Analysis and modeling of CA1 pyramidal neurons for the article: Deficits in neuronal architecture and their role in reduced neuronal network activity in a mouse model of overexpression of Dyrk1A
- T2N modeling code: T2N single neuron multi-comparmental simulation code.
- Shiny app code:
Shinyapp code. - Test data: Reconstruction set for replicating the results of the manuscript.
The Shiny app requires only a standard computer with enough RAM to support the operations defined by a user. The T2N simulation scripts can also be run in a standard computer. For minimal performance, this will be a computer with about 500 MB of RAM. For optimal performance, we recommend a computer with the following specs:
RAM: 1.5+ GB
CPU: single core, 1.6+ GHz
The runtimes below are generated using a computer with the recommended specs (16 GB RAM, 8 [email protected] GHz) and internet of speed 25 Mbps.
The package development version is tested on Linux, MacOS and Windows operating systems. The developmental version of the package has been tested on the following systems:
Linux: Centos 8
Mac OSX: Monterey 12.3.1
Windows: 10 and 11
Both the T2N modeling code and the Shiny app should be compatible with Windows, Mac, and Linux operating systems. Some attention may be needed for path specifications in scripts.
Before setting up the Shiny app, users should have R version 4.1.0 or higher, and several packages set up from CRAN.
the latest version of R can be installed by adding the EPEL repository to yum:
sudo yum install https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm
sudo dnf config-manager --set-enabled powertools
sudo bash -c "$(curl -L https://rstd.io/r-install)"
vim ~/.bashrc
export PATH=$PATH:/opt/R/4.1.0/bin/
source .bashrc
Download and install the corresponding binary .pkg file from:
https://cran.r-project.org/bin/macosx/
Download and install the corresponding binary .exe file from:
https://cran.r-project.org/bin/windows/base/
In all cases it should install in about 20 seconds.
Users should install NEURON and T2N following the documentation available at: https://github.com/MarcelBeining/T2N
Users should install the following packages prior to running the Shiny app, from an R terminal:
options("repos" = c("CRAN" = "https://cran.rstudio.com",
"rforge" = "http://R-Forge.R-project.org"))
install.packages(c('shiny', 'plotly', 'ggpubr', 'afex', 'dplyr', 'reshape2', 'xtable', 'emmeans', 'ggsignif',
'plotrix', 'scales', 'rstatix', 'Matrix'))
which will install in about 5 minutes on a machine with the recommended specs.
The Shiny app functions with all packages in the following versions:
shiny_1.6.0
plotly_4.9.4.1
ggpubr_0.4.0
afex_0.28-1
dplyr_1.0.7
reshape2_1.4.4
xtable_1.8-4
emmeans_1.6.1
ggsignif_0.6.2
plotrix_3.8-2
scales_1.2.1
rstatix_0.7.0
Matrix_1.3-3
If you are having an issue that you believe to be tied to software versioning issues, please drop us an Issue.
First download the repository code and data locally, by clicking "Code Download ZIP" or typing in a command line:
git clone https://github.com/lmanubens/EE_CA1.git
From an R session in the EE_CA1/shiny_app folder, type:
library(shiny)
runApp()
To obtain connectivity repertoires, run the script 'connectivity_repertoires.m' from the folder EE_CA1/model, the results are saved in a file called "wiring_metrics.csv". The script takes about 4 seconds.
To obtain input-output frequency curves, run the command "export MATLAB_SHELL=/bin/bash", or equivalent, from a terminal. Then run Matlab from terminal and run the script 'freqinout_stimregion_BC.m' from the folder EE_CA1/model. Different sections can be run separately to account for synaptic densities or only dendritic morphological features, and for input to Stratum Radiatum alone or both Stratum Radiatum and Lacunosum. The results are saved in a file called "freqinout_stimregion_BC.csv".
Running each set of simulations takes about 20 minutes using 8 parallel workers.
To obtain power spectrums from the set of reconstructed neurons with inhibitory feedback, run the command "export MATLAB_SHELL=/bin/bash", or equivalent, from a terminal. Then run Matlab from terminal and run the script 'net_morph_and_inh.m' or 'net_only_inhibition' from the folder EE_CA1/model. In this case both Stratum Radiatum and Lacunosum are stimulated. The results are saved in a file called "pspectrum_x.csv".
Running each set of simulations takes about 3 minutes using a single core.
For interactive usage of the web app please check:
https://linusmg.shinyapps.io/EE_TgDyrk1A/
The tabs allow users to choose specific sets of analyses of interest. The checklists in the top of the web app allow the users to choose specific metrics and data subsets of interest respectively. Each plot should be generated in a few seconds.
If you use this code or data we kindly ask that you please cite Manubens-Gil et al, 2023.