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Last modified by robing on 2022/03/25 09:55
From version 77.1
edited by robing
on 2020/05/24 19:24
Change comment: There is no comment for this version
To version 71.1
edited by denker
on 2020/05/07 14:05
Change comment: There is no comment for this version

Summary

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9 9  
10 10  Robin Gutzen^^1^^, Giulia De Bonis^^2^^, Elena Pastorelli^^2,3^^, Cristiano Capone^^2^^,
11 11  
12 -Chiara De Luca^^2,3^^, Michael Denker^^1^^, Sonja Grün^^1,4^^,
12 +Chiara De Luca^^2,3^^, Michael Denker^^1^^, Sonja Grün^^1^^,
13 13  
14 -Pier Stanislao Paolucci^^2^^, Andrew Davison^^5^^
14 +Pier Stanislao Paolucci^^2^^, Andrew Davison^^4^^
15 15  
16 -Experiments: Anna Letizia Allegra Mascaro^^6,7^^, Francesco Resta^^6^^, Francesco Saverio Pavone^^6^^, Maria-Victoria Sanchez-Vives^^8,9^^
16 +Experiments: Anna Letizia Allegra Mascaro^^5,6^^, Francesco Resta^^5^^, Francesco Saverio Pavone^^5^^, Maria-Victoria Sanchez-Vives^^7,8^^
17 17  
18 18  ,,1) Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany,,
19 19  
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21 21  
22 22  ,,3) Ph.D. Program in Behavioural Neuroscience, “Sapienza” University of Rome, Rome, Italy,,
23 23  
24 -,,4) Theoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany,,
24 +,,4) Unité de Neurosciences, Information et Complexité, Neuroinformatics Group, CNRS FRE 3693, Gif-sur-Yvette, France,,
25 25  
26 -,,5) Unité de Neurosciences, Information et Complexité, Neuroinformatics Group, CNRS FRE 3693, Gif-sur-Yvette, France,,
26 +,,5) European Laboratory for Non-linear Spectroscopy (LENS), (% style="--darkreader-inline-color:inherit; color:inherit" %)University of Florence, Florence, Italy(%%),,
27 27  
28 -,,6) European Laboratory for Non-linear Spectroscopy (LENS), (% style="--darkreader-inline-color:inherit; color:inherit" %)University of Florence, Florence, Italy(%%),,
28 +,,6) Istituto di Neuroscienze, CNR, Pisa, Italy,,
29 29  
30 -,,7) Istituto di Neuroscienze, CNR, Pisa, Italy,,
30 +,,7) Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain,,
31 31  
32 -,,8) Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain,,
33 -
34 -,,9) Institució Catalana de Recerca i Estudis Avanc ̨ats (ICREA), Barcelona, Spain,,
32 +,,8) Institució Catalana de Recerca i Estudis Avanc ̨ats (ICREA), Barcelona, Spain,,
35 35  )))
36 36  )))
37 37  
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78 78  
79 79  === ii) Local execution ===
80 80  
81 -//tested only with Linux!//
82 -
83 83  * **Get the code**
84 84  The source code of the pipeline is available via Github: [[INM-6/wavescalephant>>https://github.com/INM-6/wavescalephant]] and can be cloned to your machine ([[how to get started with Github>>https://guides.github.com/activities/hello-world/]]).
85 85  
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115 115  
116 116  All results are stored in the path specified in the //settings.py// file. The folder structure reflects the structuring of the pipeline into stages and blocks. All intermediate results are stored as //.nix// files using the [[Neo data format>>https://neo.readthedocs.io/en/stable/]] and can be loaded with ##neo.NixIO('/path/to/file.nix').read_block()##. Additionally, most blocks produce a figure, and each stage a report file, to give an overview of the execution log, parameters, intermediate results, and to help with debugging. The final stage (//stage05_wave_characterization//) stores the results as[[ //pandas.DataFrames//>>https://pandas.pydata.org/]] in //.csv// files, separately for each measure as well as in a combined dataframe for all measures.
117 117  
118 -**Examples of the output figures (for IDIBAPS dataset)**
114 +== Outlook ==
119 119  
120 -* Stage 01 - [[example signal traces and metadata>>https://drive.ebrains.eu/smart-link/cf2fa914-260d-4d61-a2da-03ea07b7f9be/]]
121 -* Stage 02 - [[background substraction>>https://drive.ebrains.eu/smart-link/586d2f3c-591b-4dfb-94ee-8c0e28050dc4/]]
122 -* Stage 02 - [[logMUA estimation>>https://drive.ebrains.eu/smart-link/c92e4b0c-0938-44e8-9f8d-00522796b2fd/]]
123 -* Stage 02 - [[processed signal trace>>https://drive.ebrains.eu/smart-link/26ed27c6-de56-4b48-a57b-f70aab629197/]]
124 -* Stage 03 - [[amplitude distribution>>https://drive.ebrains.eu/smart-link/8ba80293-ba75-4a37-8a8f-05d44cf6f65c/]]
125 -* Stage 03 - [[UP state detection>>https://drive.ebrains.eu/smart-link/ab172be0-178e-4153-a3e6-b4bace32dd50/]]
126 -* Stage 04 - [[trigger clustering>>https://drive.ebrains.eu/smart-link/4a1f0169-8b43-49ce-80c8-f2fa0f4d50d3/]]
127 -* Stage 05 - [[planar velocities>>https://drive.ebrains.eu/smart-link/f4de8073-cb40-47a7-bc82-f97d36dbae25/]]
128 -* Stage 05 - [[directionality>>https://drive.ebrains.eu/smart-link/5485032d-0121-4cde-9ea2-3e0af3f12178/]]
129 -
130 -=== Outlook ===
131 -
132 132  * Using the **KnowledgeGraph API **to insert data directly from the Knowledge Graph into the pipeline and also register and store the corresponding results as Analysis Objects. Such Analysis Objects are to incorporate **Provenance Tracking, **using [[fairgraph>>https://github.com/HumanBrainProject/fairgraph]],** **to record the details of the processing and analysis steps.
133 133  * Adding support for the pipeline to make use of **HPC** resources when running on the collab.
134 134  * Further extending the available **methods** to address a wider variety of analysis objectives and support the processing of other datatypes. Additional documentation and guides should also make it easier for non-developers to contribute new method blocks.
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143 143  * [[Sanchez-Vives, M. (2020). "Propagation modes of slow waves in mouse cortex".  //EBRAINS//>>https://doi.org/10.25493/WKA8-Q4T]]
144 144  * [[Sanchez-Vives, M. (2019). "Cortical activity features in transgenic mouse models of cognitive deficits (Fragile X Syndrome).//" EBRAINS//>>https://doi.org/10.25493/ANF9-EG3]]
145 145  
130 +
146 146  Code developed at:
147 147  
148 148  [[image:https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png||height="35" width="35"]][[INM-6/wavescalephant>>https://github.com/INM-6/wavescalephant]]
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Description
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1 -Use Case SGA2-SP3-002 KR3.2: Integrating multi-scale data and the output of simulations in a reproducible and adaptable pipeline
1 +Space for developing and hosting a showcase pipeline for performing reproducible and adaptable analysis with the focus of slow cortical waves.
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