Working Groups are composed of users and developers from across the INCF network working collaboratively to develop, refine, and/or implement community standards. Working Groups are composed of SIG members working on short-term funded projects that aim to achieve a concrete deliverable.
This SIG deals with the various tools and formats for creating and sharing representations of biological neuronal networks, and will work towards ensuring these are as interoperable and usable as possible for computational neuroscientists.Read more
The SIG aim is to collect, compile, synthesize and distribute information from task forces working on separate projects but with reproducibility in neuroimaging as an overarching theme.Read more
This SIG aims to coordinate community efforts for the development of open, use case driven and shared validatable data models (schemas, vocabularies) to enable the FAIR principles (Findable, Accessible, Interoperable and Reusable) for basic, computational and clinical neuroscience (meta)data.Read more
The aim of this working group is to develop a small, well-scoped ontology for describing electrophysiology stimulation parameters. The working group is composed of representatives from the INCF network, Human Brain Project (HBP), Neurodata Without Borders (NWB) Core Development Team, and Stimulating Peripheral Activity to Relieve Conditions (SPARC).
The… Read more
This project is for measurements of brain dynamics of a patient to their disease diagnosis. It further reduces complexities by distilling a large literature on time series analysis into a small subset. It selects only the significant features to represent the time series for analysis, with minimal loss in classification accuracy. The optimized and efficiently coded features will… Read more
Develop a web-based system that takes an analysis method as python code from a user, computes it with a diverse time-series dataset and analyzes the relation of the newly developed method with the pre-existing one.Read more
GeNN is a GPU-enhanced Neuronal Network simulation package in C++, that combines the ease of code generation, primarily for the purpose of setting up the parameters of the simulation through a model definition, with the flexibility of user-defined code, to actually run the simulation and record results. While there are several SNN libraries available, by combining GeNN and standard machine… Read more
The project aims to provide a robust mechanism for cell tracking using 2D raw image objects. Through the use of Mean Square Distance method the potential object displacements will be calculated. Another set of images will be fed as time lapse protocol. Trajectory estimate will be denoised using different modern filters such as IMM,Weiner and Multiple Channel Linear Correlation Filter.Read more
The aim is conversion of large scale cortical models into PyNN/NeuroML involves the conversion of published large scale network models into open, simulator independent and testing them across multiple simulator implementations.Read more
The project proposes an idea to create a generalized basic framework, which can coherently describe Brian models in a standard format. The standard format shall act as the foundation for exporting Brian models to NeuroML/LEMS format, human-readable like LaTeX typesetting, ModelView description and also shall be flexible enough to extend with various other model descriptors or frameworks.Read more
Improving Personalized Models of fMRI Recordings Including Individual Region-Specific HRF in The Virtual Brain
TVB also allows simulation of BOLD activity, however, it suffers from the drawback of considering a standard model of HRF across subjects as well as across brain regions of a particular subject. To improve this, we propose to first estimate the rsHRF of all the voxels from fMRI input data, and then average these values over the regions used in TVB. These values can consequently be… Read more
LORIS is an open-source framework that facilitates data sharing for neuroscience labs and sites. It hosts both frontend and backend services that help facilitate data sharing and manipulation among researchers. The codebase includes many modules that perform different functionalities. Therefore, this type of service requires automated testing to ensure that all the moving parts are working… Read more
The objective of this project is to offer end users new visualizations for time-series data within LORIS. This would allow better interpretation of data shared online through LORIS and paves the path for more comprehensive analytical tools with regards to the data being visualized. This alo requires the data uploaded to meet certain formats or to convert it to certain formats. Along with a… Read more
The REST API is an easy way to securely access, retrieve and manipulate the sensitive data about the subjects stored in LORIS. This data contained in Loris should be easily accessible to the researchers allowed to use it, but such information is very personal to the subjects, so the security of these actions on Loris’ database is of foremost importance for ensuring the subjects confidentiality… Read more
The goal of this project is to develop deep learning-based methods that can achieve image registration in one-shot resulting in much faster registration speeds. In this project, I propose to develop deep neural networks (DNNs) for MRI registration using thin-plate splines, free-form deformations, and affine transformationsRead more
The OpenDevoCell Integration with OpenWorm is to solve some of the barriers existing in OpenWorm, it not only helps the other researchers to see and appreciate our work but it would also help to organize this organization functioning in the coming days. OpenDevoCell is going to be the one-stop portal so that everyone from any part of the world can access our work in an… Read more
The project aims to contribute to NWB Showcase made available at NWB Explorer 2 on the Open Source Brain repository 3 . The proposed project will deliver multiple converted datasets to be viewed at the NWB Explorer and will integrate tutorials and analysis examples for select converted datasets.Read more
The top priorities of this proposal are:
Train a deep learning model(s) from the image dataset(s) provided.
In the process of training, develop a data augmentation pipeline which can be used on the cellular image datasets (even on the cellular images which are not involved in this project) to help build… Read more
The Workflow Designer is a prototype web-based application allowing drag-and-drop creating, editing, and running workflows from a predefined library of methods. Moreover, any workflow can be exported or imported in JSON format to ensure reusability and local execution of exported JSON configurations. The application is primarily focused on electroencephalographic signal processing and deep… Read more
Responsive dashboards for extensive exploration, monitoring, and reviewing of large neuroimaging datasets
This project will create a flexible dashboard framework which can further improve and add new features as per the changing requirements or needs of the user.Read more
Primary goal is to create a basic GUI interface for the reconstruction pipeline which gives the ability to users to provide input data, choose configurations, identify the outputs, and check logs in case of any problem which occurs during the whole process.
The SciUnit framework was developed to help researchers create unit tests for scientific models. Currently, unit tests exist for models of single neurons and small networks thereof. However, unit tests for models concerned with large-scale brain network dynamics, such as meso-scale, mean-field descriptions and corticothalamic circuit models have not been developed yet. During… Read more
Past Working Groups
This SIG aims to bring together experimentalists within the glial community with computational modellers, with objective to provide a forum to foster detailed interactions and advance astro-centric brain models.Read more
This SIG will coordinate interactions among researchers who are interested in reproducible research issues and open science. We will promote policies that support reproducibility, encourage better training in this area, and organize information about resources to make them more visible to the neuroscience community.Read more