Last modified by pierstanpaolucci on 2023/06/29 18:29
From version 13.4
edited by pierstanpaolucci
on 2021/09/22 10:38
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To version 6.1
edited by cristianocapone
on 2021/09/21 12:38
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Summary

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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
Author
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1 -XWiki.pierstanpaolucci
1 +XWiki.cristianocapone
Content
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2 2  (((
3 3  (% class="container" %)
4 4  (((
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
5 += Interactive Exploration of Brain States and Spatio-Temporal Activity Patterns in Data-Constrained Simulations =
6 +
7 += =
8 +
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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11 11  (((
12 12  (% class="col-xs-12 col-sm-8" %)
13 13  (((
14 -(% class="lead" id="HOpentheLablinkonthelefttolaunchtheinteractivesimulation" %)
15 -Open the Lab link on the left to launch the interactive simulation
17 += What can I find here? =
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17 -How the same network can generate different brain states with their specific propagation patterns and rhythms?
19 +* Notice how the table of contents on the right
20 +* is automatically updated
21 +* to hold this page's headers
18 18  
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.
23 += Who has access? =
20 20  
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 -= =
25 +Describe the audience of this collab.
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