DOI: 10.5061/dryad.83bk3j9z2
title: Data from: Scn2a insufficiency alters spontaneous neuronal Ca2+ activity in somatosensory cortex during wakefulness

description: SCN2A protein-truncating variants (PTV) can result in neurological
 disorders such as autism spectrum disorder and intellectual disability,
 but they are less likely to cause epilepsy in comparison to missense
 variants. While in vitro studies showed PTV reduce action potential
 firing, consequences at in vivo network level remain elusive. Here, we
 generated a mouse model of Scn2a insufficiency using antisense
 oligonucleotides (Scn2a ASO mice), which recapitulated key clinical
 feature of SCN2A PTV disorders. Simultaneous two-photon Ca2+ imaging and
 electrocorticography (ECoG) in awake mice showed that spontaneous Ca2+
 transients in somatosensory cortical neurons, as well as their pairwise
 co-activities were generally decreased in Scn2a ASO mice during
 spontaneous awake state and induced seizure state. The reduction of
 neuronal activities and paired co-activity are mechanisms associated with
 motor, social and cognitive deficits observed in our mouse model of severe
 Scn2a insufficiency, indicating these are likely mechanisms driving SCN2A
 PTV pathology.
description: **Scn2a insufficiency alters spontaneous neuronal Ca2+ activity in
 somatosensory cortex during wakefulness**
 https://doi.org/10.5061/dryad.83bk3j9z2 Data used to determine the
 molecular expression, behavioral phenotype, ECoG and in vivo two-photon
 calcium imaging activities in mouse model of Scn2a insufficiency and in
 control mice. Folder also includes the customized MATLAB script used for
 in vivo imaging analysis. **File structure and data description**
 qPCR.xlsx -- qPCR data on Scn2a mRNA expression (Ct values and % change
 compared to control) WesterBlot.zip -- Western Blot data on Scn2a protein
 expression 1. Gapdh.jpg -- Image of the reference protein bands, left 3
 lanes are control and right 3 lanes are Scn2a ASO treated 2. Scn2a.jpg --
 Image of the Scn2a protein bands, left 3 lanes are control and right 3
 lanes are Scn2a ASO treated 3. WesternBlotAnalysis.xlsx -- Band
 intensities calculations (% change compared to control). Colored cells are
 the finalized values reported in Figure 1B of manuscript Behavioral.xlsx
 -- data showing %duration in 3-chamber, elevated plus maze and open field.
 Also contains nesting score. CaImaging.xlsx --calcium transients events
 data: mean amplitude (ampl, dF/F), frequency (freq, events/sec),
 normalized integral (normint) and pairwise correlation (averaged
 similarity index). Genotype where 0 = control, 1 = ASO treated mice. Drug
 where 0 = baseline, 1 = after PTZ. File also shows statistical summary
 from linear mixed effect model of each parameter. ECoG.xlsx -- Spikes and
 power spectral density (PSD, V^2/Hz) from ECoG recordings.
 **Sharing/Access information** For further information about the data
 uploaded, please contact Prof. Bernd Kuhn (bkuhn@oist.jp)
 **Code/Software** Analysis\_Scripts.zip -- Scripts to analyze in vivo
 calcium imaging data. Run script on MATLAB 2018 or newer versions and add
 all subfolders and functions to path.MATLAB Toolbox required are listed
 below. * Statistics and Machine Learning * Signal Processing * Curve
 Fitting * Image Processing * Bioinformatics 1. The script
 "Analyse\_Calcium\_ASO\_01" goes from raw extracted calcium
 traces found in defined data folder which was extracted from the modified
 version of EZcalcium Ver\_0.0.1. * Different code segments are arranged in
 the following manner : * Arrange the data into a big data container * Save
 the data container file into your designated destination * Generate Ca
 Freq, amplitude, pairwise correlation using main function
 "Ca\_trace\_frequency\_amplitude" 2. Function
 "Ca\_trace\_frequency\_amplitude" use a number of subfunctions
 for pairwise correlation * shuffle\_data\_create\_ci\_neuron: will create
 a threshold value for each pair of neurons based on shuffled data *
 cosine\_similarity\_matrix: will create a pairwise cosine similarity based
 on the data 3. For the linear mixed model analysis we created an Excel
 sheet "Reformated data \_freq" then we ran the following Matlab
 scripts * importreformatted\_data: to import the data from the Excel sheet
 ( you can choose one of the first 4 sheets in the Excel file) *
 LMEmodel\_givendata: use the data created from 3.1 to build the LME model
 and display statistics. * icc\_calculate: use the data created from 3.1 to
 infer interclass correlation.