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Abstract #5535

From neurons to BOLD connectivity: a validation study

Andrea Duggento1, Luca Passamonti2,3, Gaetano Valenza4, Riccardo Barbieri5,6, Maria Guerrisi1, and Nicola Toschi1,7

1Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Roma, Italy, 2Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom, 3Istituto di Bioimmagini e Fisiologia Molecolare, Consiglio Nazionale delle Ricerche, Milano, Italy, 4Department of Information Engineering, University of Pisa, Pisa, Italy, 5Department of Electronics, Informatics and Bioengineering, Politecnico di Milano, Milano, Italy, 6Department of Anesthesia, Massachusetts General Hospital, Boston, MA, United States, 7Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States

The use of Multivariate Granger Causality (MVGC) in estimating directed BOLD connectivity is still controversial. We employ realistic complex network models based on Izhikevich neuronal populations interlinked by realistic neuronal fiber bundles which exert compounded directed influences and cascade into Baloon-model-like neurovascular coupling. We show in silico that the top 1 percentile of a BOLD connectivity matrix has a Positive Predictive Value very close to 1, and demonstrate in HCP data that functional interactions between parietal and prefrontal cortices are not symmetrical, but consists of directional connectivity from parietal areas to prefrontal cortices rather than vice versa.

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