A study & interpretation of spike train data with R

Multi-Electrode Arrays (MEA) is a well establish method to record the pulsed signals from neurons or more commonly known as Action Potentials (AP), simultaneously in the hippocampus region of a specimen. These signals need to be amplified, sorted and abstracted into a stream of binary waveform which...

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Bibliographic Details
Main Author: Goh, Peng Sian
Other Authors: Zhang Yilei
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/74645
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Institution: Nanyang Technological University
Language: English
Description
Summary:Multi-Electrode Arrays (MEA) is a well establish method to record the pulsed signals from neurons or more commonly known as Action Potentials (AP), simultaneously in the hippocampus region of a specimen. These signals need to be amplified, sorted and abstracted into a stream of binary waveform which is know as the spike train data before it is useful for further analysis. A newer method for pulsed signals recording is the functional Multineuron Calcium Imaging (fMCI). Besides having all the functions of the MEA method, its recording is precise up to a single neuron resolution and can provide the exact location of neurons and identify those which are not active during the recording process. Numerical numbers from the recording form the dataset. The dataset alone is not useful to the naked eyes. It needs to be imported into a program which will use different functions to analyse and plot informative histogram and correlation chart. Spike Train Analysis with R (STAR) is the program/package that is used in this report to analyse those data. STAR consists of statistical computation capability, it can automate the batch processing process, generate and display the results in a systematic manner. The histogram and chart generated must be carefully studied to understand how the brain function. These data could then be used in biomedical engineering for developing of neural prosthetics devices, for eg: Visual prosthetics, auditory prosthetics and motor prosthetics.