Procrustes Alignment in Individual-level Analyses of Functional Gradients DOI Open Access
Leonard Sasse, Casey Paquola, Juergen Dukart

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 26, 2024

Abstract Functional connectivity (FC) gradients provide valuable insights into individual differences in brain organization, yet aligning these across individuals poses challenges. Procrustes alignment is often employed to standardize multiple subjects, but the choice of number used introduces complexities that may impact individual-level analyses. In this study, we systematically investigate varying gradient counts on principal FC gradient, using data from four resting state fMRI datasets, including Human Connectome Project (HCP-YA), Amsterdam Open MRI Collection (AOMIC) PIOP1 and PIOP2, Cambridge Centre for Ageing Neuroscience (Cam-CAN). We find increasing enhances identification accuracy can reduce differential identifiability, as additional risk introducing nuisance signals such motion back gradient. To further probe effects, machine learning predict fluid intelligence age, a prediction analysis, revealing higher leak information lower These findings highlight trade-off between precision potential reintroduction noise. Key Points Gradient count impacts identifiability obtained The magnitude transformation correlates with measures, correlation increases alignment. age

Language: Английский

Disruption of structural connectome hierarchy in age-related hearing loss DOI Creative Commons

Yi Zhen,

Hongwei Zheng, Yi Zheng

et al.

Frontiers in Neuroscience, Journal Year: 2025, Volume and Issue: 19

Published: March 17, 2025

Age-related hearing loss (ARHL) is a common sensory disability among older adults and considered risk factor for the development of dementia. Previous work has shown altered brain connectome topology in ARHL, including abnormal nodal strength clustering coefficient. However, whether ARHL affects hierarchical organization structural how these alterations relate to transcriptomic signatures remain unknown. Here, we apply gradient mapping framework derived from diffusion magnetic resonance imaging. We focus on first three gradients that reflect distinct connectome, assess ARHL-related changes. find that, compared controls, patients exhibit widespread disruptions organization, spanning primary areas (e.g., somatomotor network) high-order association default mode network). Subsequently, by employing subcortical-weighted weighting cortical subcortical-cortical connectivity, observe show significantly connectivity left caudate, nucleus accumbens, right hippocampus, amygdala. Finally, investigate relationship between gene expression gradients. are associated with weighted profiles, relevant genes preferentially enriched inorganic ion transmembrane transport terms related regulating biological processes. Taken together, findings highlight hierarchy reveal relevance abnormalities, contributing richer understanding neurobiological substrates ARHL.

Language: Английский

Citations

0
Functional gradient characteristics analysis of preschool-aged children with autism spectrum disorder DOI
Guangrong Wu, Linfeng Song, Yuanyuan Xu

et al.

Cerebral Cortex, Journal Year: 2025, Volume and Issue: 35(4)

Published: April 1, 2025

Abstract Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by social and behavioral impairments, emerging in early childhood with unclear causes. The primary aim of this study to investigate shifts the functional gradients underlying hierarchical brain network organization ASD assess their potential contribution clinical symptom severity. Resting-state magnetic resonance imaging was used examine changes across seven major networks cohort 52 individuals 40 healthy controls. In somatomotor network, neither first nor third gradient showed significant group differences; however, two regions—right paracentral lobule right postcentral gyrus—exhibited differences second gradient. frontoparietal only left middle frontal gyrus difference. For ventral attention exhibited insula, median cingulate paracingulate gyri. default mode all three statistically differences. These results suggest neuroimaging biomarkers for assessing severity preschool-aged children.

Language: Английский

Citations

0
Multimodal analysis of disease onset in Alzheimer’s disease using Connectome, Molecular, and genetics data DOI Creative Commons

Sewook Oh,

Sunghun Kim,

Jong‐Eun Lee

et al.

NeuroImage Clinical, Journal Year: 2024, Volume and Issue: 43, P. 103660 - 103660

Published: Jan. 1, 2024

Alzheimer's disease (AD) and its related age at onset (AAO) are highly heterogeneous, due to the inherent complexity of disease. They affected by multiple factors, such as neuroimaging genetic predisposition. Multimodal integration various data types is necessary; however, it has been nontrivial high dimensionality each modality. We aimed identify multimodal biomarkers AAO in AD using an extended version sparse canonical correlation analysis, which we integrated two imaging modalities, functional magnetic resonance (fMRI) positron emission tomography (PET), form single-nucleotide polymorphisms (SNPs) obtained from initiative database. These three modalities cover low-to-high-level complementary information offer multiscale insights into AAO. identified multivariate markers fMRI, PET, SNP. Furthermore, were largely consistent with those reported existing literature. In particular, our serial mediation analysis suggests that variants influence indirectly affecting brain connectivity amyloid-beta protein accumulation, supporting a plausible path research. Our approach provides comprehensive offers novel AD.

Language: Английский

Citations

1
Prognostic model for predicting Alzheimer’s disease conversion using functional connectome manifolds DOI Creative Commons

Sunghun Kim,

Mansu Kim, Jongeun Lee

et al.

Alzheimer s Research & Therapy, Journal Year: 2024, Volume and Issue: 16(1)

Published: Oct. 9, 2024

Early detection of Alzheimer's disease (AD) is essential for timely management and consideration therapeutic options; therefore, detecting the risk conversion from mild cognitive impairment (MCI) to AD crucial during neurodegenerative progression. Existing neuroimaging studies have mostly focused on group differences between individuals with MCI (or AD) cognitively normal (CN), discarding temporal information time. Here, we aimed develop a prognostic model using functional connectivity (FC) Cox regression suitable event modeling.

Language: Английский

Citations

1
Procrustes Alignment in Individual-level Analyses of Functional Gradients DOI Open Access
Leonard Sasse, Casey Paquola, Juergen Dukart

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 26, 2024

Abstract Functional connectivity (FC) gradients provide valuable insights into individual differences in brain organization, yet aligning these across individuals poses challenges. Procrustes alignment is often employed to standardize multiple subjects, but the choice of number used introduces complexities that may impact individual-level analyses. In this study, we systematically investigate varying gradient counts on principal FC gradient, using data from four resting state fMRI datasets, including Human Connectome Project (HCP-YA), Amsterdam Open MRI Collection (AOMIC) PIOP1 and PIOP2, Cambridge Centre for Ageing Neuroscience (Cam-CAN). We find increasing enhances identification accuracy can reduce differential identifiability, as additional risk introducing nuisance signals such motion back gradient. To further probe effects, machine learning predict fluid intelligence age, a prediction analysis, revealing higher leak information lower These findings highlight trade-off between precision potential reintroduction noise. Key Points Gradient count impacts identifiability obtained The magnitude transformation correlates with measures, correlation increases alignment. age

Language: Английский

Citations

0