Author: Turki Alrobaian
Alrobaian, Turki, 2017 EEG analysis: Brain connectivity in stroke, Flinders University, School of Computer Science, Engineering and Mathematics
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Today in the modernization world everything has become so simple in one click of
button, but this fast living life and changes in way of living has led to some major
problems. Brain stroke is one of the leading problems in today’s middle or elder age
people. Science has progressed a lot and looks for many network analysis to deal with
such problems. But still it’s a field in which many unfolds still exist which creates a
hinder to successfully unturned the issue. Brain consists of 100 billion neurons and
one trillion gila. This network of brain stores experiences and houses consciousness.
Focal brain lesions affect multiple network properties simultaneously and how
changes on smaller scales influence those on larger scales.
Although understanding of the brain was enhanced by the stroke, stroke is one of the
biggest killers and a leading cause of disability. Stroke describes damage to the
neuraxis (the brain and spinal cord), resulting from an abnormality in cerebral blood
supply. It is a neurological disorder characterized by interrupted or insufficient blood
supply to certain parts of the brain. It is a significant cause of mortality and morbidity.
The main causes of ischemic stroke in large blood vessels are building up of abnormal
fatty lumps on the inner lining of arteries supplying blood to the brain, infections such
as valvular diseases, ischemic heart disease and diabetes that narrow cerebral blood
vessels or abnormal heart rhythms. In small cerebral blood vessels, fatty lumps on the
inner walls of the arteries could break off and transported by the bloodstream to lodge
in the narrower blood vessels in the brain causing embolic occlusion.
The main causes of leaking or rapturing of weak blood vessels in hemorrhagic stroke
are aneurysm and arteriovenous malformations. Aneurysm results from a weakened
part of a blood vessel ballooning. If unattended, the region continues to balloon and
weaken until it raptures and releases blood into the brain. Arteriovenous
malformations refer to a group of abnormally formed blood vessels. Any of these
blood vessel can rapture and release blood into the brain cavity. Other causes of
rapturing of weak cerebral blood vessels are cranial (head) trauma, an abnormal
accumulation of blood in the cranial cavity, disorders such as hypertension and
cerebral amyloid angiopathy tumors in the brain, the use of therapeutic
anticoagulation (blood-thinning medication) or bleeding disorders that cause a
considerable reduction in platelets.
The motivation for this work includes an electroencephalogram (EEG)-based
experiment on the performance of several mental tasks including reading, auditory,
subtraction and finger tapping among others in 9 patients with multilateral stroke, the
main challenge was to analyse that the anatomic lesion affects the functional brain
network on multiple levels.
In the past few years a large number of studies in the specific field have been
developed. A broad range of detecting follows the morphological based methods.
However, many of the methods, proposed previously failed to give good performance
at the output. Sahil Bajaj [2015] [35] proposed a method which attracts the field in
new limelight. In the paper, the author’s aims at primary motor area during motor
imagination (MI) task and how this differs during motor execution (ME) task are still
questions of interest.
A new scheme to make some improvement on this is to explore the application of
Normalised Transfer Entropy (NTE) measure to construct EEG based directed brain
network. Along with this, the bedrock is to quantify and plot the network for
statistically important connections for both stroke and healthy subjects and to
determine information flow patterns during different tasks.
Keywords: Brain Connectivity, electroencephalogram, EEG, Stroke, Normalised Transfer Entropy
Subject: Engineering thesis
Thesis type: Masters
Completed: 2017
School: School of Computer Science, Engineering and Mathematics
Supervisor: Kenneth Pope