Jiawei Li
@jiaweili.bsky.social
Postdoc @ Neural dynamics of visual cognition (Cichy lab) @FU_Berlin
interested in language🗣️📖 and its representations in the brain🧠
https://jiawei-liiiii.github.io/
interested in language🗣️📖 and its representations in the brain🧠
https://jiawei-liiiii.github.io/
Reposted by Jiawei Li
A very useful review and update on the anatomic infratstructure for language:
"Brain structural networks underlying language" by
Angela Friederici
journals.physiology.org/doi/abs/10.1...
"Brain structural networks underlying language" by
Angela Friederici
journals.physiology.org/doi/abs/10.1...
Brain structural networks underlying language | Physiological Reviews | American Physiological Society
The unique human ability to process complex language requires the interaction of multiple brain areas located in the inferior frontal and posterior temporal cortex connected by white matter fiber trac...
journals.physiology.org
November 14, 2025 at 1:41 PM
A very useful review and update on the anatomic infratstructure for language:
"Brain structural networks underlying language" by
Angela Friederici
journals.physiology.org/doi/abs/10.1...
"Brain structural networks underlying language" by
Angela Friederici
journals.physiology.org/doi/abs/10.1...
Reposted by Jiawei Li
happy to share our new paper, out now in Neuron! led by the incredible Yizhen Zhang, we explore how the brain segments continuous speech into word-forms and uses adaptive dynamics to code for relative time - www.sciencedirect.com/science/arti...
Human cortical dynamics of auditory word form encoding
We perceive continuous speech as a series of discrete words, despite the lack of clear acoustic boundaries. The superior temporal gyrus (STG) encodes …
www.sciencedirect.com
November 7, 2025 at 6:16 PM
happy to share our new paper, out now in Neuron! led by the incredible Yizhen Zhang, we explore how the brain segments continuous speech into word-forms and uses adaptive dynamics to code for relative time - www.sciencedirect.com/science/arti...
Reposted by Jiawei Li
New preprint led by @pablooyarzo.bsky.social together with @kohitij.bsky.social, Diego Vidaurre & Radek Cichy.
Using EEG + fMRI, we show that when humans recognize images that feedforward CNNs fail on, the brain recruits cortex-wide recurrent resources.
www.biorxiv.org/content/10.1... (1/n)
Using EEG + fMRI, we show that when humans recognize images that feedforward CNNs fail on, the brain recruits cortex-wide recurrent resources.
www.biorxiv.org/content/10.1... (1/n)
www.biorxiv.org
November 7, 2025 at 9:39 AM
New preprint led by @pablooyarzo.bsky.social together with @kohitij.bsky.social, Diego Vidaurre & Radek Cichy.
Using EEG + fMRI, we show that when humans recognize images that feedforward CNNs fail on, the brain recruits cortex-wide recurrent resources.
www.biorxiv.org/content/10.1... (1/n)
Using EEG + fMRI, we show that when humans recognize images that feedforward CNNs fail on, the brain recruits cortex-wide recurrent resources.
www.biorxiv.org/content/10.1... (1/n)
Reposted by Jiawei Li
This was a fabulous, once in a lifetime colloquium -- and now the videos are available in high quality on the College de France web site @college-de-france.fr
www.college-de-france.fr/fr/agenda/co...
With talks by Edvard Moser, Nancy Kanwisher, Liz Spelke, Manuela Piazza, Luca Bonatti and more!
www.college-de-france.fr/fr/agenda/co...
With talks by Edvard Moser, Nancy Kanwisher, Liz Spelke, Manuela Piazza, Luca Bonatti and more!
November 2, 2025 at 3:08 PM
This was a fabulous, once in a lifetime colloquium -- and now the videos are available in high quality on the College de France web site @college-de-france.fr
www.college-de-france.fr/fr/agenda/co...
With talks by Edvard Moser, Nancy Kanwisher, Liz Spelke, Manuela Piazza, Luca Bonatti and more!
www.college-de-france.fr/fr/agenda/co...
With talks by Edvard Moser, Nancy Kanwisher, Liz Spelke, Manuela Piazza, Luca Bonatti and more!
Amazing work and cute cat!
Delighted to share our new paper, now out in PNAS! www.pnas.org/doi/10.1073/...
"Hierarchical dynamic coding coordinates speech comprehension in the brain"
with dream team @alecmarantz.bsky.social, @davidpoeppel.bsky.social, @jeanremiking.bsky.social
Summary 👇
1/8
"Hierarchical dynamic coding coordinates speech comprehension in the brain"
with dream team @alecmarantz.bsky.social, @davidpoeppel.bsky.social, @jeanremiking.bsky.social
Summary 👇
1/8
PNAS
Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans...
www.pnas.org
October 22, 2025 at 7:40 AM
Amazing work and cute cat!
Reposted by Jiawei Li
#JNeurosci: Ferris et al. found when people recall a story that was detailed with personal interpretations or emotions, this triggers different memory mechanisms than when they recall a story that instead emphasized external, more concrete descriptions. https://doi.org/10.1523/JNEUROSCI.1936-24.2025
October 20, 2025 at 6:11 PM
#JNeurosci: Ferris et al. found when people recall a story that was detailed with personal interpretations or emotions, this triggers different memory mechanisms than when they recall a story that instead emphasized external, more concrete descriptions. https://doi.org/10.1523/JNEUROSCI.1936-24.2025
Reposted by Jiawei Li
My attempt to depict the neural architecture of language as motivated in my forthcoming book, Wired for Words. Like colors represent functional connectivity. Main insight: linguistic levels are all organized with a sensorimotor-like architecture. pbs.twimg.com/media/G2cwsM...
October 4, 2025 at 10:32 PM
My attempt to depict the neural architecture of language as motivated in my forthcoming book, Wired for Words. Like colors represent functional connectivity. Main insight: linguistic levels are all organized with a sensorimotor-like architecture. pbs.twimg.com/media/G2cwsM...
Reposted by Jiawei Li
How do humans and large language models (LLMs) represent sentences? Liu et al. design a rule inference task, revealling that both humans and LLMs implicitly decomposes a sentence into tree-structured constituents.
Active use of latent tree-structured sentence representation in humans and large language models - Nature Human Behaviour
How do humans and large language models (LLMs) represent sentences? Liu et al. design a rule inference task revealing that both humans and LLMs implicitly decompose sentences into tree-structured constituents.
www.nature.com
September 10, 2025 at 12:21 PM
How do humans and large language models (LLMs) represent sentences? Liu et al. design a rule inference task, revealling that both humans and LLMs implicitly decomposes a sentence into tree-structured constituents.
Reposted by Jiawei Li
Apply until 14 September! 👋 Together with our partners, we invite early & mid-career researchers based in Germany to participate in the Sino-German Frontiers of Science and Technology Symposium. #FrontiersOfResearch
📆 23-26 April 2026
📌 Suzhou, China
www.humboldt-foundation.de/en/apply/spo...
📆 23-26 April 2026
📌 Suzhou, China
www.humboldt-foundation.de/en/apply/spo...
Call for applications
www.humboldt-foundation.de
August 13, 2025 at 2:00 PM
Apply until 14 September! 👋 Together with our partners, we invite early & mid-career researchers based in Germany to participate in the Sino-German Frontiers of Science and Technology Symposium. #FrontiersOfResearch
📆 23-26 April 2026
📌 Suzhou, China
www.humboldt-foundation.de/en/apply/spo...
📆 23-26 April 2026
📌 Suzhou, China
www.humboldt-foundation.de/en/apply/spo...
Reposted by Jiawei Li
*Absolutely* beautiful work characterizing the neural transformations between imagery and perception! 🤩
A transformation from vision to imagery in the human brain. Intriguing new preprint by Roy & Naselaris et al for anyone interested in mental imagery!
www.biorxiv.org/content/10.1...
www.biorxiv.org/content/10.1...
A transformation from vision to imagery in the human brain
Extensive work has shown that the visual cortex is reactivated during mental imagery, and that models trained on visual data can predict imagery activity and decode imagined stimuli. These findings ma...
www.biorxiv.org
September 4, 2025 at 11:55 AM
*Absolutely* beautiful work characterizing the neural transformations between imagery and perception! 🤩
Reposted by Jiawei Li
Happy to share our new preprint. We found that brain adaptively switches between relational and item-based coding strategies based on the structure of memory contents.
@doellerlab.bsky.social
www.biorxiv.org/content/10.1...
@doellerlab.bsky.social
www.biorxiv.org/content/10.1...
Efficient coding in working memory is adapted to the structure of the environment
Working memory (WM) relies on efficient coding strategies to overcome its limited capacity, yet how the brain adaptively organizes WM representations to maximize coding efficiency based on environment...
www.biorxiv.org
August 26, 2025 at 12:54 PM
Happy to share our new preprint. We found that brain adaptively switches between relational and item-based coding strategies based on the structure of memory contents.
@doellerlab.bsky.social
www.biorxiv.org/content/10.1...
@doellerlab.bsky.social
www.biorxiv.org/content/10.1...
Reposted by Jiawei Li
Examples: audio before red line = ground-truth prompt; after = AuriStream’s prediction, visualized in the time-frequency cochleagram space.
AuriStream shows that causal prediction over short audio chunks (cochlear tokens) is enough to generate meaningful sentence continuations!
AuriStream shows that causal prediction over short audio chunks (cochlear tokens) is enough to generate meaningful sentence continuations!
August 19, 2025 at 1:12 AM
Examples: audio before red line = ground-truth prompt; after = AuriStream’s prediction, visualized in the time-frequency cochleagram space.
AuriStream shows that causal prediction over short audio chunks (cochlear tokens) is enough to generate meaningful sentence continuations!
AuriStream shows that causal prediction over short audio chunks (cochlear tokens) is enough to generate meaningful sentence continuations!
Reposted by Jiawei Li
Können Large Language Models (wie #ChatGPT) vorhersagen, wie ein #Gehirn auf visuelle Reize reagiert 🤔 Ja, sagt eine neue Studie von @adriendoerig.bsky.social der #FUBerlin in @natmachintell.nature.com
Alle Infos: tinyurl.com/2s449zc9
#KI #LLM
Alle Infos: tinyurl.com/2s449zc9
#KI #LLM
August 11, 2025 at 12:52 PM
Können Large Language Models (wie #ChatGPT) vorhersagen, wie ein #Gehirn auf visuelle Reize reagiert 🤔 Ja, sagt eine neue Studie von @adriendoerig.bsky.social der #FUBerlin in @natmachintell.nature.com
Alle Infos: tinyurl.com/2s449zc9
#KI #LLM
Alle Infos: tinyurl.com/2s449zc9
#KI #LLM
See you tomorrow at Poster A32! #CCN2025
Check out Jiawei's cool work at her poster tomorrow! Includes neural correlates of auditory processing during reading, and some mysterious negative correlations about which we'd love to hear your ideas.
We may have found the neural correlates🧠 of "the voice🗣️ in your head" when you’re reading📖!
If you’re at CCN and are interested, come chat with us! @adriendoerig.bsky.social @Radoslaw Martin Cichy
**Where:** Session A, Poster A32
**When:** Tuesday, August 12 | 1:30 – 4:30 pm
See you in Amsterdam!
If you’re at CCN and are interested, come chat with us! @adriendoerig.bsky.social @Radoslaw Martin Cichy
**Where:** Session A, Poster A32
**When:** Tuesday, August 12 | 1:30 – 4:30 pm
See you in Amsterdam!
August 11, 2025 at 4:07 PM
See you tomorrow at Poster A32! #CCN2025
We may have found the neural correlates🧠 of "the voice🗣️ in your head" when you’re reading📖!
If you’re at CCN and are interested, come chat with us! @adriendoerig.bsky.social @Radoslaw Martin Cichy
**Where:** Session A, Poster A32
**When:** Tuesday, August 12 | 1:30 – 4:30 pm
See you in Amsterdam!
If you’re at CCN and are interested, come chat with us! @adriendoerig.bsky.social @Radoslaw Martin Cichy
**Where:** Session A, Poster A32
**When:** Tuesday, August 12 | 1:30 – 4:30 pm
See you in Amsterdam!
August 8, 2025 at 12:34 PM
We may have found the neural correlates🧠 of "the voice🗣️ in your head" when you’re reading📖!
If you’re at CCN and are interested, come chat with us! @adriendoerig.bsky.social @Radoslaw Martin Cichy
**Where:** Session A, Poster A32
**When:** Tuesday, August 12 | 1:30 – 4:30 pm
See you in Amsterdam!
If you’re at CCN and are interested, come chat with us! @adriendoerig.bsky.social @Radoslaw Martin Cichy
**Where:** Session A, Poster A32
**When:** Tuesday, August 12 | 1:30 – 4:30 pm
See you in Amsterdam!
Reposted by Jiawei Li
🚨 Finally out in Nature Machine Intelligence!!
"Visual representations in the human brain are aligned with large language models"
🔗 www.nature.com/articles/s42...
"Visual representations in the human brain are aligned with large language models"
🔗 www.nature.com/articles/s42...
High-level visual representations in the human brain are aligned with large language models - Nature Machine Intelligence
Doerig, Kietzmann and colleagues show that the brain’s response to visual scenes can be modelled using language-based AI representations. By linking brain activity to caption-based embeddings from lar...
www.nature.com
August 7, 2025 at 1:06 PM
🚨 Finally out in Nature Machine Intelligence!!
"Visual representations in the human brain are aligned with large language models"
🔗 www.nature.com/articles/s42...
"Visual representations in the human brain are aligned with large language models"
🔗 www.nature.com/articles/s42...
Reposted by Jiawei Li
New paper with @mujianing.bsky.social & @prestonlab.bsky.social! We propose a simple model for human memory of narratives: we uniformly sample incoming information at a constant rate. This explains behavioral data much better than variable-rate sampling triggered by event segmentation or surprisal.
Efficient uniform sampling explains non-uniform memory of narrative stories https://www.biorxiv.org/content/10.1101/2025.07.31.667952v1
August 1, 2025 at 4:45 PM
New paper with @mujianing.bsky.social & @prestonlab.bsky.social! We propose a simple model for human memory of narratives: we uniformly sample incoming information at a constant rate. This explains behavioral data much better than variable-rate sampling triggered by event segmentation or surprisal.
Reposted by Jiawei Li
📣 Great opportunity for our Humboldt Alumni: We’re awarding €30,000 to support your innovative networking initiatives.
Apply by 30 November: www.humboldt-foundation.de/en/apply/alu...
Apply by 30 November: www.humboldt-foundation.de/en/apply/alu...
July 21, 2025 at 2:58 PM
📣 Great opportunity for our Humboldt Alumni: We’re awarding €30,000 to support your innovative networking initiatives.
Apply by 30 November: www.humboldt-foundation.de/en/apply/alu...
Apply by 30 November: www.humboldt-foundation.de/en/apply/alu...
Reposted by Jiawei Li
Check out Zaid's open "Podcast" ECoG dataset for natural language comprehension (w/ Hasson Lab). The paper is now out at Scientific Data (nature.com/articles/s41...) and the data are available on OpenNeuro (openneuro.org/datasets/ds0...).
July 7, 2025 at 9:00 PM
Check out Zaid's open "Podcast" ECoG dataset for natural language comprehension (w/ Hasson Lab). The paper is now out at Scientific Data (nature.com/articles/s41...) and the data are available on OpenNeuro (openneuro.org/datasets/ds0...).
Reposted by Jiawei Li
Vision Deep Neural Networks and Large Language Models complement each other in predicting EEG responses to images, providing a more accurate model of the time course of visuo-semantic processing in the human brain.
#NeuroAI #CompNeuro #neuroscience #AI
arxiv.org/abs/2506.19497
#NeuroAI #CompNeuro #neuroscience #AI
arxiv.org/abs/2506.19497
The time course of visuo-semantic representations in the human brain is captured by combining vision and language models
The human visual system provides us with a rich and meaningful percept of the world, transforming retinal signals into visuo-semantic representations. For a model of these representations, here we lev...
arxiv.org
July 1, 2025 at 5:08 PM
Vision Deep Neural Networks and Large Language Models complement each other in predicting EEG responses to images, providing a more accurate model of the time course of visuo-semantic processing in the human brain.
#NeuroAI #CompNeuro #neuroscience #AI
arxiv.org/abs/2506.19497
#NeuroAI #CompNeuro #neuroscience #AI
arxiv.org/abs/2506.19497
Reposted by Jiawei Li
Using in silico neuroscience, @alessandrogifford.bsky.social et al. developed a neural control algorithm to modulate the representational relationships between visual cortical areas, revealing how these areas jointly represent the world as an interconnected network.
www.nature.com/articles/s41...
www.nature.com/articles/s41...
In silico discovery of representational relationships across visual cortex - Nature Human Behaviour
Using in silico neuroscience, Gifford et al. developed a neural control algorithm to modulate the representational relationships between visual cortical areas, revealing how these areas jointly repres...
www.nature.com
June 25, 2025 at 12:39 PM
Using in silico neuroscience, @alessandrogifford.bsky.social et al. developed a neural control algorithm to modulate the representational relationships between visual cortical areas, revealing how these areas jointly represent the world as an interconnected network.
www.nature.com/articles/s41...
www.nature.com/articles/s41...
Reposted by Jiawei Li
We're happy to announce the Berlin Consciousness Symposium, an in-person event bringing together expert speakers to discuss new trends in the neuroscience of consciousness.
Date: 3rd of July 2025 at @freieuniversitaet.bsky.social @ccnberlin.bsky.social
www.ewi-psy.fu-berlin.de/en/psycholog...
Date: 3rd of July 2025 at @freieuniversitaet.bsky.social @ccnberlin.bsky.social
www.ewi-psy.fu-berlin.de/en/psycholog...
Berlin Consciousness Symposium: New Trends in the Neuroscience of Consciousness
www.ewi-psy.fu-berlin.de
June 18, 2025 at 12:56 PM
We're happy to announce the Berlin Consciousness Symposium, an in-person event bringing together expert speakers to discuss new trends in the neuroscience of consciousness.
Date: 3rd of July 2025 at @freieuniversitaet.bsky.social @ccnberlin.bsky.social
www.ewi-psy.fu-berlin.de/en/psycholog...
Date: 3rd of July 2025 at @freieuniversitaet.bsky.social @ccnberlin.bsky.social
www.ewi-psy.fu-berlin.de/en/psycholog...
Reposted by Jiawei Li
I'm super happy to see our project on topographic neural network models of visual processing out in @nathumbehav.nature.com! Have a look at @zejinlu.bsky.social's thread for details.
Now out in Nature Human Behaviour @nathumbehav.nature.com : “End-to-end topographic networks as models of cortical map formation and human visual behaviour”. Please check our NHB link: www.nature.com/articles/s41...
June 6, 2025 at 11:57 AM
I'm super happy to see our project on topographic neural network models of visual processing out in @nathumbehav.nature.com! Have a look at @zejinlu.bsky.social's thread for details.
Reposted by Jiawei Li
Now out in Nature Human Behaviour @nathumbehav.nature.com : “End-to-end topographic networks as models of cortical map formation and human visual behaviour”. Please check our NHB link: www.nature.com/articles/s41...
June 6, 2025 at 10:06 AM
Now out in Nature Human Behaviour @nathumbehav.nature.com : “End-to-end topographic networks as models of cortical map formation and human visual behaviour”. Please check our NHB link: www.nature.com/articles/s41...
Reposted by Jiawei Li
What are the organizing dimensions of language processing?
We show that voxel responses during comprehension are organized along 2 main axes: processing difficulty & meaning abstractness—revealing an interpretable, topographic representational basis for language processing shared across individuals
We show that voxel responses during comprehension are organized along 2 main axes: processing difficulty & meaning abstractness—revealing an interpretable, topographic representational basis for language processing shared across individuals
May 23, 2025 at 5:00 PM
What are the organizing dimensions of language processing?
We show that voxel responses during comprehension are organized along 2 main axes: processing difficulty & meaning abstractness—revealing an interpretable, topographic representational basis for language processing shared across individuals
We show that voxel responses during comprehension are organized along 2 main axes: processing difficulty & meaning abstractness—revealing an interpretable, topographic representational basis for language processing shared across individuals