katja seeliger

We've posted a new fMRI study of semantic relations (has-part, is-a, made-of, etc.), a key aspect of language. We find that relations are represented in the same brain regions as are other semantic concepts, though voxels tend to be selective for only one relation or another.
doi.org/10.64898/202...

GitHub - seelikat/neuro-visual-reconstruction-dataset-index: Index and overview of neuroimaging datasets for visual perception reconstruction. Index and overview of neuroimaging datasets for visual perception reconstruction. - seelikat/neuro-visual-reconstruction-dataset-index

I recently created this overview of fMRI datasets for visual reconstruction, aimed at AI/ML people.

Originally this was a 2018 post on a now inactive PhD lab blog. I had drafts expanding it for long time and thought now it's about time.

RFC and feel free to share :)

github.com/seelikat/neu...

22 years of Brain Science: what CoSyNe tells us about the evolution of Neuroscience Tracking the intellectual DNA of Computational and Systems Neuroscience through its flagship meeting

I tracked every keyword in 22 years of Cosyne abstracts to map how computational neuroscience evolved — from Bayesian brains to neural manifolds to LLMs — and where it's heading next.

Representations of semantic relations in the human cerebral cortex
www.biorxiv.org/content/10.6...

by Catherine Chen, Xue L. Gong, Fatma Deniz, Daniel L. Klein, Jack L. Gallant

📢 PhD position in the NeuroAI of Language

Why can LLMs predict brain activity so well? We're hiring a PhD student to find out -- AI interpretability meets neuroimaging
Deadline March 20
Please RT 🙏
👇
mpi.nl/career-education/vacancies/vacancy/fully-funded-4-year-phd-position-neuroai-language

GitHub - seelikat/neuro-visual-reconstruction-dataset-index: Index and overview of neuroimaging datasets for visual perception reconstruction. Index and overview of neuroimaging datasets for visual perception reconstruction. - seelikat/neuro-visual-reconstruction-dataset-index

Datasets for Reconstructing Visual Perception from Brain Data | Discussion

CfA: Workshop “Philosophical Issues in Neural Computation” (@ruhr-uni-bochum.de) Jun 2–3 2026.

Deadline: March 31.

Further Speakers: @adriendoerig.bsky.social, @francesegan.bsky.social, @olivia.science, @gualtiero.bsky.social, @seelikat.bsky.social, Oron Shagrir.

NSD-synthetic, the out-of-distribution companion dataset of NSD consisting of 7T fMRI responses to 284 artificial images, is now published.

#NeuroAI #CompNeuro #neuroscience #AI

doi.org/10.1038/s414...

Workshop on Philosophical Issues in Neural Computation Workshop on Philosophical Issues in Neural Computation June 02 – 03, 2026 Ruhr-University Bochum Abstract: The idea that the brain performs computations is widely accepted in cognitive science...

CfA: Workshop “Philosophical Issues in Neural Computation” (@ruhr-uni-bochum.de) Jun 2–3 2026.

Deadline: March 31.

Further Speakers: @adriendoerig.bsky.social, @francesegan.bsky.social, @olivia.science, @gualtiero.bsky.social, @seelikat.bsky.social, Oron Shagrir.

philevents.org/event/show/1...

Thanks so much @thetransmitter.bsky.social for this Rising Stars of Neuroscience award! 🤩

And a big thank you to @smfleming.bsky.social for the nomination!!

Advancing credibility and transparency in brain-to-image reconstruction research: Reanalysis of Koide-Majima, Nishimoto, and Majima (Neural Networks, 2024) A recent high-profile study by Koide-Majima et al. (2024) claimed a major advance in reconstructing visual imagery from brain activity using a novel variant of a generative AI-based method. However, o...

Advancing credibility and transparency in brain-to-image reconstruction research: Reanalysis of Koide-Majima, Nishimoto, and Majima arxiv.org/abs/2511.07960 by @ykamit.bsky.social et al. via @seelikat.bsky.social; #neuroscience #AI

Now accepting paper submissions for the “Neuro for AI & AI for Neuro: Towards Multi-Modal Natural Intelligence” workshop at #AAAI2026!

🔗 https://neuroai-multimodal-workshop.github.io/

@aaai.org

For a long time, some have daydreamed about whether neural networks can learn to effectively synthesize stimulation patterns to write information into the brain.

Introducing 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐨𝐟 𝐄𝐥𝐞𝐜𝐭𝐫𝐢𝐜𝐚𝐥𝐥𝐲 𝐄𝐯𝐨𝐤𝐞𝐝 𝐀𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐢𝐧 𝐇𝐮𝐦𝐚𝐧 𝐕𝐢𝐬𝐮𝐚𝐥 𝐂𝐨𝐫𝐭𝐞𝐱
www.biorxiv.org/content/10.1...

Our article is out in Annual Review of Vision Science: “Visual Image Reconstruction from Brain Activity via Latent Representation”
We trace the path from early brain decoding to modern NeuroAI, highlight progress & pitfalls, and discuss future directions www.annualreviews.org/content/jour...

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...

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...

Music genre neuroimaging dataset This dataset includes functional magnetic resonance imaging (fMRI) data collected while five subjects extensively listened to 540 music pieces from 10…

Music genre fMRI dataset by Nishimoto lab: www.sciencedirect.com/science/arti...

🧠 New preprint: Why do deep neural networks predict brain responses so well?
We find a striking dissociation: it’s not shared object recognition. Alignment is driven by sensitivity to texture-like local statistics.
📊 Study: n=57, 624k trials, 5 models doi.org/10.1101/2025...

Mindreading with Jean Rémi-King - StarTalk Special Edition What would it take to read someone’s mind? Neil deGrasse Tyson, Chuck Nice, & Gary O’Reilly explore the science of decoding our thoughts w/ Jean-Rémi King.

Had a blast chatting with @neildegrassetyson.com on @startalkradio.bsky.social ’s podcast about how AI and neuroscience come together
startalkmedia.com/show/mindrea...

Can we hear what's inside your head? 🧠→🎶
Our new paper, led by Jong-Yun Park, presents an AI-based method for reconstructing arbitrary natural sounds directly from a person's brain activity measured with fMRI.
journals.plos.org/plosbiology/...

How AI Models Are Helping to Understand — and Control — the Brain | Quanta Magazine Martin Schrimpf is crafting bespoke AI models that can induce control over high-level brain activity.

Martin Schrimpf wants to build a “digital twin” of the brain. “If we have a model of dyslexia, we can probe it and find changes to the text that make it easier for someone to read.”

🚨 Our new paper is out in @natmachintell.nature.com!
🤔 Deep neural nets (DNNs) often align with humans in performance and even representations — but do they "think" like us?
📄 “Dimensions underlying the representational alignment of deep neural networks with humans”

Donate to Support Helen's Children After Her Passing, organized by Marcus Arvan Help provide Helen De Cruz's children with a better start in life after her un… Marcus Arvan needs your support for Support Helen's Children After Her Passing

I am devastated to learn of my dear friend and fellow philosopher Helen De Cruz’s passing.

With Helen's blessing, her husband Johan and I agreed to circulate a GoFundMe on their children’s behalf.

Please feel free to share and circulate widely.

www.gofundme.com/f/support-he...

Hello, World!

After years of broadcasting into the void, I'm retuning my antenna:

Professional signal → Bluesky & LinkedIn (linkedin.com/in/umguec/)
Personal noise → Instagram (instagram.com/umguec/)

Let the decentralized brain dump commence. 🧠💩

📣 We won the "Dutch ICT Oscar"!

🏆 At the end of last year, our team was honored with the Computable Award in Digital Innovation 2024, “for visual prosthetics for the blind.”

Thank you for sharing the numbers, and also for all your efforts on building the foundation of this paper track! It is good to see that it was well-adopted by the community.

Can you share some info on the number of submitted papers, papers transferred into abstracts, number of reviewers etc.?

Visual Image Reconstruction from Brain Activity via Latent Representation Visual image reconstruction, the decoding of perceptual content from brain activity into images, has advanced significantly with the integration of deep neural networks (DNNs) and generative models. T...

Review on visual perception reconstruction by kamitanilab:
arxiv.org/abs/2505.08429

"From a psychological perspective, brain decoding supports Fechner’s concept of inner psychophysics, linking neural data with subjective experience."

Language modulates vision: Evidence from neural networks and human brain-lesion models Comparing information structures in between deep neural networks (DNNs) and the human brain has become a key method for exploring their similarities and differences. Recent research has shown better a...

Alignment between CLIP embeddings and ventral occipitotemporal cortex activity is left‐lateralized, and sensitive to language‐vision pathways: arxiv.org/abs/2501.13628

New Paper: Continuous Thought Machines

pub.sakana.ai/ctm/

Neurons in brains use timing and synchronization in the way that they compute, but this is largely ignored in modern neural nets. We believe neural timing is key for the flexibility and adaptability of biological intelligence.

Thread ↓

A composite image of parrots calling each other on tablets. Image from Kleinberger et al., 2023.

Pet parrots were taught to do video calls, and it was a hit.

The birds not only made friends with each other, and selected who they wanted to call and when, but also picked up new skills from fellow parrots.
Good enrichment option for improving captive parrot welfare.
🧪🦜

dl.acm.org/doi/10.1145/...