{"id":{"repo_id":"oxford-brookes","oai_identifier":"tle:d5e7c357-e312-4fba-8cc5-774eff36180e:d6bd9758-527a-46cd-bfe2-c433766e8fca:1"},"canonical_url":"https://search.dev.ndltd.org/etd/oxford-brookes/tle:d5e7c357-e312-4fba-8cc5-774eff36180e:d6bd9758-527a-46cd-bfe2-c433766e8fca:1","repository":{"repo_id":"oxford-brookes","name":"Oxford Brookes University","base_url":"https://radar.brookes.ac.uk/radar/oai"},"display":{"title":"Exploring the combined use of electrical and hemodynamic brain activity to investigate brain function","abstract":"This thesis explored the relationship between electrical and metabolic aspects of brain functioning in health and disease, measured with QEEG and NIRS, in order to evaluate its clinical potential. First the limitations of NIRS were investigated, depicting its susceptibility to different types of motion artefacts and the inability of the CBSI-method to remove them from resting state data. Furthermore, the quality of the NIRS signals was poor in a significant portion of the investigated sample, reducing clinical potential. Different analysis methods were used to explore both EEG and NIRS, and their coupling in an eyes open eyes closed paradigm in healthy participants. It could be reproduced that during eyes closed blocks less HbO2 (p = 0.000), more Hbb (p = 0.008), and more alpha activity (p = 0.000) was present compared to eyes open blocks. Furthermore, dynamic cross correlation analysis reproduced a positive correlation between alpha and Hbb (r: 0.457 and 0.337) and a negative correlation between alpha and HbO2 (r: -0.380 and -0.366) with a delayed hemodynamic response (7 to 8s). This was only possible when removing all questionable and physiological illogical data, suggesting that an 8s hemodynamic delay might not be the golden standard. Also the inability of the cross correlation to take non-linear relationships into account may distort outcomes. Therefore, In chapter 5 non-linear aspects of the relationship were evaluated by introducing the measure of relative cross mutual information. A newly suggested approach and the most valuable contribution of the thesis since it broadens knowledge in the fields of EEG, NIRS and general time series analysis. Data of two stroke patients then showed differences from the healthy group between the coupling of EEG and NIRS. The differences in long range temporal correlations (p= 0.000 for both cases), entropy (p< 0.040 and p =0.000), and relative cross mutual information (p < 0.003 and p < 0.013) provide the proof of principle that these measures may have clinical utility. Even though more research is necessary before widespread clinical use becomes possible.","abstract_html":"This thesis explored the relationship between electrical and metabolic aspects of brain functioning in health and disease, measured with QEEG and NIRS, in order to evaluate its clinical potential. First the limitations of NIRS were investigated, depicting its susceptibility to different types of motion artefacts and the inability of the CBSI-method to remove them from resting state data. Furthermore, the quality of the NIRS signals was poor in a significant portion of the investigated sample, reducing clinical potential. Different analysis methods were used to explore both EEG and NIRS, and their coupling in an eyes open eyes closed paradigm in healthy participants. It could be reproduced that during eyes closed blocks less HbO2 (p = 0.000), more Hbb (p = 0.008), and more alpha activity (p = 0.000) was present compared to eyes open blocks. Furthermore, dynamic cross correlation analysis reproduced a positive correlation between alpha and Hbb (r: 0.457 and 0.337) and a negative correlation between alpha and HbO2 (r: -0.380 and -0.366) with a delayed hemodynamic response (7 to 8s). This was only possible when removing all questionable and physiological illogical data, suggesting that an 8s hemodynamic delay might not be the golden standard. Also the inability of the cross correlation to take non-linear relationships into account may distort outcomes. Therefore, In chapter 5 non-linear aspects of the relationship were evaluated by introducing the measure of relative cross mutual information. A newly suggested approach and the most valuable contribution of the thesis since it broadens knowledge in the fields of EEG, NIRS and general time series analysis. Data of two stroke patients then showed differences from the healthy group between the coupling of EEG and NIRS. The differences in long range temporal correlations (p= 0.000 for both cases), entropy (p&lt; 0.040 and p =0.000), and relative cross mutual information (p &lt; 0.003 and p &lt; 0.013) provide the proof of principle that these measures may have clinical utility. Even though more research is necessary before widespread clinical use becomes possible.","abstract_has_math":false,"creators":["Driessen, A"],"institution":"Oxford Brookes University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014","date_published":"2014","updated_at":"2026-07-24T03:44:32Z","subjects":[],"languages":["en"],"rights":["All rights reserved"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://radar.brookes.ac.uk/radar/items/d5e7c357-e312-4fba-8cc5-774eff36180e/1/","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Driessen, A"]},{"key":"dc:creator","label":"Author","values":["Driessen, A"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014"]},{"key":"dc:publisher","label":"Institution","values":["Oxford Brookes University"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["All rights reserved"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://radar.brookes.ac.uk/radar/items/d5e7c357-e312-4fba-8cc5-774eff36180e/1/","https://radar.brookes.ac.uk/radar/file/d5e7c357-e312-4fba-8cc5-774eff36180e/1/driessen2014exploring.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis explored the relationship between electrical and metabolic aspects of brain functioning in health and disease, measured with QEEG and NIRS, in order to evaluate its clinical potential. First the limitations of NIRS were investigated, depicting its susceptibility to different types of motion artefacts and the inability of the CBSI-method to remove them from resting state data. Furthermore, the quality of the NIRS signals was poor in a significant portion of the investigated sample, reducing clinical potential. Different analysis methods were used to explore both EEG and NIRS, and their coupling in an eyes open eyes closed paradigm in healthy participants. It could be reproduced that during eyes closed blocks less HbO2 (p = 0.000), more Hbb (p = 0.008), and more alpha activity (p = 0.000) was present compared to eyes open blocks. Furthermore, dynamic cross correlation analysis reproduced a positive correlation between alpha and Hbb (r: 0.457 and 0.337) and a negative correlation between alpha and HbO2 (r: -0.380 and -0.366) with a delayed hemodynamic response (7 to 8s). This was only possible when removing all questionable and physiological illogical data, suggesting that an 8s hemodynamic delay might not be the golden standard. Also the inability of the cross correlation to take non-linear relationships into account may distort outcomes. Therefore, In chapter 5 non-linear aspects of the relationship were evaluated by introducing the measure of relative cross mutual information. A newly suggested approach and the most valuable contribution of the thesis since it broadens knowledge in the fields of EEG, NIRS and general time series analysis. Data of two stroke patients then showed differences from the healthy group between the coupling of EEG and NIRS. The differences in long range temporal correlations (p= 0.000 for both cases), entropy (p< 0.040 and p =0.000), and relative cross mutual information (p < 0.003 and p < 0.013) provide the proof of principle that these measures may have clinical utility. Even though more research is necessary before widespread clinical use becomes possible."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Exploring the combined use of electrical and hemodynamic brain activity to investigate brain function"]}]}],"canonical_facts":{"dc:contributor":["Driessen, A"],"dc:creator":["Driessen, A"],"dc:date":["2014"],"dc:description":["This thesis explored the relationship between electrical and metabolic aspects of brain functioning in health and disease, measured with QEEG and NIRS, in order to evaluate its clinical potential. First the limitations of NIRS were investigated, depicting its susceptibility to different types of motion artefacts and the inability of the CBSI-method to remove them from resting state data. Furthermore, the quality of the NIRS signals was poor in a significant portion of the investigated sample, reducing clinical potential. Different analysis methods were used to explore both EEG and NIRS, and their coupling in an eyes open eyes closed paradigm in healthy participants. It could be reproduced that during eyes closed blocks less HbO2 (p = 0.000), more Hbb (p = 0.008), and more alpha activity (p = 0.000) was present compared to eyes open blocks. Furthermore, dynamic cross correlation analysis reproduced a positive correlation between alpha and Hbb (r: 0.457 and 0.337) and a negative correlation between alpha and HbO2 (r: -0.380 and -0.366) with a delayed hemodynamic response (7 to 8s). This was only possible when removing all questionable and physiological illogical data, suggesting that an 8s hemodynamic delay might not be the golden standard. Also the inability of the cross correlation to take non-linear relationships into account may distort outcomes. Therefore, In chapter 5 non-linear aspects of the relationship were evaluated by introducing the measure of relative cross mutual information. A newly suggested approach and the most valuable contribution of the thesis since it broadens knowledge in the fields of EEG, NIRS and general time series analysis. Data of two stroke patients then showed differences from the healthy group between the coupling of EEG and NIRS. The differences in long range temporal correlations (p= 0.000 for both cases), entropy (p< 0.040 and p =0.000), and relative cross mutual information (p < 0.003 and p < 0.013) provide the proof of principle that these measures may have clinical utility. Even though more research is necessary before widespread clinical use becomes possible."],"dc:format":["application/pdf"],"dc:identifier":["https://radar.brookes.ac.uk/radar/items/d5e7c357-e312-4fba-8cc5-774eff36180e/1/","https://radar.brookes.ac.uk/radar/file/d5e7c357-e312-4fba-8cc5-774eff36180e/1/driessen2014exploring.pdf"],"dc:language":["en"],"dc:publisher":["Oxford Brookes University"],"dc:rights":["All rights reserved"],"dc:title":["Exploring the combined use of electrical and hemodynamic brain activity to investigate brain function"],"dc:type":["thesis"]},"updated_at":"2026-07-24T03:44:32Z"}