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Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: Computational Modeling of Genetic Contributions to Excitability and Neural Coding in Layer V Pyramidal Cells: Applications to Schizophrenia Pathology
Author(s): Maki-Marttunen, Tuomo
Devor, Anna
Phillips, William A
Dale, Anders M
Andreassen, Ole A
Einevoll, Gaute T
Keywords: voltage-gated ion channel gene
schizophrenia genetics
cortical excitability
biophysical modeling
functional genetics
neuronal code
prepulse inhibition
spatiotemporal integration
Issue Date: 26-Sep-2019
Citation: Maki-Marttunen T, Devor A, Phillips WA, Dale AM, Andreassen OA & Einevoll GT (2019) Computational Modeling of Genetic Contributions to Excitability and Neural Coding in Layer V Pyramidal Cells: Applications to Schizophrenia Pathology. Frontiers in Computational Neuroscience, 13, Art. No.: 66.
Abstract: Pyramidal cells in layer V of the neocortex are one of the most widely studied neuron types in the mammalian brain. Due to their role as integrators of feedforward and cortical feedback inputs, they are well-positioned to contribute to the symptoms and pathology in mental disorders—such as schizophrenia—that are characterized by a mismatch between the internal perception and external inputs. In this modeling study, we analyze the input/output properties of layer V pyramidal cells and their sensitivity to modeled genetic variants in schizophrenia-associated genes. We show that the excitability of layer V pyramidal cells and the way they integrate inputs in space and time are altered by many types of variants in ion-channel and Ca2+ transporter-encoding genes that have been identified as risk genes by recent genome-wide association studies. We also show that the variability in the output patterns of spiking and Ca2+ transients in layer V pyramidal cells is altered by these model variants. Importantly, we show that many of the predicted effects are robust to noise and qualitatively similar across different computational models of layer V pyramidal cells. Our modeling framework reveals several aspects of single-neuron excitability that can be linked to known schizophrenia-related phenotypes and existing hypotheses on disease mechanisms. In particular, our models predict that single-cell steady-state firing rate is positively correlated with the coding capacity of the neuron and negatively correlated with the amplitude of a prepulse-mediated adaptation and sensitivity to coincidence of stimuli in the apical dendrite and the perisomatic region of a layer V pyramidal cell. These results help to uncover the voltage-gated ion-channel and Ca2+ transporter-associated genetic underpinnings of schizophrenia phenotypes and biomarkers.
DOI Link: 10.3389/fncom.2019.00066
Rights: © 2019 Mäki-Marttunen, Devor, Phillips, Dale, Andreassen and Einevoll. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY - The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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