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Huth Lab @HuthLab

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

Joined December 2016
  • Tweets 9
  • Following 8
  • Followers 494
Photos and videos
Huth Lab retweeted
Shailee Jain@shaileeejain
24 Aug 2023
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... 1/2
Alexander Huth@alex_ander
23 Aug 2023
Our big language fMRI dataset is now officially published! 📰 The paper: nature.com/articles/s41597-0… (free pdf: nature.com/articles/s41597-0…) 🧰 Code to download data & build models: github.com/HuthLab/deep-fMRI… 💾 The dataset: openneuro.org/datasets/ds003…
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Huth Lab retweeted
Jerry Tang@jerryptang
1 May 2023
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 nature.com/articles/s41593-0…

Semantic reconstruction of continuous language from non-invasive brain recordings

Nature Neuroscience - Tang et al. show that continuous language can be decoded from functional MRI recordings to recover the meaning of perceived and imagined speech stimuli and silent videos and...

nature.com
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Huth Lab retweeted
Richard Antonello@NeuroRJ
4 Nov 2022
Why are language models so great at encoding brain responses to natural language? In our new paper (bit.ly/3Ua8MLK), we explore two new correlates of encoding performance and their implications on cognitive theories of language processing. (1/12)
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Huth Lab retweeted
Jerry Tang@jerryptang
30 Sep 2022
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 biorxiv.org/content/10.1101/…

Semantic reconstruction of continuous language from non-invasive brain recordings

A brain-computer interface that decodes continuous language from non-invasive recordings would have many scientific and practical applications. Currently, however, decoders that reconstruct continu...

biorxiv.org
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Huth Lab retweeted
Amanda LeBel@AmandaLeBel3
24 Sep 2022
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. biorxiv.org/content/10.1101/…

A natural language fMRI dataset for voxelwise encoding models

Speech comprehension is a complex process that draws on humans’ abilities to extract lexical information, parse syntax, and form semantic understanding. These sub-processes have traditionally been...

biorxiv.org
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Huth Lab retweeted
Shailee Jain@shaileeejain
22 Oct 2020
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): 2020.neurolang.org/?p=slides…

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Huth Lab retweeted
Chris Holdgraf@choldgraf
6 Dec 2018
Cool poster from @shaileeejain and @alex_ander using LSTM models to include contextual information in language encoding models! Finally some actual neuroscience @ #NeurIPS2018
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Huth Lab@HuthLab
7 Sep 2018
It was the first preprint, now it’s gonna be the first paper from our lab!
Alexander Huth@alex_ander
7 Sep 2018
Coming to NIPS this year: @shaileeejain’s paper on using LSTM language models for predicting fMRI data!
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Huth Lab retweeted
Alexander Huth@alex_ander
22 May 2018
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 x.com/biorxiv_neursci/status…

bioRxiv Neuroscience@biorxiv_neursci
21 May 2018
Incorporating Context into Language Encoding Models for fMRI biorxiv.org/cgi/content/shor… #biorxiv_neursci
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