DOI: 10.5061/dryad.8pk0p2nzt
title: Data from: From circuits to lifespan: Translating mouse and human timelines with neuroimaging based tractography

description: This repository contains data and scripts to translate ages across some
 species as well as neuroimaging scans. The dataset also contains diffusion
 MR tractography of post-mortem mouse brains, which includes tractography
 and diffusion metrics. This work builds on our Translating Time resource,
 which is a tool that equates corresponding ages during development. We
 collected 1,125 observations from age-related changes in body, bone,
 dental, and brain processes to equate corresponding ages across humans,
 mice, and rats. We also acquired high-resolution diffusion MR scans of
 mouse brains (n=16) of either sex at sdifferent postnatal ages (postnatal
 day 3, 4, 12, 21, 60) to track brain circuit maturation (e.g., olfactory
 association, transcallosal pathways).
description: We used multiple
 programs to extract data out of the attached data. We used DSI Studio
 software (https://dsi-studio.labsolver.org/) to quantify several
 diffusivity metrics (e.g., fractional anisotropy).  We also studied
 diffusion MR tractography. These tractography files can be opened with
 Trackvis, which is a free software program to open and analyze diffusion
 MR data. Go to the file tab, and click on "open track" to open
 track files.  Click on load image to load the niftii files.  
 We also collected time points to generate age alignments across
 humans and rodents. The scripts and data for these age alignments can be
 opened with the programming language R. Please see the readme file for
 more details and Cottam et al., 2025 for more details. 
 
 <strong>Reference:</strong> 
 
 Cottam NC, Ofori K, Stoll KT, Bryant M,
 Rogge JR, Hekmatyar K, Sun J, Charvet CJ. 2025. From circuits to lifespan:
 translating mouse and human timelines with neuroimaging based
 tractography. J Neurosci. In Press.  doi: 10.1523/JNEUROSCI.1429-24.2025.
 Epub ahead of print. PMID: 39870528.
description: # Data from: From circuits to lifespan: Translating mouse and human
 timelines with neuroimaging based tractography
 [https://doi.org/10.5061/dryad.8pk0p2nzt](https://doi.org/10.5061/dryad.8pk0p2nzt) ## Description of the data and file structure **Tractography:** These files can be opened with trackvis ([https://trackvis.org](https://trackvis.org)). The files in this dataset are compressed (i.e., zipped).  The tractography files includes mouse brains at different ages. The file includes information about age and ID. P stands for postnatal day followed by the individual's ID number. Each zipped file contains a .trk file and two nifti files. The file ending with .trk is a tractography file is reconstructed with high angular resolution difffusion (HARDI). Both of these files can be opened with the software program Trackvis, which is a free software program to open and analyze diffusion MR data. Go to the file tab, and click on "open track" to open track files.  Click on load image to load the niftii files.  The .trk files encode the tractographies of mouse brains and the nifti files encode brain structure information Tractography data from mouse brains at postnatal day 12: P12_S23.zip, P12_S22.zip, P12_S17.zip, P12_S16.zip Tractography data scans from mouse brains at postnatal day 4: P4_S12.zip, P4_S11.zip Tractography data scans from mouse brains at postnatal day 3: P3_S6.zip, P3_S5.zip **Diffusion MR metrics**: We include diffusion MR metrics from post-mortem mouse brains, which are generated with DSI studio. Some of these are compressed (.gz files). More information about DSI studio is available here: [https://dsi-studio.labsolver.org/doc/gui_t2.html](https://dsi-studio.labsolver.org/doc/gui_t2.html) Diffusion MR scans from mouse brains at postnatal day 3: P3_S5_dm.zip, P3_S4_dm.zip Diffusion MR scans from mouse brains at postnatal day 4: P4_S11_dm.zip, P4_S12_dm.zip Diffusion MR scans from mouse brains at postnatal day 12: P12_S23_dm.zip, P12_S22_dm.zip, P12_S17_dm.zip, P12_S16_dm.zip Diffusion MR scans from mouse brains at postnatal day 21: P21_C4_dm.zip, P21_C3_dm.zip, P21_C1_dm.zip, P21_C6_dm.zip Diffusion MR scans from mouse brains at postnatal day 60: P60_Em10_dm.zip, P60_Em9_dm.zip, P60_Em8_dm.zip, P60_Em7_dm.zip The .src file is used to generate the .fib file. The source file stores the diffusion weighted images and b-table that can be used to do reconstruction. The .fib file stores the vector field (fiber orientations) and anisotropy information (the magnitude) that can be used by DSI Studio to conduct fiber tracking. These also contain values used to calculate diffusivity metrics.  The .nii file  is a 3D stack of images that stores binary information. The files in this folder are the regions of interest  (ROI) used in this study. These ROIs span the cortical white matter. These nifti files need to be overlaid on the fib file to quantify diffusion metrics with DSI studio.    **Age alignments:** include data and scripts used to generate cross-species age alignments. Table_1.xlsx is the dataset that contains time points in humans, mice, and rats. These data are expressed in days post-conception and are used to equate corresponding ages across these species. Events are time points. These time points are classified as belonging to life history,  locomotion, brain, and bone. A value o1 means they belong to that classification whereas a value of 0 means that the time point does not belong to that category. Each time point is associated with a reference, which is where the data are from. Translating_time_Pub_ready_2_4_25.R: The R script uses data in Table_1.xlsx to equate ages across species. The script explains the process of generating age alignments from these data.  **Transcriptional analysis** include the dataset (called Gene_data.txt) and an R script (ending with file extension.R). The data and script are used to extract time points used to generate cross-species age alignments Gene_data_GSE47966.txt: Dataset that contains normalized gene expression from two humans and mice.  plateaus_gene_expression1.R: This script uses the dataset (Gene_data_GSE47966.txt) to translate ages across species ### Files and variables #### File: Translating\_time\_Pub\_ready\_2\_4\_25.R **Description:** The R script uses Table_1.xlsx to equate ages across humans, mice, and rats. The script explains the process of generating age alignments from these data.  #### File: Table\_1.xlsx **Description:** Table1.xlsx is the dataset that contains time points in humans, mice, and rats. These data are expressed in days post-conception and are used to equate corresponding ages across these species. Events are time points. These time points are classified as belonging to Life history,  Locomotion, Brain, and Bone. A value o1 means they belong to that classification whereas a value of 0 means that the time point does not belong to that category. Each time point is associated with a reference, which is where the data are from. Missing data code: NA #### File: plateaus\_gene\_expression1.R **Description:** This script uses the data to translate ages across species. This script provides additional information about Gene_data_GSE47966.txt #### File: Gene\_data\_GSE47966.txt **Description:** Dataset that contains normalized gene expression across multiple individual mice and humans.  ##### Variables * num: number * gene_id: Gene identifier. * FPKM.x.x: normalized gene expression of a given individual * FPKM.y.x: normalized gene expression of a given individual * FPKM.x.1.x: normalized gene expression of a given individual * FPKM.y.1.x: normalized gene expression of a given individual * FPKM.x.2.x: normalized gene expression of a given individual * FPKM.y.2.x: normalized gene expression of a given individual * FPKM.x.3: normalized gene expression of a given individual * FPKM.y.3: normalized gene expression of a given individual * FPKM.x.4: normalized gene expression of a given individual * FPKM.y.4: normalized gene expression of a given individual * FPKM.x.5: normalized gene expression of a given individual * FPKM.y.5: normalized gene expression of a given individual * FPKM.x.6: normalized gene expression of a given individual * FPKM.y.6: normalized gene expression of a given individual * FPKM.x.7: normalized gene expression of a given individual * FPKM.y.7: normalized gene expression of a given individual * FPKM.x: normalized gene expression of a given individual * mean.x: mean normalized gene expression * FPKM.x.y: normalized gene expression of a given individual * FPKM.y.y: normalized gene expression of a given individual * FPKM.x.1.y: normalized gene expression of a given individual * FPKM.y.1.y: normalized gene expression of a given individual * FPKM.x.2.y: normalized gene expression of a given individual * FPKM.y.2.y: normalized gene expression of a given individual * FPKM.y: normalized gene expression of a given individual * mean.y: mean normalized gene expression