Research Article
Determination of Effective Connectivity of Brain Activity in the Resting Brain
@INPROCEEDINGS{10.1007/978-3-031-60665-6_2, author={Catarina Pi\"{a}o Azevedo and Paulo A. Salgado and T.-P. Azevedo Perdico\^{u}lis and Paulo Lopes dos Santos}, title={Determination of Effective Connectivity of Brain Activity in the Resting Brain}, proceedings={Wireless Mobile Communication and Healthcare. 12th EAI International Conference, MobiHealth 2023, Vila Real, Portugal, November 29-30, 2023 Proceedings}, proceedings_a={MOBIHEALTH}, year={2024}, month={6}, keywords={State-Space Model Functional Magnetic Resonance Imaging Monte Carlo Simulation Effective Connectivity Independent Component Analysis}, doi={10.1007/978-3-031-60665-6_2} }- Catarina Pião Azevedo
Paulo A. Salgado
T.-P. Azevedo Perdicoúlis
Paulo Lopes dos Santos
Year: 2024
Determination of Effective Connectivity of Brain Activity in the Resting Brain
MOBIHEALTH
Springer
DOI: 10.1007/978-3-031-60665-6_2
Abstract
The resting brain has been extensively investigated for low frequency synchrony between brain regions, namely Functional Connectivity. However the other main stream of the brain connectivity analysis that seeks causal interactions between brain regions, Effective Connectivity, has been still little explored. Inherent complexity of brain activities in resting-state, as observed in Blood Oxygenation-Level Dependant fluctuations, calls for exploratory methods for characterizing these causal networks [1].
To determine the structure of the network that causes this dynamics, it is developed a method of identification based on least squares, which assumes knowledge of the signals of brain activity in different regions. As there is no access to functional Magnetic Resonance Imaging, data it is developed a model to obtain the Blood Oxygenation Level Dependent signals and it is implemented a reverse hemo-dynamic function. To assess the performance of the created model Monte Carlo simulations have been used.
