readers through collecting a wide range of RFID technology benefits as well as discovering the major components associated with application of this technology. Key words: RFID technology; Tracking; Inventory management; Decision makin

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). As a result, the reliability of the existing MC methods, which are mostly adopted from electromagnetic communications and not validated with practical testbeds, is highly questionable. As the first step to remove this discrepancy, in this study, we report on the fabrication of a nanoscale MC receiver based on graphene field-effect transistor biosensors. We perform its ICT characterisation in a custom-designed microfluidic MC system with the information encoded into the concentration of single-stranded DNA molecules. This experimental platform is the first practical implementation of a micro/nanoscale MC system with nanoscale MC receivers, and can serve as a testbed for developing realistic MC methods and IoNT applications.Tis work was supported in part by the ERC (Project MINERVA, ERC-2013-CoG #616922) and by the AXA Research Fund (AXA Chair for Internet of Everything at Koc University)

Vision Therapy/Orthoptics among Three to Seven Year Old Children

Background: Vision Therapy/Orthoptics(VT/O) is a package of treatments that enables patients to achieve the maximum level of visual performance.The aim was to determine the effect of three months vision therapy/orthoptics on best corrected visual acuity (BCVA), fusion, stereopsis and ocular alignment in 3-7 year old children.Materials and Methods: In this randomized clinical trial study, 80 children with amblyopia and/or non-paralytic horizontal deviations were randomly divided into intervention and control groups. Intervention group was treated by vision therapy/orthoptics for three months. These modalities included patch, red filter, sector patch, over minus lens, prism and synoptophore exercises. Controls were treated by only patching for the same period. Pre and post-treatment BCVA, fusion, stereopsis and alignment were compared. Visual performance was classified as excellent (BCVA≥20/30, deviation≤10pd and stereopsis≤70sec/are), acceptable (BCVA≥20/30, deviation ≤10pd and stereopsis 70 to 3000sec/are) and unsatisfactory (BCVA<20/30, deviation>10pd and no stereopsis).Results: A total of 80 cases (56 girls and 24 boys) with the mean age of 5.6±1.4 years entered the study. Although more improvement of fusion and stereopsis was seen in the intervention group (P<0.001 for both groups), there was no significant differences in BCVA and alignment between two groups. Also the difference of visual performance was not statistically significant between two groups, whereas the improvement was significant in each group (P<0.001, for both groups).Conclusion: Vision therapy/orthoptics treatment can be effective for improving sensory status in 3 to 7 year old children with amblyopia and/or strabismus. Further studies with larger sample sizes and focusing on accommodation and fusional amplitude are warranted

Daytime Napping and Nighttime Sleep During Pregnancy and Preterm Birth in Iran

Objectives: This study investigated the relationship between sleep quality during pregnancy and preterm birth. Methods: This longitudinal study was conducted between August 2018 and May 2019. The participants were 150 pregnant women who had been referred to 7 healthcare centers in the city of Qazvin, Iran and met the inclusion criteria. The Petersburg Sleep Quality Index, the Epworth Sleepiness Scale, and 2 questions about daytime sleep status and a demographic questionnaire were administered at 14-18 weeks and 28-32 weeks of gestation. Data were analyzed using the Mann-Whitney test, the Fisher exact test, and univariate and multivariable logistic regression. Results: In the present study, poor sleep quality affected 84.7% of the participants at 14-18 weeks and 93.3% at 28-32 weeks of gestation. The final model for preterm birth prediction incorporated age and the Petersburg Sleep Quality Index score in the second and third trimesters. Preterm birth increased by 14% with each unit increase in age. With each unit increase in the Petersburg Sleep Quality Index score in the second and third trimesters, preterm birth increased by 42% and 28%, respectively, but the p-values of these factors were not significant. Conclusions: Although a significant percentage of pregnant women had poor sleep quality, no significant relationship was found between sleep quality during pregnancy and preterm birth