Classification of fMRI data using Dynamic Time Warping based functional connectivity analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10324421" target="_blank" >RIV/00216208:11320/16:10324421 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/7760247/" target="_blank" >http://ieeexplore.ieee.org/document/7760247/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EUSIPCO.2016.7760247" target="_blank" >10.1109/EUSIPCO.2016.7760247</a>
Alternative languages
Result language
angličtina
Original language name
Classification of fMRI data using Dynamic Time Warping based functional connectivity analysis
Original language description
The synchronized spontaneous low frequency fluctuations of the BOLD signal, as captured by functional MRI measurements, is known to represent the functional connections of different brain areas. The aforementioned MRI measurements result in high-dimensional time series, the dimensions of which correspond to the activity of different brain regions. Recently we have shown that Dynamic Time Warping (DTW) distance can be used as a similarity measure between BOLD signals of brain regions [1] as an alternative of the traditionally used correlation coefficient. We have characterized the new metric's stability in multiple measurements, and between subjects in homogenous groups. In this paper we investigated the DTW metric's sensitivity and demonstrated that DTW-based models outperform correlation-based models in resting-state fMRI data classification tasks. Additionally, we show that functional connectivity networks resulting from DTW-based models as compared to the correlation-based models are more stable and sensitive to differences between healthy subjects and patient groups.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
24th European Signal Processing Conference, EUSIPCO 2016
ISBN
978-0-9928626-5-7
ISSN
2219-5491
e-ISSN
—
Number of pages
5
Pages from-to
245-249
Publisher name
IEEE
Place of publication
NEW YORK, NY 10017 USA
Event location
Budapest, Hungary
Event date
Aug 29, 2016
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000391891900049