{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/396720"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/396720","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Investigating the Impact of Sleep on Early Dynamic Functional Connectivity: A High-Density Diffuse Optical Tomography Study in Term and Preterm Neonates","abstract":"Poor sleep early in life has been shown to negatively impact neurocognitive functions such as attention, inhibition, and learning (McCann et al., 2018). The impact of sleep on neuronal maturation is especially critical for preterm neonates who experience environmental sleep disruptions early in development. Preterm birth has been associated with cognitive, social, and sleep difficulties later in life, outcomes that may be exacerbated by affected sleep (Gao et al., 2017; Stangenes et al., 2017). This thesis examines dynamic functional connectivity during sleep in term and preterm neonates using High-Density Diffuse Optical Tomography (HD-DOT), a functional near-infrared spectroscopy (fNIRS) technology. The goal of this work was to clarify the relationship between neonatal sleep states, gestational age (GA), and functional brain development. Shedding light on the intersection of these three factors serves a broader goal to improve long-term clinical outcomes for vulnerable populations staying in the neonatal intensive care unit (NICU). I acquired cot-side HD-DOT data from two neonatal cohorts (term neonate cohort: n = 44, median (range) GA = 40+0 (38+1 - 42+1) weeks; preterm neonate cohort: n = 28, median (range) GA = 35+0 (29+1 - 36+6) weeks). I then adapted fMRI co-activation pattern (CAP) analytical procedures for neonatal HD-DOT data, validating the method by showing robust correlation with static seed-based analysis of known resting-state networks. I investigated how CAPs and their temporal features varied across active sleep (AS) and quiet sleep (QS) states in term and preterm neonates to shed light on why the proportion of AS to QS evolves with age. Term neonates showed sleep-state-dependent lateralization, including QS-associated left-lateralized activity in frontal and parietal regions, suggesting QS plays a role in shaping language-related connectivity. In preterm neonates, AS was associated with longer dwell times, but this distinction from QS decreases with increasing postmenstrual age (PMA), suggesting AS may play a unique role early in development that diminishes with maturation. In a final iteration of analysis, CAPs were generated from a unified term and preterm dataset to allow for direct comparison of spatial and temporal CAP features. Preterm neonates demonstrated distinct medial patterns which may be indicative of immature interhemispheric connectivity. Term neonates exhibited longer dwell times and greater fractional occupancy in specific CAPs, particularly in frontal and central regions. Generalized linear models identified postmenstrual age (PMA) as the key predictor of these maturational differences. This is the first application of CAP analysis to neonatal HD-DOT data and the first study to directly compare dynamic functional connectivity between term and preterm neonates using CAPs. These results establish CAP analysis as a valuable tool for investigating age- and sleep-related differences in neonatal brain function. More broadly, they suggest that sleep state (particularly AS) plays a critical and evolving functional role in early brain development. This work supports aligning clinical care with natural sleep cycles as a low-cost, high-impact strategy to promote optimal brain development in NICUs.","abstract_html":"Poor sleep early in life has been shown to negatively impact neurocognitive functions such as attention, inhibition, and learning (McCann et al., 2018). The impact of sleep on neuronal maturation is especially critical for preterm neonates who experience environmental sleep disruptions early in development. Preterm birth has been associated with cognitive, social, and sleep difficulties later in life, outcomes that may be exacerbated by affected sleep (Gao et al., 2017; Stangenes et al., 2017). This thesis examines dynamic functional connectivity during sleep in term and preterm neonates using High-Density Diffuse Optical Tomography (HD-DOT), a functional near-infrared spectroscopy (fNIRS) technology. The goal of this work was to clarify the relationship between neonatal sleep states, gestational age (GA), and functional brain development. Shedding light on the intersection of these three factors serves a broader goal to improve long-term clinical outcomes for vulnerable populations staying in the neonatal intensive care unit (NICU). I acquired cot-side HD-DOT data from two neonatal cohorts (term neonate cohort: n = 44, median (range) GA = 40+0 (38+1 - 42+1) weeks; preterm neonate cohort: n = 28, median (range) GA = 35+0 (29+1 - 36+6) weeks). I then adapted fMRI co-activation pattern (CAP) analytical procedures for neonatal HD-DOT data, validating the method by showing robust correlation with static seed-based analysis of known resting-state networks. I investigated how CAPs and their temporal features varied across active sleep (AS) and quiet sleep (QS) states in term and preterm neonates to shed light on why the proportion of AS to QS evolves with age. Term neonates showed sleep-state-dependent lateralization, including QS-associated left-lateralized activity in frontal and parietal regions, suggesting QS plays a role in shaping language-related connectivity. In preterm neonates, AS was associated with longer dwell times, but this distinction from QS decreases with increasing postmenstrual age (PMA), suggesting AS may play a unique role early in development that diminishes with maturation. In a final iteration of analysis, CAPs were generated from a unified term and preterm dataset to allow for direct comparison of spatial and temporal CAP features. Preterm neonates demonstrated distinct medial patterns which may be indicative of immature interhemispheric connectivity. Term neonates exhibited longer dwell times and greater fractional occupancy in specific CAPs, particularly in frontal and central regions. Generalized linear models identified postmenstrual age (PMA) as the key predictor of these maturational differences. This is the first application of CAP analysis to neonatal HD-DOT data and the first study to directly compare dynamic functional connectivity between term and preterm neonates using CAPs. These results establish CAP analysis as a valuable tool for investigating age- and sleep-related differences in neonatal brain function. More broadly, they suggest that sleep state (particularly AS) plays a critical and evolving functional role in early brain development. This work supports aligning clinical care with natural sleep cycles as a low-cost, high-impact strategy to promote optimal brain development in NICUs.","abstract_has_math":false,"creators":["Lee, Katharine"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Austin, Topun"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-06-11","date_published":"2025-06-11","updated_at":"2026-07-22T22:24:01Z","subjects":["High Density Diffuse Optical Tomography","Neonate","Preterm Neonate","Dynamic Functional Connectivity","Co-Activation Pattern","Sleep State"],"languages":["eng"],"rights":[],"rights_urls":["https://www.repository.cam.ac.uk/bitstreams/d4185713-ea94-4b0d-819c-eecef4573951/download","http://purl.org/NET/rdflicense/allrightsreserved"],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.125997","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Austin, Topun"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["Gates Cambridge Scholarship"]},{"key":"dc:creator","label":"Author","values":["Lee, Katharine"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2025-06-11"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/396720"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["High Density Diffuse Optical Tomography","Neonate","Preterm Neonate","Dynamic Functional Connectivity","Co-Activation Pattern","Sleep State"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://www.repository.cam.ac.uk/bitstreams/d4185713-ea94-4b0d-819c-eecef4573951/download","http://purl.org/NET/rdflicense/allrightsreserved"]},{"key":"dc:rights.embargodate","label":"Dc Rights Embargodate","values":["2027-02-11"]},{"key":"dc:rights.embargotype","label":"Dc Rights Embargotype","values":["embargo"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.17863/CAM.125997"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://www.repository.cam.ac.uk/bitstreams/3d75e9d6-d040-43e0-a470-67847ba94c64/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Poor sleep early in life has been shown to negatively impact neurocognitive functions such as attention, inhibition, and learning (McCann et al., 2018). 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I acquired cot-side HD-DOT data from two neonatal cohorts (term neonate cohort: n = 44, median (range) GA = 40+0 (38+1 - 42+1) weeks; preterm neonate cohort: n = 28, median (range) GA = 35+0 (29+1 - 36+6) weeks). I then adapted fMRI co-activation pattern (CAP) analytical procedures for neonatal HD-DOT data, validating the method by showing robust correlation with static seed-based analysis of known resting-state networks. I investigated how CAPs and their temporal features varied across active sleep (AS) and quiet sleep (QS) states in term and preterm neonates to shed light on why the proportion of AS to QS evolves with age. Term neonates showed sleep-state-dependent lateralization, including QS-associated left-lateralized activity in frontal and parietal regions, suggesting QS plays a role in shaping language-related connectivity. In preterm neonates, AS was associated with longer dwell times, but this distinction from QS decreases with increasing postmenstrual age (PMA), suggesting AS may play a unique role early in development that diminishes with maturation. In a final iteration of analysis, CAPs were generated from a unified term and preterm dataset to allow for direct comparison of spatial and temporal CAP features. Preterm neonates demonstrated distinct medial patterns which may be indicative of immature interhemispheric connectivity. Term neonates exhibited longer dwell times and greater fractional occupancy in specific CAPs, particularly in frontal and central regions. Generalized linear models identified postmenstrual age (PMA) as the key predictor of these maturational differences. This is the first application of CAP analysis to neonatal HD-DOT data and the first study to directly compare dynamic functional connectivity between term and preterm neonates using CAPs. These results establish CAP analysis as a valuable tool for investigating age- and sleep-related differences in neonatal brain function. More broadly, they suggest that sleep state (particularly AS) plays a critical and evolving functional role in early brain development. 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I acquired cot-side HD-DOT data from two neonatal cohorts (term neonate cohort: n = 44, median (range) GA = 40+0 (38+1 - 42+1) weeks; preterm neonate cohort: n = 28, median (range) GA = 35+0 (29+1 - 36+6) weeks). I then adapted fMRI co-activation pattern (CAP) analytical procedures for neonatal HD-DOT data, validating the method by showing robust correlation with static seed-based analysis of known resting-state networks. I investigated how CAPs and their temporal features varied across active sleep (AS) and quiet sleep (QS) states in term and preterm neonates to shed light on why the proportion of AS to QS evolves with age. Term neonates showed sleep-state-dependent lateralization, including QS-associated left-lateralized activity in frontal and parietal regions, suggesting QS plays a role in shaping language-related connectivity. In preterm neonates, AS was associated with longer dwell times, but this distinction from QS decreases with increasing postmenstrual age (PMA), suggesting AS may play a unique role early in development that diminishes with maturation. In a final iteration of analysis, CAPs were generated from a unified term and preterm dataset to allow for direct comparison of spatial and temporal CAP features. Preterm neonates demonstrated distinct medial patterns which may be indicative of immature interhemispheric connectivity. Term neonates exhibited longer dwell times and greater fractional occupancy in specific CAPs, particularly in frontal and central regions. Generalized linear models identified postmenstrual age (PMA) as the key predictor of these maturational differences. This is the first application of CAP analysis to neonatal HD-DOT data and the first study to directly compare dynamic functional connectivity between term and preterm neonates using CAPs. These results establish CAP analysis as a valuable tool for investigating age- and sleep-related differences in neonatal brain function. More broadly, they suggest that sleep state (particularly AS) plays a critical and evolving functional role in early brain development. This work supports aligning clinical care with natural sleep cycles as a low-cost, high-impact strategy to promote optimal brain development in NICUs."],"dc:format.checksum.md5":["ee995b83fec50d89b8b3bce0d5212489","87eda9de84448d1f82354d60eee3eb5f"],"dc:identifier.doi":["https://doi.org/10.17863/CAM.125997"],"dc:identifier.uri":["https://www.repository.cam.ac.uk/bitstreams/3d75e9d6-d040-43e0-a470-67847ba94c64/download"],"dc:language":["eng"],"dc:publisher.institution":["University of Cambridge"],"dc:relation.isreferencedby.uri":["https://www.repository.cam.ac.uk/handle/1810/396720"],"dc:rights":["https://www.repository.cam.ac.uk/bitstreams/d4185713-ea94-4b0d-819c-eecef4573951/download","http://purl.org/NET/rdflicense/allrightsreserved"],"dc:rights.embargodate":["2027-02-11"],"dc:rights.embargotype":["embargo"],"dc:subject":["High Density Diffuse Optical Tomography","Neonate","Preterm Neonate","Dynamic Functional Connectivity","Co-Activation Pattern","Sleep State"],"dc:title":["Investigating the Impact of Sleep on Early Dynamic Functional Connectivity: A High-Density Diffuse Optical Tomography Study in Term and Preterm Neonates"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral"],"dc:type.qualificationname":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-22T22:24:01Z"}