Kayson Fakhar

I'm starting to think the argument between low vs. high dimensional neural activity literally just comes from plotting the PCs in linear vs. log y-scale

Advances on design considerations in Developmental Cognitive Neuroscience

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Advances on design considerations in Developmental Cognitive Neuroscience - ScienceDirect www.sciencedirect.com/science/arti...

New paper in Imaging Neuroscience by Ajay D. Halai, Marta M. Correia, et al:

Comparing the effect of multi-gradient echo and multi-band fMRI during a semantic task

doi.org/10.1162/IMAG...

Optimism for abundant whole-brain connectomes and connectomic screening - Nature Methods Connectomics has so far outpaced the Moore’s law predictions about technological progress. At this pace, many whole-brain connectomes and connectomic screening will soon be realistic.

Optimism for abundant whole-brain connectomes and connectomic screening | Nature Methods www.nature.com/articles/s41...

😩😩😩😩😩

Number of days without a Bluesky discussion on neural manifolds about to set to zero again.

Mapping the genetic landscape across 14 psychiatric disorders - Nature Genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders identifies five underlying genomic factors that explain the majority of the genetic variance of the individual disorders...

1/4 Thrilled to be sharing new work published today in Nature describing the third wave of results from the PGC Cross-Disorder Group. This reflects a massive group effort to examine shared and unique genetic signal across >1 million cases for 14 psychiatric disorders. www.nature.com/articles/s41...

YouTube video by Neuroscience & Philosophy Salon Prof. Lucina Uddin from UCLA discusses her views on brain networks as studied with functional MRI

𝗕𝗿𝗮𝗶𝗻 𝗻𝗲𝘁𝘄𝗼𝗿𝗸𝘀, 𝘄𝗵𝗮𝘁 𝗮𝗿𝗲 𝘁𝗵𝗲𝘆?
@lucinauddin.bsky.social explains many of the challenges and controversies! Great discussion too.
Check out the latest Neuroscience & Philosophy Salon.
youtu.be/pP5swFPR0Ns

❗️NEW OPINION PIECE 🗨

Want to find out how apathy might be more than evaluating cost and benefit? ⚖️ Then read on!

V excited for the release of my first opinion piece on #apathy as a failure of active inference in @cp-trendsneuro.bsky.social with thanks to my co-author @cambridgeftd.bsky.social 😊

🚨Funded PhD studentship project🚨
"Leveraging population activity trajectories to optimise Brain-computer interfaces for arm movement" with myself & @katjakornysheva.bsky.social

By: Jan 9th 2026

Info on project, funding & how to apply:  more.bham.ac.uk/mrc-aim/phd-... (submit to Nottingham)

How are better tools and bigger datasets transforming the field? In a new special report, @thetransmitter.bsky.social explores the state of neuroscience and provides context on the field's focus, output, people and funding. Explore now: www.thetransmitter.org/state-of-neu...

Finally got the job ad—looking for 2 PhD students to start spring next year:

www.gao-unit.com/join-us/

If comp neuro, ML, and AI4Neuro is your thing, or you just nerd out over brain recordings, apply!

I'm at neurips. DM me here / on the conference app or email if you want to meet 🏖️🌮

Need more fMRI data (beyond the amazing NSD)? Introducing MOSAIC! Incredible effort led expertly by Ben Lahner, with help from grad student Mayukh Deb. Work in collaboration with the amazing Aude Oliva! @neurosky.bsky.social. More below..

The perplexing “connected cluster axiom” – Inverse Complexity Lab Research group on inverse problems in complex systems and network science.

I wrote a blog post about the often stated but never explained assumption that communities in graphs should always be connected.

This is inconsistent with statistical significance and null models that underlie the most widely employed methods.

skewed.de/lab/posts/co...

This was fun!! Thanks so much for having me over :)

Exciting new work from @lindenmp.bsky.social and friends!

Inferring intrinsic neural timescales using optimal control theory
www.nature.com/articles/s41...

Great read. Too many people assume that the role of theory papers in neuro is to "explain neural data". I'm not even sure we can explain anything yet. Data is more like a muse for theory.

Networks are #complex and their dynamics often look chaotic. But we can reconstruct latent spaces where their behavior becomes strikingly regular, revealing functional organization across biology, society and technology.

How? 👉 rdcu.be/eSsqn 🧪🧠🦠🧬🌐

Kudos to Andrea, @dzanc.bsky.social & Sebastiano!

This Wednesday! I will be talking about curiosity in infants, children, adults (and artifcial neural networks)

Topological turning points across the human lifespan - Nature Communications Researchers discovered five phases of brain rewiring across the lifespan. The eras of childhood, adolescence, adulthood, early aging, and late aging each have characteristic rewiring of structural connections across the whole brain.

One of our top-rated posts on @altmetric.com this past week was published open access in @natcomms.nature.com. You can read 'Topological turning points across the human lifespan' here: spklr.io/63329BX7zL

#Neuroskyence #neuroimaging 🧠

"Neuroscientists need better training in computational methods."

We got you.

Join us in July: neuromatch.io/courses/

Our #ComputationalNeuroscience course is the perfect way to gain practical experience and build a strong foundation in this field.

This equivocation of oscillations and continual learning is a bit of stretch... I'm surprised they didn't get dinged by the reviewers for neuro-babble. openreview.net/forum?id=nbM...

Please repost: another kind of Black-Friday deal!

What neuroscience can tell AI about learning in continuously changing environments Nature Machine Intelligence - Durstewitz et al. explore what artificial intelligence can learn from the brain’s ability to adjust quickly to changing environments. By linking neuroscience...

Unlike current AI systems, animals can quickly and flexibly adapt to changing environments.

This is the topic of our new perspective in Nature MI (rdcu.be/eSeif), where we relate dynamical and plasticity mechanisms in the brain to in-context and continual learning in AI. #NeuroAI

Cross-Species Cortical Geometry Reveals Conserved Gradients Across Primates and Human-Specific Expansion https://www.biorxiv.org/content/10.1101/2025.11.28.691123v1

🚨Friends, we’re happy to share that our book is available for pre-order! 🎉
We aimed to cover all the foundations of the topic in an accessible manner for a large audience.
It could help set up a bachelor-level curriculum on the topic.
Pre-orders are very key for the fate of books: shorturl.at/Dxbif

Researchers from MRC Cognition and Brain Sciences Unit, University of Cambridge and University of Cambridge showed that the brain stays in the adolescent phase until our early thirties. Find out more in the BBC article 👉 https://www.bbc.co.uk/news/articles/cgl6klez226o

Why do some people lose memory faster with age? A mega-analysis of 13 longitudinal datasets (3,700+ adults, 10,000+ MRIs) shows that memory decline tracks brain atrophy, especially in the hippocampus, and that these links strengthen with age, but not APOE status: www.nature.com/articles/s41...

1/6 New preprint 🚀 How does the cortex learn to represent things and how they move without reconstructing sensory stimuli? We developed a circuit-centric recurrent predictive learning (RPL) model based on JEPAs.
🔗 doi.org/10.1101/2025...
Led by @atenagm.bsky.social @mshalvagal.bsky.social