Xi-Han Zhang
@xi-hanzhang.bsky.social
53 followers 23 following 12 posts
PhD student @YalePsychology | @HarvardChanSPH‘19 | @OUC1924 ‘17 computational biology, neuroscience, affective dynamics, mechanisms of change
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Reposted by Xi-Han Zhang
sidchop.bsky.social
🧩New study: "Network Constraints on 𝘪𝘯 𝘷𝘪𝘷𝘰 Synaptic Alterations in Schizophrenia"

medrxiv.org/content/10.1...

We map a prominent brain-wide pattern of synaptic defects in people with Schizophrenia using PET, then model the molecular, cellular & connectomic features shaping this pattern 🧵1/3👇
Reposted by Xi-Han Zhang
loiclabache.bsky.social
🚨 New #preprint: The molecular and cellular underpinnings of human brain lateralization

🔗 doi.org/10.1101/2025...

🧠 We identify an acetylcholine-norepinephrine axis underlying functional lateralization, along with mitochondrial and cellular correlates. 🧵1/9👇

#neuroskyence
The molecular and cellular underpinnings of human brain lateralization
Hemispheric specialization is a fundamental characteristic of human brain organization, where most individuals exhibit left-hemisphere dominance for language and right-hemisphere dominance for visuosp...
doi.org
xi-hanzhang.bsky.social
I'm a huge fan of surfplot now!
xi-hanzhang.bsky.social
5/6 Functional network assignment can be predicted by cell-type abundances in post-mortem tissue. Motor, visual, and limbic networks, ventral attention/salient networks can be well-predicted. Default, frontoparietal/control, and dorsal attention networks are easier to be predicted as each other.
xi-hanzhang.bsky.social
4/6: Large-scale networks possess distinct cellular profiles, hinting at computing motifs for specialized functions. For example, dorsal attention network is enriched by layer 2/3 and layer 5 ITs, whereas ventral attention/salient network is enriched by layer 6 neurons.
xi-hanzhang.bsky.social
3/6: Multivariate cellular profiles track the functional gradient architecture of cortex. Permutational canonical correlation analysis, reveals linear combinations of cell type distributions that maximally correlate to each functional gradient.
xi-hanzhang.bsky.social
2/6: Univariate cell type distributions align with gradient topographies: SNCG and SST interneurons and excitatory L5 IT are preferably localized at transmodal, and the L4 IT at the unimodal end. Cell types are imputed from gene expression in bulk tissue samples and single-nucleus data.
xi-hanzhang.bsky.social
1/6: Here, we examine associations between the spatial abundance of cell-types with functional gradients and networks across the cortical sheet.
xi-hanzhang.bsky.social
w/ @avramholmes.bsky.social @sidchop.bsky.social @elvisha.bsky.social KevinAnderson, Hao-Ming Dong, Prashant Emani, Mark Gerstein, Daniel Margulies.
xi-hanzhang.bsky.social
Thank you for writing such great views for our work!