Last modified by pierstanpaolucci on 2023/06/29 18:29

From version 32.1
edited by cristianocapone
on 2021/10/01 11:28
Change comment: Uploaded new attachment "fig_live_poster_2021.png", version {1}
To version 34.1
edited by pierstanpaolucci
on 2021/10/01 12:01
Change comment: There is no comment for this version

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1 -XWiki.cristianocapone
1 +XWiki.pierstanpaolucci
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13 13  (((
14 14  **How the same network can generate different brain states with their specific propagation patterns and rhythms?**
15 15  
16 -In this Jupyter Lab environment, 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.
16 +In this Jupyter Lab environment, 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.
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18 -[[image:example1.png]]
18 +[[image:fig_live_poster_2021.png]]
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20 -[[image:example2.png]]
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22 22  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.
23 23  
24 24  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).
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31 31  
32 32  The latest version of the code presented in the drive of this collab can be found at (5).
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34 +The interactive model is registered in the EBRAINS Knowledge Graph at (6)
35 +
34 34  **Acknowledgment**
35 35  
36 36  This model is developed in the framework of the "Slow Waves, Brain States Transitions, Cognitive Functions and Complexity" Use Case collaboration that aims to the integration of experimental data, models and analysis pipelines in a multi-scale, multi-methodology approach.
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53 53  
54 54  (% class="wikigeneratedid" id="H" %)
55 55  (5) [[https:~~/~~/github.com/APE-group/InteractiveExplorationBrainStates>>https://github.com/APE-group/InteractiveExplorationBrainStates]]
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59 +(% class="wikigeneratedid" %)
60 +(6) [[https:~~/~~/search.kg.ebrains.eu/instances/3ebdd555-f965-477c-8a0e-4c220014d138>>url:https://search.kg.ebrains.eu/instances/3ebdd555-f965-477c-8a0e-4c220014d138]] Interactive Exploration of Brain States and Spatio-Temporal Activity Patterns in Data-Constrained Simulations
56 56  )))
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68 68  )))
69 69  )))