Yanliang Shi
@YanliangShi
Postdoc of Computational Neuroscience @PrincetonNeuro
Scientists need engineers. How can we foster career growth and retention of these highly skilled staff? Read our opinion piece here: thetransmitter.org/craft-and-care…
Excited to share my work with @EngelTatiana, out now in @NatNeuro! We show that RNNs use low-dimensional latent circuit mechanisms for cognitive tasks. We find that context-dependent decisions in both RNNs and PFC arise from latent inhibitory mechanisms. nature.com/articles/s4159…
An incredible lineup of speakers at our workshop "Data-Driven Discovery: AI and Modeling in Biology"! Join us virtually at the Allen Institute from Sept 23-25, 2024—here are the agenda and live stream: alleninstitute.org/events/data-dr…
I'm excited to share that our paper, "Statistically inferred neuronal connections in subsampled neural networks strongly correlate with spike train covariances", was just published in Physical Review E! journals.aps.org/pre/abstract/1…
Going to SfN this year? Join us for a workshop on how to use our Brainwide Map dataset to test your own hypotheses! For more information and to register, visit internationalbrainlab.org/sfn2023
Whole brain BARseq (in situ sequencing) applied to 9 mouse brains...10.3M neurons
What makes cortical areas different? We used BARseq to sequence 10.3 million cells across 9 mouse brains in situ. We found that cortical areas have distinct cell type compositions that are shaped by peripheral inputs. biorxiv.org/content/10.110… 1/17
Open position in Computational Neuroscience at York! 🥳 We have a wonderful community of researchers at York and very exciting funding opportunities through @vistayorku and @ConnectedMinds3! Let me know if you have any questions. yorku.ca/vpepc/faculty-…
Cognitive processes are elusive: each decision takes a unique path observed only in spikes of heterogeneous neurons. In a new preprint, we trace decisions spike-by-spike to uncover the dynamics and geometry of the neural population code for choice. biorxiv.org/content/10.110…
⚡️Announcing️Lightning Pose⚡️ A pose estimation method that learns from both labeled images and a lot of unlabeled videos, via inductive biases like temporal smoothness, posture feasibility, and multi-view consistency. Preprint: tinyurl.com/litpose
Introducing the Allen Brain Cell (ABC) Atlas [ʙᴇᴛᴀ] representing ~5,200 newly transcriptomic-defined cell types and their spatial locations across the whole mouse brain. 🧵 Access ABC Atlas data visualization & pre-publication #openscience datasets: knowledge.brain-map.org/data/LVDBJAW8B…
Which brain regions process information related to sensation, decisions, actions, and prior beliefs? Are these signals widely distributed across the entire brain or concentrated within specific regions? Find out from the Brain-Wide Map just released by @IntlBrainLab on #biorxiv.
We are excited to present a Brain-Wide Map of neural activity during a complex decision-making behavior, a product of the monumental effort of 22 labs: 547 Neuropixels recordings in 267 brain regions from 115 mice collected in 11 labs 🐭 (1/8) biorxiv.org/content/10.110…
🚨Another pre-print alert!🚨Here we use the electrophysiology data from the Brain Wide Map as well as widefield data to investigate the question “Where in the brain is prior knowledge represented?” Recordings in 267 brain regions from 121 mice (1/8) biorxiv.org/content/10.110…
We are excited to present a Brain-Wide Map of neural activity during a complex decision-making behavior, a product of the monumental effort of 22 labs: 547 Neuropixels recordings in 267 brain regions from 115 mice collected in 11 labs 🐭 (1/8) biorxiv.org/content/10.110…
Here, the authors show that intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity. By @roxana_zeraati, @EngelTatiana, @SelfOrgAnna, @YanliangShi, @SteinmetzNeuro, @GeezleTweet, @Alex2Thiele nature.com/articles/s4146…
What approach can explain the link between the brain and behavior? Shall we focus on neural circuits or manifolds? With @chrismlangdon & @MGENK, we provide a unifying perspective on manifolds and circuits, just out in @NatRevNeurosci: nature.com/articles/s4158…. #tweeprint 👇
Thank you so much @MPICybernetics, in particular, Sophia Jahns, for writing such a nice and accessible cover for our study!
Networks looking like road systems can slow down the pace of neural activity. New results by @roxana_zeraati @SelfOrgAnna @EngelTatiana show how the brain can modulate its timescales. Read the full story: kyb.tuebingen.mpg.de/timescalesappl @uni_tue @Princeton
Thrilled to share our paper "Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity" now out @NatureComms! nature.com/articles/s4146… We added interesting new analyses to our preprint version (thanks to the reviewers!) #tweeprint👇
Our article has been published in Nature Communications! Thank you to the editors, reviewers, and my co-authors @EngelTatiana @anne_churchland for a thoughtful and thorough editorial process. The updated article is available at rdcu.be/c278F
In decision-making tasks excitatory and inhibitory neurons show selectively for an upcoming choice. @EngelTatiana, @anne_churchland, and I explore the effects of inhibitory choice selectivity in decision making circuits using mean-field and RNN models. biorxiv.org/content/10.110…
Spatial and temporal correlations in neural networks with structured connectivity, Yan-Liang Shi et al @YanliangShi @roxana_zeraati @SelfOrgAnna @EngelTatiana #Neuroscience go.aps.org/3ipstkX More in our Collection on the Physics of Neuroscience: go.aps.org/3bCA0cm
Our work is out today @PhysRevResearch within the Collection: Physics of Neuroscience. We show how dynamics and connectivity jointly define the spatial and temporal profiles of neural correlations. Thanks to @roxana_zeraati, @SelfOrgAnna, & @EngelTatiana! journals.aps.org/prresearch/abs…