Joanna Moodie
@joannamoodie.bsky.social
29 followers 31 following 10 posts
Postdoc @edinunilbc.bsky.social 🧠🧬she/her
Posts Media Videos Starter Packs
Pinned
joannamoodie.bsky.social
New preprint! Which regions of the human brain are most strongly related to individual differences in general cognitive functioning? And what are the underlying neurobiological properties of those areas? | bioRxiv | doi: 10.1101/2024.12.17.628670 🧠
Reposted by Joanna Moodie
scotcogageing.bsky.social
And it's over already! A big thanks to everyone who came today, who presented their work, and to our fab organiser, Lizzie Bradford, for hosting us.

If you'd like to join SCAN, send a message or sign up via the link in the bio. As you can see, we're a friendly bunch!
joannamoodie.bsky.social
9️⃣ Many thanks to participants from @ukbiobank.bsky.social @genscot.bsky.social and @edinunilbc.bsky.social, and to all co-authors.
joannamoodie.bsky.social
8️⃣ In the supplement we also i) provide the largest analysis of meta-analytic subcortical volumetric-cognitive associations; ii) investigate the effect of smoothing tolerance and iii) will make the newly created maps openly accessible upon publication.
joannamoodie.bsky.social
7️⃣ Together, we provide a compendium of cortex-wide and regional spatial correlations among general and specific facets of brain cortical organisation and higher order cognitive functioning.
joannamoodie.bsky.social
6️⃣ In addition to calculating cortex-wide spatial correlations, we calculate spatial correlations within regions. These analyses show two important things: 1) the relative strength of correlations for different regions, and 2) the homogeneity of correlations among regions.
joannamoodie.bsky.social
5️⃣ We also calculate correlations between g-morphometry and age-morphometry associations and find that areas of the brain most associated with g are also those that are most strongly associated with age: correlations range from r = -0.355 to -0.622.
joannamoodie.bsky.social
4️⃣ The 33 neurobiological cortical profiles spatially covary along four major dimensions (accounting for 65.9% of the variance). Encouragingly, the largest dimension strongly recapitulates the principal gradient (unimodal ➡️ amodal brain regions).
joannamoodie.bsky.social
3️⃣ Then, we bring together brain maps of 33 cortical characteristics (e.g., neurotransmitter receptor densities, gene expression, metabolism, and cytoarchitectural similarity) to quantify the neurobiological properties of the brain regions most implicated in cognitive differences
joannamoodie.bsky.social
2️⃣ These associations (|β| range = < 0.001 to 0.17) show good cross-cohort agreement (mean spatial correlation r = 0.57, SD = 0.18).
joannamoodie.bsky.social
1️⃣ We run the largest vertex-wise meta-analysis of general cognitive function-morphometry associations (meta-analytic N = 38,379).
joannamoodie.bsky.social
New preprint! Which regions of the human brain are most strongly related to individual differences in general cognitive functioning? And what are the underlying neurobiological properties of those areas? | bioRxiv | doi: 10.1101/2024.12.17.628670 🧠