The slow waves (0.5-4 Hz) observed during NREM sleep exhibit significant alterations influenced by experience-related plasticity and brain maturation. Existing literature predominantly suggests that slow waves originate from the cortex in both children and adults. However, research involving animal models and intracranial recordings from epilepsy patients has highlighted the potential pivotal role of subcortical structures, particularly the thalamus, in orchestrating and coordinating cortical slow waves. Previous studies using high-density electroencephalography (EEG) have suggested that subcortical structures, especially the thalamus, are involved in the generation and synchronization of large, widespread slow waves originating from the somatomotor cortex, while smaller, more localized slow waves may predominantly depend on cortico-cortical interactions. Despite these insights, the specific influence of subcortical structures on slow waves remains underexplored, primarily due to the spatial limitations of EEG technology. More importantly, there is a notable lack of evidence regarding these mechanisms in children. To address these gaps, we employed simultaneous EEG-fMRI, combining the high spatial resolution of fMRI with the capability of EEG to recognize individual graphoelements of sleep. This approach allows us to move beyond the traditional study of sleep based on polysomnography. The first aim of this Thesis is to investigate the cortical and subcortical correlates of slow waves in children. Our findings indicate that developmental changes in slow-wave distribution occur around a stable origin hotspot in the somatomotor cortex. Furthermore, the involvement of the cortical and thalamic default mode network in sleep slow waves increases with age, reflecting the relatively slow maturation of this functional network. Finally, our results suggest that maturation in slow- wave properties during development depend on changes in thalamic regulation. The second aim is to examine whether the thalamus plays different roles in regulating and expressing distinct subtypes of slow waves. Our results demonstrate the existence of two distinct synchronization mechanisms for slow waves: subcortico-cortical synchronization, which can lead to large and widespread slow waves and is associated with changes in autonomic activity, and cortico-cortical synchronization, which leads to smaller, more localized slow waves. These functional mechanisms may undergo distinct regulatory processes and may serve different functions across the sleeping night. In conclusion, these studies underscore the importance of a comprehensive characterization of sleep slow waves across the lifespan. Such understanding is crucial for guiding future research aimed at investigating the role of sleep in normal and pathological development and aging and at building targeted therapeutic interventions.

Beyond the cortex: cerebral hemodynamic changes associated with NREM sleep slow waves across the lifespan

BERGAMO, DAMIANA
2024

Abstract

The slow waves (0.5-4 Hz) observed during NREM sleep exhibit significant alterations influenced by experience-related plasticity and brain maturation. Existing literature predominantly suggests that slow waves originate from the cortex in both children and adults. However, research involving animal models and intracranial recordings from epilepsy patients has highlighted the potential pivotal role of subcortical structures, particularly the thalamus, in orchestrating and coordinating cortical slow waves. Previous studies using high-density electroencephalography (EEG) have suggested that subcortical structures, especially the thalamus, are involved in the generation and synchronization of large, widespread slow waves originating from the somatomotor cortex, while smaller, more localized slow waves may predominantly depend on cortico-cortical interactions. Despite these insights, the specific influence of subcortical structures on slow waves remains underexplored, primarily due to the spatial limitations of EEG technology. More importantly, there is a notable lack of evidence regarding these mechanisms in children. To address these gaps, we employed simultaneous EEG-fMRI, combining the high spatial resolution of fMRI with the capability of EEG to recognize individual graphoelements of sleep. This approach allows us to move beyond the traditional study of sleep based on polysomnography. The first aim of this Thesis is to investigate the cortical and subcortical correlates of slow waves in children. Our findings indicate that developmental changes in slow-wave distribution occur around a stable origin hotspot in the somatomotor cortex. Furthermore, the involvement of the cortical and thalamic default mode network in sleep slow waves increases with age, reflecting the relatively slow maturation of this functional network. Finally, our results suggest that maturation in slow- wave properties during development depend on changes in thalamic regulation. The second aim is to examine whether the thalamus plays different roles in regulating and expressing distinct subtypes of slow waves. Our results demonstrate the existence of two distinct synchronization mechanisms for slow waves: subcortico-cortical synchronization, which can lead to large and widespread slow waves and is associated with changes in autonomic activity, and cortico-cortical synchronization, which leads to smaller, more localized slow waves. These functional mechanisms may undergo distinct regulatory processes and may serve different functions across the sleeping night. In conclusion, these studies underscore the importance of a comprehensive characterization of sleep slow waves across the lifespan. Such understanding is crucial for guiding future research aimed at investigating the role of sleep in normal and pathological development and aging and at building targeted therapeutic interventions.
29-ott-2024
Inglese
BETTA, MONICA
Bernardi, Giulio
Scuola IMT Alti Studi di Lucca
Lucca, Italia
186
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/375347
Il codice NBN di questa tesi è URN:NBN:IT:IMTLUCCA-375347