6 research outputs found

    Fibre-specific laterality of white matter in left and right language dominant people

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    Language is the most commonly described lateralised cognitive function, relying more on the left hemisphere compared to the right hemisphere in over 90% of the population. Most research examining the structure-function relationship of language lateralisation only included people showing a left language hemisphere dominance. In this work, we applied a state-of-the-art "fixel-based" analysis approach, allowing statistical analysis of white matter micro- and macrostructure on a fibre-specific level in a sample of participants with left and right language dominance (LLD and RLD). Both groups showed a similar extensive pattern of white matter lateralisation including a comparable leftwards lateralisation of the arcuate fasciculus, regardless of their functional language lateralisation. These results suggest that lateralisation of language functioning and the arcuate fasciculus are driven by independent biases. Finally, a significant group difference of lateralisation was detected in the forceps minor, with a leftwards lateralisation in LLD and rightwards lateralisation for the RLD group

    Disruption of brainstem monoaminergic fibre tracts in multiple sclerosis as a putative mechanism for cognitive fatigue: a fixel-based analysis

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    In multiple sclerosis (MS), monoaminergic systems are altered as a result of both inflammation-dependent reduced synthesis and direct structural damage. Aberrant monoaminergic neurotransmission is increasingly considered a major contributor to fatigue pathophysiology. In this study, we aimed to compare the integrity of the monoaminergic white matter fibre tracts projecting from brainstem nuclei in a group of patients with MS (n=68) and healthy controls (n=34), and to investigate its association with fatigue. Fibre tracts integrity was assessed with the novel fixel-based analysis that simultaneously estimates axonal density, by means of ‘fibre density’, and white matter atrophy, by means of fibre ‘cross section’. We focused on ventral tegmental area, locus coeruleus, and raphe nuclei as the main source of dopaminergic, noradrenergic, and serotoninergic fibres within the brainstem, respectively. Fourteen tracts of interest projecting from these brainstem nuclei were reconstructed using diffusion tractography, and compared by means of the product of fibre-density and cross- section (FDC). Finally, correlations of monoaminergic axonal damage with the modified fatigue impact scale scores were evaluated in MS. Fixel-based analysis revealed significant axonal damage – as measured by FDC reduction – within selective monoaminergic fibre-tracts projecting from brainstem nuclei in MS patients, in comparison to healthy controls; particularly within the dopaminergic-mesolimbic pathway, the noradrenergic-projections to prefrontal cortex, and serotoninergic-projections to cerebellum. Moreover, we observed significant correlations between severity of cognitive fatigue and axonal damage within the mesocorticolimbic tracts projecting from ventral tegmental area, as well as within the locus coeruleus projections to prefrontal cortex, suggesting a potential contribution of dopaminergic and noradrenergic pathways to central fatigue in MS. Our findings support the hypothesis that axonal damage along monoaminergic pathways contributes to the reduction/dysfunction of monoamines in MS and add new information on the mechanisms by which monoaminergic systems contribute to MS pathogenesis and fatigue. This supports the need for further research into monoamines as therapeutic targets aiming to combat and alleviate fatigue in MS

    Advancing the Study of Functional Connectome Development

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    A better understanding of functional changes in the brain across childhood offers the potential to better support neurodevelopmental and learning challenges. However, neuroimaging tools such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are vulnerable to head motion and other artifacts, and studies have had limited reproducibility. To accomplish research goals, we need to understand the reliability and validity of data collection, processing, and analysis strategies. Neuroimaging datasets contain individually unique information, but identifiability is reduced by noise or lack of signal, suggesting it can be a measure of validity. The goal of this thesis was to use identifiability to benchmark different methodologies, and describe how identifiability associates with age across early childhood. I first compared several different fMRI preprocessing pipelines for data collected from young children. Preprocessing techniques are often controversial due to specific drawbacks and have typically been assessed with adult datasets, which have much less head motion. I found benefits to the use of global signal regression and temporal censoring, but overly strict censoring can impact identifiability, suggesting noise removed must be balanced against signal retained. I also compared several different EEG measures of functional connectivity (FC). EEG can be vulnerable to volume conduction artifacts that can be mitigated by only considering shared information with a time delay between signals. However, I found that mitigation strategies result in lower identifiability, suggesting that while removing confounding noise they also discard substantial signal of interest. Individual experiences may shape development in an individually unique way, which is supported by evidence that adults have more individually identifiable patterns of FC than children. I found that across 4 to 8 years of age, identifiability increased via increased self-stability, but without changes in similarity-to-others. In the absence of ground truth, it is difficult to argue for or against analysis decisions based solely on a theoretical framework and need to also be validated. My work highlights the importance of not thinking about techniques in a valid-invalid dichotomy; certain methods may be sub-optimal while still being preferable to alternatives if they better manage the trade off between noise removed and signal retained

    Brain Function in Early Childhood: Individual Differences in Age and Attentive Traits

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    Children, like adults, are unique individuals with complex interwoven relationships between brain function, behaviour, and phenotypic traits, which further interact with rapid developmental processes. A nuanced description of variability between children will add to our knowledge of how they think and behave, and potentially advance the development of personalized early interventions. With functional magnetic resonance imaging (fMRI), we have gained insight into brain responses – however, due to practical considerations, we have been unable to render a complete understanding of brain-behaviour relationships in young children. The use of naturalistic stimuli in fMRI studies has increased the ecological validity and the retention of developmental neuroimaging data. In this dissertation, I sought to explore the relationships between age, attentive traits, and inter-individual variability of brain function in young children in naturalistic paradigms. I conducted a scoping review to synthesize the current and historical task- and naturalistic-fMRI literature on the development of visual processing in the brain, through the lens of two influential theories: the interactive specialization and maturational frameworks. I found that while there is generally a consensus of progressive development of visual brain function throughout childhood, there is not enough evidence to fully support other aspects of these theories. I also conducted two experiments, using naturalistic fMRI and an analysis technique called inter-subject correlation (ISC), which quantifies the spatiotemporal similarity of brain activity between individuals, to explore how age and attentive traits affect inter-individual variability of brain function in children aged 4-8 years. I found that children’s brain responses to movies “homogenized” with increasing age in our sample, with greater variability seen in the younger children. Further, both inattention and hyperactivity were associated with ISC in the sample, though the relationships with these traits were different in widespread regions of the brain. Together, my research advances our understanding of functional brain responses in children and underscores the importance of an individual differences approach to developmental neuroimaging
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