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The measurement of visual function in infants and young children is crucial for early detection and treatment of eye conditions that can lead to visual deprivation and affect visual development. However, the limited cooperation and inability to provide verbal responses in infants make the accurate and efficient measurement of visual function challenging. This project aims to develop a ready-to-deploy application suite that will address these limitations by integrating hardware devices or deep learning-based infant eye trackers, and visual stimuli analysis into a user-friendly graphical user interface (GUI).

The platinum open access overlay neuroscience journal - Neurons, Behavior, Data Analysis, and Theory – NBDT is ready for inclusion in PubMed Central (PMC). However, PMC requires full-text machine-readable XML article file deposits. These files contain the complete article text in machine-readable language, with front-matter metadata. At the moment, final paper submissions to NBDT are in LaTeX format. While there are tools that provide LaTeX to XML conversion (as required by PMC), no single tool does it seamlessly without errors for the template corresponding to NBDT. The current project aims to build an application providing this functionality. The project will build over the LaTeXML tool to enhance custom bindings as required for NBDT submissions. The first step would be to enhance the bindings for body matter, as Scholastica (which hosts NBDT) already provides it for front-matter binding. In addition, to make the application platform-independent, it will be extended to provide custom front-matter and back-matter bindings. It shall also contribute verification engines to automate XML verification, JATS verification, and PMC-specific verification. The application shall make it convenient to bridge NBDT submissions and the PMC archival process.

<p>This Project is about quantifying the quality of the Validation Tests (CerebTests), a part of CerebUnit Ecosystem for validation tests which needs to be implemented as a sub-module in CerebStats, another part of the CerebUnit ecosystem for statistical functions.</p>

<p>This proposal outlines the steps and experience needed for a javascript based data visualization tool for LORIS through the React framework. A method to validate uploaded data will be needed to be integrated as well with proper testing and documentation after weekly meetings and feedback from mentor(s) to ensure project deadlines are met.</p>

Project Deliverables • Implement a Project edit button, file and project rename functionality, fix edit project popup , allow editing list of notebooks , and add images to each type of notebook. • Implement support for Jupyter notebooks. Users should be able to upload, view, and edit Jupyter notebooks on the platform. Use Jupyter Lite, or nbviewer, or nbconvert to render notebooks in HTML format. • Allow users to fork existing projects. Forking should create a new project that is linked to the original, allowing users to experiment with changes without affecting the original project. • Improve the project creation and editing process. Add validations for project names to ensure uniqueness. Enhance the project edit functionality to prefill forms with existing information and update project names and routes when edited. • Implement a user permission system to differentiate between project members and followers. Users can join projects as members or follow them with the project owner's permission. • Set up a continuous integration system for automated Docker container generation. • Migrate the project's blob storage to Jetstream. Ensure a seamless transition with minimal downtime and data loss. Set up automated, regular database backups. • Bug Fixes: Address existing bugs in the platform, such as issues with the registration code, disappearing navbar account menu, and join button behavior, to improve user experience and platform stability. • Implement an organization system where users can create and manage organizations. Organizations can have multiple projects and users associated with them. Define roles such as admin, members, and followers within organizations to manage permissions and access levels. • Implement comments in projects and logs along with a reply-to field, vote field to up/down voting, and a ‘flag’ field for flagging.

The proposal aims to address the issue of the expensive and inaccessible research publishing industry by leveraging modern internet-based social technology to create an open reviewing and quality-ranking web portal. The portal will facilitate manuscript submission and an automated, free, community-based open access, peer review, and quality-rating system. The project will develop a proof of concept portal using ReactJS/NextJS and TailwindCSS for the frontend, Django for the backend, and PostgreSQL as the database server. The deliverables include a functional web portal that allows for detailed comments, ratings, and reputation-based filtering, which can improve the quality of research and provide a platform for communities of reviewers to form and manage the reviewing process. The system will eventually be tested with the Aperture Neuro open access publishing platform of the Organization for Human Brain Mapping (OHBM), in consultation with that community.

<p>This project aims to improve the automated testing of the LORIS codebase. This will be achieved through writing both unit and integration tests, as well as improving the datasets available in the LORIS database that can be used for testing. The majority of the automated testing will be for the backend services, although some frontend tests may be developed as well.</p>

To Remove Bootstrap from the application and substitute the design with pure SCSS.To finish implementing the CSS global variables and add component wise CSS variables to improve the reusability of code in the application.To add CSV viewing functionality on the datasets of AnalySim to view, filter, and browse through the columns of the file. To create a feature on the Jupyter notebooks to make the Notebooks downloadable.To improve the Registration page, Explore section page, and my Dashboard page design and make the User Interface consistent throughout the application.To remove the pages and the page links that are unused in the application. To improve and redesign the project creation page. To make the design of the application consistent throughout the application to create a great User experience.

I am planning to improve how AnalySim looks by simplifying pages to assure that it is both practical and easy for users to navigate through it. I also plan to modify the aesthetics of the website by ensuring that all pages go by the same color scheme, as there are some pages with similar colors to each other, but not the same hex code. I will also make sure all pages are under the same Angular and Bootstrap technology. I want to create GIFs that will not only aid in navigating the website but also represent the graphs that will be generated on AnalySim.I also plan to create web pages to query, browse and filter a CSV file. -Update the existing interface to the latest Angular -Add Bootstrap technology to all website pages -Design the Website to have a consistent look -Continue implementation of design -Create new pages that are needed for various operations such as browsing projects, filtering projects, searching for topics, etc. -Create a graphical design that is modern and unique to this project, maybe by incorporating some meaningful GIFs. -Create a page to browse CSV files -Create a webpage to query and filter a CSV file -Create a webpage to display various interactive graphics that can be used for -publication by researchers such as histograms -Assure that users can download and print high-quality images -Assure that all web pages are printable -Simplify web pages -Create guidelines that are easy to understand as GIFs to help people navigate the system -Communicate and help other developers on the project to make sure that the system functions properly -Make the footer consistent on all pages, without wasting so much space -Finalize the Contact Us page

This project focuses on enhancing the overall workflow by improving the detection and configuration of the Emscripten toolchain. It aims to optimize data transfer between the WebAssembly simulation and JavaScript for efficient result visualization. Additionally, it provides user-friendly tools for website customization and plot display. Comprehensive documentation will be included to ensure ease of use and integration.

<p>Currently the human assistive system collects the EEG data, processes it and trains customized classifiers. With the increasing number of tested subjects, the goal is to store the rapidly growing data in a distributed storage system such as Apache Hadoop. Data processing would also be implemented on the distributed system using the MapReduce framework and its extension Apache Spark.</p> <p>The goal of this project is to create a scalable system which would enable storage of very large datasets and quick, distributed training of classifiers on those large datasets. Another goal is to provide the users with a GUI for browsing and managing the distributed filesystem as well as building full machine learning pipelines.</p>

<p>A GIN micro-service which allows the users to design efficient workflows for their work - probably by automating Snakemake, and build the workflows with a Continuous Integration (CI) service. Given the GIN user base of neuro-scientists and other professionals from the related fields, shouldn’t be involved in writing thousands of repeated workflows for their data, and then testing them manually. This tool increases their efficiency by almost exponential levels by eradicating redundancy from their work.</p>

<p>This project is a continuous work for the GSoC2018 Dynamic Signal Processing Workflow Designer. The previous existing project is a Web-based GUI to deal with the cumulative signal, offering users configurable component blocks to design their own workflows in the GUI and execute the workflows without making change on code. This year, to make this designer also process the continuous stream and mixed data, and improve the executing efficiency, make the code more understandable and maintainable, redesign and refactor are needed for the workflow designer.</p>

<p>The release of a new NWB version makes it necessary the reintegration of this format into the awesome open-source in-browser neuroscientific simulator, Geppetto. This integration will allow any Geppetto based application to be able to provide visualization of simulated data alongside of electrophysiology recordings.</p> <p>The purpose of this project is to make the above happen.</p>

Editing CSV/Displaying CSV files CSV file viewing and sorting for AnalySim datasets, that can be sorted and filtered. I will study how to create and edit/delete CSV files using javascript, From here i will convert the CSV into an .html Table to be shown to the user Implementation of selecting columns and constraints that filters the data based on these conditions Account Confirmation Email Will have a backend implementation to ensure that the email is functional and confirmed. When creating an account, a link should be sent to user’s email, and when clicked it should be confirmed on the backend that the account is valid .net core framework to add code into the database to verify the email. Getting permission from project owner This function will enable the owner to select people that they want to work with on their project. Ensuring permission will prevent any bad actors from messing up a project. Add an invite notification when an owner invites a collaborator to the project Enable editing/admin permission to requested user/collaborator

Eye tracking has varieties of applications ranging across usability and user experience research, gaming, driving, and gaze-based interaction for accessibility to healthcare. The smartphone gaze could also provide a digital phenotype for screening or monitoring health conditions such as autism spectrum disorder, dyslexia, concussion, and more The project idea is to develop an eye tracker using deep learning in Python using TensorFlow/PyTorch. The work was to improve and update a neural network based, state of the art eye tracker

<p>The project will focus on constructing a Web GUI for Reconstruction pipeline. The reconstruction pipeline takes RMN images as input and processes them, then produces files that are compatible with TVB. Links together tools like Freesurfer, MRtrix, FSL, Pegasus WMS. Integrate the GUI with workflow engine (Pegasus) in order to provide job status and job execution statistics is the main part of the project. GUI for such a pipeline would greatly improve our user experience. So, in this project our goal is to make the GUI more interactive and user-friendly.</p>

The Active Segmentation platform for ImageJ (ASP/IJ) was developed in the scope of GSOC 2016 - 2021. The plugin provides a general-purpose environment that allows biologists and other domain experts to use transparently state-of-the-art techniques in machine learning to achieve excellent image segmentation and classification. ImageJ is a public-domain Java image processing program extensively used in life and material sciences. The program was designed with an open architecture that provides extensibility via plugins computing different filters and region descriptors (i.e. image features). The feature space and the classification results produced by the platform are stored in several separate files. The idea is that the types and values of image features and classification outcomes would be stored in an SQLite database for cross-comparisons between sessions. The candidate is required to use the SQLite database engine in order to integrate it with the GUI of ASP/IJ.

LORIS is a comprehensive data management platform that supports diverse datasets in neuroscience research, including imaging, behavioural, clinical, and genetic data. As part of my contributions, I will focus on implementing new modules to extend the platform’s capabilities. These modules may include advanced data processing pipelines, automated anomaly detection for quality control, and enhanced user authentication mechanisms to ensure secure access to sensitive medical data. Additionally, I aim to develop tools for improved data annotation, visualisation, and integration with external analytics frameworks. By enhancing the modular architecture of LORIS, my work will help streamline research workflows, improve data integrity, and facilitate broader adoption of the platform within the scientific community.

<p>ImageJ is an open source Java image processing and analysis library used extensively in biomedical sciences. Active Segmentation is a plugin providing user interface to scientists, allowing them to use Machine Learning algorithms for segmentation and classification tasks. The aim of the Active Segmentation is to provide researchers an extensible toolbox enabling them to select custom filters and machine learning algorithms for their research. Moreover, it provides the support for scientists without strictly technical background (does not require programming skills to apply above mentioned tools). The idea behind this project is to extend active segmentation with modern deep learning methods for image analysis using Deeplearning4j library.</p>

<p>Maxima is a computer algebra system, which has been growing for the past 40 years. However, given the growing use of Python in Neuroscience, under the need of a common platform for scientific computation and numerical capabilities, I propose:</p> <ol> <li>To work on making a Maxima-to-Python translator, which will be entirely accessible from a running Maxima instance. It will be a loadable Maxima add-on.</li> <li>To write tests for the translator, to ensure it is not buggy and is usable.</li> <li>To document the code for both - the end user, and developer.</li> </ol>

We are trying to solve the difficulty of collaboration among multiple users working on large datasets, particularly in analyzing datasets with many parameters and essential features that need to be filtered, measured, and analyzed. The solution is AnalySim, a data-sharing platform that simplifies collaboration by providing easy sharing, analysis, visualization, and collaboration capabilities on datasets. The first deliverable is the ability to embed Jupyter notebooks, Observablehq notebooks, and Google Collab notebooks on the website using an interactive panel. The second deliverable is an interactive panel or interface that displays a dataset's different types of features, including minimum, maximum, mean, number of non-zero, and the number of invalid values. The interface should show other visualization options like histograms, pie charts, multi-series line charts, pie charts, graphs, and visualizations representing data with more than two dimensions, e.g., 3D Scatter plots, 3D Mesh Plots, 3D line plots, box plots, and bubble charts. The third deliverable is the ability for users to add publications related to the datasets in a project. We will achieve this by creating a text editor page where users can add content, edit content, remove content, add tables, and add images. The text editor should allow users to add latex code so that users can publish mathematical analyses of the findings. We will also implement a page that gets the list of publications, which should contain clickable items that redirect to another page that details the publication. Finally, we will refactor some of the code to maintain a better project structure, encapsulate numerous fragments of the same code in another method to improve the readability of the code and remove deprecated methods.

The project develops an improved Python-based CLI for the CBRAIN distributed computing platform, aiming on usability and modular design. It replaces complex command usage with interactive, prompt-based workflows, reducing reliance on memorization. The system leverages existing CBRAIN API routes and restructures the codebase into a clean, feature-based architecture. It supports user, project, file, task, and data provider management, along with advanced operations like authentication, batch processing, multi-session, data upload / download, file querying / selection and server control. Administrative tools for logs, quotas, and system monitoring are included. Overall, the project delivers a scalable, maintainable, and user-friendly CLI that enhances productivity.