diff --git a/docs/examples/tutorial_calcium_imaging.py b/docs/examples/tutorial_calcium_imaging.py
index 2c9e11b9..2df962cc 100644
--- a/docs/examples/tutorial_calcium_imaging.py
+++ b/docs/examples/tutorial_calcium_imaging.py
@@ -95,7 +95,7 @@
 # ---------------------
 # Here we compute the tuning curves of all the neurons
 
-tcurves = nap.compute_1d_tuning_curves_continous(transients, angle, nb_bins = 120)
+tcurves = nap.compute_1d_tuning_curves_continuous(transients, angle, nb_bins = 120)
 
 print(tcurves)
 
@@ -123,8 +123,8 @@
 # %%
 # Now we can compute the tuning curves for each half of the recording and plot the tuning curves for the fifth region of interest. 
 
-half1 = nap.compute_1d_tuning_curves_continous(transients, angle, nb_bins = 120, ep = halves.loc[[0]])
-half2 = nap.compute_1d_tuning_curves_continous(transients, angle, nb_bins = 120, ep = halves.loc[[1]])
+half1 = nap.compute_1d_tuning_curves_continuous(transients, angle, nb_bins = 120, ep = halves.loc[[0]])
+half2 = nap.compute_1d_tuning_curves_continuous(transients, angle, nb_bins = 120, ep = halves.loc[[1]])
 
 plt.figure(figsize=(12, 5))
 plt.subplot(1,2,1)
diff --git a/docs/index.md b/docs/index.md
index a6d37f6d..a07b494b 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -28,7 +28,8 @@ Community
 To ask any questions or get support for using pynapple, please consider joining our slack. Please send an email to thepynapple[at]gmail[dot]com to receive an invitation link.
 
 New release :fire:
------------------
+------------------
+
 Starting with 0.4, pynapple rely on the [numpy array container](https://numpy.org/doc/stable/user/basics.dispatch.html) approach instead of Pandas. Pynapple builtin functions will remain the same except for functions inherited from Pandas. Typically this line of code in `pynapple<=0.3.6` :
 ```python
 meantsd = tsdframe.mean(1)