A model for classification based on the functional connectivity pattern dynamics of the brain
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10324420" target="_blank" >RIV/00216208:11320/16:10324420 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/7838066/" target="_blank" >http://ieeexplore.ieee.org/document/7838066/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ENIC.2016.037" target="_blank" >10.1109/ENIC.2016.037</a>
Alternative languages
Result language
angličtina
Original language name
A model for classification based on the functional connectivity pattern dynamics of the brain
Original language description
Synchronized spontaneous low frequency fluctuations of the so called BOLD signal, as measured by functional Magnetic Resonance Imaging (fMRI), are known to represent the functional connections of different brain areas. Dynamic Time Warping (DTW) distance can be used as a similarity measure between BOLD signals of brain regions as an alternative of the traditionally used correlation coefficient and the usage of the DTW algorithm has further advantages: beside the DTW distance, the algorithm generates the warping path, i.e. the time-delay function between the compared two time-series. In this paper, we propose to use the relative length of the warping path as classification feature and demonstrate that the warping path itself carries important information when classifying patients according to cannabis addiction. We discuss biomedical relevance of our findings as well.
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
2016 Third European Network Intelligence Conference (ENIC)
ISBN
978-1-5090-3455-0
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
203-208
Publisher name
IEEE
Place of publication
New York, NY, USA
Event location
Wrocław, Poland
Event date
Sep 5, 2016
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—