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...	...	@@ -6,13 +6,13 @@
6	6
7	7	== Purpose ==
8	8
9		-It is a Jupyter Widget intended for the visualization of brain signals represented as time series.
	9	+It is a JupyterLab Widget intended for the visualization of brain signals represented as time series.
10	10
11	11	== Backends ==
12	12
13	13	Starting with //**tvb-widgets 1.5.0**, //the TS widget comes in 2 forms, corresponding to the 2 different libraries (we called them backends) used for plotting: **matplotlib **and **plotly**. The matplotlib backend, build on top of the **mne** library, offers more advanced scientifical features, while the plotly backend has a more appealing look and moves faster when talking about the basic interactions.
14	14
15		-Below you can see the TS widget with each backend option (first one using the matplotlib backend, the second one using the plotly backend).
	15	+Below you can see the TS widget with each backend option (first one using the matplotlib backend, second one using the plotly backend).
16	16
17	17	(% style="text-align:center" %)
18	18	[[image:matplotlib.png]]
...	...	@@ -75,29 +75,29 @@
75	75	%matplotlib widget
76	76	)))
77	77
78		- Then, the **TimeSeriesWidget** (from the tvb-widgets API) and the **//display//** function should be imported:
	78	+Then, simply import the **plot_timeseries** method, which gives you access to the TS widget:
79	79
80	80	(% class="box" %)
81	81	(((
82		-from tvbwidgets.api import TimeSeriesWidget
83		-from IPython.core.display_functions import display
	82	+from tvbwidgets.api import plot_timeseries
84	84	)))
85	85
86		-Assuming that the user has already created or imported a valid input, this is how the widget can be initialized and how an input can be assigned to it, using the //**add_datatype** //method (example below assumes that **//tsr//  **is a TVB TimeSeries datatype):
87	87
88		-(% class="box" %)
89		-(((
90		-tsw = TimeSeriesWidget()
91		-tsw.add_datatype(tsr)
92		-)))
	86	+Assuming that the user has already created or imported a valid input, this is how the widget can be initialized and displayed (example below assumes that **tsr  **is a TVB TimeSeries datatype):
93	93
94		-Finally, to display and interact with the TimeSeries widget, the **//get_widget//**// //method is used inside the //**display **//function:
95		-
96	96	(% class="box" %)
97	97	(((
98		-display(tsw)
	90	+backend = 'plotly' # change to 'matplotlib' to see the other TS widget
	91	+
	92	+plot_timeseries(data=tsr, backend=backend)
99	99	)))
100	100
	95	+After running the code from above into a Jupyter cell, you should see the TS widget corresponding to the backend you selected.
	96	+
101	101	{{html}}
102	102	<iframe width="840" height="480" src="https://www.youtube.com/embed/VmueiXMxbVk" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
103	103	{{/html}}
	100	+
	101	+== 1. TS widget with matplotlib and mne ==
	102	+
	103	+As it was already mentioned, the matplotlib widget offers more advanced scientifical fearures. In the video below, you can see some of the functionalities that this backend provides, like increasing/decreasing signal amplitude, selecting/deselecting certain signals, selecting different dimensions (state variable/mode) from the input data, navigating through the timeline, etc.