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on 2021/09/22 10:35
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Title
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1 -Interactive Exploration of Brain States and Spatio Temporal Activity Patterns in Data-Constrained Simulations
1 +Interactive Exploration of Brain States and Spatio-Temporal Activity Patterns in Data-Constrained Simulations
Content
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2 2  (((
3 3  (% class="container" %)
4 4  (((
5 -= My Collab's Extended Title =
6 -
7 -My collab's subtitle
5 +(% class="lead" id="HInteractiveExplorationofBrainStatesandSpatio-TemporalActivityPatternsinData-ConstrainedSimulations" %)
6 +(% style="color: rgb(243, 156, 18); background-color: rgb(255, 255, 255)" %)Explore brain states and spatio-temporal cortical activity patterns on your own
8 8  )))
9 9  )))
10 10  
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12 12  (((
13 13  (% class="col-xs-12 col-sm-8" %)
14 14  (((
15 -= What can I find here? =
14 +(% class="lead" id="HOpentheLablinkonthelefttolaunchtheinteractivesimulation" %)
15 +Open the Lab link on the left to launch the interactive simulation
16 16  
17 -* Notice how the table of contents on the right
18 -* is automatically updated
19 -* to hold this page's headers
17 +How the same network can generate different brain states with their specific propagation patterns and rhythms?
20 20  
21 -= Who has access? =
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.
22 22  
23 -Describe the audience of this collab.
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.
22 +
23 +The connectivity of the model was inferred from cortical activity acquired using GECI imaging technique. Even if the connectivity of the model was inferred from a single brain-state, the neuromodulated model supports the emergence of a rich dynamic repertoire of spatio-temporal propagation patterns, from those corresponding to deepests levels of anesthesia (spirals) to classical postero-anterior and rostro-caudal waves up to the transition to asynchronous activity, with the dissolution of the slow-wave features (1).
24 +
25 +The experimental data set from which the model has been inferred has been provided by LENS and it is available in the EBRAINS KG (2)
26 +
27 +(1) Capone, C. et al. (2021) “Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse” arXiv:2104.07445 [[https:~~/~~/arxiv.org/abs/2104.07445>>https://arxiv.org/abs/2104.07445]]
28 +
29 +(2) Resta, F., Allegra Mascaro, A. L., & Pavone, F. (2020). //Study of Slow Waves (SWs) propagation through wide-field calcium imaging of the right cortical hemisphere of GCaMP6f mice// [Data set]. EBRAINS. [[DOI: 10.25493/3E6Y-E8G>>url:https://doi.org/10.25493%2F3E6Y-E8G]]
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31 += =
24 24  )))
25 25  
26 26  
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