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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Dataset In-vivo estimation of axonal morphology from MRI and EEG data

Authors: Oliveira, Rita; De Lucia, Marzia; Lutti, Antoine;

Dataset In-vivo estimation of axonal morphology from MRI and EEG data

Abstract

This dataset includes the data underlying the conclusions made in the scientific article: "In-vivo estimation of axonal morphology from MRI and EEG data" Rita Oliveira, Andria Pelentritou, Giulia Di Domenicantonio, Marzia De Lucia, Antoine Lutti https://www.frontiersin.org/articles/10.3389/fnins.2022.874023 The main objective is to use data collected in-vivo in humans to estimate microscopic morphologic features of the white matter tracts. The in-vivo data estimated along a white matter tract of interest includes: • the MRI g-ratio sampled along the visual transcallosal white matter tract • a measure of conduction velocity estimated from an EEG measure of interhemispheric transfer time (IHTT) The microscopic morphologic features of white matter we estimate are: • the axonal radius distribution, P(r) • the g-ratio dependence on the radius, g(r) ------------------------------------------------------------------------- CONTENT: This package includes data for all the 14 subjects used in the corresponding scientific article: • G-ratio values sampled along the transcallosal visual tract double vector (# MRI_gratio samples x 1): G_ratio_samples.mat • Length of the transcallosal visual tract double: Tract_length.mat • Current source densities (pA.m) of each trial, brain vertice and time point for the left brain visual cortex double 3 matrix (#trials x #vertices x #timepoints): Source_reconstruction_left_brain_V1V2.mat • Current source densities (pA.m) of each trial, brain vertice and time point for the right brain visual cortex double 3 matrix (#trials x #vertices x #timepoints): Source_reconstruction_right_brain_V1V2.mat • Vector of the time sample of the EEG epochs double vector (1 x #time points): time_vec.mat The codes used in the analysis of this data are available on our online repository: https://github.com/LREN-physics/AxonalMorphology. ------------------------------------------------------------------------- AUTHORS: Author: Rita Oliveira PIs: Marzia De Lucia, Antoine Lutti Laboratory for Neuroimaging Research Lausanne University Hospital & University of Lausanne, Lausanne, Switzerland Copyright (C) 2022 Laboratory for Neuroimaging Research

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Keywords

axon morphology, EEG, IHTT, in-vivo-histology, MRI

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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