Linden Parkes
@lindenmp.bsky.social
🇦🇺 Assistant Professor of Psychiatry. Network neuroscience, NeuroAI, multimodal MRI, precision psychiatry. parkeslab.com
HIRING: Staff Scientist @ NeRD Lab at Boston Children's Hospital. Come join a powerhouse lab of 14 remarkable women. Looking for someone who loves neurodevelopment, sleep, & psychopathology, thrives on collaboration, & is excited to become the scientific backbone of our lab. tinyurl.com/mveskh4p
pyhctsa is out! A native Python port of the majority of the hctsa feature library (highly comparative time-series analysis). Thousands of interpretable time-series features available via a pip install. Built by Joshua Moore. Paper: doi.org/10.21105/jos... Code: github.com/DynamicsAndN...
Thrilled to share our new paper deriving an ”Exposome Network” of functional connectivity capturing multidimensional env. exposures in youth, now out in DCN! 🌟🧠 doi.org/10.1016/j.dc... Huge thank you Sarah Lichenstein, @yiplab.bsky.social & our amazing Connecticut Collab! ❤️ #devpsy #neuroimaging
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Arielle Keller@ariellekeller.bsky.social · 9mo agoHappy New Preprint Friday!* Thrilled to share new results in collab with Sarah Lichenstein & @yiplab.bsky.social showing our brain's functional connections reflect the environments we grow up in! tinyurl.com/exposomeConnectivity #neuroskyence #PsychSciSky #DevPsy #cognition *can this be a thing??
Our paper "Neural timescales from a computational perspective" is finally out in @natneuro.nature.com: www.nature.com/articles/s41... We discuss how computational models and methods can distill empirical observations on neural timescales into quantitative, testable theories of brain computation.
Neural timescales from a computational perspective - Nature Neuroscience
This review integrates computational approaches to provide a unified view on how data analysis methods, biophysical mechanistic models and machine learning approaches can help to uncover the origins a...
nature.com
Interested in the principles shaping connectome architecture? See our latest in @cp-cell.bsky.social led by F Normand @nsb-lab.bsky.social A simple model using geometric eigenmodes captures cortical connectomes of different species. Paper: tinyurl.com/3r43spf5 Thread: tinyurl.com/vx74hp6u
Want to be the new manager for the @ohbmofficial.bsky.social journal @apertureohbm.bsky.social? 🧠 Apply here!
New work on the effects of psychedelics on hierarchical cortical propagations out in PNAS! www.pnas.org/doi/10.1073/... Counter to our expectations, psychedelics attenuated bottom-up propagations into the Default Mode Network across substances and species. Thread below:
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...
pnas.org
Coming to #OHBM2026? We'll see you there! 🇫🇷 🥖 🥐 Make sure you check out the awesome work led by @ambrains.bsky.social 🥳 🙌: Poster #0903: The spatial extent of thalamic connectivity shapes the diversity and control of whole-brain dynamics Monday, June 15, 13:45-14:45 Tuesday, June 16, 12:30-13:30
Our paper “Multiscale heterogeneity of atypical functional connectivity in autism” is now out in Nature Mental Health www.nature.com/articles/s44... With @alexfornito.bsky.social, Jan Buitelaar, Marianne Oldehinkel
Multiscale heterogeneity of atypical functional connectivity in autism - Nature Mental Health
Using normative modeling to measure the interindividual variability of atypical brain functional connectivity in autism, the authors identify heterogeneity at the level of specific connections alongsi...
nature.com
Our latest, led by @ivaili.bsky.social out now in Nature Mental Health using normative modelling to understand the heterogeneity of atypical FC in autism. Peep the thread...
Iva Ilioska@ivaili.bsky.social · 2mo agoOur paper “Multiscale heterogeneity of atypical functional connectivity in autism” is now out in Nature Mental Health www.nature.com/articles/s44... With @alexfornito.bsky.social, Jan Buitelaar, Marianne Oldehinkel
Here's bonus slides on cross-validation tests, separate from our preprint. Covering: 1. paired (sign-flip) permutation test 2. label-swap permutation test 3. sample-level vs fold-averaged stats 4. a common misapplication of the corrected t-test 5. three bootstrap variants 1/N
Thomas Yeo@bttyeo.bsky.social · 3mo agoIn a meta-analysis of 210 biomedical AI studies that statistically compared models under cross-validation, 97% used invalid statistical tests. Here's our new preprint doi.org/10.64898/202... led by @tianchu.bsky.social @hetuli.bsky.social @shaoshiz.bsky.social @nichols.bsky.social 1/N
In a meta-analysis of 210 biomedical AI studies that statistically compared models under cross-validation, 97% used invalid statistical tests. Here's our new preprint doi.org/10.64898/202... led by @tianchu.bsky.social @hetuli.bsky.social @shaoshiz.bsky.social @nichols.bsky.social 1/N
So we propose SHARP, which involves repeated split-half to generate pairs of independent statistics. There are still 3 unknowns — mean, variance, between-repetition correlation — but the independent pairs provide a 3rd information source to estimate all 3 unknowns. 7/N
Large-scale data infrastructure and AI-powered analytics to elevate your advanced imaging research are available at the Center for Advanced Human Brain Imaging Research (CAHBIR) in the Rutgers Brain Health Institute (BHI) CAHBIR capabilities brochure: brainhealthinstitute.rutgers.edu/wp-content/u...
Attending #SOBP2026? Let us know what you’re presenting so we can share with the community! 🧠🧬
Come see the latest from ACORN Lab at #SOBP2026! 🐿️🧠🗽 Thread below! 👇
Really excited to share a new preprint! 𝗛𝗼𝘄 𝗱𝗼 𝗯𝗿𝗮𝗶𝗻𝘀 𝘀𝘁𝗮𝘆 𝗿𝗼𝗯𝘂𝘀𝘁 & 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝘄𝗵𝗶𝗹𝗲 𝗯𝗲𝗶𝗻𝗴 𝗶𝗻𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝘆 𝘀𝗽𝗮𝗿𝘀𝗲? We explore how! www.biorxiv.org/content/10.6... We built Connectome-based Neural Networks (CoNNs) using Drosophila wiring (larva&adult) & compared with random networks with same sparsity.
Our latest publication grapples with how the brain could implement gradient descent by sending learning targets top-down, gating plasticity with dendritic inhibition, and updating synaptic weights with biologically observed learning rules like BTSP. www.cell.com/cell-reports...
Cellular and subcellular specialization enables biology-constrained deep learning
Galloni et al. introduce “dendritic target propagation”: a Dale’s law-compliant learning algorithm for cortical microcircuits with soma- and dendrite-targeting inhibition and realistic connectivity co...
cell.com
Aaron Milstein@neurosutras.bsky.social · last yr.New #NeuroAI #compneurosky preprint! To better understand how target-directed learning works in the brain, we sought to engineer an artificial neural network capable of solving complex image classification tasks that comprises only experimentally-supported biological building blocks. (1/15)
Our latest work looking at the neuroanatomical basis of impulsivity in youth is out now in Molecular Psychiatry!
Neuroanatomy reflects individual variability in impulsivity in youth - Molecular Psychiatry
Molecular Psychiatry - Neuroanatomy reflects individual variability in impulsivity in youth
nature.com
Check out my latest editorial reflecting on OHBM 2025 and emphasizing the power our community has to advance diversity and inclusion in research.
The power of community | Published in Aperture Neuro
By Elvisha Dhamala. Looking ahead, our field must continue to prioritize diversity among researchers and commit to studying brain function and dysfunction across varied populations, life stages, and s...
apertureneuro.org
Ever wondered how GABAergic interneurons shape cognition? The IN-CODE consortium's latest NeuroView article introduces a "population approach", shifting the focus from individual interneurons to cooperative networks. Dive into the future of interneuron research here: doi.org/10.1016/j.ne...
The 6x US memory champion – Nelson Dellis – can memorize a deck of cards in 40 seconds and knows the first 10K digits of pi. To figure out how, he let us peak inside his brain. Here is what we learned in our precision brain mapping study www.biorxiv.org/content/10.6... youtube.com/shorts/MryMq...
how does his brain do it ? #neuroscience #memory #sport Nelson Dellis 6x US memory champion
YouTube video by Roselyne Chauvin
youtube.com
🚨Another new one from the lab! Cascades and convergence: Dynamic signal flow in a synapse-level brain network We simulate sensory cascades in a bona fide biological neural network. With Caio Seguin, Maria Grazia Puxeddu, and @misicbata.bsky.social! journals.plos.org/complexsyste...
Cascades and convergence: Dynamic signal flow in a synapse-level brain network
Author summary To understand how the brain processes and merges information from our senses, we need more than just a “wiring map” of its connections; we need to see how signals actually travel throug...
journals.plos.org
I couldn't find a tool to plot different #neuroimaging data in one consistent style, so I made one! Meet yabplot (yet another brain plot) - a #Python package for (sub)cortex & tracts.🧠 - Simple API - Built-in atlases - Custom atlas support 🔗 github.com/teanijarv/ya... (drop a ⭐️!)
We think of white matter as the highways of the brain. But when we followed development along those highways, we were surprised. The journey is more complex than we thought. My final PhD paper, “Two Axes of White Matter Development”, is now out in @natcomms.nature.com! 🛣️🧠✨ 🔗 bit.ly/wm2axes
🚨 New paper from @apodschun.bsky.social (with Sebastian Markett, Urs Braun, and myself) Exploring the Role of the Rich Club in Network Control of Neurocognitive States onlinelibrary.wiley.com/doi/10.1002/...
Exploring the Role of the Rich Club in Network Control of Neurocognitive States
Using a network control theoretical framework, we found that the brain's rich club does not optimally control dynamics of the brain. Instead, size-matched sets of random peripheral regions had a sign...
onlinelibrary.wiley.com
The revised version of our paper on the impact of top-down feedback is now out @elife.bsky.social: doi.org/10.7554/eLif... tl;dr: we show that using human-brain-like feedback/anatomy in a deep RNN leads to human-like visual biases! This work was led by @tmshbr.bsky.social #NeuroAI 🧠📈 🧪
doi.org
Intelligence is not just about having "strong" brain connections. It’s also about how efficiently the brain coordinates processing speed across regions. @lindenmp.bsky.social and @jason-z-kim.bsky.social share what their computer model is revealing about cognitive power: https://bit.ly/3LQuoxT
Computer model predicts aspects of cognitive performance
The Allen Human Brain Atlas helped researchers design a model that looked at “intrinsic neural timescales”
bit.ly
