# Systems-Level Dysconnectivity in First Episode Psychosis > **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2022 · $737,239 ## Abstract Schizophrenia (Sz) is a debilitating major mental illness with life-long disability that disproportionately burdens the healthcare system and society. Despite decades of research, the underlying mechanisms of pathophysiology in Sz are unknown. Attempts for determining brain abnormalities in Sz have gone beyond searching for one to a few lesion locations to focusing on functional (dys)connectivity between systems-level brain circuits and the associated neural events that underlie the failure in functional integration of information across distributed circuits. Effective connectivity refers to the influence of activity in one area on activity in another at a later time, allowing inferences about directionality. Our overarching hypothesis is that long-range cortical effective connectivity is a fundamental biological system abnormality in schizophrenia, particularly between prefrontal cortex and sensory areas. This proposal comprises a systems-level examination of structure, function, and connectivity in a distributed system known to be impaired in Sz, the temporal lobe auditory cortices and the inferior frontal gyrus auditory-executive cortex involved in the generation of mismatch negativity (MMN), an index of automatic auditory change detection. We will examine effective connectivity between nodes of this distributed system, and use computational modeling to translate neurophysiological information from EEG & MEG to synaptic conductances, indicating possible molecular mechanisms of the systems-level deficits. Central to our approach is testing of individuals at their first clinical contact for schizophrenia-spectrum psychosis (first episode schizophrenia-spectrum, FESz), where the progressive primary and secondary disease effects on brain structure and function are minimized. Pathophysiology proximal to disease onset very likely reflects processes critical to disease etiology. In FESz, we test 3 auditory tests of increasing pattern complexity to differentially tax the auditory change detection system, measure brain activity with combined high-temporal resolution EEG & MEG measures of neurophysiology, and construct high-spatial resolution measures of brain structure to project sensor activity to cortical sources, compared and contrasted between FESz and well individuals (AIM 1). Using advanced measures of spectral effective connectivity (phase transfer entropy) on the source-resolved activity, we will determine dysconnectivity between the frontal and temporal cortical sources in FESz on these tasks (AIM 2). Next, using computational modeling of a laminar cortical circuit to replace single equivalent dipoles at each source, we will determine synaptic conductance deficits in AMPA, GABA, and NMDA activity that may underlie the dysconnectivity in FESz (AIM 3). Finally, to assess changes in brain structure, function, and connectivity after the onset of psychosis, we will test participants longitudinally 6 months later to track progressive impairments (AI... ## Key facts - **NIH application ID:** 10515542 - **Project number:** 1R01MH126951-01A1 - **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH - **Principal Investigator:** Dean F Salisbury - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $737,239 - **Award type:** 1 - **Project period:** 2022-07-01 → 2027-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10515542 ## Citation > US National Institutes of Health, RePORTER application 10515542, Systems-Level Dysconnectivity in First Episode Psychosis (1R01MH126951-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10515542. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*