Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortex
- University of Oslo, Norway
- Allen Institute for Brain Science, United States
- Allen Institute, United States
- Norwegian University of Life Sciences, Norway
Abstract
Local field potential (LFP) recordings reflect the dynamics of the current source density (CSD) in brain tissue. The synaptic, cellular and circuit contributions to current sinks and sources are ill-understood. We investigated these in mouse primary visual cortex using public Neuropixels recordings and a detailed circuit model based on simulating the Hodgkin-Huxley dynamics of >50,000 neurons belonging to 17 cell types. The model simultaneously captured spiking and CSD responses and demonstrated a two-way dissociation: Firing rates are altered with minor effects on the CSD pattern by adjusting synaptic weights, and CSD is altered with minor effects on firing rates by adjusting synaptic placement on the dendrites. We describe how thalamocortical inputs and recurrent connections sculpt specific sinks and sources early in the visual response, whereas cortical feedback crucially alters them in later stages. These results establish quantitative links between macroscopic brain measurements (LFP/CSD) and microscopic biophysics-based understanding of neuron dynamics and show that CSD analysis provides powerful constraints for modeling beyond those from considering spikes.
Data availability
The files necessary to run simulations of the different model versions presented in the paper as well as data resulting from simulations of those model versions are publicly available in Dryad: https://doi.org/10.5061/dryad.k3j9kd5b8The experimental data set utilized is publicly available at: https://portal.brain-map.org/explore/circuits/visual-coding-neuropixelsThe code generated for data analysis and producing the figures in this manuscript is publicly available at: https://github.com/atleer/CINPLA_Allen_V1_analysis.git.
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Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortexDryad Digital Repository, doi:10.5061/dryad.k3j9kd5b8.
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20191003_AIBS_mouse_ecephys_brain_observatory_1_1DANDI Archive 000021.
Article and author information
Author details
Alexander J Stasik
Funding
Simula School of Research
- Atle E Rimehaug
European Union Horizon 2020 Research and Innovation program (785907)
- Espen Hagen
European Union Horizon 2020 Research and Innovation program (945539)
- Espen Hagen
Research Council of Norway (COBRA - project number 250128)
- Alexander J Stasik
IKTPLUSS-IKT and Digital Innovation (300504)
- Alexander J Stasik
National Institute of Neurological Disorders and Stroke (R01NS122742)
- Yazan N Billeh
- Josh H Siegle
- Kael Dai
- Shawn R Olsen
- Christof Koch
- Anton Arkhipov
National Institute of Biomedical Imaging and Bioengineering (R01EB029813)
- Yazan N Billeh
- Josh H Siegle
- Kael Dai
- Shawn R Olsen
- Christof Koch
- Anton Arkhipov
Allen Institute
- Yazan N Billeh
- Josh H Siegle
- Kael Dai
- Shawn R Olsen
- Christof Koch
- Anton Arkhipov
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Tirin Moore, Howard Hughes Medical Institute, Stanford University, United States
Version history
- Preprint posted: February 25, 2022 (view preprint)
- Received: February 23, 2023
- Accepted: July 10, 2023
- Accepted Manuscript published: July 24, 2023 (version 1)
- Version of Record published: August 1, 2023 (version 2)
- Version of Record updated: August 11, 2023 (version 3)
Copyright
© 2023, Rimehaug et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Uncovering circuit mechanisms of current sinks and sources with biophysical simulations of primary visual cortex
eLife 12:e87169.
https://doi.org/10.7554/eLife.87169
Further reading
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- Computational and Systems Biology
- Medicine
Background:
Preterm birth is the leading cause of neonatal morbidity and mortality worldwide. Most cases of preterm birth occur spontaneously and result from preterm labor with intact (spontaneous preterm labor [sPTL]) or ruptured (preterm prelabor rupture of membranes [PPROM]) membranes. The prediction of spontaneous preterm birth (sPTB) remains underpowered due to its syndromic nature and the dearth of independent analyses of the vaginal host immune response. Thus, we conducted the largest longitudinal investigation targeting vaginal immune mediators, referred to herein as the immunoproteome, in a population at high risk for sPTB.
Methods:
Vaginal swabs were collected across gestation from pregnant women who ultimately underwent term birth, sPTL, or PPROM. Cytokines, chemokines, growth factors, and antimicrobial peptides in the samples were quantified via specific and sensitive immunoassays. Predictive models were constructed from immune mediator concentrations.
Results:
Throughout uncomplicated gestation, the vaginal immunoproteome harbors a cytokine network with a homeostatic profile. Yet, the vaginal immunoproteome is skewed toward a pro-inflammatory state in pregnant women who ultimately experience sPTL and PPROM. Such an inflammatory profile includes increased monocyte chemoattractants, cytokines indicative of macrophage and T-cell activation, and reduced antimicrobial proteins/peptides. The vaginal immunoproteome has improved predictive value over maternal characteristics alone for identifying women at risk for early (<34 weeks) sPTB.
Conclusions:
The vaginal immunoproteome undergoes homeostatic changes throughout gestation and deviations from this shift are associated with sPTB. Furthermore, the vaginal immunoproteome can be leveraged as a potential biomarker for early sPTB, a subset of sPTB associated with extremely adverse neonatal outcomes.
Funding:
This research was conducted by the Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services (NICHD/NIH/DHHS) under contract HHSN275201300006C. ALT, KRT, and NGL were supported by the Wayne State University Perinatal Initiative in Maternal, Perinatal and Child Health.
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- Computational and Systems Biology
- Genetics and Genomics
Runs of homozygosity (ROH) segments, contiguous homozygous regions in a genome were traditionally linked to families and inbred populations. However, a growing literature suggests that ROHs are ubiquitous in outbred populations. Still, most existing genetic studies of ROH in populations are limited to aggregated ROH content across the genome, which does not offer the resolution for mapping causal loci. This limitation is mainly due to a lack of methods for the efficient identification of shared ROH diplotypes. Here, we present a new method, ROH-DICE, to find large ROH diplotype clusters, sufficiently long ROHs shared by a sufficient number of individuals, in large cohorts. ROH-DICE identified over 1 million ROH diplotypes that span over 100 SNPs and are shared by more than 100 UK Biobank participants. Moreover, we found significant associations of clustered ROH diplotypes across the genome with various self-reported diseases, with the strongest associations found between the extended HLA region and autoimmune disorders. We found an association between a diplotype covering the HFE gene and hemochromatosis, even though the well-known causal SNP was not directly genotyped or imputed. Using a genome-wide scan, we identified a putative association between carriers of an ROH diplotype in chromosome 4 and an increase in mortality among COVID-19 patients (P-value=1.82×10-11). In summary, our ROH-DICE method, by calling out large ROH diplotypes in a large outbred population, enables further population genetics into the demographic history of large populations. More importantly, our method enables a new genome-wide mapping approach for finding disease-causing loci with multi-marker recessive effects at a population scale.
