Last modified by pierstanpaolucci on 2023/06/29 18:29
From version 9.1
edited by pierstanpaolucci
on 2021/09/21 15:29
Change comment: There is no comment for this version
To version 9.2
edited by pierstanpaolucci
on 2021/09/21 15:37
Change comment: There is no comment for this version

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16 16  (((
17 17  = Open the Lab link on the left to launch the interactive simulation =
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19 +How the same network can generate different brain states with their specific propagation patterns and rhythms?
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21 +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.
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23 +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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25 +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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27 +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)
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29 +(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
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19 19  = =
20 20  )))
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