Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/30419
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMaki-Marttunen, Tuomoen_UK
dc.contributor.authorDevor, Annaen_UK
dc.contributor.authorPhillips, William Aen_UK
dc.contributor.authorDale, Anders Men_UK
dc.contributor.authorAndreassen, Ole Aen_UK
dc.contributor.authorEinevoll, Gaute Ten_UK
dc.date.accessioned2019-11-06T01:00:15Z-
dc.date.available2019-11-06T01:00:15Z-
dc.date.issued2019-09-26en_UK
dc.identifier.other66en_UK
dc.identifier.urihttp://hdl.handle.net/1893/30419-
dc.description.abstractPyramidal 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.en_UK
dc.language.isoenen_UK
dc.publisherFrontiers Mediaen_UK
dc.relationMaki-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. https://doi.org/10.3389/fncom.2019.00066en_UK
dc.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 - https://creativecommons.org/licenses/by/4.0/). 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.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectvoltage-gated ion channel geneen_UK
dc.subjectschizophrenia geneticsen_UK
dc.subjectcortical excitabilityen_UK
dc.subjectbiophysical modelingen_UK
dc.subjectfunctional geneticsen_UK
dc.subjectneuronal codeen_UK
dc.subjectprepulse inhibitionen_UK
dc.subjectspatiotemporal integrationen_UK
dc.titleComputational Modeling of Genetic Contributions to Excitability and Neural Coding in Layer V Pyramidal Cells: Applications to Schizophrenia Pathologyen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.3389/fncom.2019.00066en_UK
dc.identifier.pmid31616272en_UK
dc.citation.jtitleFrontiers in Computational Neuroscienceen_UK
dc.citation.issn1662-5188en_UK
dc.citation.volume13en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderEuropean Commission (Horizon 2020)en_UK
dc.citation.date26/09/2019en_UK
dc.contributor.affiliationSimula Research Laboratoryen_UK
dc.contributor.affiliationUniversity of California, San Diegoen_UK
dc.contributor.affiliationPsychologyen_UK
dc.contributor.affiliationUniversity of California, San Diegoen_UK
dc.contributor.affiliationUniversity of Osloen_UK
dc.contributor.affiliationNorwegian University of Life Sciencesen_UK
dc.identifier.scopusid2-s2.0-85073688591en_UK
dc.identifier.wtid1470641en_UK
dc.contributor.orcid0000-0001-6036-2255en_UK
dc.date.accepted2019-09-09en_UK
dc.description.refREF Compliant by Deposit in Stirling's Repositoryen_UK
dc.date.filedepositdate2019-11-05en_UK
Appears in Collections:Psychology Journal Articles

Files in This Item:
File Description SizeFormat 
fncom-13-00066.pdfFulltext - Published Version2.46 MBAdobe PDFView/Open


This item is protected by original copyright



A file in this item is licensed under a Creative Commons License Creative Commons

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.