Official repository for "A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains", NeurIPS-23.
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Updated
Feb 6, 2024 - Jupyter Notebook
Official repository for "A Dual-Stream Neural Network Explains the Functional Segregation of Dorsal and Ventral Visual Pathways in Human Brains", NeurIPS-23.
Load and model the brain data of the Algonauts Project 2023 Challenge.
Code for my Master's Thesis "Deep Neural Encoding Models of the Human Visual Cortex to Predict fMRI Responses to Natural Visual Scenes" and my submission for the "Algonauts Project 2023 Challenge".
MIND: Mixture-of-Experts Integrated Decoder for Multimodal Brain Encoding (ICASSP 2026)
A lightweight multimodal brain-encoding research prototype distilled from TRIBE v2 for predicting fMRI responses to naturalistic video.
🧠 Find songs that feel alike by how a brain would respond to them, not by tempo or genre.
Validates whether META's TRIBE v2 predicted brain activations help LLMs understand emotion. 3-condition A/B/C experiment, 100 samples, ElevenLabs audio + local LLM inference.
Neural attention analytics — predict brain responses to any video using TRIBE v2 (Meta FAIR)
Subcortical response analysis for video stimuli using TRIBE v2.
Compare two videos by the brain response Meta's TRIBE v2 predicts. Serverless GPU backend on Modal, 3D cortex viewer in React + three.js.
Predicting a new person's EEG/fMRI responses to images from a few hundred labels: borrow other people's encoders, then fit a small personal map. Prespecified tests on THINGS-EEG1/2, Alljoined, NSD and NOD.
Neuroimaging preprocessing, brain decoding, and visual brain encoding using fMRI, EEG/MEG, CNNs, VLMs, and transformer representations
Exploring AI brain encoding models and neural activation mapping
Simulate a persona reading your copy, predict the cortical response with Meta's TRIBEv2, and get evidence-grounded rewrites.
Don't follow the herd. Predict it. Brain-encoded swarm social simulation engine. First project built on Meta TRIBE v2.
Functional ultrasound vs. a brain foundation model on the same speech experiment. Measures fUSI response timing from data (later and broader than the fMRI convention), and replays the paradigm through Meta's TRIBE v2 with acoustic controls: its audio pathway is fooled by reversed speech. Tested, reproducible pipeline.
fMRI encoding models comparing biological visual hierarchy (NSD 7T) against CNNs, Vision Transformers, and Multimodal CLIP with interactive visualization.
Modular brain encoding pipeline aligning transformer-based NLP embeddings with fMRI data for brain-language analysis.
Predicts a human audience's second-by-second neural engagement with a movie trailer before anyone watches it. Meta FAIR TRIBE v2 (V-JEPA2 + Wav2Vec-BERT + Llama 3.2) turns video into 20,484 fMRI vertices, mapped across 7 brain regions into 5 emotions, with scene peaks, personas and a PDF report.
Drop a clip. See which cortical regions it would drive in an average brain. In-silico fMRI around Meta TRIBE v2 — encoding, not decoding.
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