Description: How memory representation changes in different cortical and subcortical regions under 7T, and how the stability of such representations predicts memory quality. We used representational similarity analysis and drift diffusion modeling to explore the data.
Project url: https://github.com/Lingwei-oy/memory_NSD
Contributors: Michelle Shipkova, Chaebin Yoo, Sahithyan Sivakumaran, Ozoswita Roy Deb, Eva Lout, Lingwei Ouyang, [Denisse Bolaños-Ramirez] (https://github.com/DenisseeBR), Vinay, & Halil
Description: A repository containging scripts to perform infomap community detection on the Drosophilia Connectome from flywire.ai. Contains a GUI to run Infomap community detection with the ability to adjust number of synapses to include (measure of degree), which classes of neurotransmitters, and number of internal trials. Contains plotting GUI to visualize infomap communties across different hierarchical levels and options to adjust size based on neuron degree. Project url: https://github.com/NeuroHackademy2025/fly_connectome Contributors: Nathan Labora, Jake Chernicky,Ilia Ernston
Description: Welcome to NeuroSites — a curated collection of customizable templates for neuroscience-related websites, including lab pages, personal research sites, and event pages.
Project url: https://github.com/NeuroHackademy2025/NeuroSites
Contributors: Isha Chhabra & Juan Garcia & Menghan Yang & Chloe Hampson & Emina Ayyildiz
Description: Predicting cognitive decline based on brain volume using OASIS-2 (Open Access Series of Imaging Studies) data, which consists of a longitudinal collection of older adults with and without dementia characterization.
Project url: https://github.com/NeuroHackademy2025/high-dimensionality-prediction
Contributors: Gabriela Franca & Sam Brunson & Vanessa Morgan &
Jocelyn Ricard & Xin Du & Yewande Taiwo & Maria Pitteri & Bijay Adhikari & Tengwen Fan & Ais Sheldon
Description: An Aggregated, Curated, & Itemized Collection of Open and Available Precision Functional Mapping (PFM) from Resting State fMRI Data
Project url: https://github.com/NeuroHackademy2025/precision-paths
Contributors: Jonathan Ahern & Elizabeth Li Shuxuan & Sujin Park
Description: Real-time fMRI neurofeedback processing package for closed-loop experiments. Current version enables real-time pattern classification with a pretrained scikit-learn classifier object.
Project url: https://github.com/NeuroHackademy2025/neuroloopy
Contributors: Caleb Jerinic-Brodeur & Deepasri Prasad & Hildelith Leyser & Lynn Kurteff & Nikhitha D
Description: A flexible python package that allows you to take a label from any space (volume or surface, template or native), and project it into the sapce of any structural image/map of the brain to extract metrics of strucutral properties.
Project url: https://github.com/NeuroHackademy2025/func-struct_extractor
Contributors: Jamie Mitchell & John Romero & Svenja Seuffert
Description: Create a tool that analyzes DICOM headers and leverages Large Language Models (LLM) to automatically generate heuristic files for HeuDiConv, streamlining the conversion from DICOM to BIDS.
Project url: https://github.com/NeuroHackademy2025/llm-heuristics
Contributors: Tien Tong
Description: A Python package that builds on MNE to provide modular, BCI-task-specific visualization and preprocessing.
Project url: https://github.com/NeuroHackademy2025/bci-vis
Contributors: Niv Cohen
Description: This analysis is aimed at discovering differences between healthy and depressed brains using the Transdiagnostic connectome project. We tested differences in network metrics like global efficiency and nodal degree between healthy and depressed populations and used functional connectivity to predict the degree of depression using a graph neural network.
Project url: https://github.com/NeuroHackademy2025/func_connectivity
Contributors: Andrea Fernandes & Chris Weinberger & Clara Pecci & Danial Khoshsoroor & Diego Ramirez Gonzalez & Samantha Eaton
Description: Based on previous work, we tried a new approach to compute the cortical magnification on HCP retinotopy data.
Project url: https://github.com/NeuroHackademy2025/pRF-project_NH2025
Contributors: Adrian Wong & Uriel Lascombes
Description: FAIRyTale is an open-source tool that helps researchers align their project structure with the FAIR (Findable, Accessible, Interoperable, Reusable) and Open Science principles. It supports two main workflows: (1) Create a FAIR-ready repository by uploading your files — the tool automatically organizes them into a standardized structure. (2) Validate an existing project folder — check if your current project follows FAIR principles and get recommendations for improvement.
Project url: https://github.com/NeuroHackademy2025/open-science-pipeline
Contributors: Florencia Altschuler & Annika Andersson & Illiana Sandoval & Jaime Rios
Description: In this analysis project, we are extracting patterns of functional dynamics during a naturalistic fMRI task and comparing that activity to narrative event boundaries.
Project url: https://github.com/natalie-mcclain/narratives-project
Contributors: Natalie McClain & Ben Scheve
Description: We compared deep learning and machine learning methods to create biomarkers for predicting tumor (glioma) grade (lo v. hi) using FA in an open access dataset (PDGM).
Project url: https://github.com/NeuroHackademy2025/GlioGrade
Contributors: Carli Fine & Jessica Ojeda & Nate Overholtzer & Mahsa Servati & Isla Xiao & Dan Zhou
Description: Using HBN dMRI dataset to predict developmental stage (age)
Project url: https://github.com/NeuroHackademy2025/EEG_DTI_analysis
Contributors: Lital Cohen-Blum
Description: In this exploratory data analysis project, we examined the functional and effective connectivity between healthy and depressed individuals using the Transdiagnostic connectome project. We used machine learning to predict how prevalent how each brain region contributes to the diagnosis of depression.
Project url: https://github.com/NeuroHackademy2025/fmri_animal_model_translation
Contributors: Yashoda Krishna Das, Anudeep Vadrevu, Mert Ozkan & Giulia Vasirani