The continuous plastic and recurring networking of the human brain subtends an inherent dynamic property of the organ. Robust evidence has described the networking between distant but functionally interrelated regions in the brain (e.g. static functional connectivity) to be linked to a variety of cognitive processes and disrupted in neurodegenerative disorders. In recent years, the neuroscientific community has grown an interest in better understanding the spatiotemporal organization of functionally interacting brain regions. When derived from restingstate functional MRI (rs-fMRI), dynamic or time-varying connectivity (TVC) estimates result from temporal fluctuation correlations of BOLD fMRI time series between brain regions. However, given the novelty of this research line, there are still various challenges involved in TVC analysis and a standardized validated approach to quantify functional brain dynamics is lacking. These challenges represent fundamental limitations that affects experimental precision and reproducibility in neuroscience studies using TVC. This Ph.D. thesis focuses on the influence of several experimental variables in functional TVC estimates and their relationship with neuro-metabolism. It also investigates novel applications of TVC in populations of healthy controls and several brain disorders, including the consideration of different MRI scanner fields and MR protocols (functional BOLD and edited MR spectroscopy). The main work of this thesis is described in five studies. The first three studies address several open issues about TVC and its relationship to experimental variables, cognitive functions and neuro-metabolism on healthy volunteers. Study #1 shows that TVC results are critically affected by fast fMRI protocols. Study #2 shows that TVC is very sensitive to head motion and differently affected by different commonly used motion denoising strategies. Study #3 shows that changes in working memory cognitive load produce correlated changes of TVC and neurometabolism (GABA and Glutamate) in the left medial prefrontal cortex. This study also introduces a novel experimental design that interleaves fMRI with MR spectroscopy acquisitions. The last two studies evaluate novel clinical applications of TVC. Study #4 shows that in Parkinson’s disease volunteers there are associations between subcortical structures TVC and inhibitory neurotransmission. In Study #5 we completed a longitudinal study that evaluates post-surgery reorganization of functional networks of glioma patients, considering tumor laterality and grade. Our main findings are that removal of left lateralized tumors shows slower recovery and that the default mode network may be important to consider in presurgical planning given its role in supporting longitudinal cognitive outcome. We also show preliminary promising results of TVC’s prediction of patient's cognitive outcome and improve pre-surgical planning. Overall, this dissertation contributes novel data about the sensitivity of TVC to various experimental variables, considerations that are important when comparing studies or planning new ones. The feasibility of novel interleaved fMRI and MR spectroscopy opens the path for its use in future studies investigating BOLD and neuro-metabolite activation, in health and disease. The findings of our glioma study have been incorporated in a public tool that is routinely used by the Neurosurgery Unit of the Santa Chiara Hospital, Trento. Future work is also proposed that may contribute towards the use of TVC for basic neuroscience and clinical research.

Human brain functional dynamic connectivity: challenges and potentials in health and disease studies / Saviola, Francesca. - (2022 Nov 07), pp. 1-230.

Human brain functional dynamic connectivity: challenges and potentials in health and disease studies

Saviola, Francesca
2022-11-07

Abstract

The continuous plastic and recurring networking of the human brain subtends an inherent dynamic property of the organ. Robust evidence has described the networking between distant but functionally interrelated regions in the brain (e.g. static functional connectivity) to be linked to a variety of cognitive processes and disrupted in neurodegenerative disorders. In recent years, the neuroscientific community has grown an interest in better understanding the spatiotemporal organization of functionally interacting brain regions. When derived from restingstate functional MRI (rs-fMRI), dynamic or time-varying connectivity (TVC) estimates result from temporal fluctuation correlations of BOLD fMRI time series between brain regions. However, given the novelty of this research line, there are still various challenges involved in TVC analysis and a standardized validated approach to quantify functional brain dynamics is lacking. These challenges represent fundamental limitations that affects experimental precision and reproducibility in neuroscience studies using TVC. This Ph.D. thesis focuses on the influence of several experimental variables in functional TVC estimates and their relationship with neuro-metabolism. It also investigates novel applications of TVC in populations of healthy controls and several brain disorders, including the consideration of different MRI scanner fields and MR protocols (functional BOLD and edited MR spectroscopy). The main work of this thesis is described in five studies. The first three studies address several open issues about TVC and its relationship to experimental variables, cognitive functions and neuro-metabolism on healthy volunteers. Study #1 shows that TVC results are critically affected by fast fMRI protocols. Study #2 shows that TVC is very sensitive to head motion and differently affected by different commonly used motion denoising strategies. Study #3 shows that changes in working memory cognitive load produce correlated changes of TVC and neurometabolism (GABA and Glutamate) in the left medial prefrontal cortex. This study also introduces a novel experimental design that interleaves fMRI with MR spectroscopy acquisitions. The last two studies evaluate novel clinical applications of TVC. Study #4 shows that in Parkinson’s disease volunteers there are associations between subcortical structures TVC and inhibitory neurotransmission. In Study #5 we completed a longitudinal study that evaluates post-surgery reorganization of functional networks of glioma patients, considering tumor laterality and grade. Our main findings are that removal of left lateralized tumors shows slower recovery and that the default mode network may be important to consider in presurgical planning given its role in supporting longitudinal cognitive outcome. We also show preliminary promising results of TVC’s prediction of patient's cognitive outcome and improve pre-surgical planning. Overall, this dissertation contributes novel data about the sensitivity of TVC to various experimental variables, considerations that are important when comparing studies or planning new ones. The feasibility of novel interleaved fMRI and MR spectroscopy opens the path for its use in future studies investigating BOLD and neuro-metabolite activation, in health and disease. The findings of our glioma study have been incorporated in a public tool that is routinely used by the Neurosurgery Unit of the Santa Chiara Hospital, Trento. Future work is also proposed that may contribute towards the use of TVC for basic neuroscience and clinical research.
XXXIV
2021-2022
Università degli Studi di Trento
Cognitive and Brain Sciences
Jovicich, Jorge
no
Inglese
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/360041
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