Jin Liu @_Jin_Liu
Cognitive neuroscience California, USA Joined March 2017-
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New opportunity alert! 🧠 The research topic 'Brain mapping across the lifespan: advancements and clinical applications' is currently accepting submissions in Frontiers in Human Neuroscience. Submit your article before the deadline on 23 February 2026. frontiersin.org/research-topic….
Many children struggle to learn math—but it’s not well understood why. A @ScienceAdvances study finds links between brain structure, genes, and individual differences in mathematical abilities and predicts learning outcomes in two math tutoring cohorts. scim.ag/7gr
Many children struggle to learn math, but it’s not well understood why. A new study identifies links between brain structure, genes, and individual differences in mathematical abilities and predicts learning outcomes in two math tutoring cohorts. scim.ag/79Q
📢NEWS ‼️Dr. Jin Liu and Dr. Hyesang Chang’s study uncovers atypical #cognitive and #neural mechanisms underlying learning in children with #ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood #autism. elifesciences.org/articles/86035
Excited to share our work published in NeuroImage ! Many thanks to @HeLabBNU & amazing team and @Tengdazhao , and others inc @XinyuanLiang1 @ DingnaDuan @_Jin_Liu @ YuhanChen @ XindiWang @xuhong_liao @mingruixia @yetianmed @ XiYu !
Excited to share our work published in NeuroImage ! Many thanks to @HeLabBNU & amazing team and @Tengdazhao , and others inc @XinyuanLiang1 @ DingnaDuan @_Jin_Liu @ YuhanChen @ XindiWang @xuhong_liao @mingruixia @yetianmed @ XiYu !
Curious about the neural circuit mechanisms underlying the #defaultmodenetwork? A preprint from @TzuHaoHarryChao, @LiMingHsu2 at @ShihYYI’s lab and @ByeongwookL at Vinod Menon’s lab @StanfordPSY used #fiberphotometry and #fMRI to shed light on this topic: biorxiv.org/content/10.110…
In this work, we collected a large multisite R-fMRI dataset from 2,234 individuals in China and the postmortem gene expression data from #AIBS to investigate the functional connectome #hierarchy in #MDD and establish their associations with the #transcriptome profile.
In this work, we collected a large multisite R-fMRI dataset from 2,234 individuals in China and the postmortem gene expression data from #AIBS to investigate the functional connectome #hierarchy in #MDD and establish their associations with the #transcriptome profile.
Our latest by @_Jin_Liu and @mingruixia now out in @NeuroImage_EiC . We conduct a #transcriptome #chronnectome association study to investigate the spatial configurations of #dynamic brain networks and their linkages with transcriptional profiles. sciencedirect.com/science/articl…
Our latest by @YuehuaXu_bnu and @miaocao2 now out in Cerebral Cortex @OxfordJournals. We use rs-fMRI in neonates to characterize the development and emergence of individual variability in the functional architecture of the prenatal brain. academic.oup.com/cercor/article…
congrats！
Our work is just on preprint @DanKennedyIU @ Lisa Byrge: Non-replication of functional connectivity differences in ASD: a multi-site study biorxiv.org/content/10.110… Thanks to @LindenParkes sharing his codes for fMRI preprocessing.
Resting brain dynamics at different timescales capture distinct aspects of human behavior | nature.com/articles/s4146… | new work by @R_Liegeois & @bttyeo et al
Transcriptional Signatures of the Hierarchical Chronnectome Organization in the Human Brain biorxiv.org/content/10.110…
New from BCCL, by Taylor Bolt, with @TheColeLab: The situation or the person? Individual and task‐evoked differences in BOLD activity onlinelibrary.wiley.com/doi/10.1002/hb…
Humans have stronger brain connectivity in areas related to information integration and language than chimpanzees do. A study published in PNAS this week suggests that information integration is key to the development of human higher-order cognition: ow.ly/p7Ot30o6UzA
Here are my slides on "Reliable individual functional networks and their relationship to behavior": slideshare.net/EmilyFinn2/fin…
Stationary multivariate AR model explains (apparently dynamic) resting state functional connectivity just fine.
Stationary multivariate AR model explains (apparently dynamic) resting state functional connectivity just fine.
Absolutely amazing result: new brain measure ("morphometric similarity networks") explains *40%* of variance in IQ! biorxiv.org/content/early/…
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