Changes for page Interactive Exploration of Brain States and Spatio-Temporal Activity Patterns in Data-Constrained Simulations
Last modified by pierstanpaolucci on 2023/06/29 18:29
From version 13.1
edited by pierstanpaolucci
on 2021/09/21 15:45
on 2021/09/21 15:45
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To version 9.1
edited by pierstanpaolucci
on 2021/09/21 15:29
on 2021/09/21 15:29
Change comment:
There is no comment for this version
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... ... @@ -2,7 +2,10 @@ 2 2 ((( 3 3 (% class="container" %) 4 4 ((( 5 -(% class="lead" id="HInteractiveExplorationofBrainStatesandSpatio-TemporalActivityPatternsinData-ConstrainedSimulations" %) 5 += Interactive Exploration of Brain States and Spatio-Temporal Activity Patterns in Data-Constrained Simulations = 6 + 7 += = 8 + 6 6 Explore brain states and spatio-temporal cortical activity patterns on your own 7 7 ))) 8 8 ))) ... ... @@ -11,23 +11,8 @@ 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 += Open the Lab link on the left to launch the interactive simulation = 16 16 17 -How the same network can generate different brain states with their specific propagation patterns and rhythms? 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. 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]] 30 - 31 31 = = 32 32 ))) 33 33