Jivesh Ramduny

@jivr.bsky.social

Postdoc with @BaskinSommers and @KavliAtYale. fMRI methods for inclusive and reproducible science. Alum @tcddublin | @KingsCollegeLon | @EdinburghUni | @NTUsg.

SO excited to share that I'll be joining Stanford University as an Assistant Professor in Psychology starting September 2027!! I’m launching the Emotions, Computation, and Choice Lab, where we investigate how emotions guide social cognition and behavior. www.heffner-lab.com

Emotions, Computation, and Choice Lab

Explore research on how emotions influence social cognition, decision-making, and AI interactions at the Emotions, Computation, and Choice Lab at Stanford University. Join us to study emotions and beh...

heffner-lab.com

🧠 New preprint! How does the brain build specialized, efficient representations as we grow up? We used manifold learning to track the "intrinsic dimensionality" (ID) of brain activity in ~800 participants (aged 3mo–53yrs), as they performed naturalistic tasks and rested/slept.

Bild
bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 2mo ago

Developmental tuning of functional manifold dimensionality across the human brain https://www.biorxiv.org/content/10.64898/2026.07.24.740635v1

Thank you to my wonderful team for their help on this - Chase Antonacci, @greyes.bsky.social, @eugiampetruzzi.bsky.social, @jivr.bsky.social, Gracie Grimsrud, @mellwoodlowe.bsky.social, and @russpoldrack.org!

Russ Poldrack@russpoldrack.org · 2mo ago

In this new preprint, @jocelynricard.bsky.social argues for a more intentional and principled approach to the measurement of neighborhood-level effects on brain development. www.biorxiv.org/content/10.6...

The more often you hear something, the more likely you are to believe that it is true. But please, don't believe everything you hear about teens today. Science and how well they are doing, despite the suffering of adults around them, tells a different story.

Excited that Imaging Neuroscience has gotten its impact factor. Note that the impact factor is artificially low for the first year of any journal (because of the way it is calculated), so we expect the impact factor to improve next year. See more statistics below

Imaging Neuroscience@imagingneurosci.bsky.social · 4mo ago

A note on first IF for new journals: IF is based on citations in year 3 of papers published in years 1 and 2. As papers from year 1 have longer to accrue citations, the smaller launch-year output reduces the first combined calculation. This effect disappears the following year.

Excited to be at #ohbm2026 @ohbmofficial.bsky.social presenting our real-time fMRI paper just published in @natneuro.nature.com ! come learn more at my talk on Wed at 9am in the symposium on “Closed-loop fMRI Neurofeedback” in Room E

Erica Busch@elbusch.bsky.social · 4mo ago

Our new paper is out this week in Nature Neuroscience! www.nature.com/articles/s41... We built a BCI that works with the brain's natural geometry — and we found that people could learn to play a video game with their brains in <1 hr of training. This efficiency is groundbreaking & here's why:

Our new paper is out this week in Nature Neuroscience! www.nature.com/articles/s41... We built a BCI that works with the brain's natural geometry — and we found that people could learn to play a video game with their brains in <1 hr of training. This efficiency is groundbreaking & here's why:

Human learning of noninvasive brain–computer interfaces via manifold geometry - Nature Neuroscience

Busch et al. use nonlinear neural manifolds to help humans gain rapid control over a noninvasive brain–computer interface, allowing them to learn how to play a video game with real-time fMRI neurofeed...

nature.com

Our new preprint is out! We examined the associations between multimodal brain measures (structure, microstructure, function) and psychopathology domains to predict adolescent functioning using the ABCD Study. In collab with @yiplab.bsky.social and co!

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 4mo ago

Distinct associations between multimodal brain measures and psychopathology domains predict adolescent functioning https://www.biorxiv.org/content/10.64898/2026.06.03.729937v1

If you are looking to pursue a doctoral program, postdoc position, or postbac role, and interested in computational neuroscience broadly, @elbusch.bsky.social 's lab would be a great stepping stone! She is a great scholar with an interdisciplinary focus. Plus, she has a very cute dog named Junie!

Erica Busch@elbusch.bsky.social · 4mo ago

🎉🎉🎉🎉 I'm thrilled and humbled to share some major updates! (A 🧵 but TLDR: graduated from Yale, joining Sungkyunkwan University in South Korea as an IBS Young Scientist Fellow this summer, and starting as an assistant professor in Vanderbilt's College of Connected Computing in Fall 2027!)

So glad to finally share work years in the making! What started with fMRI effect size benchmarks ended up showing that conventional study planning detects ~half of expected brain effects, suggesting more distributed processes than the lit shows (+ new methods for mass univ effect/power estimation)

BildBild
B

How much does the childhood environment shape the brain? In our new preprint, we study the exposome (300+ environmental exposures) and link it to white matter structure in 8,000+ kids. 🧠✨ 🔗 Read the preprint: bit.ly/4wfsybZ 🧵 Thread below

White matter reflects the childhood exposome

The childhood environment is critical for brain development. However, most neuroimaging studies examine individual environmental measures (e.g., socioeconomic status) or a limited set of exposures, obscuring how the combination of complex, real-world exposures jointly influence brain development. Here we investigated how white matter shape and tissue properties are linked to the childhood exposome, a multidimensional measure capturing over 300 environmental exposures. Using multi-shell diffusion MRI from 8,183 children (ages 9-10) in the ABCD study, we quantified microstructural and macrostructural properties across 62 person-specific white matter tracts. The exposome showed widespread and highly replicable associations with both white matter microstructure and macrostructure: more advantaged environments were associated with larger tract macrostructure and lower orientation dispersion. Principal component analysis revealed that the dominant axis of exposome-white matter covariation aligns with the cortical sensorimotor-association hierarchy, such that tracts spanning this hierarchy exhibit the strongest associations with the exposome. Multivariate models demonstrated that patterns of white matter features explained 25% of the variance in the exposome in unseen individuals. Notably, white matter-based prediction of cognition was markedly reduced after accounting for the exposome (~82% reduction in explained variance), indicating that brain-cognition associations overlap substantially with variance captured by the exposome. These findings generalized to independent data from the Healthy Brain Network (n=869), which differs substantially from ABCD in MRI acquisition, participant selection, and childhood environments. Together, these results suggest that white matter architecture strongly reflects the childhood environment. ### Competing Interest Statement A.A.B. has consulted for Octave Bioscience and holds equity in Centile Bioscience. RB is on the Advisory Board and holds equity in Taliaz Health. D.A.F. is a founder of Turing Medical. Any potential conflict of interest has been reviewed and managed by the University of Minnesota. D.A.F. is an inventor of the FIRMM Technology 2198 (FIRMM, real-time monitoring and prediction of motion in MRI scans, exclusively licensed to Turing Medical). Any potential conflict of interest has been reviewed and managed by the University of Minnesota. This research was supported by funding from the National Institutes of Health (T32MH019112 to S.L.M.; R37MH125829 to D.A.F. and T.D.S.; 2R01MH112847 to R.T.S. and T.D.S.; R01MH120482 to T.D.S.; 2R01MH113550 to T.D.S.; R01MH123550 to R.T.S; F30MH138048 to K.Y.S.; RF1MH121868, RF1MH121867, RF1MH126699, R01AG060942, U19AG066567, R01EY033628, and R01EB027585 to A.R.; R01MH134886 to R.B.; T32MH016804 and T32MH018951 to V.J.S; R01MH133843 to A.A.B.; F31MH136685 to J.B.). S.L.M. was supported by the Hartwell Foundation (S.L.M.); G.S. was supported by a postdoctoral fellowship from the Canadian Institutes of Health Research (CIHR). A.S.K. is supported by a NARSAD Young Investigator Award from the Brain and Behavior Research Foundation. M.D.H. was supported by the German Research Foundation (project number 572317568). LMS was supported by a NSF SBE Postdoctoral Research Fellowship (#2507497).

bit.ly

Our lab (w/ @patrickgbissett) is hiring a full-time research coordinator to work with us on cognitive control, dense fMRI, computational modeling, and human-AI interaction. Designed for post-bacs looking to start a Ph. D in ~2 years. Please repost. phxc1b.rfer.us/STANFORDNLbWAG

Social Science Research Coordinator (Hybrid Opportunity) in School of Humanities and Sciences, Stanford, California, United States

Professor Russ Poldrack’s lab is seeking a new full-time Research Coordinator. The RC will work closely with and report directly to Dr. Patrick...

phxc1b.rfer.us

Posting on behalf of Brendan: Common feature selection practices may capture only the “tip of the iceberg” of distributed brain–behavior relationships Specifically, typically discarded features can predict behavior just as well as top-ranked ones, yet produce diverging interpretations

Nature Human Behaviour@nathumbehav.nature.com · 6mo ago

Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers