{ "cells": [ { "cell_type": "markdown", "id": "realistic-photograph", "metadata": {}, "source": [ "# Predict Stop Signal Response Time (SSRT)\n", "\n", "This notebook uses stop signal task fMRI data derived contrasts from the ABCD study to \n", "predict stop signal response time (SSRT). This is an example of a regression type machine learning,\n", "and additionally includes an extra example of how to plot ROIs feature importance on brain surfaces from nilearn. \n", "\n", "## Loading Data\n", "\n", "We will be loading data from is essentially a big csv file with all the different columns, some slightly processed, from the ABCD DEAP rds (saved r dataframe). The benefit of this approach is that while a little slow, we can just load any column of interest easily as a dataframe." ] }, { "cell_type": "code", "execution_count": 1, "id": "shaped-indonesian", "metadata": {}, "outputs": [], "source": [ "import BPt as bp\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "id": "focal-olive", "metadata": {}, "outputs": [], "source": [ "def load_from_rds(names, eventname='baseline_year_1_arm_1'):\n", " \n", " data = pd.read_csv('data/nda_rds_201.csv',\n", " usecols=['src_subject_id', 'eventname'] + names,\n", " na_values=['777', 999, '999', 777])\n", " \n", " data = data.loc[data[data['eventname'] == eventname].index]\n", " data = data.set_index('src_subject_id')\n", " data = data.drop('eventname', axis=1)\n", " \n", " return data" ] }, { "cell_type": "code", "execution_count": 3, "id": "extended-plain", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['subjectid',\n", " 'src_subject_id',\n", " 'eventname',\n", " 'anthro_1_height_in',\n", " 'anthro_2_height_in',\n", " 'anthro_3_height_in',\n", " 'anthro_height_calc',\n", " 'anthro_weight_cast',\n", " 'anthro_weight_a_location',\n", " 'anthro_weight1_lb']" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# This way we can look at all column available\n", "all_cols = list(pd.read_csv('data/nda_rds_201.csv', nrows=0))\n", "all_cols[:10]" ] }, { "cell_type": "code", "execution_count": 4, "id": "instant-vintage", "metadata": {}, "outputs": [], "source": [ "# Use python list comprehensions to get lists of the column names of interest\n", "contrasts = ['tfmri_sst_all_correct.go.vs.fixation_beta_',\n", " 'tfmri_sst_all_correct.stop.vs.correct.go_beta_',\n", " 'tfmri_sst_all_incorrect.stop.vs.correct.go_beta_']\n", "\n", " \n", "parcs = ['.destrieux', '_subcort.aseg']\n", "\n", "data_cols = [col for col in all_cols\n", " if any([ct for ct in contrasts if ct in col])\n", " and any([p for p in parcs if p in col])] + ['sex']\n", "target_col = ['tfmri_sst_all_beh_total_mean.rt']" ] }, { "cell_type": "code", "execution_count": 5, "id": "atmospheric-mauritius", "metadata": {}, "outputs": [], "source": [ "# Load the actual data from the saved csv\n", "df = load_from_rds(data_cols + target_col)" ] }, { "cell_type": "code", "execution_count": 6, "id": "substantial-angel", "metadata": {}, "outputs": [], "source": [ "# Cast from a dataframe to BPt Dataset class\n", "data = bp.Dataset(df)\n", " \n", "# Obsificate subject ID for public example\n", "data.index = list(range(len(data)))\n", "\n", "# Set optional verbosity of\n", "data.verbose = 1" ] }, { "cell_type": "code", "execution_count": 7, "id": "precise-reggae", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dropped 27 Columns\n" ] } ], "source": [ "data = data.drop_cols(exclusions=['.ventricle', '_csf', '.white.matter'], scope='_subcort.aseg')" ] }, { "cell_type": "markdown", "id": "material-building", "metadata": {}, "source": [ "Data in BPt can have one of three roles, these are 'data' by default, 'target' for variable to predict, and 'non input' for variables which we don't use directly as input features. We set 'sex' as non input in this example." ] }, { "cell_type": "code", "execution_count": 8, "id": "cultural-english", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Dropped 6 Rows\n" ] }, { "data": { "text/html": [ "
| \n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.ant.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.ant.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.ant.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.ant.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.post.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.post.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.frontomargin.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.frontomargin.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.occipital.inf.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.occipital.inf.rh\n", " | ...\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_inf.lat.vent.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_inf.lat.vent.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_pallidum.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_pallidum.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_putamen.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_putamen.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_thalamus.proper.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_thalamus.proper.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_ventraldc.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_ventraldc.rh\n", " | 
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0\n", " | 0.168032\n", " | 0.153849\n", " | 0.045860\n", " | 0.023883\n", " | 0.081824\n", " | 0.015926\n", " | 0.142664\n", " | 0.035705\n", " | -0.169860\n", " | -0.128688\n", " | ...\n", " | -0.036716\n", " | 0.052883\n", " | -0.006478\n", " | -0.025535\n", " | 0.030901\n", " | -0.022286\n", " | 0.091828\n", " | 0.158497\n", " | 0.101536\n", " | 0.234851\n", " | 
| 1\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | ...\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | NaN\n", " | 
| 2\n", " | 0.052402\n", " | 0.101880\n", " | 0.111399\n", " | 0.124650\n", " | 0.113433\n", " | 0.125727\n", " | 0.579317\n", " | 0.611870\n", " | 0.224255\n", " | 0.343618\n", " | ...\n", " | -0.070160\n", " | 0.097003\n", " | 0.026871\n", " | 0.191424\n", " | 0.026224\n", " | 0.036808\n", " | 0.091165\n", " | 0.044027\n", " | 0.071074\n", " | 0.042021\n", " | 
| 3\n", " | -0.092771\n", " | 0.007574\n", " | 0.182024\n", " | 0.115439\n", " | 0.096595\n", " | 0.096851\n", " | 0.289666\n", " | -0.129820\n", " | 0.188761\n", " | 0.178344\n", " | ...\n", " | 0.342260\n", " | -0.114128\n", " | -0.097753\n", " | -0.082544\n", " | -0.145369\n", " | -0.187083\n", " | -0.159170\n", " | -0.113892\n", " | -0.242210\n", " | -0.175904\n", " | 
| 4\n", " | -0.144128\n", " | -0.074626\n", " | -0.001618\n", " | 0.142387\n", " | 0.241128\n", " | 0.227172\n", " | -0.141231\n", " | 0.475396\n", " | 0.573906\n", " | 1.363352\n", " | ...\n", " | -0.183606\n", " | -0.118741\n", " | -0.055955\n", " | 0.046954\n", " | -0.018277\n", " | 0.092319\n", " | 0.053306\n", " | 0.060963\n", " | 0.116601\n", " | -0.102220\n", " | 
| ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | 
| 11870\n", " | -0.103273\n", " | -0.060990\n", " | 0.008791\n", " | 0.186439\n", " | 0.059300\n", " | 0.047829\n", " | 0.130752\n", " | 0.184572\n", " | 0.100078\n", " | 0.049040\n", " | ...\n", " | 0.010403\n", " | -0.149049\n", " | -0.024082\n", " | 0.016314\n", " | -0.045987\n", " | -0.090321\n", " | 0.066490\n", " | 0.055350\n", " | 0.022404\n", " | 0.095318\n", " | 
| 11871\n", " | -0.060443\n", " | -0.123368\n", " | -0.024308\n", " | -0.122978\n", " | -0.143336\n", " | -0.098973\n", " | 0.327409\n", " | 0.055603\n", " | -0.203490\n", " | -0.129804\n", " | ...\n", " | -0.168353\n", " | 0.058014\n", " | -0.080418\n", " | 0.080907\n", " | -0.095893\n", " | -0.069077\n", " | 0.009947\n", " | 0.034421\n", " | 0.007450\n", " | -0.075879\n", " | 
| 11872\n", " | 0.012809\n", " | 0.010143\n", " | 0.012343\n", " | -0.006711\n", " | -0.072679\n", " | -0.084823\n", " | -0.203417\n", " | -0.210167\n", " | -0.270940\n", " | -0.143613\n", " | ...\n", " | -0.044618\n", " | 0.116003\n", " | 0.264322\n", " | 0.134182\n", " | 0.323175\n", " | 0.366650\n", " | 0.254944\n", " | 0.388157\n", " | 0.411429\n", " | 0.312342\n", " | 
| 11873\n", " | 0.164396\n", " | 0.202513\n", " | 0.376726\n", " | 0.257396\n", " | 0.371823\n", " | 0.123384\n", " | 0.507308\n", " | 0.788963\n", " | 0.260868\n", " | 0.246349\n", " | ...\n", " | 0.538963\n", " | -0.930948\n", " | -0.225716\n", " | -0.347940\n", " | -0.305339\n", " | -0.380956\n", " | -0.123154\n", " | -0.251212\n", " | -0.270063\n", " | -0.336481\n", " | 
| 11874\n", " | 0.116179\n", " | 0.136342\n", " | -0.045182\n", " | 0.180420\n", " | 0.341190\n", " | -0.183304\n", " | 0.914101\n", " | 1.593521\n", " | 0.295187\n", " | 2.117747\n", " | ...\n", " | -0.322345\n", " | -0.053627\n", " | 0.089375\n", " | -0.217486\n", " | -0.092425\n", " | -0.142340\n", " | 0.049234\n", " | -0.110444\n", " | 0.205795\n", " | 0.036157\n", " | 
11869 rows × 507 columns
\n", "| \n", " | tfmri_sst_all_beh_total_mean.rt\n", " | 
|---|---|
| 0\n", " | 303.070588\n", " | 
| 1\n", " | NaN\n", " | 
| 2\n", " | 207.210728\n", " | 
| 3\n", " | 241.179775\n", " | 
| 4\n", " | 391.927948\n", " | 
| ...\n", " | ...\n", " | 
| 11870\n", " | 169.889647\n", " | 
| 11871\n", " | 335.764988\n", " | 
| 11872\n", " | 332.246959\n", " | 
| 11873\n", " | 358.591304\n", " | 
| 11874\n", " | 210.954955\n", " | 
11869 rows × 1 columns
\n", "| \n", " | sex\n", " | 
|---|---|
| 0\n", " | F\n", " | 
| 1\n", " | F\n", " | 
| 2\n", " | M\n", " | 
| 3\n", " | M\n", " | 
| 4\n", " | M\n", " | 
| ...\n", " | ...\n", " | 
| 11870\n", " | M\n", " | 
| 11871\n", " | F\n", " | 
| 11872\n", " | F\n", " | 
| 11873\n", " | F\n", " | 
| 11874\n", " | F\n", " | 
11869 rows × 1 columns
\n", "| \n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.ant.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.ant.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.ant.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.ant.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.post.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.cingul.mid.post.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.frontomargin.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.frontomargin.rh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.occipital.inf.lh\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort.destrieux_g.and.s.occipital.inf.rh\n", " | ...\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_inf.lat.vent.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_inf.lat.vent.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_pallidum.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_pallidum.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_putamen.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_putamen.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_thalamus.proper.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_thalamus.proper.rh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_ventraldc.lh\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_beta_subcort.aseg_ventraldc.rh\n", " | 
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0\n", " | 0.168032\n", " | 0.153849\n", " | 0.045860\n", " | 0.023883\n", " | 0.081824\n", " | 0.015926\n", " | 0.142664\n", " | 0.035705\n", " | -0.169860\n", " | -0.128688\n", " | ...\n", " | -0.036716\n", " | 0.052883\n", " | -0.006478\n", " | -0.025535\n", " | 0.030901\n", " | -0.022286\n", " | 0.091828\n", " | 0.158497\n", " | 0.101536\n", " | 0.234851\n", " | 
| 2\n", " | 0.052402\n", " | 0.101880\n", " | 0.111399\n", " | 0.124650\n", " | 0.113433\n", " | 0.125727\n", " | 0.579317\n", " | 0.611870\n", " | 0.224255\n", " | 0.343618\n", " | ...\n", " | -0.070160\n", " | 0.097003\n", " | 0.026871\n", " | 0.191424\n", " | 0.026224\n", " | 0.036808\n", " | 0.091165\n", " | 0.044027\n", " | 0.071074\n", " | 0.042021\n", " | 
| 3\n", " | -0.092771\n", " | 0.007574\n", " | 0.182024\n", " | 0.115439\n", " | 0.096595\n", " | 0.096851\n", " | 0.289666\n", " | -0.129820\n", " | 0.188761\n", " | 0.178344\n", " | ...\n", " | 0.342260\n", " | -0.114128\n", " | -0.097753\n", " | -0.082544\n", " | -0.145369\n", " | -0.187083\n", " | -0.159170\n", " | -0.113892\n", " | -0.242210\n", " | -0.175904\n", " | 
| 4\n", " | -0.144128\n", " | -0.074626\n", " | -0.001618\n", " | 0.142387\n", " | 0.241128\n", " | 0.227172\n", " | -0.141231\n", " | 0.475396\n", " | 0.573906\n", " | 1.363352\n", " | ...\n", " | -0.183606\n", " | -0.118741\n", " | -0.055955\n", " | 0.046954\n", " | -0.018277\n", " | 0.092319\n", " | 0.053306\n", " | 0.060963\n", " | 0.116601\n", " | -0.102220\n", " | 
| 5\n", " | -0.243239\n", " | -0.152293\n", " | -0.078217\n", " | -0.061314\n", " | -0.044547\n", " | -0.096233\n", " | 0.298622\n", " | -0.083202\n", " | -0.082675\n", " | -0.071584\n", " | ...\n", " | 0.015237\n", " | 0.129581\n", " | 0.222719\n", " | 0.122448\n", " | 0.244788\n", " | 0.159455\n", " | 0.342455\n", " | 0.230097\n", " | 0.133497\n", " | 0.230591\n", " | 
| ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | ...\n", " | 
| 11870\n", " | -0.103273\n", " | -0.060990\n", " | 0.008791\n", " | 0.186439\n", " | 0.059300\n", " | 0.047829\n", " | 0.130752\n", " | 0.184572\n", " | 0.100078\n", " | 0.049040\n", " | ...\n", " | 0.010403\n", " | -0.149049\n", " | -0.024082\n", " | 0.016314\n", " | -0.045987\n", " | -0.090321\n", " | 0.066490\n", " | 0.055350\n", " | 0.022404\n", " | 0.095318\n", " | 
| 11871\n", " | -0.060443\n", " | -0.123368\n", " | -0.024308\n", " | -0.122978\n", " | -0.143336\n", " | -0.098973\n", " | 0.327409\n", " | 0.055603\n", " | -0.203490\n", " | -0.129804\n", " | ...\n", " | -0.168353\n", " | 0.058014\n", " | -0.080418\n", " | 0.080907\n", " | -0.095893\n", " | -0.069077\n", " | 0.009947\n", " | 0.034421\n", " | 0.007450\n", " | -0.075879\n", " | 
| 11872\n", " | 0.012809\n", " | 0.010143\n", " | 0.012343\n", " | -0.006711\n", " | -0.072679\n", " | -0.084823\n", " | -0.203417\n", " | -0.210167\n", " | -0.270940\n", " | -0.143613\n", " | ...\n", " | -0.044618\n", " | 0.116003\n", " | 0.264322\n", " | 0.134182\n", " | 0.323175\n", " | 0.366650\n", " | 0.254944\n", " | 0.388157\n", " | 0.411429\n", " | 0.312342\n", " | 
| 11873\n", " | 0.164396\n", " | 0.202513\n", " | 0.376726\n", " | 0.257396\n", " | 0.371823\n", " | 0.123384\n", " | 0.507308\n", " | 0.788963\n", " | 0.260868\n", " | 0.246349\n", " | ...\n", " | 0.538963\n", " | -0.930948\n", " | -0.225716\n", " | -0.347940\n", " | -0.305339\n", " | -0.380956\n", " | -0.123154\n", " | -0.251212\n", " | -0.270063\n", " | -0.336481\n", " | 
| 11874\n", " | 0.116179\n", " | 0.136342\n", " | -0.045182\n", " | 0.180420\n", " | 0.341190\n", " | -0.183304\n", " | 0.914101\n", " | 1.593521\n", " | 0.295187\n", " | 2.117747\n", " | ...\n", " | -0.322345\n", " | -0.053627\n", " | 0.089375\n", " | -0.217486\n", " | -0.092425\n", " | -0.142340\n", " | 0.049234\n", " | -0.110444\n", " | 0.205795\n", " | 0.036157\n", " | 
8520 rows × 507 columns
\n", "6816 rows × 507 columns - Train Set
1704 rows × 507 columns - Test Set
| \n", " | tfmri_sst_all_beh_total_mean.rt\n", " | 
|---|---|
| 0\n", " | 303.070588\n", " | 
| 2\n", " | 207.210728\n", " | 
| 3\n", " | 241.179775\n", " | 
| 4\n", " | 391.927948\n", " | 
| 5\n", " | 287.037037\n", " | 
| ...\n", " | ...\n", " | 
| 11870\n", " | 169.889647\n", " | 
| 11871\n", " | 335.764988\n", " | 
| 11872\n", " | 332.246959\n", " | 
| 11873\n", " | 358.591304\n", " | 
| 11874\n", " | 210.954955\n", " | 
8520 rows × 1 columns
\n", "6816 rows × 1 columns - Train Set
1704 rows × 1 columns - Test Set
| \n", " | sex\n", " | 
|---|---|
| 0\n", " | 0\n", " | 
| 2\n", " | 1\n", " | 
| 3\n", " | 1\n", " | 
| 4\n", " | 1\n", " | 
| 5\n", " | 1\n", " | 
| ...\n", " | ...\n", " | 
| 11870\n", " | 1\n", " | 
| 11871\n", " | 0\n", " | 
| 11872\n", " | 0\n", " | 
| 11873\n", " | 0\n", " | 
| 11874\n", " | 0\n", " | 
8520 rows × 1 columns
\n", "6816 rows × 1 columns - Train Set
1704 rows × 1 columns - Test Set
| \n", " | mean_scores_r2\n", " | mean_scores_explained_variance\n", " | mean_scores_neg_mean_squared_error\n", " | std_scores_r2\n", " | std_scores_explained_variance\n", " | std_scores_neg_mean_squared_error\n", " | mean_timing_fit\n", " | mean_timing_score\n", " | 
|---|---|---|---|---|---|---|---|---|
| subjects\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | 
| M\n", " | 0.033538\n", " | 0.035266\n", " | -6382.616684\n", " | 0.010401\n", " | 0.009289\n", " | 485.944440\n", " | 6.773705\n", " | 0.015207\n", " | 
| F\n", " | 0.055129\n", " | 0.055459\n", " | -6093.100561\n", " | 0.011371\n", " | 0.011138\n", " | 488.356616\n", " | 6.585156\n", " | 0.016477\n", " | 
| \n", " | index\n", " | 0\n", " | 
|---|---|---|
| 0\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort...\n", " | 0.096960\n", " | 
| 1\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort...\n", " | -0.067299\n", " | 
| 2\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort...\n", " | 0.696026\n", " | 
| 3\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort...\n", " | -0.732170\n", " | 
| 4\n", " | tfmri_sst_all_correct.go.vs.fixation_beta_cort...\n", " | -1.197480\n", " | 
| ...\n", " | ...\n", " | ...\n", " | 
| 502\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_bet...\n", " | 3.734274\n", " | 
| 503\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_bet...\n", " | -1.032871\n", " | 
| 504\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_bet...\n", " | -2.059234\n", " | 
| 505\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_bet...\n", " | -1.065423\n", " | 
| 506\n", " | tfmri_sst_all_incorrect.stop.vs.correct.go_bet...\n", " | -1.673626\n", " | 
507 rows × 2 columns
\n", "