Wiki source code of Interactive Exploration of Brain States and Spatio-Temporal Activity Patterns in Data-Constrained Simulations
Version 15.1 by pierstanpaolucci on 2021/09/22 10:42
Show last authors
| author | version | line-number | content |
|---|---|---|---|
| 1 | (% class="jumbotron" %) | ||
| 2 | ((( | ||
| 3 | (% class="container" %) | ||
| 4 | ((( | ||
| 5 | (% class="lead" id="HInteractiveExplorationofBrainStatesandSpatio-TemporalActivityPatternsinData-ConstrainedSimulations" %) | ||
| 6 | (% style="background-color:#ffffff; color:#f39c12" %)Explore brain states and spatio-temporal cortical activity patterns on your own | ||
| 7 | ))) | ||
| 8 | ))) | ||
| 9 | |||
| 10 | (% class="row" %) | ||
| 11 | ((( | ||
| 12 | (% class="col-xs-12 col-sm-8" %) | ||
| 13 | ((( | ||
| 14 | (% class="lead" id="HOpentheLablinkonthelefttolaunchtheinteractivesimulation" %) | ||
| 15 | Open the Lab link on the left to launch the interactive simulation | ||
| 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 | The predecessor of this model can be found at (3) | ||
| 28 | |||
| 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>>https://arxiv.org/abs/2104.07445]] | ||
| 30 | |||
| 31 | (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]] | ||
| 32 | |||
| 33 | (3) Mean Field Simulation of whole mouse hemisphere with parameters inferred from optical recordings [[https:~~/~~/search.kg.ebrains.eu/instances/e572362f-9461-4f9d-81e2-b69cd44185f4>>https://search.kg.ebrains.eu/instances/e572362f-9461-4f9d-81e2-b69cd44185f4]] | ||
| 34 | |||
| 35 | = = | ||
| 36 | ))) | ||
| 37 | |||
| 38 | |||
| 39 | (% class="col-xs-12 col-sm-4" %) | ||
| 40 | ((( | ||
| 41 | {{box title="**Contents**"}} | ||
| 42 | {{toc/}} | ||
| 43 | {{/box}} | ||
| 44 | |||
| 45 | |||
| 46 | ))) | ||
| 47 | ))) |