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Multiscale Computer Modeling to Investigate Schizophrenia Risk Genes/Proteins.
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Lytton, William
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Spring 2020
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2020-04-22
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Doctoral Dissertation
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Abstract
Schizophrenia is a devastating and complex illness, with abnormalities across molecular, synaptic, cellular, and microcircuit levels. Because of such complexity, it is difficult to develop medications that can target cognitive impairment, one of the main causes of disability in schizophrenia. In this thesis, I have used a multiscale modeling (MSM) approach to investigate
how schizophrenia-risk genes/proteins would change the dynamics of two phenomena involved in
information processing, and thus cognition, in the brain.
In the first part of this work, I investigated how the interaction between various proteins affect intradendritic Ca2+ wave dynamics. These proteins included smooth endoplasmic reticulum Ca2+ ATPase (SERCA) and voltage gated calcium channels, both implicated in schizophrenia pathology.
In the second part of this thesis, I used a computer model of the CA3 region of the hippocampus to investigate the mechanistic link from genes/proteins to microcircuit dynamics (gamma oscillations and information flow), and how multi-target pharmacotherapy can be used to therapeutically alter microcircuit dynamics. This work connects changes at the molecular level, through changes in neuronal activity, to alterations in information transfer across the hippocampus.
This thesis mechanistically links molecular pathological changes, which can be modified through medications, to higher levels dynamics implicated in information processing. Such a mechanistic link has the promise to identify therapeutic targets to improve information processing in schizophrenia, and thus alleviate cognitive symptoms.
Citation
Sherif, Mohamed (2020). Multiscale Computer Modeling to Investigate Schizophrenia Risk Genes/Proteins. [Doctoral dissertation, SUNY Downstate Health Sciences University]. SUNY Open Access Repository. https://soar.suny.edu/handle/20.500.12648/15838