Jesse Brown

Absolutely well deserved, congratulations Jack!

The history and future of resting-state functional magnetic resonance imaging - Nature This Review provides an overview of the history of resting-state functional MRI research, which has helped to reveal the spatiotemporal organization of the brain, and discusses how it can contribute f...

When I first started working with resting state fMRI as a postdoc, there was a lot of skepticism about what we could learn from it. 20 years later, it's hard to imagine where the field of neuroscience would be without it. Here's a summary 🧠 www.nature.com/articles/s41...

‘Get rid of the pseudoscience’: top doctor’s plan to improve America’s health Eric Topol says we can prevent age-related disease and live fuller lives – but only if we reject anti-science ‘malarkey’

Using the advances in the science of aging to prevent the major age-related diseases (no reversal of aging required) www.theguardian.com/world/2025/m... @theguardian.com

🔴 Our `Brain and AI` team at Meta has a new Research Engineer position in Paris to work on infrastructure and scale deep learning experimentations:

www.metacareers.com/jobs/1769841...

We'll favor industry experience or Github track record.

fMRI must break out of its silo We need to develop research programs that link phenomena across levels, from genes and molecules to cells, circuits, networks and behavior.

The scientific community needs to develop processes to support, hire and retain researchers whose work sits between traditional fields of study, writes @avramholmes.bsky.social

#neuroskyence

www.thetransmitter.org/future-of-fm...

Most people haven’t heard of this test, which is available in the US. It accurately predicts Alzheimer’s (not just if there’s a risk, but when). It is modulated by exercise and likely other lifestyle factors.
Here’s (almost) everything we know about it
erictopol.substack.com/p/the-breakt...

It's shocking how little is known about the brainstem red nucleus. In our new paper “The human brainstem’s red nucleus was upgraded to support goal-directed action” out now in @naturecomms.bsky.social we show that current thinking on the red nucleus is in need of a serious upgrade. rdcu.be/ehbOy

Human lifespan changes in the brain’s functional connectome - Nature Neuroscience Sun et al. report human lifespan changes in the brain’s functional connectome in 33,250 individuals, which highlights critical growth milestones and distinct maturation patterns and offers a normative...

Happy to share that our article “Human lifespan changes in the brain’s functional connectome” is now published online at Nature Neuroscience @natureneuro.bsky.social !

Many thanks to all collaborators & data contributors, and the editor team & reviewers!

www.nature.com/articles/s41...

The Fredericks Lab! - with deliberately poor photoshopping of lab members who couldn't be there that day.

We are HIRING!! Postdoc for multimodal imaging lab at Yale. If you get excited about preclinical and prodromal states, atypical Alzheimer’s, graph theory, predictive modeling, and/or baked goods at lab meetings, come join us: postdocs.yale.edu/postdoctoral...

Please share with your circles!

YouTube video by Lex Clips Mechanistic Interpretability explained | Chris Olah and Lex Fridman

100%. Chris Olah's interview with Lex is a good companion. www.youtube.com/watch?v=rini...

Proxies aren't the thing, the thing is the thing. Just don't forget what the "thing" is.

A generalized epilepsy network derived from brain abnormalities and deep brain stimulation - Nature Communications Ji et al. identify an idiopathic generalised epilepsy network that links heterogeneously distributed brain abnormalities to a common brain network and deep brain stimulation sites which reduce general...

Is generalized epilepsy a seizure of the whole brain or a specific brain network?

In our new paper out now in @naturecomms.bsky.social, we investigate this by combining brain abnormalities and DBS with the human connectome.

Paper: nature.com/articles/s41...

A 🧵 below:

Looks right. Cool!

Can you see the decussation?

More to come on Hugging Face - a leaderboard, open models, and growing this dataset.

Scans are ready to go out of the box - denoised (CAT12), skull-stripped, and registered to standard space. Split into balanced train/validation/test sets.

Useful for building brain age models or Alzheimer's disease classifiers. Subjects (n=2607) come from across the lifespan (age 6-98) and Alzheimer's spectrum from five public datasets (radiata.ai/public-studies).

radiata-ai/brain-structure · Datasets at Hugging Face We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Here's a new open dataset of ~4000 processed brain structural MRIs from across the lifespan:
huggingface.co/datasets/rad...

Get it in three lines of code:
pip install datasets
from datasets import load_dataset
ds = load_dataset("radiata-ai/brain-structure", trust_remote_code=True)

YouTube video by Kempner Institute at Harvard University Rethinking Brain Mechanisms in the Light of Evolution with Paul Cisek

Rethinking Brain Mechanisms in the Light of Evolution with Paul Cisek youtu.be/CnT7jaQX4X8?... - if you want to understand what brains are for (and their functional organisation), this is the way... 👍👏

Dynamical constraints on neural population activity - Nature Neuroscience Oby, Degenhart, Grigsby and colleagues used a brain–computer interface to challenge monkeys to override their natural time courses of neural activity. They found the time courses to be highly robust, ...

Using a brain–computer interface to challenge monkeys to override their natural time courses of neural activity reveals that the time courses are highly robust, suggestive of network-level computational mechanisms

@aaronbatista.bsky.social and colleagues

www.nature.com/articles/s41...

Try it out at radiata.ai and let me know if you have any questions at contact@radiata.ai.

- compare models based on imaging-derived phenotypes or embeddings
- bring classification model feature weights back to the brain so you can validate their neuroanatomy

- harmonize private datasets to ~4000 publicly available scans to instantly boost your training/testing sample sizes
- explore models interactively, so you can quickly compare true positives versus false positives or find the optimal model cutoff

YouTube video by Radiata Radiata Brain Imaging Classification

Here's how you can build classifiers for brain structural MRI data on radiata.ai.

www.youtube.com/watch?v=oDan...

We built this to make it easier to:
- set up and run machine learning models on the fly with no installs

- harmonize private datasets to ~4000 publicly available scans to instantly boost your training/testing sample sizes
- explore models interactively, so you can quickly compare true positives versus false positives or find the optimal model cutoff

Understanding LLM Embeddings for Regression With the rise of large language models (LLMs) for flexibly processing information as strings, a natural application is regression, specifically by preprocessing string representations into LLM embeddi...

Pretty amazing that we can now do regression with words and concepts (via LLM embeddings) as predictors.

arxiv.org/abs/2411.14708

We'd love to hear your thoughts at contact@radiata.ai.

YouTube video by Radiata Radiata Brain Latent Space

Our brain biomarker engine is live at radiata.ai. Here's how you can use our interactive latent space to explore brain anatomy individual differences in structural MRI scans. www.youtube.com/watch?v=EaJy...

Enjoying this, giving me 1996 feels and hope for the next wave.