diff --git a/notebooks/03_prep_normgrid_targeting.ipynb b/notebooks/03_prep_normgrid_targeting.ipynb
index 6217f8c..cd6c121 100644
--- a/notebooks/03_prep_normgrid_targeting.ipynb
+++ b/notebooks/03_prep_normgrid_targeting.ipynb
@@ -34,6 +34,7 @@
     "import seaborn as sns\n",
     "import networkx as nx\n",
     "from simnibs import opt_struct\n",
+    "from simnibs.utils.nnav import brainsight\n",
     "from joblib import Parallel, delayed\n",
     "import templateflow\n",
     "import subprocess\n",
@@ -403,10 +404,57 @@
     "collapsed": false
    }
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "def get_optmat(row):\n",
+    "    opt_top = np.vstack([row.bxv, row.byv, row.bzv, np.array([row.bx, row.by, row.bz])]).T\n",
+    "    opt = np.vstack([opt_top, np.array([[0,0,0,1]])])\n",
+    "    return opt"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "for subject in subjects:\n",
+    "    src_surf_dir = liston_root / f'sub-{subject}/anat/T1w/fsaverage_LR32k/'\n",
+    "    headmodel_dir = anat_dir /f'sub-{subject}/HeadModel'\n",
+    "    sim_out_dir = anat_dir / f'sub-{subject}/Simulation'\n",
+    "    sim_dir = sorted(sim_out_dir.glob('simulation-*'))[-1]\n",
+    "    for session in [1]:\n",
+    "        for smoothing in [2.55]:\n",
+    "            bs_targ_path = sim_dir / f'sub-{subject}_ses-{session}_smoothing-{smoothing}_brainsighttarget.txt'\n",
+    "            bs = brainsight()\n",
+    "            row = stim_stats_rev.query('subject == @subject & session == @session & smoothing == @smoothing & rep_rva_rank == 1').iloc[0]\n",
+    "            optmat = get_optmat(row)\n",
+    "            bs.write(optmat, bs_targ_path.as_posix(), overwrite=True)"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "_ = [print(foo) for foo in bs_targ_path.read_text().split('\\n')]"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
   {
    "cell_type": "markdown",
    "source": [
-    "## The rest of this coe is for comparing sessions"
+    "## The rest of this code is for comparing sessions"
    ],
    "metadata": {
     "collapsed": false