Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
An Exploratory study on default mode network's time course analysis
Download
index.pdf
Date
2012
Author
Akın, Burak
Metadata
Show full item record
Item Usage Stats
156
views
101
downloads
Cite This
At resting state, some parts of the human brain is more active than the other areas. Furthermore, the resting state activity in these areas exhibit a sudden decrease when the same areas are recruited in a task. Default mode network (DMN) is one of the resting state networks in the human brain, revealed through functional magnetic resonance (fMR) data acquisition while the subject is in an idle state. The aim of this study is to examine time-course properties of resting state default-mode network by using independent component analysis. Two different conditions are used for this purpose, based on Independent Component Analysis (ICA) method: In the first condition, the whole-brain, including GM, WM, CSF areas are admitted for analysis; in the second condition ICA is performed only for the cortical gray matter voxels, which contain the actual neuronal bed from which the BOLD signal in the fMR images are obtained. Our results indicate that performing ICA exclusively on the GM areas does not provide extra benefit, on the contrary, it spoils the inherent characteristics of the fMR signal as observed in some higher order statistics such as increased skewness and kurtosis.
Subject Keywords
Magnetic resonance imaging.
,
Neurophysiology.
,
Brain mapping.
URI
http://etd.lib.metu.edu.tr/upload/12615233/index.pdf
https://hdl.handle.net/11511/22225
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Analyzing effective connectivity of brain using fMRI data : DCM and PPI
Mojtahedi, Sina; Halıcı, Uğur; Çiçek, Metehan; Department of Biomedical Engineering (2013)
In neuroscience and biomedical engineering fields, one of the most important issues nowadays is finding a relationship between different brain regions when it is stimulated. Connectivity is an important research area in neuroscience which tries to determine the relationship between different brain region when the brain is stimulated externally or internally. Three main type of connectivity are discussed in this field: Anatomical, Functional and Effective connectivity. Importance of effective connectivity is...
Investigation of age dependent contrast and T1 differences in MR images at 3.0 T: a study on MPRAGE, SPIN ECHO and FLASH protocols
Aktaş, Hayriye; Gökçay, Didem; Doğru, Ewa; Department of Biomedical Engineering (2013)
During healthy aging, the brain undergoes several structural changes such as brain atrophy, decreased volume of GM and WM and increase in CSF volume. These changes introduce prominent low contrast effects to the MRI images of the aging population, causing segmentation problems in the data processing pipeline. Measures of tissue characteristics such as T1, T2 provide unique and complementary information to widely used measures of brain atrophy. In this study, image quality metrics such as contrast, SNR, CNR ...
Functional magnetic resonance imaging (fMRI) simulator
Arslankoz, Kamil; Gökçay, Didem; Department of Medical Informatics (2015)
Functional magnetic resonance imaging (fMRI) utilizes the change in the oxygenation of blood to predict active areas in the brain. fMRI consists of multiple low resolution whole brain images, for which, the contrast difference in corresponding voxels among all images are studied. In this study, an fMRI simulator has been developed which generates customized 4D fMRI data that can be used as a ground truth for comparing/benchmarking different fMRI analysis methods. This simulator can be also used for educatio...
Resting state brain connectivity via bicoherence and coherence
Kandemir, Ahmet Levent; Özkurt, Tolga Esat; Department of Medical Informatics (2018)
The human brain is a complex and dynamical system, which consists of segregated areas specialized for perceptual or motor processing. Task-specific functions are only carried out by integration of these segregated regions. Thus, in order to understand the human brain, it is very important to understand underlying network structure. There are various metrics to investigate the brain connectivity and each day, new metrics are introduced in the field. This study concentrates on bicoherence analysis. Bicoherenc...
A Hierarchical representation and decoding of fMRI data by partitioning a brain network
Moğultay, Hazal; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2017)
In this study, we propose a hierarchical network representation of human brain extracted from fMRI data. This representation consists of two levels. In the first level, we form a network among the voxels, smallest building block of fMRI data. In the second level, we define a set of supervoxels by partitioning the first level network into a set of subgraphs, which are assu med to represent homogeneous brain regions with respect to a predefined criteria. For this purpose, we develop a novel brain parcellation...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Akın, “An Exploratory study on default mode network’s time course analysis,” M.S. - Master of Science, Middle East Technical University, 2012.
