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Resting MEGI Functional Connectivity in Schizophrenia predicts symptoms.
Resting MEGI Functional Connectivity in Schizophrenia predicts symptoms.

The goal here is to examine the spatiotemporal dynamics of brain networks involved in speech, language and memory processes. We specifically focus on overt speech production, its interaction with auditory feedback processing, and with language and memory processes. Several recent studies have shown that speaking causes "speaking-induced suppression" or SIS - a suppressed response to self-produced speech when compared to identical speech from an external source - in auditory cortex and associative regions. In our own recent work, we have shown that SIS is present in auditory cortex, and does not result from overall inhibition of auditory cortex during speaking. Rather, SIS results from a comparison between actual auditory input and an internal "speaking-induced prediction" (SIP) of that auditory input. What is the functional significance of SIS and SIP? Based on several lines of evidence, we have developed a conceptual working model for SIS and SIP. The principal goal of this research is to test predictions from this model. Our overall approach capitalizes on unique real-time speech feedback alteration methods developed by our research team, the excellent spatial resolution of functional magnetic resonance imaging (fMRI), the excellent temporal resolution of electromagnetic source imaging (ESI) and advanced analyses methods that we have developed for reconstructing spatiotemporal dynamics and connectivity of distributed cortical networks