Exploring Correlation-Based Brain Networks with Adaptive Signed Random Walks

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: April 27, 2023

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 networks their association cognitive processes or disorders. Common approaches, such as thresholding binarization, often disregard negative connections, which may result in loss critical information. This study introduces an adaptive signed random walk (ASRW) model for analyzing correlation- based that incorporates both positive connections. calculates transition probabilities between regions function activities connection strengths, dynamically updating on differences node activity strengths at each time step. Results show classical approach, only considers absolute value underestimates mean first passage (MFPT) compared to proposed ASRW model. Our captures wide range interactions dynamics within network, providing more comprehensive understanding its structure function. suggests considering has potential offer valuable interregional coordination underlying various behaviors.

Language: Английский

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Abnormal multi-layered dynamic cortico-subcortical functional connectivity in major depressive disorder and generalized anxiety disorder

Journal of Psychiatric Research, Journal Year: 2023, Volume and Issue: 167, P. 23 - 31

Published: Oct. 6, 2023

Language: Английский

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Social support and overeating in young women: The role of altering functional network connectivity patterns and negative emotions

Appetite, Journal Year: 2023, Volume and Issue: 191, P. 107069 - 107069

Published: Oct. 11, 2023

Language: Английский

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How to measure functional connectivity using resting-state fMRI? A comprehensive empirical exploration of different connectivity metrics

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

Published: March 18, 2024

Background: Functional connectivity in the context of functional magnetic resonance imaging is typically quantified by Pearson or partial correlation between regional time series blood oxygenation level dependent signal. However, a recent interdisciplinary methodological work proposes more than 230 different metrics to measure similarity types series. Objective: Hence, we systematically evaluated how results typical research approaches neuroimaging vary depending on metric choice. We further explored which most accurately detect neural decline induced age and malignant brain tumors, aiming initiate debate best assessing research. Methods: addressed both questions using four independent datasets, comprising multimodal data from total 1187 individuals. analyzed resting-state sequences calculate 20 representative distinct mathematical domains. used T1- T2-weighted images compute volumes, diffusion-weighted build structural connectomes, pseudo-continuous arterial spin labeling perfusion. Results: First, our demonstrate that differ fundamentally Second, show correlational distance are appropriate cover age. In this context, performs worse other metrics. Third, findings suggest FC choice depends utilized scanning parameters, regions interest, individual investigated. Lastly, beyond major objective study, provide evidence favor perfusion measured via as robust entity mirroring age-related cognitive decline. Conclusion: Our empirical evaluation supports theoretical framework. Future studies need comprehensively define study-specific property assess property, confounding may bias conclusions.

Language: Английский

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Olfactory combinatorial coding supports risk-reward decision making inC. elegans

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

Published: June 23, 2024

Abstract Olfactory-driven behaviors are essential for animal survival, but mechanisms decoding olfactory inputs remain poorly understood. We have used whole-network Ca ++ imaging to study coding in Caenorhabditis elegans. show that the odorant 1-octanol is encoded combinatorially periphery as both an attractant and a repellant. These integrated centrally, their relative strengths determine sensitivity valence of behavioral response through modulation locomotory reversals speed. The balance these pathways also dictates activity command interneurons, which control reversals. This serves regulatory node modulation, allowing C. elegans weigh opportunities hazards its environment when formulating responses. Thus, can be simultaneously opposite valence, focusing attention on integration determining perception, response, plasticity.

Language: Английский

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