Huth Lab

computational & experimental neuroscience/CS lab at UC Berkeley. fMRI + language + machine learning. Looking for students and postdocs! PI: @alex_ander

[Shailee Jain @shaileeejain]

Our ✨Large-scale fMRI dataset on naturalistic language✨is now out in Nature Scientific Data!

MANY hours (5 to 16 per indiv) on MANY ppl (8 indiv)!

We also included code to fit encoding models exactly like all @HuthLab papers!

Pls read @alex_ander's awesome thread on...

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[Jerry Tang @jerryptang]

Our language decoding paper (@AmandaLeBel3 @shaileeejain @alex_ander) is out! We found that it is possible to use functional MRI scans to predict the words that a user was hearing or imagining when the scans were collected https://t.co/hpYSGAHNQi

[Richard Antonello @NeuroRJ]

Why are language models so great at encoding brain responses to natural language?
In our new paper (https://t.co/V8Gil16otn), we explore two new correlates of encoding performance and their implications on cognitive theories of language processing. (1/12)

[Jerry Tang @jerryptang]

very excited to share our paper on reconstructing language from non-invasive brain recordings! we introduce a decoder that takes in fMRI recordings and generates continuous language descriptions of perceived speech, imagined speech, and possibly much more https://t.co/HJ34WYG8ab

[Amanda LeBel @AmandaLeBel3]

New Dataset Alert!

I'm very happy to official announce a naturalistic language fMRI dataset now available! This dataset includes 8 participants listening to 5 hours each of the moth radio hour. https://t.co/7xBusEeUE4

[Shailee Jain @shaileeejain]

Excited to attend my first #SNL2020 today and learn from *real* neuroscientists! Come hear me talk about some new research on **Discovering patterns of semantic integration across the🧠** :)

Slide session B (11:30-13:00 hrs PT): https://t.co/GoiBZgf3o7

[Chris Holdgraf @choldgraf]

Cool poster from @shaileeejain and @alex_ander using LSTM models to include contextual information in language encoding models! Finally some actual neuroscience @ #NeurIPS2018

[Huth Lab @HuthLab]

It was the first preprint, now it’s gonna be the first paper from our lab!

[Alexander Huth @alex_ander]

Coming to NIPS this year: @shaileeejain’s paper on using LSTM language models for predicting fMRI data!

[Alexander Huth @alex_ander]

ayy it's the first preprint from my lab! 🎉 @shaileeejain uses LSTM language models to generate features that incorporate context & are better at predicting brain activity than word embeddings https://t.co/uPdocsxRcZ