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 members working on short-term funded projects that aim to achieve a concrete deliverable.
This Working Group 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.
The Working Group 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.
This Working Group 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 (…
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,…
- Reduce complexities by distilling a large literature on time series analysis into a small subset
- Minimize loss of classification accuracy by using only significant features to represent the time series, with minimal loss in classification accuracy
- Package coded features…
- Develop a new web-based system to compare different time series analysis methods
- System will take python code input, compute it with a diverse time-series dataset, and analyze the relation of the newly developed method with the pre-existing one.
- Combine GeNN and other machine learning packages using Python (PyGeNN, TensorFlow, Jupyter for tutorials) and C++ (GeNN)
- Provide easier code generation and code flexibility
- Compare the performance of different models
- Provide a robust mechanism for cell tracking using 2D raw image objects
- Use the Mean Square Distance method to calculate the potential object displacement
- Denoise the trajectory estimate using different modern filters such as IMM,Weiner and Multiple Channel Linear…
- Convert published large scale network models into open, simulator independent models
- Test models across multiple simulator implementations
- Create a general, interoperable framework to 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, and ModelView description
Improving Personalized Models of fMRI Recordings Including Individual Region-Specific HRF in The Virtual Brain
To simulate subject- and region-specific BOLD signals by estimating the rsHRF of all the voxels from fMRI input data, then averaging these values over the regions used in TVB.
- Develop deep learning-based methods to achieve faster image registration
- Develop deep neural networks (DNNs) for MRI registration using thin-plate splines, free-form deformations, and affine transformations
- Contribute to the NWB Showcase
- Deliver multiple converted datasets
- Integrate tutorials and analysis examples for select converted datasets
- Train a deep learning model(s) from the image dataset(s) provided
- Develop a data augmentation pipeline which can be used on the cellular image datasets (incl. images which are not involved in this project) to help build a model robust enough for its purpose
- Make the…
To allow drag-and-drop creating, editing, and running workflows in JSON format from a predefined library of methods, focusing on EEG signal processing and deep learning workflows
Responsive dashboards for extensive exploration, monitoring, and reviewing of large neuroimaging datasets
Create a flexible dashboard framework which can be customized to suit user requirements
Past Working Groups
This Working Group 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 Working Group 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