neural-decoding

A MATLAB package for modelling multivariate stimulus-response data

Emotion classification from Brain EEG signals using a hybrid CNN-Transformer model and various ML algorithms.

The open closed-loop OS for gamma-entrainment research — a Rust/WASM/edge harness to measure, adapt & compare 40 Hz multisensory stimulation protocols with signed, reproducible evidence. Research-grade, not a medical device.

Bio-Silicon Synergetic Intelligence System

The code repository for "MB2C: Multimodal Bidirectional Cycle Consistency for Learning Robust Visual Neural Representations" in PyTorch

Compact and interpretable MEG-to-audio retrieval with explicit spatial and temporal filters.

Code for "MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training" at ICML 2026

Stable and aligned spike sorting and decoding over long-term recordings in BCI

Code supplement for "The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models"

CVPR 2026 | Structure-aware label-free test-time calibration for cross-subject EEG-to-image retrieval.

Code for the paper "Towards Unified Brain-to-Text Decoding Across Speech Production and Perception"

Code repository for "CRISP: Curriculum based Sequential neural decoders for Polar code family" - ICML 2023

Image Reconstruction from Brain fMRI imaging using Diffusion Models

[INTERSPEECH 2025]Official code for "MiSTR: Multi-Modal iEEG-to-Speech Synthesis with Transformer-Based Prosody Prediction and Neural Phase Reconstruction"

Transformer-based EEG intent detection model classifying real vs. imagined movements for assistive robotics applications.

This repository is for ACL 2022 findings paper: Cross-Modal Cloze Task: A New Task to Brain-to-Word Decoding.

Hippocampus spike activity related to the depression-related behaviors after stress. Propose the stress determinator

Scripts to perform hyperalignment and movie segment decoding using the Budapest dataset.

Code for the paper "Predicting Artificial Neural Network Representations to Learn Recognition Model for Music Identification from Brain Recordings".

Open-source, local-first EEG/MEG language-decoding research toolkit with bounded data access, honest baselines, reproducible caches, and explicit proof boundaries.