Final feedback

main.tex

@@ -97,13 +97,13 @@
 
 \authors{Stefano Moia\textsuperscript{1, 2}, %
 Hao-Ting Wang\textsuperscript{3}, %
-Anibal S Heinsfeld\textsuperscript{4, 5}, %
+Anibal S. Heinsfeld\textsuperscript{4, 5}, %
 Dorota Jarecka\textsuperscript{6}, %
 Yu-Fang Yang\textsuperscript{7}, %
 Stephan Heunis\textsuperscript{8}, %
 Arshitha Basavaraj\textsuperscript{9}, %
-Johanna M. M.  Bayer\textsuperscript{10, 11}, %
-Roza G Bayrak\textsuperscript{12}, %
+Johanna M. Bayer\textsuperscript{10, 11}, %
+Roza G. Bayrak\textsuperscript{12}, %
 Pierre-Louis Bazin\textsuperscript{13, 14}, %
 Isil Poyraz Bilgin\textsuperscript{3, 15}, %
 Steffen Bollmann\textsuperscript{16, 17}, %
@@ -117,16 +117,16 @@
 Jan Ernsting\textsuperscript{25, 26, 27}, %
 Inês Esteves\textsuperscript{28}, %
 Oscar Ferrante\textsuperscript{29}, %
-Kelly G Garner\textsuperscript{30}, %
+Kelly G. Garner\textsuperscript{30}, %
 Rémi Gau\textsuperscript{31}, %
-Elodie  Germani\textsuperscript{32}, %
-Tara TG Ghafari\textsuperscript{29}, %
-Satrajit S Ghosh\textsuperscript{6, 33}, %
+Elodie Germani\textsuperscript{32}, %
+Tara Ghafari\textsuperscript{29}, %
+Satrajit S. Ghosh\textsuperscript{6, 33}, %
 Sarah Elizabeth Goodale\textsuperscript{34}, %
-Cassandra D Gould van Praag\textsuperscript{35, 36}, %
+Cassandra D. Gould van Praag\textsuperscript{35, 36}, %
 Samuel Guay\textsuperscript{37}, %
 Omer Faruk Gulban\textsuperscript{38, 23}, %
-Yaroslav O  Halchenko\textsuperscript{39}, %
+Yaroslav O. Halchenko\textsuperscript{39}, %
 Michael Hanke\textsuperscript{8, 40}, %
 Peer Herholz\textsuperscript{41}, %
 Katja Heuer\textsuperscript{42}, %
@@ -135,19 +135,19 @@
 Renzo Huber\textsuperscript{45}, %
 Ole Jensen\textsuperscript{29}, %
 Kan Keeratimahat\textsuperscript{46}, %
-Julian Q Kosciessa\textsuperscript{47}, %
+Julian Q. Kosciessa\textsuperscript{47}, %
 Sladjana Lukic\textsuperscript{48}, %
 Neville Magielse\textsuperscript{8, 49, 50}, %
-Christopher J Markiewicz\textsuperscript{51}, %
-Caroline G Martin\textsuperscript{52}, %
+Christopher J. Markiewicz\textsuperscript{51}, %
+Caroline G. Martin\textsuperscript{52}, %
 Camille Maumet\textsuperscript{53}, %
 Anna Menacher\textsuperscript{54}, %
 Jeff Mentch\textsuperscript{6, 55}, %
 Shammi More\textsuperscript{8, 40}, %
 Leonardo Muller-Rodriguez\textsuperscript{56, 57}, %
 Samuel A. Nastase\textsuperscript{58}, %
 Eliana Nicolaisen-Sobesky\textsuperscript{8}, %
-Dylan M Nielson\textsuperscript{59}, %
+Dylan M. Nielson\textsuperscript{59}, %
 Christopher R. Nolan\textsuperscript{30}, %
 François Paugam\textsuperscript{60, 61}, %
 Pedro Pinheiro-Chagas\textsuperscript{62}, %
@@ -158,16 +158,16 @@
 Roberta Rocca\textsuperscript{65}, %
 Jacob Sanz-Robinson\textsuperscript{66}, %
 Kelvin Sarink\textsuperscript{26}, %
-Kevin R Sitek\textsuperscript{67}, %
+Kevin R. Sitek\textsuperscript{67}, %
 Nadine Spychala\textsuperscript{68}, %
 Rüdiger Stirnberg\textsuperscript{24}, %
 Michał Szczepanik\textsuperscript{8}, %
 Mohammad Torabi\textsuperscript{69}, %
 Roberto Roberto Toro\textsuperscript{42}, %
 Sebastian GW Urchs\textsuperscript{70}, %
 Sofie L. Valk\textsuperscript{14, 8, 71}, %
-Adina S Wagner\textsuperscript{8, 72}, %
-Laura K Waite\textsuperscript{8}, %
+Adina S. Wagner\textsuperscript{8, 72}, %
+Laura K. Waite\textsuperscript{8}, %
 Alexander Q. Waite\textsuperscript{8}, %
 Lea Waller\textsuperscript{73}, %
 Tyler James Wishard\textsuperscript{74, 75}, %
@@ -260,21 +260,21 @@
 \begin{abstract}
 OHBM Brainhack 2022 took place in June 2022. The first hybrid OHBM hackathon, it had an in-person component taking place in Glasgow and three hubs around the globe to improve inclusivity and fit as many timezones as possible.
 In the buzzing setting of the Queen Margaret Union and of the virtual platform, 23 projects were presented for development.
-Following are the reports of 12 of those, as well as a recapitulation of the organisation of the event. 
+Following are the reports of 14 of those, as well as a recapitulation of the organisation of the event. 
 \end{abstract}
 
 \section*{Introduction}
 
-The Organisation of Human Brain Mapping BrainHack (shortened as OHBM
-Brainhack in the article ) is a yearly satellite event of the main OHBM
+The Organisation of Human Brain Mapping BrainHack (shortened to OHBM
+Brainhack in the article) is a yearly satellite event of the main OHBM
 meeting, organised by the Open Science Special Interest Group following
 the model of Brainhack hackathons \parencite{Gau2021}.
 Where other hackathons set up a competitive environment based on
-outperforming other participants' projects, Brainhacks privilege a
+outperforming other participants' projects, Brainhacks fosters a
 collaborative environment in which participants can freely collaborate
 and exchange ideas within and between projects.
 
-This edition of the OHBM Brainhack, that run across the world over four
+This edition of the OHBM Brainhack, that ran across the world over four
 days, was particularly special for two reasons: it celebrated the tenth
 year anniversary of Brainhack, and, like the main OHBM conference, it
 was the first edition to feature an in-person event after two years of
@@ -287,14 +287,14 @@ \section*{Introduction}
   Providing a hybrid event incorporating the positive aspects of
   in-person and virtual events alike,
 \item
-  Celebrating the 10\textsuperscript{th} year anniversary of the
-  Brainhack by bringing back a hands-on newcomer-friendly hacking and
+  Celebrating the 10\textsuperscript{th} anniversary of the
+  Brainhack by bringing back newcomer-friendly hands-on hacking and
   learning experience, enhancing the Hacktrack and formatting the
   Traintrack as a collection of materials to consult beforehand and as
   spontaneous meetings of the participants aimed to learn together,
 \item
   Bridging the gap between the Brainhack community and the main
-  neuroimaging software developer group, e.g. AFNI, FSL, SPM,
+  neuroimaging software developer groups, e.g. AFNI, FSL, SPM,
 \item
   Due to amount of work required to meet the previous three principles,
   incorporating from the beginning a team of core organisers with a
@@ -306,9 +306,7 @@ \section*{Introduction}
   events overall. 
 \end{enumerate}
 
-The next pages, after a quick explanation of each main contribution of
-the core team, are dedicated to the summaries of the projects that were
-developed during the four days of hacking.
+After a quick explanation of each main contribution of the core team, the next pages are dedicated to the summaries of the projects that were developed during the four days of hacking.
 
 \section{Hacktrack}
 
@@ -318,12 +316,12 @@ \section{Hacktrack}
 Stefano Moia}
 %
 
-The key component of each Brainhack is hacking. Hacking part, known as
+The key component of each Brainhack is hacking. The hacking part, known as
 hacktrack, is where attendees collaborate on projects and explore their
 own ideas. There are 4 elements of hacktrack that were organised:
 project submission, project pitch, hacking period and project summary.
 For the project submission, we used the GitHub issue submission process
-that was used during the recent years. We updated and simplified a
+that was used during recent years. We updated and simplified a
 project template from previous years and asked project leaders to open
 an issue for each project. Each issue after quick check was approved by
 the moderators and automatic workflows written by the team were
@@ -341,7 +339,7 @@ \section{Hacktrack}
 This edition we allowed remote attendance from other locations. We
 organised three hubs aiming to cover all time zones, including 1)
 Asia-Pacific, 2) Glasgow, Europe, Middle East, and Africa, and 3) the
-Americas, to foster inclusiveness in hybrid conference format. We also
+Americas, to foster inclusiveness in the hybrid conference format. We also
 ensured that each hub had one live streamed session with the physical
 hub in Glasgow.
 
@@ -369,11 +367,11 @@ \section{Traintrack}
 space not used for hacking) for attendees to self-organise. Participants
 were encouraged to form study groups on five suggested topics: 1)
 setting up your system for analysis 2) python for data analysis, 3)
-Machine learning for neuroimaging, 4) Version control systems, 5) Cloud
+machine learning for neuroimaging, 4) version control systems, 5) cloud
 resource. The curated content was advertised on the main hackathon
 website. One dedicated channel was created on the hackathon Discord
-server. Individuals can determine the nature of their experiences and
-the skills they would like to acquire. Participants can form their own
+server. Individuals could determine the nature of their experiences and
+the skills they liked to acquire. Participants could form their own
 study group and on any selected topic. We would like to continue the
 experimentation on this format in the coming year.
 
@@ -389,7 +387,7 @@ \section{Platforms, website, and IT}
 The first solution was the project's advertisement, in which the
 community promotes their projects, the goals for the Hackathon, and
 relevant information to get people interested and set to collaborate. To
-do so, we have used the Github Issues feature in the Hackathon
+do so, we used the Github Issues feature in the Hackathon
 repository as the entrance for projects. Github Issues has been proven
 to be accepted by the community that relies on Github for code
 versioning, and was a successful approach in past hackathons.

summaries/VASOMOSAIC.tex

@@ -9,7 +9,7 @@ \subsection{MOSAIC for VASO fMRI}
 R\"udiger Stirnberg, %
 Philipp Ehses, %
 \"Omer Faruk G\"ulban, %
-Benedikt A Poser}
+Benedikt A. Poser}
 
 Vascular Space Occupancy (VASO) is a functional magnetic resonance imaging (fMRI) method that is used for high-resolution cortical layer-specific imaging \parencite{Huber2021a}. Currently, the most popular sequence for VASO at modern SIEMENS scanners is the one by \textcite{Stirnberg2021a} from the DZNE in Bonn, which is employed at more than 30 research labs worldwide. This sequence concomitantly acquires fMRI BOLD and blood volume signals. In the SIEMENS' reconstruction pipeline, these two complementary fMRI contrasts are mixed together within the same time series, making the outputs counter-intuitive for users. Specifically:
 

summaries/neuroscout.tex

@@ -11,7 +11,7 @@ \subsection{Neuroscout: A platform for fast and flexible re-analysis of (natural
 Jeff Mentch, %
 Kevin Sitek, %
 Caroline Martin, %
-Leonardo Muller, %
+Leonardo Muller-Rodriguez, %
 Kan Keeratimahat, %
 Dylan Nielson}
 

summaries/physiopy-documentation.tex

@@ -4,8 +4,8 @@
 
 \subsection{Physiopy - Documentation of Physiological Signal Best Practices}
 
-\authors{Ines Esteves, %
-Sarah E. Goodale, %
+\authors{Sarah E. Goodale, %
+Ines Esteves, %
 Roza G. Bayrak, %
 Neville Magielse, %
 Stefano Moia, %
@@ -23,7 +23,7 @@ \subsection{Physiopy - Documentation of Physiological Signal Best Practices}
 
 Physiological data provides a representation of a subject’s internal state with respect to peripheral measures (i.e., heart rate, respiratory rate, etc.). Recording physiological measures is key to gain understanding of sources of signal variance in neuroimaging data that arise from outside of the brain \parencite{chen2020}. This has been particularly useful for functional magnetic resonance imaging (fMRI) research, improving fMRI time-series model accuracy, while also improving real-time methods to monitor subjects during scanning \parencite{bulte2017, caballero-gaudes2017}. 
 
-Physiopy (\url{https://github.com/physiopy}) is an open and collaborative community, formed around the promotion of physiological data collection in neuroimaging studies. Physiopy is focused on two main objectives. The first is the community-based development of tools for fMRI-based physiological processing. At the moment, there are three toolboxes: \textit{phys2bids} (physiological data storage and conversion to BIDS format \parencite{phys2bids}, \textit{peakdet} (physiological data processing), and \textit{phys2denoise} (fMRI denoising). The second objective is advancing the general knowledge of physiological data collection in fMRI by hosting open sessions to discuss best practices of physiological data acquisition, preprocessing, and analysis, and promoting community involvement. Physiopy maintains documentation with best practices guidelines stemming from these joint discussions and recent literature.
+Physiopy (\url{https://github.com/physiopy}) is an open and collaborative community, formed around the promotion of physiological data collection and incorporation in neuroimaging studies. Physiopy is focused on two main objectives. The first is the community-based development of tools for fMRI-based physiological processing. At the moment, there are three toolboxes: \textit{phys2bids} (physiological data storage and conversion to BIDS format \parencite{phys2bids}, \textit{peakdet} (physiological data processing), and \textit{phys2denoise} (fMRI denoising). The second objective is advancing the general knowledge of physiological data collection in fMRI by hosting open sessions to discuss best practices of physiological data acquisition, preprocessing, and analysis, and promoting community involvement. Physiopy maintains documentation with best practices guidelines stemming from these joint discussions and recent literature.
 
 At the OHBM 2022 Brainhack, we aimed to improve our community documentation by expanding on best practices documentation, and gathering libraries of complementary open source software. This provides new users resources for learning about the process of physiological collection as well as links to already available resources.The short-term goal for the Brainhack was to prepare a common platform (and home) for our documentation and repositories. We prioritised fundamental upkeep and content expansion, adopting Markdown documents and GitHub hosting to minimise barriers for new contributors. Over the course of the Brainhack, and with the joint effort within three hubs (Glasgow, EMEA and Americas), we were able to improve the current community website by rethinking its structure and adding fundamental content relative to who we are, contributions, and updated best practices, such as creating home pages, easy to find and navigate contribution tabs, adding new information from community best practices discussions as well as links to relevant software and datasets. Additionally, we  aggregated the information scattered across different repositories, allowing important information for both the community and new collaborators to be accessible in a single location. 
 

summaries/rba.tex

@@ -7,7 +7,7 @@ \subsection{Handling multiple testing problem through effect calibration: implem
 \authors{%
 Lea Waller, %
 Kelly Garner, %
-Christopher R Nolan, %
+Christopher R. Nolan, %
 Daniel Borek, %
 Gang Chen}