Gradient-based framework for aging and risk factors
Poster No:
1804
Submission Type:
Abstract Submission
Authors:
Chen Cheng1, Xiuhui Chen2, Samyogita Hardikar3
Institutions:
1Taiyuan University of Technology, Taiyuan, Shanxi, 2Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology,, Leipzig, Germany
First Author:
Co-Author(s):
Samyogita Hardikar
Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology,
Leipzig, Germany
Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology,
Leipzig, Germany
Introduction:
In industrialized societies, blood pressure increases with age, and age-related declines in cardiovascular function may impair cerebral blood flow (CBF) regulation, leading to the disruption of neuronal micro-environmental homeostasis. In addition, previous researches found that aging is considered as a biological process affected by some risk factors such as bmi, ApoE genotype and smoke state. The integration of gradient concepts into fMRI neuroimaging approaches suggests that combining advanced fMRI with cortical gradients could enhance our understanding of brain aging and the pathogenesis of neurodegenerative disorders.
Methods:
We will use data from the LIFE-Adult study, a population based cohort study with over 2500 selected participants from Leipzig Germany. The examination was completed in November 2014 and included questionnaires, anthropometry, blood measurements and MRI. The blood measurement was performed after an overnight fast. The study includes participants between 20 - 79 years of age. We plan to derive functional connectivity gradients for each participant via principal component analysis, which is an established technique to linearly reduce the dimensionality of large-scale connectivity data. Then we will use statistical analysis with linear regression models.
Results:
The first three group-averaged gradients, projected from established functional communities into a 3D gradient space, were represented in left lateral and medial views. The word clouds representing the results from a meta-analysis to decode the most likely terms used to describe the pattern of gradient, where the size of the word represents the magnitude of the relationship, and the color represents the direction (warmer colors = positive relationship, cooler colors = negative relationship). We also find the association of gradient value with age and cardiovascular risk factors, controlling for sex and head motion.
Conclusions:
In summary, our study explored global functional gradient using 3D gradient spaces, unveiling compactly localized functional communities. We discovered associations with age, cardiovascular risk factors and the cognitive competence, adjusting for sex and head motion. These findings contribute valuable insights into the complex relationships between functional connectivity gradients and demographic and health factors.
Emotion, Motivation and Social Neuroscience:
Social Cognition
Lifespan Development:
Aging 2
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 1
Keywords:
Aging
Cognition
FUNCTIONAL MRI
Other - Gradient
1|2Indicates the priority used for review