@HuthLab

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

 Berkeley, CA
cs.utexas.edu/~huth
Joined December 2016
  • Tweets9
  • Following8
  • Followers492
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_ander23 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…

A natural language fMRI dataset for voxelwise encoding models

Scientific Data - A natural language fMRI dataset for voxelwise encoding models

nature.com
1
4
1
24
2,459
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
15
76
24
212
43,433
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)
3
62
4
214
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
52
438
348
2,180
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
3
57
7
226
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…
7
2
22
Cool poster from @shaileeejain and @alex_ander using LSTM models to include contextual information in language encoding models! Finally some actual neuroscience @ #NeurIPS2018
1
3
20
It was the first preprint, now it’s gonna be the first paper from our lab!
Alexander Huth@alex_ander7 Sep 2018
Coming to NIPS this year: @shaileeejain’s paper on using LSTM language models for predicting fMRI data!
1
1
4
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 xitter.cf/biorxiv_neursci/status…
bioRxiv Neuroscience@biorxiv_neursci21 May 2018
Incorporating Context into Language Encoding Models for fMRI biorxiv.org/cgi/content/shor… #biorxiv_neursci
2
25
1
75
Load more