Sh K Abdulaev, D. Tarumov, K. Markin, Aleksandra А. Ustyuzhina
{"title":"Resting-state functional magnetic resonance imaging: features of statistical processing of ROI-analysis data","authors":"Sh K Abdulaev, D. Tarumov, K. Markin, Aleksandra А. Ustyuzhina","doi":"10.17816/rmmar623485","DOIUrl":null,"url":null,"abstract":"BACKGROUND: In many works, to study intra- and inter-network connections, a method for constructing networks is used — ROI-analysis (region of interest analysis). The conflicting results obtained when assessing brain connectivity using ROI-analysis can be explained by methodological differences associated with the statistical processing of fMRI data. In this regard, it is relevant to conduct a study with a comparative assessment of various statistical methods of ROI-analysis in processing resting state fMRI data. \nAIM: to assess the functional connectivity of the main resting state networks of the brain using ROI-analysis using various statistical approaches. \nMATERIALS AND METHODS: We analyzed data from 15 resting-state fMRI studies of the brain of patients without neurological and mental pathology. fMRI scanning was performed on a Phillips Ingenia 1.5 T scanner using a gradient echo-planar imaging (EPI-BOLD) sequence. ROI-analysis was used to build networks. Statistical data processing was performed using methods: functional network connectivity, randomization/permutation spatial pairwise clustering statistics, and threshold-free cluster enhancement. \nRESULTS: The number of connections between the structures of brain networks recorded using the method of functional network connectivity is 280, spatial pairwise clustering — 186, threshold-free cluster enhancement — 182. An interesting fact is that negative connections were identified only when using parametric statistics. \nCONCLUSION: A comparative assessment of methods for statistical processing of fMRI data during ROI-analysis was carried out. The functional network connectivity method based on multivariate parametric statistics turned out to be more informative than randomization/permutation spatial pairwise clustering statistics and the method based on threshold-free cluster enhancement. Despite the growing popularity in recent years of resting-state fMRI in the study of functional activity and connectivity of the brain, there are no standardized algorithms for constructing networks of the brain.","PeriodicalId":167099,"journal":{"name":"Russian Military Medical Academy Reports","volume":"10 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Military Medical Academy Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17816/rmmar623485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
BACKGROUND: In many works, to study intra- and inter-network connections, a method for constructing networks is used — ROI-analysis (region of interest analysis). The conflicting results obtained when assessing brain connectivity using ROI-analysis can be explained by methodological differences associated with the statistical processing of fMRI data. In this regard, it is relevant to conduct a study with a comparative assessment of various statistical methods of ROI-analysis in processing resting state fMRI data.
AIM: to assess the functional connectivity of the main resting state networks of the brain using ROI-analysis using various statistical approaches.
MATERIALS AND METHODS: We analyzed data from 15 resting-state fMRI studies of the brain of patients without neurological and mental pathology. fMRI scanning was performed on a Phillips Ingenia 1.5 T scanner using a gradient echo-planar imaging (EPI-BOLD) sequence. ROI-analysis was used to build networks. Statistical data processing was performed using methods: functional network connectivity, randomization/permutation spatial pairwise clustering statistics, and threshold-free cluster enhancement.
RESULTS: The number of connections between the structures of brain networks recorded using the method of functional network connectivity is 280, spatial pairwise clustering — 186, threshold-free cluster enhancement — 182. An interesting fact is that negative connections were identified only when using parametric statistics.
CONCLUSION: A comparative assessment of methods for statistical processing of fMRI data during ROI-analysis was carried out. The functional network connectivity method based on multivariate parametric statistics turned out to be more informative than randomization/permutation spatial pairwise clustering statistics and the method based on threshold-free cluster enhancement. Despite the growing popularity in recent years of resting-state fMRI in the study of functional activity and connectivity of the brain, there are no standardized algorithms for constructing networks of the brain.