Sharif Digital Repository

An effective and self-organized differentiation of human neural stem cells (hNSCs) into neurons was developed by the pulsed laser stimulation of the cells on graphene films (prepared by drop-casting a GO suspension onto quartz substrates). The effects of graphene oxide (GO) and hydrazine-reduced graphene oxide (rGO) sheets on the proliferation of hNSCs were examined. The higher proliferation of the cells on the GO was assigned to its better hydrophilicity. On the other hand, the rGO sheets, which have significantly better electrical conductivity than GO, exhibited more differentiation of the cells into neurons. The pulsed laser stimulation not only resulted in an accelerated differentiation... 

Many potential therapies are currently being studied that may promote neural regeneration and guide regenerating axons to form correct connections following injury. It has been shown that adult neurons have some limited regenerative capabilities, and the lack of connection formation between neurons is not an intrinsic inability of these cells to form axons after being damaged, but rather the inhibitory microenvironment of the injured tissue prevents regeneration. In this study, the polarization and chemotaxis of neuronal stem cells (NSC) in response to quantified gradients of nerve growth factor (NGF) was examined. To accomplish this, a microfluidic device was designed and fabricated to... 

We introduce dynamic plastic continuous neural network (DPCNN), which is comprised of neurons distributed in a nonlinear plastic medium where wire-like connections of neural networks are replaced with the continuous medium. We use finite element method to model the dynamic phenomenon of information processing within the DPCNNs. During the training, instead of weights, the properties of the continuous material at its different locations and some properties of neurons are modified. Input and output can be vectors and/or continuous functions over lines and/or areas. Delay and feedback from neurons to themselves and from outputs occur in the DPCNNs. We model a simple form of the DPCNN where the... 

In this study, the polarization and navigation of neuronal cells was studied in response to quantified gradients of nerve growth factor (NGF). To accomplish this, a microfluidic device was designed and fabricated to generate stable concentration gradients of biomolecules in a cell culture chamber within a 3D microenvironment. Numerical simulation was implemented to optimize the device geometry for generating a uniform concentration gradient of NGF which was found to remain stable for multiple hours. Neural Stem/ Progenitor Cell (NSCs) migration and differentiation was studied within this microfluidic device in response to NGF concentration and within a 3D environment of collagen matrix.... 

Inferior temporal (IT) cortex is the most important part of the brain and plays an important role in response to visual stimuli. In this study, object decoding has been performed using neuron spikes in IT cortex region. Single Unit Activity (SUA) was recorded from 123 neurons in IT cortex. Pseudo-population firing rate vectors were created, then dimension reduction was done and an Artificial Neural Network (ANN) was used for object decoding. Object decoding accuracy was calculated for various window lengths from 50 ms to 200 ms and various window steps from 25 ms to 100 ms. The results show that 150 ms length and 50 ms window step size gives an optimum performance in average accuracy  

This study presents a cellular-based mapping for a special class of dynamical systems for embedding neuron models, by exploiting an efficient memristor crossbar-based circuit for its implementation. The resultant reconfigurable memristive dynamical circuit exhibits various bifurcation phenomena, and responses that are characteristic of dynamical systems. High programmability of the circuit enables it to be applied to real-time applications, learning systems, and analytically indescribable dynamical systems. Moreover, its efficient implementation platform makes it an appropriate choice for on-chip applications and prostheses. We apply this method to the Izhikevich, and FitzHugh-Nagumo neuron... 

It is now widely accepted that memristive devices are promising candidates for the emulation of the behavior of biological synapses in neuromorphic systems. This is mainly because of the fact that like the strength of synapse, memristance of the memristive device can be tuned actively for example by the application of voltage or current. In addition, it is also possible to fabricate high density of memristive devices through the nano-crossbar structures. In this paper, we will show that there are some problems associated with memristive devices, which are playing the role of biological synapses. For example, we show that the variation rate of the memristance depends completely on the initial... 

Introduction: Proximal spinal muscular atrophy (SMA) is one of the most significant neurodegenerative diseases amongst the autosomal-recessive genetic disorders which is caused by the absence of protein survival of motor neuron (SMN). A critical nucleotide difference in SMN2 compared to SMN1 gene leads to an inefficient protein. Hence, homozygous lack of SMN1 provides a progressive disease. Due to the high prevalence, up to now, several molecular diagnostic methods have been used which most of them are lengthy, expensive, and laborious. Methods: In the present study, we exploited a gold nanoprobe-based method for semi-quantitative SMN1 gene dosage analysis compared to SMN2. The assay was... 

For the application of human neural stem cells (hNSCs) in neural regeneration and brain repair, it is necessary to stimulate hNSC differentiation towards neurons rather than glia. Due to the unique properties of graphene in stem cell differentiation, here we introduce reduced graphene oxide (rGO)/TiO2 heterojunction film as a biocompatible flash photo stimulator for effective differentiation of hNSCs into neurons. Using the stimulation, the number of cell nuclei on rGO/TiO2 increased by a factor of ∼1.5, while on GO/TiO2 and TiO2 it increased only ∼48 and 24%, respectively. Moreover, under optimum conditions of flash photo stimulation (10 mW cm-2 flash intensity and 15.0 mM ascorbic acid in... 

A signaling pathway is a sequence of proteins and passenger molecules that transmits information from the cell surface to target molecules. Understanding signal transduction process requires detailed description of the involved pathways. Several methods and tools resolved this problem by incorporating genomic and proteomic data. However, the difficulty of obtaining prior knowledge of complex signaling networks limited the applicability of these tools. In this study, based on the simulation of signal flow in signaling network, we introduce a method for determining dominant pathways and signal response to stimulations. The model uses topology-weighted transit compartment approach and comprises... 

In this study, the artificial neural network (ANN) was used for the prediction of WDT. The inputs to network are molar mass and pressure, and the output is WDT at each input. A two-layer network with different hidden neurons and different learning algorithms such as LM, SCG, GDA and BR were examined. The network with 16 hidden neurons and Levenberg-Marquardt (LM) train function showed the best results in comparison with the other networks. Also, the predicted results of this network were compared with the thermodynamic models and better accordance with experimental data for ANN was concluded  

In this paper, we investigated phase synchronization in delayed dynamical networks. Non-identical spiking Hindmarsh-Rose neurons were considered as individual dynamical systems and coupled through a number of network structures such as scale-free, Erdos-Rényi, and modular. The individual neurons were coupled through excitatory chemical synapses with uniform or distributed time delays. The profile of spike phase synchrony was different when the delay was uniform across the edges as compared to the case when it was distributed, i.e., different delays for the edges. When an identical transmission delay was considered, a quasi-periodic pattern was observed in the spike phase synchrony. There... 

Development of novel engineering techniques that can promote new clinical treatments requires implementing multidisciplinary in-vitro and in-vivo approaches. In this study, we have implemented microfluidic devices and in-vivorat model to study the mechanism of neural stem cell migration and differentiation.These studies can result in the treatment of damages to the neuronal system. In this research, we have shown that by applying appropriate ranges of biochemical and biomechanical factors as well as by exposing the cells to electromagnetic fields, it is possible to improve viability, proliferation, directional migration and differentiation of neural stem cells. The results of this study can... 

A new approach is introduced to estimate the formal information of neurons. Formal Information, mainly discusses about the aspects of the response that is related to the stimulus. Estimation is based on introducing a mathematical nonlinear model with Hammerstein-Wiener system estimator. This method of system identification consists of three blocks to completely describe the nonlinearity of input and output and linear behaviour of the model. The introduced model is trained by 166 spikes of neurons and other 166 spikes are used to test and validate the model. The simulation results show the R-Value of 92.6 % between estimated and reference information rate. This shows improvement of 1.41 % in... 

Local circuits in the cortex and hippocampus are endowed with resonant, oscillatory firing properties which underlie oscillations in various frequency ranges (e.g. gamma range) frequently observed in the local field potentials, and in electroencephalography. Synchronized oscillations are thought to play important roles in information binding in the brain. This paper addresses the collective behavior of interacting locally synchronized oscillations in realistic neural networks. A network of five neurons is proposed in order to produce locally synchronized oscillations. The neuron models are Hindmarsh-Rose type with electrical and/or chemical couplings. We construct large-scale models using... 

There has been a strong push recently to examine biological scale simulations of neuromorphic algorithms to achieve stronger inference capabilities. This paper presents a set of piecewise linear spiking neuron models, which can reproduce different behaviors, similar to the biological neuron, both for a single neuron as well as a network of neurons. The proposed models are investigated, in terms of digital implementation feasibility and costs, targeting large scale hardware implementation. Hardware synthesis and physical implementations on FPGA show that the proposed models can produce precise neural behaviors with higher performance and considerably lower implementation costs compared with... 

The impact of adding correlation to a population of neurons on the information and the activity of the population is one of the fundamental questions in recent system neuroscience. In this paper, we would like to introduce topology-based correlation at the level of storing patterns in a recurrent network. We then study the effects of topological patterns on the activity and memory capacity of the network. The general aim of the present work is to show how the repertoire of possible stored patterns is determined by the underlying network topology.Two topological probability rules for pattern selection in recurrent network are introduced. The first one selects patterns according to a... 

We introduce a modified-firing-rate model based on Hebbian-type changing synaptic connections. The existence and stability of solutions such as rest state, bumps, and traveling waves are shown for this type of model. Three types of kernels, namely exponential, Mexican hat, and periodic synaptic connections, are considered. In the former two cases, the existence of a rest state solution is proved and the conditions for their stability are found. Bump solutions are shown for two kinds of synaptic kernels, and their stability is investigated by constructing a corresponding Evans function that holds for a specific range of values of the kernel coefficient strength (KCS). Applying a similar... 

Modeling is one of assessing tools for better understanding of human body organs and study of diseases. One of the brain diseases is ADHD, which has been studied before, mostly by means of EEG signals. In this paper, the mean-field model, which is a model of neuron-population spiking, and the Power Spectrum of the resulting spikes have been studied by changing parameters of model. The results show that there is a meaningful relationship between firing activity of ADHD patients neuron population and the parameters of mean-field model and Power Spectrum of spikes. In addition, the effects of stimulant medications for ADHD patients on firing activity and power spectrum of firing activity of... 

Instrumental responses are hypothesized to be of two kinds: habitual and goal-directed, mediated by the sensorimotor and the associative cortico-basal ganglia circuits, respectively. The existence of the two heterogeneous associative learning mechanisms can be hypothesized to arise from the comparative advantages that they have at different stages of learning. In this paper, we assume that the goal-directed system is behaviourally flexible, but slow in choice selection. The habitual system, in contrast, is fast in responding, but inflexible in adapting its behavioural strategy to new conditions. Based on these assumptions and using the computational theory of reinforcement learning, we...