brain-encoding

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".

A lightweight multimodal brain-encoding research prototype distilled from TRIBE v2 for predicting fMRI responses to naturalistic video.

MIND: Mixture-of-Experts Integrated Decoder for Multimodal Brain Encoding (ICASSP 2026)

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.

🧠 Find songs that feel alike by how a brain would respond to them, not by tempo or genre.

Modular brain encoding pipeline aligning transformer-based NLP embeddings with fMRI data for brain-language analysis.

Don't follow the herd. Predict it. Brain-encoded swarm social simulation engine. First project built on Meta TRIBE v2.

Drop a clip. See which cortical regions it would drive in an average brain. In-silico fMRI around Meta TRIBE v2 — encoding, not decoding.

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.