SchottdorfLab

First preprint from the lab! Using intracellular recordings & analysis of 2-photon imaging data, we show that spiking & neuromodulatory input during experience drive a reorganization of visuomotor inputs in V1 layer 2/3 neurons, consistent with enhanced visuomotor cancellation - bioRxiv link below.

Two-photon calcium imaging at 24,000 lines/s, with the resonant axis spanning 4x what other systems can do. Inertia-free. Diffraction-limited. No tradeoffs. Che-Hang Yu developed a 4x angle multiplier for laser scanning. His paper is out today: opg.optica.org/optica/fullt... 1/n #fluorescenceFriday

Compact deep neural network models of the visual cortex Nature - Parsimonious deep neural network models can be used for prediction of visual neuron responses.

DNN models of the brain are getting bigger. Are we replacing one complicated system in vivo with another in silico?

In new work, we seek the *smallest* DNN models of visual cortex, balancing prediction with parsimony.

It turns out these compact models are surprisingly small!

rdcu.be/e5H8G

hey team! I need advice! If there were theoretically an organization whose sole purpose was to systematically identify and break nuisance and stupid IP in the biomedical space, creating shareware equivalents, what would be the highest value targets? e.g., AAV serotypes, antibodies, CRISPR, 1/n

CascadeTorch: a PyTorch version of Cascade for spike inference I’m glad to share a PyTorch-based implementation of spike inference from calcium imaging data: CascadeTorch, now available on GitHub. The original Cascade repository remains fully supported. …

Interested in deep learning-based spike inference with Cascade? We re-implemented the code in Torch -previously in Tensorflow - for better compatibility.

Blog: gcamp6f.com/2026/02/17/c...

GitHub: github.com/PTRRupprecht...

Mathematical Methods in Computational Neuroscience Summer school in Eresfjord, Norway (July 8th - 26th, 2024)

Applications are now open for the summer school: 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐚𝐥 𝐌𝐞𝐭𝐡𝐨𝐝𝐬 𝐢𝐧 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐍𝐞𝐮𝐫𝐨𝐬𝐜𝐢𝐞𝐧𝐜𝐞

🧠 Apply before March 15: www.compneuronrsn.org

📍 Located in beautiful Eresfjord 🇳🇴
🗓️ Between July 6-24

Supported by the @kavlifoundation.org
In collaboration with @kavlintnu.bsky.social

@sebastianseung.bsky.social Did you follow through on your plan to visit Epstein island?

Here’s a trainee sticking their neck out to ask a fair and important question. Admiration! (And obviously, follow @juliecharlton.bsky.social).

Hey @eboyden3.bsky.social care to explain?

New @pnas.org paper out 🎉

“Representational drift reflects ongoing balancing of stochastic changes by Hebbian learning”

👉 doi.org/10.1073/pnas...

What drives representational drift in neural populations? Here’s the short version. 👇

🧪🧠

1/5

Neural representations of visual memory in inferotemporal cortex reveal a generalizable framework for translating between spikes and field potentials Translating neurophysiological findings requires understanding the relationship between common measures of brain activity in animals (spiking activity) and humans (local field potentials, LFP). Prior ...

🚨 New preprint!

Why do some insights from spikes translate to field potentials while others don't? In this paper we compare visual memory representations in spikes and LFPs to propose a general framework that answers this question.

www.biorxiv.org/content/10.6...

🧵 (1/10)

🧠🟦 🧠💻

That means so much <3 @elbusch.bsky.social

With Masashi launching his new lab, we’ll be recruiting a new postdoc in the Oldenburg Lab.
Work: high-precision multiphoton holography, neural coding, motor cortex circuits, all-optical physiology.
If you’re interested, just reach out.

Proud to share that my first postdoc, Masashi Hasegawa, will be starting his own lab as a Chica and Heinz Schaller Research Group Leader at Heidelberg University! He’ll be continuing our holography-based work on cortical circuits. Phenomenal scientist, even better human.

*Fully funded PhD student positions available to discover what changes in 🧠 when we learn something new.*

You think virtual reality + laser scanning microscopy are cool? You like 💻 and 🐭? Come join us!

Apply either through
www.udel.edu/academics/co...
or
www.udel.edu/academics/co...

State-space trajectories and traveling waves following distraction Cortical activity shows the ability to recover from distractions. We analyzed neural activity from the prefrontal cortex (PFC) of monkeys performing working memory tasks with mid-memory-delay distract...

Let me google that for you :-) www.biorxiv.org/content/10.1... Using the Churchland jPCA method. Worth reading in full

Our work with @pawa-pawa.bsky.social is out in Nature Machine Intelligence! The choice of activation function affects the representations, dynamics, and circuit solutions that emerge in RNNs trained on cognitive tasks. Activation matters!
www.nature.com/articles/s42...

MIT’s McGovern Institute and Department of Brain and Cognitive Sciences welcome new faculty member Sven Dorkenwald - MIT McGovern Institute The McGovern Institute and the Department of Brain and Cognitive Sciences are pleased to announce the appointment of Sven Dorkenwald as an assistant professor starting in January 2026. A trailblazer i...

Excited to share more widely: I am starting the Dorkenwald Lab at MIT (McGovern Institute + BCS) in January 2026. We study the organizational principles of neuronal circuits using connectomics.

And we are hiring postdocs & tech associates! dorkenwaldlab.com/join

Even colleagues who should know better are claiming that we are halting animal research. No, we're not. Now this NYT opinion piece appears (gift link) www.nytimes.com/2025/10/08/o... You can't just move everything to cell culture, organoids, and computers. Even this NYT piece admits that. 1/3

Mouse vs. AI: A Neuroethological Benchmark for Visual Robustness and Neural Alignment Visual robustness under real-world conditions remains a critical bottleneck for modern reinforcement learning agents. In contrast, biological systems such as mice show remarkable resilience to environ...

🚨Our NeurIPS 2025 competition Mouse vs. AI is LIVE!

We combine a visual navigation task + large-scale mouse neural data to test what makes visual RL agents robust and brain-like.

Top teams: featured at NeurIPS + co-author our summary paper. Join the challenge!

Whitepaper: arxiv.org/abs/2509.14446

From the popular series "Figures that look like Kraftwerk Albums". Fig. 3 in Georgopoulos et al. Science 1986. Contributions of individual neurons to a shared coding direction in state space — pubmed.ncbi.nlm.nih.gov/3749885/

Working memory expands shared task representations in cortex Cognition is thought to emerge from the flexible organization of neural activity, yet how this organization reconfigures across behaviors varying in cognitive load remains unclear. We investigated how...

Using calcium imaging with single cell resolution across brain areas while mice solve two VR navigation problems, we discovered that neural manifolds can change in size based on working memory demands! Check out Mika Diamanti's amazing work: www.biorxiv.org/content/10.1...

Working memory expands shared task representations in cortex https://www.biorxiv.org/content/10.1101/2025.09.29.679345v1

Transitions in dynamical regime and neural mode during perceptual decisions - Nature Simultaneous recordings were made of hundreds of neurons in the rat frontal cortex and striatum, showing that decision commitment involves a rapid, coordinated transition in dynamical regime and neura...

How does the brain decide? 🧠

Our new @nature.com paper shows that neural activity switches from an 'evidence gathering' to a 'commitment' state at a precise moment we call nTc.

After nTc, new evidence is ignored, revealing a neural marker for the instant when the mind is made up.

rdcu.be/eGUrv

Thrilled that our new review "Motor Working Memory" is now in press at TiCS!

@cp-trendscognsci.bsky.social
@cellpress.bsky.social

By me +
Hanna Hillman

We argue that a dedicated research program on 'working memory for movements' is long overdue

Link: authors.elsevier.com/a/1lmMX4sIRv...

(1/8) New paper from our team!

Yu Duan & Hamza Chaudhry introduce POCO, a tool for predicting brain activity at the cellular & network level during spontaneous behavior.

Find out how we built POCO & how it changes neurobehavioral research 👇

arxiv.org/abs/2506.14957

Hm. yesss. Great Nerd Sniping potential to do the math for TCRM. My hunch is that Eq. (2) in arxiv.org/html/2504.02... could be a great starting point to add the Dxy constraint. Would be a super cool extension of CRM

Our latest project find shared representations while controlling for confounds is out www.biorxiv.org/content/10.1... Check @s-michelmann.bsky.social 's thread for the executive summary. Code in python and matlab: github.com/s-michelmann... — Now is play time 👨‍💻

🚀Excited to share our project: Canonical Representational Mapping for Cognitive Neuroscience. @schottdorflab.bsky.social and I propose a novel multivariate method to isolate neural representations aligned with specific cognitive hypotheses 🧵https://www.biorxiv.org/content/10.1101/2025.09.01.673485v1

Hi Harrison, this would be hard to compare; you would need some sort of regularization for PSL. The secret sauce of CRM is this regularization. Without it, it's just plain old CCA.