Association between brain functional connectivity and actigraphy
Poster No:
246
Submission Type:
Abstract Submission
Authors:
jungeun cho1,2, Dageon Yeo3,4, narae kim3,4, Bumhee Park4,5
Institutions:
1Department of Convergence Healthcare Medicine, Graduate School of Ajou University, Suwon, Republic of Korea, 2Department of Digital Healthcare, Ajou University School of Medicine, Suwon, Korea, Republic of, 3Department of Biomedical Sciences, Graduate School of Ajou University, Suwon, Republic of Korea, 4Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea, Republic of, 5Office of Biostatistics, Medical Research Collaborating Center, Ajou Research Institute for innovative, Suwon, Korea, Republic of
First Author:
jungeun cho
Department of Convergence Healthcare Medicine, Graduate School of Ajou University|Department of Digital Healthcare, Ajou University School of Medicine
Suwon, Republic of Korea|Suwon, Korea, Republic of
Department of Convergence Healthcare Medicine, Graduate School of Ajou University|Department of Digital Healthcare, Ajou University School of Medicine
Suwon, Republic of Korea|Suwon, Korea, Republic of
Co-Author(s):
Dageon Yeo
Department of Biomedical Sciences, Graduate School of Ajou University|Department of Biomedical Informatics, Ajou University School of Medicine
Suwon, Republic of Korea|Suwon, Korea, Republic of
Department of Biomedical Sciences, Graduate School of Ajou University|Department of Biomedical Informatics, Ajou University School of Medicine
Suwon, Republic of Korea|Suwon, Korea, Republic of
narae kim
Department of Biomedical Sciences, Graduate School of Ajou University|Department of Biomedical Informatics, Ajou University School of Medicine
Suwon, Republic of Korea|Suwon, Korea, Republic of
Department of Biomedical Sciences, Graduate School of Ajou University|Department of Biomedical Informatics, Ajou University School of Medicine
Suwon, Republic of Korea|Suwon, Korea, Republic of
Bumhee Park
Department of Biomedical Informatics, Ajou University School of Medicine|Office of Biostatistics, Medical Research Collaborating Center, Ajou Research Institute for innovative
Suwon, Korea, Republic of|Suwon, Korea, Republic of
Department of Biomedical Informatics, Ajou University School of Medicine|Office of Biostatistics, Medical Research Collaborating Center, Ajou Research Institute for innovative
Suwon, Korea, Republic of|Suwon, Korea, Republic of
Introduction:
Neurodegenerative diseases like Alzheimer's disease (AD) are closely associated with amyloid beta (Aβ) accumulation, and rest-activity patterns have been identified as a potential biological marker of this process. Actigraphy has immense potential to explain the onset of dementia, daytime activity reflects the balance of the activity-rest cycle, with lower levels linked to early AD-related changes. CPM(Connectome-based predictive modelling) is robust methods to examine extensive changes in brain functional connectivity, because it allows relationships to be estimated by individual cognitive status. This study aims to explore the relationship between actigraphy and brain functional connectivity(FC), emphasizing actigraphy's potential as a digital biomarker to predict dementia onset and progression.
Methods:
This study utilized 133 participants from BICWALZS. Participants underwent functional magnetic resonance imaging (fMRI), locomotor activity assessment (using actigraphy), and clinical assessments. They were then divided into groups based on the presence or absence of amyloid deposition (amyloid deposition = 40, not amyloid deposition = 93). Using CPM(Connectome-based predictive modelling), we analyzed the relationship between functional connectivity and actigraphy. CPM is a simple method of analysis with functional connectivity and interest variables. To assess group differences in the relationship between FC features derived by CPM and actigraphy, a general linear model (GLM) was applied adjusting for age, sex, and education on MATLAB.
Results:
The result shows that brain connectivity associated with daytime activity differs depending on whether amyloid deposition or not. We analyzed a difference in FC features derived from CPM of the amyloid positive group compared to the negative group. And we calculated the linear model adjusting for age, sex, and education (F = 12.2, β of group = -4.16, p<0.01). Notably, M10 (the Most Active 10-Hour Period) explained that the amyloid positive group has distinct differences in the connectivity of DMN-SalA and DMN-Aud. In contrast, the negative group exhibited weaker intra-DMN connectivity (Figure 1).
·Significant brain connectivity using CPM
Conclusions:
SalA, which has connectivity with the DMN, is involved in detection and integration of emotional and sensory stimuli, and modulating the switch between the internally directed cognition. In case of amyloid deposition, brain function declines and functional connectivity becomes unstable, leading to different network patterns compared to the group without amyloid accumulation. The inverse relationship between daytime activity and brain functional connectivity suggests the importance of activities that appropriately stimulate relevant functional connectivity in patients with dementia.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 2
Univariate Modeling
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
FUNCTIONAL MRI
Other - Dementia, Amyloid positivity, Actigraphy, CPM, functional connectivity, GLM
1|2Indicates the priority used for review
Abstract Information
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
Roh, H. W., Choi, J. G., Kim, N. R., Choe, Y. S., Choi, J. W., Cho, S. M., ... & Kim, E. Y. (2020). Associations of rest-activity patterns with amyloid burden, medial temporal lobe atrophy, and cognitive impairment. EBioMedicine, 58.
Xilin Shen, Emily S. Finn, Dustin Scheinost, Monica D. Rosenberg, Marvin M. Chun, Xenophon Papademetris, R Todd Constable (2017). Using connectome-based predictive modeling to predict individual behavior from brain connectivity
Uddin, Lucina Q. (19 November 2014). "Salience processing and insular cortical function and dysfunction". Nature Reviews Neuroscience. 16 (1): 55–61.
Winer, J. R., Lok, R., Weed, L., He, Z., Poston, K. L., Mormino, E. C., & Zeitzer, J. M. (2024). Impaired 24-h activity patterns are associated with an increased risk of Alzheimer’s disease, Parkinson’s disease, and cognitive decline. Alzheimer's Research & Therapy, 16(1), 35.