cerc-aai/BFM-EEG-700m

General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data

[General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data]

Model Details

Model Description

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• —Model type: T5-large
• —License: [More Information Needed]
• —Finetuned from model: Chronos-t5-large

How to Get Started with the Model

Visit our GitHub to Get Started with the Model.

Here is colab notebook for inference of the Moabb dataset.

Training Data:

The training data used was the NMT EEG dataset. NMT is an open-source, annotated dataset comprising healthy and pathological EEG recordings. It consists of 2,417 recordings from unique participants, providing multichannel EEG data along with labels indicating the participants' pathological state, classified as normal or abnormal. Each EEG channel is treated as an independent time series, which is further divided into two segments: a context window for conditioning and a prediction target window.

Hyperparameters are the same as those used in the Chronos paper.