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95	95	After running the code from above into a Jupyter cell, you should see the TS widget corresponding to the backend you selected.
96	96
97		-== 1. TS Widget with matplotlib and mne ==
	97	+== 1. TS widget with matplotlib and mne ==
98	98
99	99	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.
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102	102	<iframe width="840" height="480" src="https://www.youtube.com/embed/hozEkVhkWeA" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
103	103	{{/html}}
104	104
105		-== 2. TS Widget with plotly ==
	105	+
106	106
107		-Starting with //**tvb-widgets version 1.5.0**//, we introduced a second TS Widget, which uses the **plotly.py** library to create the interactive plot. Below you can watch small tutorials on how to use and interact with this widget.
	107	+== 1. TS widget with matplotlib and mne ==
108	108
109		-=== 2.1. Basic controls of the plot ===
110		-
111		-If you hover over a signal, a tooltip will appear where you can see the exact value from that point and the name of the channel you are hovering over. Next, you can zoom in, by dragging and creating an area inside the plot or from the plotly tools area and zoom out, from the same tools area. To come back to the original view, you can click the 'Reset axes' button (house icon) from the tools area.
112		-
113		-To the right of the plot there is a legend, showing the channels which are plotted. The '**[R]**' notation means that the signal is **resampled** so that all of it can be viewed inside the plot. The '**~~20**' notation means that 20 consecutive points are aggregated into a single point in the plot. As you zoom in in the plot, the number of aggregated points decreases. This is all done using the [[**plotly-resampler**>>https://predict-idlab.github.io/plotly-resampler/]] package.
114		-
115		-Moreover, clicking on a channel name from the legend will toggle its visibility inside the plot. This means that the signal corresponding to that channel //is not removed, but just invisible// in the plot. Double clicking on a channel  from the legend will isolate it, meaning that will be the only visible channel in the plot and the rest of them will be hidden. Double clicking again will make all the channels visible again. If you wish to hide all the channels or make all of them visible, use the 'Hide All' and 'Show All' buttons.
116		-
117		-{{html}}
118		-<iframe width="840" height="480" src="https://www.youtube.com/embed/x4ksyKIFUAk" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
119		-{{/html}}
120		-
121		-
122		-=== 2.1. Moving through the timeline and channels list ===
123		-
124		-To move through the timeline or channels list, go to your cursor over the X (for timeline) and Y (for channels) axes and drag it to navigate.
125		-
126		-{{html}}
127		-<iframe width="840" height="480" src="https://www.youtube.com/embed/nZYZxHui-Ao" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
128		-{{/html}}
129		-
130		-=== 2.2. Modify spacing between channels ===
131		-
132		-To modify the spacing between the channels, go with your cursor over the beginning/end of the Y axis (where the channels list is) and drag it to the outside of the plot area. To decrease the spacing, drag your cursor to the inside of the plot area. To reset the spacing to the default values, click on the 'Reset axes' button (Home icon) from the plotly tools area.
133		-
134		-{{html}}<iframe width="840" height="480" src="https://www.youtube.com/embed/q_olB7uRSc4" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>{{/html}}
135		-
	109	+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.