DOI: 10.5061/dryad.jh9w0vtnq
title: Ex vivo Mesoscale human temporal lobe dataset

description: The human hippocampus is essential to cognition and emotional processing.
 Its function is defined by its connectivity. Although some pathways have
 been well-established, our knowledge about anterior-posterior connectivity
 and the distribution of fibers from major fiber bundles remain limited.
 Mesoscale (250 mm isotropic acquisition, upsampled to 125 mm) resolution
 MR images of the human temporal lobe afforded a detailed visualization of
 fiber tracts, including those that related anterior-posterior
 substructures defined as subregions (head, body, tail) and subfields
 (cornu ammonis 1-3, dentate gyrus) of the hippocampus. Fifty pathways were
 dissected between the head and body, highlighting an intricate mesh of
 connectivity between these two subregions. Along the body subregion, 12
 lamellae were identified based on morphology and the presence of
 interlamellar fibers that appear to connect neighboring lamellae at the
 edge of the external limb of the granule cell layer (GCL). Translamellar
 fibers (i.e. longitudinal fibers crossing more than 2 lamellae) were also
 evident at the edge of the internal limb of the GCL. The dentate gyrus of
 the body was the main site of connectivity with the fimbria. Unique
 pathways were dissected within the fimbria that connected the body of the
 hippocampus with the amygdala and the temporal pole. A topographical
 segregation within the fimbria was determined by fibers’ hippocampal
 origin, illustrating the importance of mapping the spatial distribution of
 fibers. Elucidating the detailed structural connectivity of the
 hippocampus is crucial to develop better diagnostic markers of
 neurological and psychiatric conditions, as well as to devise novel
 surgical interventions.
description: <strong>Magnetic Resonance Imaging</strong>
 Samples were placed in an 9.4.7T/30 cm Bruker AV3 HD microimaging
 scanner equipped with a B-GA12S HP gradient set capable of 660 mT/m
 maximum gradient strength and a 72 mm quadrature birdcage resonator
 running Paravision 6.0.1 (Bruker Biospin, Billerica, MA) with a 72 mm
 inner diameter quadrature birdcage RF coil. Multi-shell diffusion MR
 images were acquired with a 3D diffusion-weighted multi-shot spin-echo EPI
 sequence with the following parameters: TR = 500 ms, TE = 26 ms, diffusion
 duration δ = 5 ms, diffusion spacing Δ = 13 ms, EPI segments = 30. A 1.2
 partial Fourier acceleration in PE1 was used with a zero-filling
 acceleration factor 1.2 in the read and PE2 dimensions for an isotropic
 resolution of 250 μm. A total of 94 images were collected with
 diffusion-weighted shells consisting of b = 1000, 2000, 4000, 6000
 s/mm<sup>2</sup> with 12, 18, 24, 36 directions, respectively
 (~68 hours total scanning time). Each shell was acquired separately and
 included 2 B0 images each (8 in total).  
 <strong>Diffusion MRI Processing</strong>
 Diffusion MR images were processed using DSI Studio (version June
 2024, available at http://www.dsistudio.labsolver.org) (Yeh et al., 2013)
 on an iMac (3.5 GHz Quad-core Intel Core i5, 4 GB of Radeon Pro 575
 Graphics card, 16 Gb of RAM at 2400 Mhz DDR4, 3 TB disc space) running the
 Sequoia MacOS (15.0). To process the diffusion images, the samples were
 masked using a signal threshold to remove background prior to processing.
 Multi-shell diffusion MRI scans were reconstructed using Generalized
 Q-sampling Imaging (GQI) with a diffusion sampling length ratio of 0.6, as
 well as a 2x upsampling to an effective isotropic image resolution of 125
 μm to improve tractographical seeding and the spatial location of fiber
 tracts. Image files for individual scalar indices were calculated, as well
 as diffusion encoded color (DEC) images and restricted diffusion images
 (RDI), which were helpful in the delineation of individual regions of
 interest (ROIs). Quality control (QC) considered tissue
 quality by assessing various measures across samples. All tissue samples
 were weighed on a laboratory balance (Navigator, Ohaus) prior to MR
 imaging. A ROI for the whole specimen was drawn on mean diffusion MR
 images in DSI studio to measure total sample volume. To calculate tissue
 density, the sample volume was divided by its mass. A consistent tissue
 density between samples ranging from 1.35 to 1.82
 g/mm<sup>3</sup> was observed. No effect of age or biological
 sex was evident, indicating equivalent tissue quality across samples.
 Neighboring DWI correlations (r) &gt;0.8 were found across all
 datasets, indicating very high-quality diffusion MR images suitable for
 tractography. Post-mortem time (PMT) is a crucial variable in post-mortem
 tissue studies. However, it did not appear to systematically affect the
 measurements of scalar indices within our cut-off time (48 hours) for
 sample collection.
description: # Ex Vivo Mesoscale Human Temporal Lobe Dataset
 [https://doi.org/10.5061/dryad.jh9w0vtnq](https://doi.org/10.5061/dryad.jh9w0vtnq) ## Description of the data and file structure Mesoscale diffusion MRI data was acquired at a 250 um isotropic resolution. Processing using DSI studio upsampled this 2x to 125 um resolution dataset to provide a more detailed anatomical context. The entire human temporal lobe is available for 16 subjects at various ages, as described in the article accompanying this data set. ### Files and variables A total of 16 individual .fib files contained processed diffusion MR images for tractography and diffusion measurements are contained within the *MRI_GQI__Files.zip* file. Details about each subject can be found in Table 1 of the accompanying publication. Each file belongs to 1 subject. Matching ROIs are contained in 5 separate zip files: *ROIs_fimbria.zip, ROIs_hippocampus.zip, ROIs_regional_subfields.zip (head, body, tail), ROIs_HC_subfields.zip (CA1, CA2, CA3, Dentate Gyrus)*. #### File: MRI\_GQI\_Files.zip **Description:** MRI diffusion images processed using the GQI model in DSI Studio. Processed files for 16 subjects are included in this dataset. ## Code/software Files can be opened with DSI Studio (freely available at [https://dsi-studio.labsolver.org](https://dsi-studio.labsolver.org))