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59	59	Aside from this support, the HBP also organizes outreach activities targeted at different scientific communities. In this regard, a special focus is placed on young researchers who wish to learn how to use EBRAINS.
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61		-In order to learn how to use EBRAINS, it is helpful to understand how other scientific projects have been translated into EBRAINS workflows. Also in this regard, HBP seeks to support EBRAINS users. Following this idea, we (the authors of this paper) investigated the possibility of writing a white paper that serves as a database of different workflows and making them available to other researchers. In order to collect such usecases, we decided to combine the outreach efforts of the education program and the student ambassadors of the HBP with SLU formalization and technical coordination (TC). A students’ workshop was chosen as the best means of collecting usecases.
	61	+In order to learn how to use EBRAINS, it is helpful to understand how other scientific projects have been translated into EBRAINS workflows. Also in this regard, HBP seeks to support EBRAINS users. Following this idea, we (the authors of this paper) investigated the possibility of writing a white paper that serves as a database of different workflows and making them available to other researchers. In order to collect such usecases, we decided to combine the outreach efforts of the education program and the student ambassadors of the HBP with SLU formalization and technical coordination (TC). A students’ workshop was chosen as the best means of collecting use-cases.
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63	63	With the students’ workshop we wanted to accomplish the following goals:
64		-• Collecting different neuroscientific projects suitable for creating workflows in EBRAINS • Presenting the different EBRAINS tools and computing resources to the students
65		-• Teaching students how to create their own EBRAINS workflows
66		-• Supporting students in creating their first workflows
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	65	+
	66	+* • Collecting different neuroscientific projects suitable for creating workflows in EBRAINS.
	67	+* Presenting the different EBRAINS tools and computing resources to the students.
	68	+* Teaching students how to create their own EBRAINS workflows.
	69	+* Supporting students in creating their first workflows.
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68	68	Accordingly we structured the workflow as follows:
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70	70	In the first part we introduced the different EBRAINS tools and services.
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74	74	In the third part we asked students to present their scientific project idea. For this part we asked students to give a presentation prior to the workshop. There was no requirement for the project to have already produced any kind of results or to have used EBRAINS tools. There was only one thing that was important: presenting the scientific idea.
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76		-How to create EBRAINS workflows from these scientific projects was discussed after the presentations. Here, the mural board were of great assistance and helped the students and tutors to streamline. An example of such a filled-out mural board is illustrated in Fig? here a figure is missing with an example of a filled out mir board. In this last part of the workshop, we reserved extra time for students to ask questions, seek assistance, and/or present and discuss their first Mural boards.
	79	+How to create EBRAINS workflows from these scientific projects was discussed after the presentations. Here, the mural board were of great assistance and helped the students and tutors to streamline. In this last part of the workshop, we reserved extra time for students to ask questions, seek assistance, and/or present and discuss their first Mural boards.
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78	78	The workshop idea proved to be successful. During the 1,5 days of the workshop, we had 9 participants, of which 5 agreed to share their workflows in this paper.
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83	83	* Nalan Kraunanayake, a PhD in Biomedical Engineering and Prof. Dr. Stanislav S. Makhanov both working at Thammasat University in Thailand (workflow 3)
84	84	* Igori Comarovschii, Mickkel Vinding and Prof. Daniel Lundqvist from the Karolinska Institute as well as Pascal Helson for the KTH Royal Institute of Technology in Sweden (workflow 4)
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86		-
87	87	• PhD student Niccolò Mattiello of Gerardo Biella’s group at the University of Pavia (workflow 5)
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89		-• Katia Djerround, a master student at the Algerian University of Science and Technology Houari Boumediene, Nathaniel Adibuer, a research assistant at the University of Ghana, and Aziz Ullah Khan, a professional engineer from X
	91	+• Katia Djerround, a master student at the Algerian University of Science and Technology Houari Boumediene, Nathaniel Adibuer, a research assistant at the University of Ghana, and Aziz Ullah Khan, a professional engineer.
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91		-Figure 2: Mural board presented to the students during the workshop with an invite to fill it out. Each field on the board had a short caption and a short explanation of what to fill in: Team: the team name, the members and and one sentence per each group member to introduce themselves; Background:Explaining the main trends of the state of the art to address the research question the reasearchers are working on; Problem: Decomposing the main challenge into subproblems; Vision: Where does the research group want to go? What are dreams of the researchers for future researchers working in your field?; Impact: What difference will the researchers make? Who else will benefit from the designed workflow?; Solution elements: Brainstorm the elements which would be key to solve your problem; Challenges:What is missing to achieve ther researcher’s vision and can they address this using EBRAINS tools?; Workflow: Associating solution elements to EBRAINS components, and ordering them in a workflow; the construction of diagrams make use of the symbols described in 1.
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	95	+[[image:Marissa Diaz_2023-03-02_14-43-52.png]]
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	97	+(% class="small" %)Figure 2: Mural board presented to the students during the workshop with an invite to fill it out. Each field on the board had a short caption and a short explanation of what to fill in: Team: the team name, the members and and one sentence per each group member to introduce themselves.
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	100	+Background: Explaining the main trends of the state of the art to address the research question the reasearchers are working on; Problem: Decomposing the main challenge into subproblems; Vision: Where does the research group want to go? What are dreams of the researchers for future researchers working in your field?; Impact: What difference will the researchers make? Who else will benefit from the designed workflow?; Solution elements: Brainstorm the elements which would be key to solve your problem; Challenges:What is missing to achieve the researcher’s vision and can they address this using EBRAINS tools?; Workflow: Associating solution elements to EBRAINS components, and ordering them in a workflow; the construction of diagrams make use of the symbols described in 1.
	101	+
93	93	In the following chapter, the scientific projects and the corresponding workflows are explained. An overview of the tools used in these workshops is given in the table 1. Tools are categorized here according to their fields of application. A short description of each tool is provided, along with a link to a more detailed explanation.
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100	100	One of the use-cases, for example, focuses on establishing a methodology to facilitate the creation of 6
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102		-brain atlases for a particular target group. Other studies investigate phenomena like contour grouping, oscillation in Parkinson’s Disease, cell and network properties of the entorhinal cortex, and the use of imaging signals, specifically the EEG, to improve brain-computer interfaces. [This needs to be extended to show cases and other cases]
	111	+brain atlases for a particular target group. Other studies investigate phenomena like contour grouping, oscillation in Parkinson’s Disease, cell and network properties of the entorhinal cortex, and the use of imaging signals, specifically the EEG, to improve brain-computer interfaces.
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104	104	In order to help the reader to quickly identify the most relevant use cases, we will briefly sketch each use case in a couple of sentences. This will include a quick overview of the use case content, the data it treats, EBRAINS tools used, maturity level achieved so far and information on the research group.
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106		-subsection 3.2 The researchers at Research Center Sant Joan de Déu in Spain, Christian Mata and Christian Stephan-Otto, desire to create anatomical brain templates of specific human subgroups from images in the BIDS format. Among the tools they are using are the Knowledge Graph, Quick NII, and the Brain Atlas of EBRAINS. [The maturity level of this project is probably already advanced but this is something we have to ask them]
	115	+subsection 3.2 The researchers at Research Center Sant Joan de Déu in Spain, Christian Mata and Christian Stephan-Otto, desire to create anatomical brain templates of specific human subgroups from images in the BIDS format. Among the tools they are using are the Knowledge Graph, Quick NII, and the Brain Atlas of EBRAINS.
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108		-subsection 3.3 In the third workflow, Nalan Kraunanayake, a PhD in Biomedical Engineering and Prof. Dr. Stanislav S. Makhanov both working at Thammasat University in Thailand, present a project in which contour grouping is investigated. Using robot simulations of visual neuro function, the group explores how local and global stimulus properties affect contour grouping. Here, EBRAINS tools and services such as the NRP, NEST and L2L support this research. [The maturity level of this project is not known - we have to ask them]
	117	+subsection 3.3 In the third workflow, Nalan Kraunanayake, a PhD in Biomedical Engineering and Prof. Dr. Stanislav S. Makhanov both working at Thammasat University in Thailand, present a project in which contour grouping is investigated. Using robot simulations of visual neuro function, the group explores how local and global stimulus properties affect contour grouping. Here, EBRAINS tools and services such as the NRP, NEST and L2L support this research.
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110	110	subsection 3.4 Igori Comarovschii, Mickkel Vinding and Prof. Daniel Lundqvist from the Karolinska Institute as well as Pascal Helson for the KTH Royal Institute of Technology in Sweden present a work- flow that investigates beta oscillations in Parkinson’s Disease and the possibility of DBS treatment. To this end, a multiscale model is constructed based on MEG data collected under different experimental conditions. In particular the effect of DBS should be studied in this model. Thus, the overall goal is to create a workflow that leads from raw MEG data to a prediction of how MEG activity is influenced by DBS. This is accomplished with the aid of BIDS manager, Knowledge Graph, TVB, TVB imaging pipeline, NEST, and L2L. [The maturity level of this project is probably already advanced but this is something we have to ask them]
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112		-subsection 3.5 PhD student Niccolò Mattiello of Gerardo Biella’s group at the University of Pavia is investigating the different functional interactions of heterogeneous neurons in the entorhinal and perirhinal cortex. With this aim in mind he first focuses on single neuron model properties, collecting and analysing the data with the help of Neo, Elephant, Elephant Vis, BluePyEfe and Neuro Tech Mesh and, in a subsequent step investigates how the different experimental results influence the neuron’s activity in a simulated environment using Arbor, Neuron, BluePyEfe, BluePyOpt, L2L, Validation Framework and Hippo Unit. In a second step a larger cortical network is considered. Here data analysis can be carried out via Nutil and VisuAlign, Ilastik and Neuro Tech Mesh. For the creation of a model of a large network and its simulation, Brain Scafold Builder, Arbor, Core Neuron ViSimple, Neuroscheme, BluePyOpt, L2L, and Network Unit are considered. [The maturity level of this project is not known - we have to ask him]
	121	+subsection 3.5 PhD student Niccolò Mattiello of Gerardo Biella’s group at the University of Pavia is investigating the different functional interactions of heterogeneous neurons in the entorhinal and perirhinal cortex. With this aim in mind he first focuses on single neuron model properties, collecting and analysing the data with the help of Neo, Elephant, Elephant Vis, BluePyEfe and Neuro Tech Mesh and, in a subsequent step investigates how the different experimental results influence the neuron’s activity in a simulated environment using Arbor, Neuron, BluePyEfe, BluePyOpt, L2L, Validation Framework and Hippo Unit. In a second step a larger cortical network is considered. Here data analysis can be carried out via Nutil and VisuAlign, Ilastik and Neuro Tech Mesh. For the creation of a model of a large network and its simulation, Brain Scafold Builder, Arbor, Core Neuron ViSimple, Neuroscheme, BluePyOpt, L2L, and Network Unit are considered.
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114	114	Worflow 6:Katia Djerround, a master student at the Algerian University of Science and Technology Houari Boumediene, Nathaniel Adibuer, a research assistant at the University of Ghana, and Aziz Ullah Khan, a professional engineer from X, aim to develop a systematic approach for utilizing EEG data in Brain Computer Interfaces (BCI). A GDPR compliant data storage location combined with a standard data processing procedure should be made possible using the Health data cloud and tools like Frites and Neo. As a second step, the potential of MEG data for steering a robot is examined using the NRP. Finally, the loop is closed by exploring the potential of EEG signals to interact with a robotic application via a TVB simulation embedded in a NRP environment. Currently, this project is in the planning stage.
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117	117	**3.1 Workflow 1**
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