RESUMO
The global ageing of populations calls for effective, ecologically valid methods to support brain health across adult life. Previous evidence suggests that music can promote white matter (WM) microstructure and grey matter (GM) volume while supporting auditory and cognitive functioning and emotional well-being as well as counteracting age-related cognitive decline. Adding a social component to music training, choir singing is a popular leisure activity among older adults, but a systematic account of its potential to support healthy brain structure, especially with regard to ageing, is currently missing. The present study used quantitative anisotropy (QA)-based diffusion MRI connectometry and voxel-based morphometry to explore the relationship of lifetime choir singing experience and brain structure at the whole-brain level. Cross-sectional multiple regression analyses were carried out in a large, balanced sample (N = 95; age range 21-88) of healthy adults with varying levels of choir singing experience across the whole age range and within subgroups defined by age (young, middle-aged, and older adults). Independent of age, choir singing experience was associated with extensive increases in WM QA in commissural, association, and projection tracts across the brain. Corroborating previous work, these overlapped with language and limbic networks. Enhanced corpus callosum microstructure was associated with choir singing experience across all subgroups. In addition, choir singing experience was selectively associated with enhanced QA in the fornix in older participants. No associations between GM volume and choir singing were found. The present study offers the first systematic account of amateur-level choir singing on brain structure. While no evidence for counteracting GM atrophy was found, the present evidence of enhanced structural connectivity coheres well with age-typical structural changes. Corroborating previous behavioural studies, the present results suggest that regular choir singing holds great promise for supporting brain health across the adult life span.
Assuntos
Canto , Substância Branca , Humanos , Adulto , Masculino , Pessoa de Meia-Idade , Idoso , Feminino , Adulto Jovem , Canto/fisiologia , Idoso de 80 Anos ou mais , Substância Branca/diagnóstico por imagem , Substância Branca/fisiologia , Substância Branca/anatomia & histologia , Envelhecimento/fisiologia , Estudos Transversais , Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Encéfalo/anatomia & histologia , Substância Cinzenta/diagnóstico por imagem , Substância Cinzenta/anatomia & histologia , Substância Cinzenta/fisiologia , Imagem de Difusão por Ressonância Magnética , Imagem de Tensor de DifusãoRESUMO
Smaller manually-segmented amygdala volumes have been associated with poorer motor and cognitive function in Huntington's disease (HD). Manual segmentation is the gold standard in terms of accuracy; however, automated methods may be necessary in large samples. Automated segmentation accuracy has not been determined for the amygdala in HD. We aimed to determine which of three automated approaches would most accurately segment amygdalae in HD: FreeSurfer, FIRST, and ANTS nonlinear registration followed by FIRST segmentation. T1-weighted images for the IMAGE-HD cohort including 35 presymptomatic HD (pre-HD), 36 symptomatic HD (symp-HD), and 34 healthy controls were segmented using FreeSurfer and FIRST. For the third approach, images were nonlinearly registered to an MNI template using ANTS, then segmented using FIRST. All automated methods overestimated amygdala volumes compared with manual segmentation. Dice overlap scores, indicating segmentation accuracy, were not significantly different between automated approaches. Manually segmented volumes were most statistically differentiable between groups, followed by those segmented by FreeSurfer, then ANTS/FIRST. FIRST-segmented volumes did not differ between groups. All automated methods produced a bias where volume overestimation was more severe for smaller amygdalae. This bias was subtle for FreeSurfer, but marked for FIRST, and moderate for ANTS/FIRST. Further, FreeSurfer introduced a hemispheric bias not evident with manual segmentation, producing larger right amygdalae by 8%. To assist choice of segmentation approach, we provide sample size estimation graphs based on sample size and other factors. If automated segmentation is employed in samples of the current size, FreeSurfer may effectively distinguish amygdala volume between controls and HD.
Assuntos
Tonsila do Cerebelo/diagnóstico por imagem , Doença de Huntington/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Adulto , Idoso , Automação , Viés , Estudos de Coortes , Progressão da Doença , Feminino , Lateralidade Funcional , Humanos , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Tamanho da Amostra , Adulto JovemRESUMO
In Huntington's disease (HD), the presence of neurodegeneration in brain regions other than the striatum has been recently gaining attention. The amygdala is one such area, which has been investigated in only eight structural magnetic resonance imaging studies to date, but with inconsistent findings. This is the largest MRI study to date examining manually traced amygdala volumes in HD participants and the relationship of amygdala volumes to clinical measures of HD. Our study included 35 healthy control participants, and groups of 35 pre-symptomatic, and 36 symptomatic HD participants. When comparing the pre-symptomatic and symptomatic HD groups together against the control group, amygdala volumes were significantly lower in HD than controls and in symptomatic HD than pre-symptomatic HD. When examining relationships between amygdala volumes and clinical measures of HD, significantly smaller amygdala volumes were associated with worse motor and cognitive signs. For pre-symptomatic HD participants who were close to disease onset, smaller amygdala volumes were also associated with higher levels of anxiety symptoms. These findings suggest that the amygdala is affected in pre-symptomatic and symptomatic HD, and that the amygdala is related to the clinical profile of HD before onset of motor symptoms.