University of Nevada, Las Vegas; Center for Academic Enrichment and Outreach
Las Vegas (Nev.)
The etiology of schizophrenia remains largely elusive, thus dampening the effectiveness of current treatment strategies. Abnormal neural migration and neurogenesis in the hippocampus have been suggested to be involved in schizophrenia (Jakob & Beckmann, 1994). A few approaches, including computational modeling, have investigated schizophrenia as a network disorder. Computational modeling uses mathematics to predict the behavior of biological systems based on the input of a set of parameters collected from laboratory experiments. In this study, we constructed a computational model to explore the ramifications of additional PV neurons migrating to an aberrant location in the hippocampus and interfering with a closed-loop circuit between a preexisting PV neuron and 10 pyramidal neurons. Evidence suggests that PV neurons provide GABAergic input and oscillating gamma rhythmicity (30-80 Hz) to pyramidal neurons in the CA1 region of the hippocampus (Tukker et al., 2007). We predict that asynchronous release of action potentials from a migratory PV neuron will decrease the level of excitation and reduce the gamma-band activity in our closed-loop computational circuit. If this computational model can make an accurate prediction, it may serve to be a reliable tool to probe the direction of future research in not only schizophrenia, but in a wide range of mental afflictions.
Mental illness; Schizophrenia; Schizophrenia--Treatment
Medicine and Health Sciences | Mental and Social Health | Psychiatric and Mental Health | Psychology
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Bedoy, E. H.,
A Computational Perspective of Schizophrenia.
Available at: https://digitalscholarship.unlv.edu/mcnair_posters/42