Really excited to share our new preprint "Geometric influences on the regional organization of the mammalian brain" with @AFornito and a superstar 17-person team! (1/n).

RT @biorxiv_neursci: Cellular basis for cortical network aging in primates #biorxiv_neursci.

Check this new work by @TrangCao2016. Massive analysis on multiple sites and multiple disorders.

Due to unforeseen circumstances, we've extended the deadline to apply for our Systems and Comp Neuro postdoc position by a week (new deadline: May 25)! 🥳. If you have experience in modelling brain dynamics &/or analysing (s, d, f)MRI, we want you! Please help spread the word 👇.

Applications for our postdoc position closes in 6 days! (Deadline: May 18 11:55pm AEST) . If you are interested in MRI, modelling of brain dynamics, and genetics in health, disease, or across evolution, we would love for you to join our team👇👇.

Please share with anyone who you think might be interested. @OHBM_Australia @ACNS_ECR @AusNeuroSoc @ACNS_Official @biolpsychaust @OHBM_Trainees.

The job is for at least two years, and we're looking for someone who can start before the end of the year. Job ad closes on May 28 (see link for details). DM or email me at james{dot}pang1@monash{dot}edu for further questions.

We are hiring!. @AurinaArn and I are jointly looking for a talented Postdoc in Systems and Comp Neuro at Monash (AUS). If you like neuroimaging 🧠, comp models 💻, genetics 🧬, brain disorders 🤕, and/or evolution 🐵🐭, this could be the job for you!!.

For anyone interested in using our methods, the paper's associated GitHub page will be released soon. In the meantime, check out the preprint's main text and supps for all the juicy details. Can also send a DM or email at james{dot}pang1{at}monash{dot}edu for more info. (15/n).

We started this work in 2021, so it has been a long 4 yrs of study! So big thanks to @AFornito P Robinson @Kevin_M_Aquino @PriscilaTLevi @DrAlexHolmes @marija_marki X Shen @tffunck @receptorworld @rubykong92 @bttyeo J Tiego @BellgroveMark @constable_todd E Lake @DrBreaky (14/n).

In summary, this work points to a fundamental role that geometry plays not just in shaping brain function but also in its regional organization that is conserved across the mammalian species. (13/n).

We find highly robust correspondence between model solutions vs geometric modes and model parcs vs geometric parcs, demonstrating that the reaction-diffusion process may represent a conserved developmental mechanism for establishing the regional organization of the brain. (12/n)

We want to go further and provide mechanistic insights into why our geometric parcellations work so well. Hence, we go back to the initial motivation of this study and develop a computational model that mimics the reaction and diffusion of patterning molecules. (11/n)

Fourth, we can even go to the individual level, only needing individual-specific cortical surfaces. (10/n)

Third, the approach and homogeneity results are generalizable to non-neocortical structures such as subcortical and allocortical structures (i.e., HIP, AMY, THA, NAc, GP, PUT, CAU). (9/n)

Second, thanks to the data in the beautiful study of Schwartz et al. (2023, Nat Comms), we show that we can generate parcs for 24 other mammalian species, covering the Primata, Scandentia, Dermoptera, Rodentia, and Lagomorpha orders. Most don't even have parcs to date! (8/n)

The great thing about our approach is that it only requires T1w MRI, so it is highly generalizable!. First, it is generalizable to mammals (macaque, marmoset, mousse neocortices), with superior homogeneity against 15 existing parcs across 114 FC and non-FC phenotypes. (7/n)

We also find that the homogeneity of the geometric parcs remains superior across 242 non-FC cortical phenotypes, covering diverse properties of morphometry, microstructure, cytoarchitecture, metabolism, gene expression, chemoarchitecture, and fMRI task activations! (6/n)

Focusing first on the human neocortex, we find that the geometric parcs produce regions that are more functionally homogeneous (FC based on 3 independent resting-state fMRI datasets) than those in nearly all 17 cortical parcs commonly used in the field. (5/n)

Inspired by this equivalence, we use the geometric eigenmodes (which can be derived directly from T1w MRI) to develop a simple, hierarchical approach for generating a multiscale parcellation of any brain structure. We term as geometric parcellations. (4/n)

We know that patterning molecules (morphogens) are crucial for areal specification early in development. Interestingly, their expressions align with the rostrocaudal, mediolateral, and dorsoventral axes, corres. to low-order geometric modes. Image from O'Leary et al. (2017) (3/n)