SPM12's SliceTiming sets TR value in header to zero

SPM_slicetiming_sets_TR_to_zero.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load dataset and verify TR value in header"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nibabel as nb\n",
    "from nilearn.datasets import fetch_adhd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/line/nilearn_data/adhd/data/0010042/0010042_rest_tshift_RPI_voreg_mni.nii.gz'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filename = fetch_adhd(n_subjects=1)['func'][0]\n",
    "filename"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to unzip the file to make it accessible to SPM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/line/nilearn_data/adhd/data/0010042/0010042_rest_tshift_RPI_voreg_mni.nii'"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "!gunzip $filename\n",
    "filename = filename.replace('.gz', '')\n",
    "filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3.0, 3.0, 3.0, 2.0)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load image and show spatial and temporal resolution\n",
    "img = nb.load(filename)\n",
    "img.header.get_zooms()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we see clearly that the TR of the functional image is 2.0 seconds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(61, 73, 61, 176)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# And how many slices does the image have?\n",
    "img.header.get_data_shape()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Perform SPM12's SliceTiming correction\n",
    "\n",
    "We will use Nipype to run SPM's SliceTiming correction, but the underlying execution is the same and happens also if one runs SPM as a GUI.\n",
    "\n",
    "For this case we assume that the data was recorded in ascending order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nipype.interfaces.spm import SliceTiming"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "st = SliceTiming()\n",
    "st.inputs.in_files = filename\n",
    "st.inputs.num_slices = 61\n",
    "st.inputs.time_repetition = 2.0\n",
    "st.inputs.time_acquisition = 2. - 2./61.\n",
    "st.inputs.slice_order = list(range(61))\n",
    "st.inputs.ref_slice = int(61/2)\n",
    "res = st.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/line/nilearn_data/adhd/data/0010042/a0010042_rest_tshift_RPI_voreg_mni.nii'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output = res.outputs.timecorrected_files\n",
    "output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And if we now again investigate the TR in the NIfTI header, we get a value of `0.0`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3.0, 3.0, 3.0, 0.0)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nb.load(output).header.get_zooms()"
   ]
  }
 ],
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