{ "cells": [ { "cell_type": "markdown", "id": "54e73c60", "metadata": {}, "source": [ "# Functional connectivity with [`nilearn`](http://nilearn.github.io)" ] }, { "cell_type": "code", "execution_count": 1, "id": "ce1cef2f", "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "import warnings\n", "warnings.filterwarnings(\"ignore\")" ] }, { "cell_type": "markdown", "id": "69e37943", "metadata": {}, "source": [ "In this tutorial, we'll see how the Python library `nilearn` allows us to easily perform machine learning analyses with neuroimaging data,\n", "specifically functional magnetic resonance imaging (fMRI).\n", "\n", "You may notice that the name `nilearn` is reminiscent of [`scikit-learn`](https://scikit-learn.org),\n", "a popular Python library for machine learning.\n", "This is no accident!\n", "Nilearn and scikit-learn were created by the same team,\n", "and nilearn is designed to bring machine **LEARN**ing to the NeuroImaging (**NI**) domain.\n", "\n", "When performing a machine learning analysis, our data often look something like this:" ] }, { "cell_type": "code", "execution_count": 2, "id": "046ef3cd", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | site | \n", "subject | \n", "age | \n", "age_resid | \n", "sex | \n", "group | \n", "fsArea_L_V1_ROI | \n", "fsArea_L_MST_ROI | \n", "fsArea_L_V6_ROI | \n", "fsArea_L_V2_ROI | \n", "... | \n", "fsCT_R_p47r_ROI | \n", "fsCT_R_TGv_ROI | \n", "fsCT_R_MBelt_ROI | \n", "fsCT_R_LBelt_ROI | \n", "fsCT_R_A4_ROI | \n", "fsCT_R_STSva_ROI | \n", "fsCT_R_TE1m_ROI | \n", "fsCT_R_PI_ROI | \n", "fsCT_R_a32pr_ROI | \n", "fsCT_R_p24_ROI | \n", "
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0 | \n", "ABIDEII-KKI_1 | \n", "29293 | \n", "8.893151 | \n", "13.642852 | \n", "2.0 | \n", "1.0 | \n", "2750.0 | \n", "306.0 | \n", "354.0 | \n", "2123.0 | \n", "... | \n", "3.362 | \n", "2.827 | \n", "2.777 | \n", "2.526 | \n", "3.202 | \n", "3.024 | \n", "3.354 | \n", "2.629 | \n", "2.699 | \n", "3.179 | \n", "
1 | \n", "ABIDEII-OHSU_1 | \n", "28997 | \n", "12.000000 | \n", "16.081732 | \n", "2.0 | \n", "1.0 | \n", "2836.0 | \n", "186.0 | \n", "354.0 | \n", "2261.0 | \n", "... | \n", "2.809 | \n", "3.539 | \n", "2.944 | \n", "2.769 | \n", "3.530 | \n", "3.079 | \n", "3.282 | \n", "2.670 | \n", "2.746 | \n", "3.324 | \n", "
2 | \n", "ABIDEII-GU_1 | \n", "28845 | \n", "8.390000 | \n", "12.866264 | \n", "1.0 | \n", "2.0 | \n", "3394.0 | \n", "223.0 | \n", "373.0 | \n", "2827.0 | \n", "... | \n", "2.435 | \n", "3.321 | \n", "2.799 | \n", "2.388 | \n", "3.148 | \n", "3.125 | \n", "3.116 | \n", "2.891 | \n", "2.940 | \n", "3.232 | \n", "
3 | \n", "ABIDEII-NYU_1 | \n", "29210 | \n", "8.300000 | \n", "13.698139 | \n", "1.0 | \n", "1.0 | \n", "3382.0 | \n", "266.0 | \n", "422.0 | \n", "2686.0 | \n", "... | \n", "3.349 | \n", "3.344 | \n", "2.694 | \n", "3.030 | \n", "3.258 | \n", "2.774 | \n", "3.383 | \n", "2.696 | \n", "3.014 | \n", "3.264 | \n", "
4 | \n", "ABIDEII-EMC_1 | \n", "29894 | \n", "7.772758 | \n", "14.772459 | \n", "2.0 | \n", "2.0 | \n", "3080.0 | \n", "161.0 | \n", "346.0 | \n", "2105.0 | \n", "... | \n", "2.428 | \n", "2.940 | \n", "2.809 | \n", "2.607 | \n", "3.430 | \n", "2.752 | \n", "2.645 | \n", "3.111 | \n", "3.219 | \n", "4.128 | \n", "
5 rows × 1446 columns
\n", "\n", " | csf | \n", "white_matter | \n", "global_signal | \n", "std_dvars | \n", "dvars | \n", "framewise_displacement | \n", "t_comp_cor_00 | \n", "t_comp_cor_01 | \n", "t_comp_cor_02 | \n", "t_comp_cor_03 | \n", "... | \n", "cosine00 | \n", "cosine01 | \n", "cosine02 | \n", "cosine03 | \n", "trans_x | \n", "trans_y | \n", "trans_z | \n", "rot_x | \n", "rot_y | \n", "rot_z | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "439.699409 | \n", "451.645460 | \n", "525.387206 | \n", "0.000000 | \n", "0.000000 | \n", "0.000000 | \n", "-0.093142 | \n", "-0.047009 | \n", "0.110108 | \n", "-0.132180 | \n", "... | \n", "0.109104 | \n", "0.109090 | \n", "0.109066 | \n", "0.109033 | \n", "-0.000233 | \n", "-0.076885 | \n", "0.062321 | \n", "0.000732 | \n", "0.000352 | \n", "0.000841 | \n", "
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2 | \n", "439.744498 | \n", "450.981505 | \n", "525.324735 | \n", "0.885710 | \n", "14.068359 | \n", "0.054112 | \n", "-0.051778 | \n", "-0.012647 | \n", "-0.014665 | \n", "0.003982 | \n", "... | \n", "0.108990 | \n", "0.108632 | \n", "0.108038 | \n", "0.107207 | \n", "-0.000227 | \n", "-0.069893 | \n", "0.083102 | \n", "0.000143 | \n", "0.000364 | \n", "0.000716 | \n", "
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4 | \n", "440.115442 | \n", "450.678959 | \n", "525.656775 | \n", "0.830847 | \n", "13.196932 | \n", "0.051438 | \n", "-0.032434 | \n", "-0.021743 | \n", "0.003173 | \n", "0.063508 | \n", "... | \n", "0.108723 | \n", "0.107567 | \n", "0.105651 | \n", "0.102986 | \n", "-0.000226 | \n", "-0.084204 | \n", "0.085079 | \n", "0.000183 | \n", "0.000548 | \n", "0.000682 | \n", "
5 rows × 28 columns
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