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Designing Electrophysiological Characterization System of Biological Cells Based on the Use of Nanostructured Electrodes
, Ph.D. Dissertation Sharif University of Technology ; Vossoughi, Manouchehr (Supervisor) ; Sasanpour, Pezhman (Supervisor) ; Mohammadpour, Raheleh (Supervisor)
Abstract
In the last half century, the recording of the electrophysiological activities of the neurons has been one of the most effective methods for neuroscience development. One of the techniques used to record the activity of the nerve cells is the use of multi-electrode arrays (MEAs). Current MEAs still face limitations such as low signal-to-noise ratio (SNR) and low spatial resolution. There is a need to develop arrays that are smaller in size and have less impedance to achieve better spatial resolution and lower noise levels. The main focus of this research is on the designing and fabrication of multi-electrode arrays and improvement of their properties using nanostructures and conductive...
Design and Fabrication of 2D Multi-Electrode Array (MEA)Devices to Evaluate Functionality of Neural Cell Network and Cardiac Cells
, M.Sc. Thesis Sharif University of Technology ; Fardmanesh, Mehdi (Supervisor)
Abstract
Microelectrode array technology is a broad platform for studying and characterization of the electrophysiological properties of excitable tissues derived from both brain and heart in vitro. Microelectrode arrays can either record or stimulate cells by accessing multiple sites of neural networks and cell tissues and detect signals from all sources around each electrode simultaneously. By using recorded signals, one can detect cell potential changes and its minor fluctuations. Unlike intracellular recording techniques, the noninvasive interface of microelectrode arrays with cells provides durable studying of neural networks and cell tissues. Using related microelectronics fabrication...
Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model
, Article Australasian Physical and Engineering Sciences in Medicine ; Volume 39, Issue 3 , 2016 , Pages 717-726 ; 01589938 (ISSN) ; Pouladian, M ; Jameie, S. B ; Abbaspour Tehrani Fard, A ; Sharif University of Technology
Springer Netherlands
2016
Abstract
Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000...
Digital implementation of a biological astrocyte model and its application
, Article IEEE Transactions on Neural Networks and Learning Systems ; Volume 26, Issue 1 , 2014 , Pages 127-139 ; 2162237X (ISSN) ; Bavandpour, M ; Ahmadi, A ; Abbott, D ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2014
Abstract
This paper presents a modified astrocyte model that allows a convenient digital implementation. This model is aimed at reproducing relevant biological astrocyte behaviors, which provide appropriate feedback control in regulating neuronal activities in the central nervous system. Accordingly, we investigate the feasibility of a digital implementation for a single astrocyte and a biological neuronal network model constructed by connecting two limit-cycle Hopf oscillators to an implementation of the proposed astrocyte model using oscillator-astrocyte interactions with weak coupling. Hardware synthesis, physical implementation on field-programmable gate array, and theoretical analysis confirm...