Computational Modeling of Genetic Contributions to Excitability and Neural Coding in Layer V Pyramidal Cells: Applications to Schizophrenia Pathology

Frontiers in Computational Neuroscience

Gaute T. Einevoll²  Anders M. Dale³  Anna Devor⁵  Ole A. Andreassen⁶  William A. Phillips⁷  Tuomo Mäki-Marttunen⁸ 

[1] Department of Neurosciences, University of California San Diego, La Jolla, CA, United States;Department of Physics, University of Oslo, Oslo, Norway;Department of Radiology, University of California San Diego, La Jolla, CA, United States;Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway;Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, United States;NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway;Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom;Simula Research Laboratory, Oslo, Norway;

关键词: voltage-gated ion channel gene;    schizophrenia genetics;    cortical excitability;    biophysical modeling;    functional genetics;    neuronal code;   

DOI  :  10.3389/fncom.2019.00066

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown