Some Results on Dynamic Causal Modeling of Auditory Hallucinations

Abstract

AbstractHallucinations, and more specifically auditory hallucinations (AH), are a perplexing phenomena experienced by many people. Though they are a clinical symptom in some mental diseases, such as Schizophrenia, they are also experienced by normal, healthy persons. There are several models of the mechanics happening in the brain leading to hallucinations, which involve auditory, language and emotion regions. On the other hand, there is not much empirical evidence due to the evanescence of the phenomena, and the difficulty to capture meaningful data. Recent works on resting state functional Magnetic Resonance Imaging (rs-fMRI) data, are providing confirmation of some brain localizations. Dynamic Causal Modeling (DCM) provides estimations of neural effective connectivity parameters from the experimental fMRI data, and recently has been proposed to work on rs-fMRI data. We provide preliminar results on a dataset that recently has been useful to find confirmation of AH model effects.KeywordsFunctional ConnectivityMultiAgent SystemSuperior Temporal GyrusAuditory HallucinationDynamic Causal ModelingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.