Spatio-temporal fMRI data in the spiking neural network

Saharuddin, Shaznoor Shakira and Murli, Norhanifah (2018) Spatio-temporal fMRI data in the spiking neural network. International Journal on Advanced Science, Engineering and Information Technology, 8 (6). pp. 2670-2676. ISSN 2088-5334

Text AJ 2018 (874) Spatio-temporal fMRI data in the spiking neural network.pdf Restricted to Registered users only Download (513kB) | Request a copy

Abstract

Deep learning machine that employs Spiking Neural Network (SNN) is currently one of the main techniques in computational intelligence to discover knowledge from various fields. It has been applied in many application areas include health, engineering, finances, environment and others. This paper addresses a classification problem based on a functional Magnetic Resonance Image (fMRI) brain data experiment involving a subject who reads a sentence or looks at a picture. In the experiment, Signal to Noise Ratio (SNR) is used to select the most relevant features (voxels) before they were propagated in an SNN-based learning architecture. The spatio-temporal relationships between Spatio Temporal Brain Data (STBD) are learned and classified accordingly. All the brain regions are taken from data with label starplus-04847-v7.mat. The overall results of this experiment show that the SNR method helps to get the most relevant features from the data to produced higher accuracy for Reading a Sentence instead of Looking a Picture.

Item Type:	Article
Uncontrolled Keywords:	NeuCube; Functional Magnetic Resonance Imaging (fMRI); Feature Selection; Brain Data Classification; SpatioTemporal Brain Data (STBD)
Subjects:	T Technology > TR Photography > TR624-835 Applied photography. Including artistic, commercial, medical photography, photocopying processes
Divisions:	Faculty of Computer Science and Information Technology > Department of Multimedia
Depositing User:	UiTM Student Praktikal
Date Deposited:	13 Jan 2022 06:29
Last Modified:	13 Jan 2022 06:29
URI:	http://eprints.uthm.edu.my/id/eprint/5516

Actions (login required)

View Item