New Annual Review with @nathanieldaw.bsky.social: “Planning in the Brain: It's Not What You Think It Is.” We argue that the brain's 'planning' machinery is mostly used for learning from simulated experience, and that thinking prospectively at decision time is just one special case of this process.
@hhmi-science.bsky.social's
#FreemanHrabowski Scholars Program offers early career faculty up to $10M over 10 yrs, plus salary & benefits
Stable, sustained support can transform your career:
Senior Postdoc? This year's competition has a program for you too. Applications open 11/3! bit.ly/4vhC0LA
⏳ Two weeks left to send us your Satellite Workshop proposals for the #BernsteinConference 2026!
🗓️ Deadline: April 29, 15:00 CEST
More info 👉 bit.ly/40HybkI
#BernsteinNetwork #CompNeuro
I’m excited to share that I’ll be starting my computational neurosci & machine learning lab at UCLA this July! ☀️
We’ll be working on computational methods for high-throughput neural data analysis, optical interrogation of neural circuits, & mechanistic models of artificial+bio neural systems. ⤵️
My main postdoc work is now published: www.nature.com/articles/s41...! We (myself, Isabel Low, Frances Cho, and @lgiocomo.bsky.social) discovered task-relevant remote representations in entorhinal cortex independent of CA1. #paperthread below! 1/13
Today, we’re thrilled to report “A right-hemispheric language network at single-neuron resolution”, the first systematic investigation into the #single #neuron correlates of #language functions in the #right #hemisphere of the #human #brain. #neuroskyence 🧪
www.biorxiv.org/content/10.6...
My lab at U Göttingen is looking for a PostDoc or PhD student to work on an ERC-funded project at the intersection of computer vision, graphics & neuroscience.
It is wonderful to be back in Europe to attend #Cosyne2026, reconnecting with old friends and learning about a lot of exciting work, especially the work by Jeff Magee. Stay curious and see you all next time.
New paper out in PLOS Computational Biology!
We introduce iSTTC, a robust method to estimate intrinsic neural timescales from single-unit recordings.
Congrats to Irina Pochinok for leading the project!
Package: github.com/iinnpp/isttc
Paper: journals.plos.org/ploscompbiol...
To accommodate applicants and PIs attending Cosyne, we’ve extended the MCN application deadline to Sunday, Mar 22.
Please repost.
Excited to be in Lisbon for my first #cosyne26 and to present TONIGHT on my work on developmental changes to spectral tuning and vocalization processing (and their interactions) in the postnatal auditory cortex! Poster 1-167, come to learn more or just to see me fight through the jet lag!
How does the brain build a memory?
A common assumption is that the neurons activated during an experience collectively form the memory engram.
In our new Nature Neuroscience paper (finally out!), we show that this is not the case.
www.nature.com/articles/s41...
The deadline for applying to the Methods in Computational Neuroscience summer course at MBL in Woods Hole is approaching (March 16)! An exciting course with an amazing lineup of lecturers in a beautiful location www.mbl.edu/education/ad...
Interested in cell type diversity, the cortical operating regime, and how recurrent connections shape the integration of feedforward and feedback inputs during context-dependent processing? Come check out my poster [1-038] at #Cosyne2026.
Link: doi.org/10.64898/2026.02.06.704473
Happy to announce our latest preprint with Friedrich Schuessler and Simone Ciceri: www.biorxiv.org/content/10.6...
A good part of animal behaviour and cognition is innate. Have you ever wondered how the underlying neural circuits develop? We may have a suggestion.
I will present a poster on this work at Cosyne and would be very happy to discuss it further with anyone interested.
🚨 preprint alert!
Check out our revised manuscript out on bioRxiv, where we strengthen the link between D1-dependent dopamine signaling in the anterior insular cortex and the control of anxiety.
@anna-beyeler.bsky.social
www.biorxiv.org/content/10.1...
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
Finally, we highlight the importance of ubiquitous biological features, such as recurrent connections and input-output nonlinearities, in shaping the integration of feedforward and feedback inputs during context-dependent processing. (11/11)
We show that assessing cell-type-specific circuit stabilization requires patterned perturbations, where paradoxical effects manifest along specific activity modes. We further characterize the spatial structure of the required patterned perturbations. (10/11)
As shown below, although SST is required for stabilization across the top optimized models under this stimulus condition, a uniform excitatory perturbation of SST does not always paradoxically decrease in its mean activity; in several models, the mean activity instead increases. (9/11)
Interestingly, we find that in high-dimensional spatially extended models, even when a specific inhibitory cell type is required for circuit stabilization, a uniform perturbation of it does not necessarily produce a paradoxical change in its mean activity. (8/11)
Most previous computational studies have focused on either population models or networks lacking explicit spatial structure. Perturbations used to probe paradoxical effects are typically applied uniformly to all inhibitory neurons, every inhibitory neuron receives the same perturbative input. (7/11)
As shown in Tsodyks et al. (1997), Sanzeni et al. (2020), and Sadeh & Clopath (2021), inhibition stabilization is commonly associated with paradoxical effects, whereby inhibitory activity paradoxically decreases in response to excitatory current injection into the inhibitory population. (6/11)
More specifically, while PV-mediated stabilization is indispensable across all models and stimulus conditions, SST-mediated stabilization is also required, and likely in a stimulus-dependent manner. (5/11)
This context-dependent shift in the dominance of cell-type-specific inhibition is accompanied by a corresponding change in cell-type-specific inhibition stabilization, that is, a change in the requirement of a particular inhibitory cell type for stabilization. (4/11)
Analysis of well-fitting models reveals that the dominant inhibitory cell type affecting excitatory neurons is not fixed but dynamically varies with stimulus and space. (3/11)
To answer these questions, we use data-driven approaches to construct spatially extended circuit models that capture the responses of diverse cell types in the mouse primary visual cortex during context-dependent processing. (2/11)
Excited to share our new work from @kenmiller.bsky.social lab!
How do different cell types, interacting via recurrent connections, give rise to context-dependent processing and circuit stability, and what dynamical signatures reveal their individual roles? (1/11)
doi.org/10.64898/2026.02.06.704473
Our paper is out in @natneuro.nature.com!
www.nature.com/articles/s41...
We develop a geometric theory of how neural populations support generalization across many tasks.
@zuckermanbrain.bsky.social
@flatironinstitute.org
@kempnerinstitute.bsky.social
1/14