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

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)

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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.

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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