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By Pierre Bergeret
July 15, 2026
An automated tool that trains a multimodal classification model (EEG + fMRI) to predict phenotypic variables (sex, age, diagnosis) and assess whether fusing both modalities improves prediction compared to each modality alone.
By Katrina Mae Tapang, Monika Folkierska-Żukowska, & Xinni Wang
June 26, 2026
Thyroid hormone levels potentially impact cortical structures and cognitive performance. This project aims to investigate if TSH levels and cortical structure can predict cognitive performance for executive function, attention, and working memory using Elastic Net Regression.
By Bradley Austin-Keiller
June 19, 2026
pSynchronicity is a real-time synchrony-feedback prototype built with goofi-pipe. Multiple participants tap along to a metronome, then keep tapping together once it stops. A modular node pipeline timestamps taps, scores how ‘in sync’ the group is moment-by-moment, and drives live visual feedback. MIDI tapping is the first test signal, but the pipeline is designed to later accept movement, respiration, or heart-rate data as forms of interpersonal synchrony.
By Grace Burns, Alena Ionova, Gaithtry Rameswaran, & Talia Fiaani
This project investigates how resting-state functional connectivity differs between sleep and wake states using simultaneous EEG and fMRI data from the OpenNeuro “Simultaneous EEG and fMRI signals during sleep from humans” dataset. By comparing default mode network connectivity and EEG frequency-band connectivity across states, the project found minimal differences at the network level but a reliable increase in theta-band connectivity during sleep, highlighting the value of combining modalities to characterize state-dependent brain connectivity.
By Sebastian Rodriguez
June 11, 2026
This project is a complete and reproducible ML pipeline using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to: Predict tau PET SUVR as a continuous outcome, predict tau positivity as a binary outcome (classify participants as tau-positive or tau-negative), and identify which predictors drive model performance using SHAP explainability
By Oceane Mourgues, Hugo Delhaye, & Lune Bellec
June 8, 2026
An interactive and reproducible framework for organizing, visualizing, and acoustically analyzing crowd sound stimuli. Features include automated feature extraction, dimensionality reduction (PCA, UMAP), statistical group comparison, and interactive audio exploration with waveform and spectrogram visualization.
By Arthur Toulouse
June 20, 2025
Focal epilepsy is a type of epilepsy in which seizures originate from a specific region of the brain, often associated with structural abnormalities visible on neuroimaging. Accurate localization of the epileptogenic zone is essential for effective treatment planning, especially in cases considered for surgical intervention. In this project, we aim to classify the anatomical region of seizure onset using structural MRI data (T1-weighted images) processed with FreeSurfer.
By Hugo Albert Plante
This project aims to accurately compute the optic nerve g-ratio, a key neuroimaging marker reflecting myelin integrity in nerve fibers. Using advances quantitative MRI techniques, it analyses the human optic nerve’s microstructure non-invasively. By integrating MP2RAGE and diffusion MRI, it seeks to improve assessment of myelin and nerve health, contributing to better understanding, early detection, and diagnosis of neurological diseases like multiple sclerosis (MS).
By Ingrid Campbell, & Amanda/Tianyi Liu
June 19, 2025
In this project we use EEG patterns to predict treatment responses for individuals with ADHD across different age groups. Project reports are incorporated in the BHS website.
By Samantha Bjelis, & Fardin Islam
Using EEG band power to investigate cognitive states during golf swings and correlate them with subjective performance ratings.
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159 participants have uploaded their projects.
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