1 citations · 1 across the 2 of their papers we have counts for
4 papers
MEG-Mamba: A Scalable State-Space Foundation Model for Magnetoencephalography
Chetan Gohil, SungJun Cho, Oiwi Parker Jones +1
Magnetoencephalography (MEG) is an imaging technique that offers a non-invasive, millisecond-resolution view of human brain activity. The increasing availability of MEG data presen…
A Systematic Evaluation of Sample-Level Tokenization Strategies for MEG Foundation Models
SungJun Cho, Chetan Gohil, Rukuang Huang +2
Recent success in natural language processing has motivated growing interest in large-scale foundation models for neuroimaging data. Such models often require discretization of con…
MEG-GPT: A transformer-based foundation model for magnetoencephalography data
Rukuang Huang, Sungjun Cho, Chetan Gohil +2
Modelling the complex spatiotemporal patterns of large-scale brain dynamics is crucial for neuroscience, but traditional methods fail to capture the rich structure in modalities su…
osl-ephys: A Python toolbox for the analysis of electrophysiology data
Mats W. J. van Es, Chetan Gohil, Andrew J. Quinn +1
We describe OHBA Software Library for the analysis of electrophysiological data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique an…