{"id":{"repo_id":"njit","oai_identifier":"oai:digitalcommons.njit.edu:theses-1306"},"canonical_url":"https://search.dev.ndltd.org/etd/njit/oai:digitalcommons.njit.edu:theses-1306","repository":{"repo_id":"njit","name":"NJIT","base_url":"https://digitalcommons.njit.edu/do/oai/"},"display":{"title":"Reliability of resting brain networks using FMRI","abstract":"Resting state FMRI studies on human subjects are primarily focused on elaborating effects of resting state brain networks on task induced paradigm and to check consistency of these networks between different groups of populations. Recent studies have shown consistency of RSFC networks within same subjects with intra-site and intra-session variation. The primary objective of this study was to check consistency of resting state networks between sites and between different groups of people in spite of change in scanning parameters and population. A total of 437 subjects resting state FMRI data from six different sites were collected varying in age group from 21 to 40 years, with scanning parameters varying from site to site. All the data was pre-processed in exactly similar fashion to reduce effects of site variation and to make group comparison feasible. It was hypothesized that in spite of variation in scanning parameters and population differences, cross-correlation values of time series between 97 ROIs chosen in the brain, should be consistent. To compare resting state connectivity measures, scatter plots of cross-correlation co-efficient between ROIs across sites were used. The investigation demonstrated a strong correlation between cross correlation values for pair of ROIS between sites. These findings suggest reliability and consistency of resting state brain networks between sites.","abstract_html":"Resting state FMRI studies on human subjects are primarily focused on elaborating effects of resting state brain networks on task induced paradigm and to check consistency of these networks between different groups of populations. Recent studies have shown consistency of RSFC networks within same subjects with intra-site and intra-session variation. The primary objective of this study was to check consistency of resting state networks between sites and between different groups of people in spite of change in scanning parameters and population. A total of 437 subjects resting state FMRI data from six different sites were collected varying in age group from 21 to 40 years, with scanning parameters varying from site to site. All the data was pre-processed in exactly similar fashion to reduce effects of site variation and to make group comparison feasible. It was hypothesized that in spite of variation in scanning parameters and population differences, cross-correlation values of time series between 97 ROIs chosen in the brain, should be consistent. To compare resting state connectivity measures, scatter plots of cross-correlation co-efficient between ROIs across sites were used. The investigation demonstrated a strong correlation between cross correlation values for pair of ROIS between sites. These findings suggest reliability and consistency of resting state brain networks between sites.","abstract_has_math":false,"creators":["Gohel, Suril Rajeshkumar"],"institution":null,"degree_name":"Master of Science in Biomedical Engineering - (M.S.)","degree_level":null,"degree_discipline":"Biomedical Engineering","degree_department":null,"school":null,"contributors":["Bharat Biswal","Tara L. Alvarez","Richard A. Foulds"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-05-31T07:00:00Z","date_published":"2009-05-31T07:00:00Z","updated_at":"2026-07-24T03:23:16Z","subjects":["Resting state FRMI","Resting state network consistency","Biomedical Engineering and Bioengineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.njit.edu/theses/307","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bharat Biswal","Tara L. Alvarez","Richard A. Foulds"]},{"key":"dc:creator","label":"Author","values":["Gohel, Suril Rajeshkumar"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biomedical Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Biomedical Engineering - (M.S.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Resting state FRMI","Resting state network consistency","Biomedical Engineering and Bioengineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.njit.edu/theses/307"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Resting state FMRI studies on human subjects are primarily focused on elaborating effects of resting state brain networks on task induced paradigm and to check consistency of these networks between different groups of populations. Recent studies have shown consistency of RSFC networks within same subjects with intra-site and intra-session variation. The primary objective of this study was to check consistency of resting state networks between sites and between different groups of people in spite of change in scanning parameters and population. A total of 437 subjects resting state FMRI data from six different sites were collected varying in age group from 21 to 40 years, with scanning parameters varying from site to site. All the data was pre-processed in exactly similar fashion to reduce effects of site variation and to make group comparison feasible. It was hypothesized that in spite of variation in scanning parameters and population differences, cross-correlation values of time series between 97 ROIs chosen in the brain, should be consistent. To compare resting state connectivity measures, scatter plots of cross-correlation co-efficient between ROIs across sites were used. The investigation demonstrated a strong correlation between cross correlation values for pair of ROIS between sites. These findings suggest reliability and consistency of resting state brain networks between sites."]},{"key":"dc:title","label":"Title","values":["Reliability of resting brain networks using FMRI"]}]}],"canonical_facts":{"dc:contributor":["Bharat Biswal","Tara L. Alvarez","Richard A. Foulds"],"dc:creator":["Gohel, Suril Rajeshkumar"],"dc:description.abstract":["Resting state FMRI studies on human subjects are primarily focused on elaborating effects of resting state brain networks on task induced paradigm and to check consistency of these networks between different groups of populations. Recent studies have shown consistency of RSFC networks within same subjects with intra-site and intra-session variation. The primary objective of this study was to check consistency of resting state networks between sites and between different groups of people in spite of change in scanning parameters and population. A total of 437 subjects resting state FMRI data from six different sites were collected varying in age group from 21 to 40 years, with scanning parameters varying from site to site. All the data was pre-processed in exactly similar fashion to reduce effects of site variation and to make group comparison feasible. It was hypothesized that in spite of variation in scanning parameters and population differences, cross-correlation values of time series between 97 ROIs chosen in the brain, should be consistent. To compare resting state connectivity measures, scatter plots of cross-correlation co-efficient between ROIs across sites were used. The investigation demonstrated a strong correlation between cross correlation values for pair of ROIS between sites. These findings suggest reliability and consistency of resting state brain networks between sites."],"dc:identifier":["https://digitalcommons.njit.edu/theses/307"],"dc:subject":["Resting state FRMI","Resting state network consistency","Biomedical Engineering and Bioengineering"],"dc:title":["Reliability of resting brain networks using FMRI"],"dc:type":["Thesis"],"thesis:degree_discipline":["Biomedical Engineering"],"thesis:degree_name":["Master of Science in Biomedical Engineering - (M.S.)"]},"updated_at":"2026-07-24T03:23:16Z"}