diff --git a/docs/_toc.yml b/docs/_toc.yml
index f2c65a72..f838d792 100644
--- a/docs/_toc.yml
+++ b/docs/_toc.yml
@@ -19,6 +19,8 @@ parts:
   - file: visualization/visualize_2p_responses.ipynb
   - file: visualization/visualize_unit_spikes.ipynb
   - file: visualization/visualize_2p_vr_behavior.ipynb
+  - file: visualization/visualize_neuropixels_probes.ipynb
+  - file: visualization/visualize_templates.ipynb
 - caption: First-Order Analysis
   chapters:
   - file: first-order/receptive_fields.ipynb
diff --git a/docs/visualization/visualize_unit_spikes.ipynb b/docs/visualization/visualize_unit_spikes.ipynb
index 62500ca0..58650bc2 100644
--- a/docs/visualization/visualize_unit_spikes.ipynb
+++ b/docs/visualization/visualize_unit_spikes.ipynb
@@ -7,7 +7,7 @@
    "source": [
     "# Visualizing Neuronal Unit Spikes\n",
     "\n",
-    "In our files, the data contains a *spike train* array for each putative neuron. These are arrays of timestamps when a neuron spikes. Since neurons spike different numbers of times and during different times, it would be difficult to analyze many neurons together with the data in this form. One way to solve this is to make a 3-Dimensional *spike matrix*. This is a 3D array with the dimensions `neurons`, `time`, and `trials`. The spike matrix consists of time bins which contain the count of spikes at each time, for each neuron, and for each trial. The spike matrix can be sliced or averaged to produce useful 2D plots, or can be plugged in to more complex analysis. One application of this can be seen in [Statistically Testing Spike Responses to Stimulus](../first-order/test_unit_spikes.ipynb)."
+    "In our files, the data contains a *spike train* array for each putative neuron. These are arrays of timestamps when a neuron spikes. Since neurons spike different numbers of times and during different times, it would be difficult to analyze many neurons together with the data in this form. One way to solve this is to make a 3-Dimensional *spike matrix*. This is a 3D array with the dimensions `neurons`, `time`, and `trials`. The spike matrix consists of time bins which contain the count of spikes at each time, for each neuron, and for each trial. The spike matrix can be sliced or averaged to produce useful 2D plots, or can be plugged in to more complex analysis. One application of this can be seen in [Statistically Testing Spike Responses to Stimulus](../first-order/test_unit_responses.ipynb)."
    ]
   },
   {
@@ -1128,7 +1128,7 @@
    "metadata": {},
    "source": [
     "### Spike Plots From Spike Matrix\n",
-    "To demonstrate visually how it can be used, the plots below show different slices of the spike matrix. The first plot, *Unit Spikes Across Trials* shows the spiking behavior of one Unit across all trials. Set `unit` below to change which unit you'd like be shown. Following this is the *Unitwise Spike Plot*, which shows the spikes of all Units during the time window of one trial. Finally, the *Average Unitwise Spike Plot* shows the spikes of all units averaged across all trials. By themselves, these plots don't tell much. Useful versions of similar plots are depicted in notebooks such as [Identifying Optotagged Units](../first-order/optotagging.ipynb), and [Statistically Testing Spike Responses to Stimulus](../first-order/test_unit_spikes.ipynb)"
+    "To demonstrate visually how it can be used, the plots below show different slices of the spike matrix. The first plot, *Unit Spikes Across Trials* shows the spiking behavior of one Unit across all trials. Set `unit` below to change which unit you'd like be shown. Following this is the *Unitwise Spike Plot*, which shows the spikes of all Units during the time window of one trial. Finally, the *Average Unitwise Spike Plot* shows the spikes of all units averaged across all trials. By themselves, these plots don't tell much. Useful versions of similar plots are depicted in notebooks such as [Identifying Optotagged Units](../first-order/optotagging.ipynb), and [Statistically Testing Spike Responses to Stimulus](../first-order/test_unit_responses.ipynb)"
    ]
   },
   {