Last modified by pierstanpaolucci on 2023/06/29 18:29
From version 16.1
edited by pierstanpaolucci
on 2021/09/22 10:43
Change comment: There is no comment for this version
To version 17.1
edited by pierstanpaolucci
on 2021/09/22 10:46
Change comment: There is no comment for this version

Summary

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3 3  (% class="container" %)
4 4  (((
5 5  (% class="lead" id="HInteractiveExplorationofBrainStatesandSpatio-TemporalActivityPatternsinData-ConstrainedSimulations" %)
6 -(% style="background-color:#ffffff; color:#f39c12" %)Explore brain states and spatio-temporal cortical activity patterns on your own
6 +Open the Lab link on the left to
7 +
8 +(% class="lead" %)
9 +Explore brain states and spatio-temporal cortical activity patterns on your own
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8 8  )))
9 9  
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13 13  (((
14 -(% class="lead" id="HOpentheLablinkonthelefttolaunchtheinteractivesimulation" %)
15 -Open the Lab link on the left to launch the interactive simulation
17 +**How the same network can generate different brain states with their specific propagation patterns and rhythms?**
16 16  
17 -How the same network can generate different brain states with their specific propagation patterns and rhythms?
18 -
19 19  In this Jupyter Lab the user can interactively change the neuromodulated fatigue parameters and observe in real-time the emergence of different categories of slow- wave wave-propagation patterns and the transition to an asynchronous regime on a columnar mean-field model equipped with lateral connections inferred from experimentally acquired cortical activity.
20 20  
21 21  The model displays the dorsal view of a mouse cortical hemisphere sampled by pixels of 100-micron size over a 25 mm2 field of view.
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40 40  (((
41 41  {{box title="**Contents**"}}