Jerry Tang

postdoctoral fellow at UT Austin interested in language disorders and brain-computer interfaces

[Jerry Tang @jerryptang]

This was an incredibly rewarding project to work on. Thanks to the amazing team that made this possible! Carly Millanski, Allison Chen, Lisa Wauters, Jordyn Anders, @ShilpaShamapant , @smwilsonau, @alex_ander, Maya Henry

8/8

[Jerry Tang @jerryptang]

We're excited to share our new study on decoding brain activity in participants with post-stroke aphasia! We think this is an important step towards cognitive brain-computer interfaces for patients with language disorders

https://t.co/UrzC5qgzDO

1/8

[Jerry Tang @jerryptang]

We also found good decoding performance from individual brain regions. This suggests that we could move our decoder from fMRI into more portable systems. The best regions differed across participants so we think fMRI will remain very important for localizing recording sites

7/8

[Catherine Chen @cathychen23]

How does the human brain represent semantic information from different languages?

Our new preprint suggests that bilingual language comprehension relies on shared semantic representations that are systematically modulated by each language!

1/n

[Catherine Chen @cathychen23]

Do brain representations of language depend on whether the inputs are pixels or sounds?

Our @CommsBio paper studies this question from the perspective of language timescales. We find that representations are highly similar between modalities! https://t.co/xVaMHKcCOi

1/8

[Jerry Tang @jerryptang]

I’ll be presenting this work at the #NeurIPS2023 5pm poster session on Wednesday — come by to chat about the relationship between language and vision in the brain!

[Alexander Huth @alex_ander]

Multimodal transformers make it possible to transfer fMRI encoding models between language and vision! (though mostly from L->V and not V->L 🤔) New paper from @jerryptang @_du_meng @vvobot @vasudev_lal https://t.co/sO8F1vBp65

[Amanda LeBel @AmandaLeBel3]

This paper and dataset is now officially published in Scientific Data!! And not only that but we have nearly doubled the amount of data and stimulus available since the preprint version.

Link to paper here: https://t.co/fxaZGAK0pZ

1/n

[Frank Willett @WillettNeuro]

Our new study is out today in Nature! We demonstrate a brain-computer interface that turns speech-related neural activity into text, enabling a person with paralysis to communicate at 62 words per minute - 3.4 times faster than prior work. 1/3 https://t.co/6pB7NLAqjG

[Kaylo Littlejohn @KayloLittlejohn]

Our paper on a high-performance neuroprosthesis for speech decoding and avatar control is out in Nature! Thankful to work with such a great interdisciplinary team on this. https://t.co/8qiSKaxAFq

[Shailee Jain @shaileeejain]

🌟NEW PREPRINT🌟
🤖-based🧠models are all the rage!

But,
- How do we interpret 🧠if 🤖are SO un-interpretable?
- How do we _test_ if🤖are good models of 🧠? (No, your prediction score is NOT the answer)

Our new paper (co-lead @vvobot) shows you how!
https://t.co/jFKkSUo4b3

1/9

[Jerry Tang @jerryptang]

And here's a short explainer of how our decoder works and what it can do! https://t.co/WkTU7J6vAg

[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

[Jerry Tang @jerryptang]

If you want to learn more about brain decoding, I wrote a quick introduction to how brain decoding technology works and how we think it could impact society https://t.co/ChSoqE0Mpn

[Jerry Tang @jerryptang]

https://t.co/ZcvJUQg719

[Jerry Tang @jerryptang]

this is generating a lot of discussion and we wanted to clear a few things up. first, we take privacy very seriously and reject the use of brain decoders for surveillance, interrogation, and other unethical applications

[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

[Jerry Tang @jerryptang]

many thanks to the fantastic team @AmandaLeBel3 @shaileeejain @alex_ander that made this possible. we'll be at SNL and SFN over the next few months, so drop by if you'd like to learn more! (7/7)