Article

BrainLM: A foundation model for brain activity recordings

2023-09-13

Abstract excerpt

<h4> A bstract </h4> We introduce the Brain Language Model (BrainLM), a foundation model for brain activity dynamics trained on 6,700 hours of fMRI recordings. Utilizing self-supervised masked-prediction training, BrainLM demonstrates proficiency in both fine-tuning and zero-shot inference tasks. Fine-tuning allows for the accurate prediction of clinical variables like age, anxiety, and PTSD as well as forecast...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 89c91cdc-c524-5a10-b22d-7e381ba0e451
DOI: 10.1101/2023.09.12.557460

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

BrainLM: A foundation model for brain activity recordingsDOI 10.1101/2023.09.12.557460Read

Towards a general-purpose foundation model for fMRI analysisSemantic proximity Read

Unsupervised Representation Learning Reveals Individualized Neurophysiological ProfilesSemantic proximity Read

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of ConfoundsSemantic proximity Read

st-DenseViT: A Weakly Supervised Spatiotemporal Vision Transformer for Dense Prediction of Dynamic Brain NetworksSemantic proximity Read

Modeling individual-level long-range brain dynamics from short fMRI scansSemantic proximity Read

osl-dynamics: A toolbox for modelling fast dynamic brain activitySemantic proximity Read

PI-FC: Pre-training Individual-specific Functional Connectome through State-invariant Contrastive LearningSemantic proximity Read

Explanatory latent representation of heterogeneous spatial maps of task-fMRI in large-scale datasetsSemantic proximity Read

Interpretable Transformer Models for rs-fMRI Epilepsy Classification and Biomarker DiscoverySemantic proximity Read

Predicting brain activity using TransformersSemantic proximity Read

Representation Learning of Resting State fMRI with Variational AutoencoderSemantic proximity Read

Quantifying Dysregulation of fMRI-Derived Control Circuits for Computational PsychiatrySemantic proximity Read