Analysis of fMRI time series : neutrosophic-entropy based clustering algorithm

2022
journal article
article
3
cris.lastimport.wos2024-04-09T22:37:08Z
dc.abstract.enAnalysis of Functional Magnetic Resonance imaging (fMRI) time series plays a vital role in identifying the activation behaviour of neurons in the human brain. However, due to the complexity of the fMRI data, its analysis is challenging. Some studies show that the clustering methods can be beneficial in this respect. We apply a Neutrosophic Set-Based Clustering Algorithm (NEBCA) to fMRI time series datasets by this motivation. For the experimental purpose, we consider fMRI time series related to working memory tasks and resting-state. The clusters with different densities for the two analyzed cases are determined and compared. The identified differences indicate brain regions involved with the processing of the short-memory tasks. The corresponding brain areas are denoted according to Automated Anatomical Labeling (AAL) atlas. The statistical reliability of the findings is verified through various statistical tests. The presented results demonstrate the utility of the neutrosophic set based algorithm in brain neural data analysis.pl
dc.affiliationWydział Zarządzania i Komunikacji Społecznej : Instytut Psychologii Stosowanejpl
dc.affiliationWydział Fizyki, Astronomii i Informatyki Stosowanej : Instytut Fizyki Teoretycznejpl
dc.contributor.authorSingh, Pritpal - 443208 pl
dc.contributor.authorWątorek, Marcin - 431761 pl
dc.contributor.authorCeglarek, Anna - 235724 pl
dc.contributor.authorFąfrowicz, Magdalena - 127888 pl
dc.contributor.authorOświęcimka, Paweł - 429732 pl
dc.date.accessioned2023-02-20T06:24:55Z
dc.date.available2023-02-20T06:24:55Z
dc.date.issued2022pl
dc.date.openaccess0
dc.description.accesstimew momencie opublikowania
dc.description.number3pl
dc.description.physical224-229pl
dc.description.publication0,4pl
dc.description.versionostateczna wersja wydawcy
dc.description.volume13pl
dc.identifier.doi10.12720/jait.13.3.224-229pl
dc.identifier.eissn1798-2340pl
dc.identifier.urihttps://ruj.uj.edu.pl/xmlui/handle/item/307981
dc.languageengpl
dc.language.containerengpl
dc.rightsUdzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 4.0 Międzynarodowa*
dc.rights.licenceCC-BY-NC-ND
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.pl*
dc.share.typeotwarte czasopismo
dc.subject.enneutrosophic setpl
dc.subject.enentropypl
dc.subject.enclusteringpl
dc.subject.enfunctional Magnetic Resonance Imaging (fMRI) time seriespl
dc.subtypeArticlepl
dc.titleAnalysis of fMRI time series : neutrosophic-entropy based clustering algorithmpl
dc.title.journalJournal of Advances in Information Technologypl
dc.typeJournalArticlepl
dspace.entity.typePublication
cris.lastimport.wos
2024-04-09T22:37:08Z
dc.abstract.enpl
Analysis of Functional Magnetic Resonance imaging (fMRI) time series plays a vital role in identifying the activation behaviour of neurons in the human brain. However, due to the complexity of the fMRI data, its analysis is challenging. Some studies show that the clustering methods can be beneficial in this respect. We apply a Neutrosophic Set-Based Clustering Algorithm (NEBCA) to fMRI time series datasets by this motivation. For the experimental purpose, we consider fMRI time series related to working memory tasks and resting-state. The clusters with different densities for the two analyzed cases are determined and compared. The identified differences indicate brain regions involved with the processing of the short-memory tasks. The corresponding brain areas are denoted according to Automated Anatomical Labeling (AAL) atlas. The statistical reliability of the findings is verified through various statistical tests. The presented results demonstrate the utility of the neutrosophic set based algorithm in brain neural data analysis.
dc.affiliationpl
Wydział Zarządzania i Komunikacji Społecznej : Instytut Psychologii Stosowanej
dc.affiliationpl
Wydział Fizyki, Astronomii i Informatyki Stosowanej : Instytut Fizyki Teoretycznej
dc.contributor.authorpl
Singh, Pritpal - 443208
dc.contributor.authorpl
Wątorek, Marcin - 431761
dc.contributor.authorpl
Ceglarek, Anna - 235724
dc.contributor.authorpl
Fąfrowicz, Magdalena - 127888
dc.contributor.authorpl
Oświęcimka, Paweł - 429732
dc.date.accessioned
2023-02-20T06:24:55Z
dc.date.available
2023-02-20T06:24:55Z
dc.date.issuedpl
2022
dc.date.openaccess
0
dc.description.accesstime
w momencie opublikowania
dc.description.numberpl
3
dc.description.physicalpl
224-229
dc.description.publicationpl
0,4
dc.description.version
ostateczna wersja wydawcy
dc.description.volumepl
13
dc.identifier.doipl
10.12720/jait.13.3.224-229
dc.identifier.eissnpl
1798-2340
dc.identifier.uri
https://ruj.uj.edu.pl/xmlui/handle/item/307981
dc.languagepl
eng
dc.language.containerpl
eng
dc.rights*
Udzielam licencji. Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 4.0 Międzynarodowa
dc.rights.licence
CC-BY-NC-ND
dc.rights.uri*
http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.pl
dc.share.type
otwarte czasopismo
dc.subject.enpl
neutrosophic set
dc.subject.enpl
entropy
dc.subject.enpl
clustering
dc.subject.enpl
functional Magnetic Resonance Imaging (fMRI) time series
dc.subtypepl
Article
dc.titlepl
Analysis of fMRI time series : neutrosophic-entropy based clustering algorithm
dc.title.journalpl
Journal of Advances in Information Technology
dc.typepl
JournalArticle
dspace.entity.type
Publication
Affiliations

* The migration of download and view statistics prior to the date of April 8, 2024 is in progress.

Views
5
Views per month
Views per city
Ashburn
1
Beijing
1
Kishangarh
1
Los Angeles
1
Downloads
singh_watorek_ceglarek_fafrowicz_oswiecimka_analysis_of_fmri_time_series_neutrosophic-entropy_2022.pdf
10