Abstract
The human brain is a highly connected network with complex patterns of correlated and anticorrelated activity. Analyzing functional connectivity matrices derived from neuroimaging data can provide insights into the organization of brain networks and their association with cognitive processes or disorders. Common approaches, such as thresholding or binarization, often disregard negative connections, which may result in the loss of critical information. This study introduces an adaptive signed random walk (ASRW) model for analyzing correlation-based brain networks that incorporates both positive and negative connections. The model calculates transition probabilities between brain regions as a function of their activities and connection strengths, dynamically updating probabilities based on the differences in node activity and connection strengths at each time step. Results show that the classical random walk approach, which only considers the absolute value of connections, underestimates the mean first passage time (MFPT) compared to the proposed ASRW model. Our model captures a wide range of interactions and dynamics within the network, providing a more comprehensive understanding of its structure and function. This study suggests that considering both positive and negative connections, has the potential to offer valuable insights into the interregional coordination underlying various cognitive processes and behaviors.
Original language | English |
---|---|
Title of host publication | Proceedings - 2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2023 |
Editors | XiaoMing Zhao, Qingli Li, Lipo Wang |
Publisher | IEEE Xplore |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 979-8-3503-3075-5 |
ISBN (Print) | 979-8-3503-3076-2 |
DOIs | |
Publication status | Published online - 2 Jan 2024 |
Publication series
Name | Proceedings - 2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2023 |
---|
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Brain
- Correlation networks
- Random Walks
- fMRI