Martin Vinck

PhD Research Fellow in computational neuroscience/brain physics (290338) | University of Oslo Job title: PhD Research Fellow in computational neuroscience/brain physics (290338), Employer: University of Oslo, Deadline: Tuesday, December 9, 2025

PhD position in computational neuroscience/brain physics to work with us on biophysical modeling of electric and magnetic brain signals at University of Oslo as part of the Marie Curie EU project @neuronanotechdn.bsky.social. Application deadline: December 9th.
www.jobbnorge.no/en/available...

Congrats, awesome work!

Traveling waves across scales: Different mechanisms but same canonical computation? The review proposes a novel mechanistic distinction between first- and second-order traveling waves that subserves a same canonical computation by ordering neuronal processing to impose a computationa...

🚨New publication!
I am extremely happy to share this new review article in elife on #Traveling_Waves!

@erc.europa.eu
@upcite.bsky.social

elifesciences.org/articles/106...

nice paper on inter-personal / inter-brain interactions with many implications how to measure & conceptualize these interactions

We just need people pushing on both th and exp ends and that's fine. I do think the really consolidated theory we have is of single neurons (eg cable, HH, nernst eq) and not on networks of neurons. But we are missing a lot of single neuron data to perhaps figure out more complex single neuron laws.

List of SFN presentations from the Hoffman lab

Here are our contributions for #SFN2025 #SFN25, Sunday and Monday morning. Hope to see you there!

Learning-dependent cholinergic plasticity reconfigures cortical circuit dynamics Neuromodulation by acetylcholine (ACh) plays a critical role in reshaping neural dynamics in the neocortex as a function of development, behavioral state, and learning [1][1]–[6][2]. Prior work sugges...

See our latest - collab with @jess-cardin.bsky.social, led by @andrewmoberly.bsky.social. We combined mesoscopic and 2p imaging to show that learning-dependent plasticity of ACh release in visual cortex drives enhanced visual representations and conditioned behavior. 1/5 tinyurl.com/3cfea6df

New preprint:

Neural manifolds that orchestrate walking and stopping

Here we develop a new theory for neural generation of walking and how it can stop- Next we test the theory using Neuropixels probes in the lumber spinal cord of freely moving rats. See more:

www.biorxiv.org/content/10.1...

Postdoc Position: Neural Circuitry Underlying Working Memory | Radboud University Do you want to work as a Postdoc Position: Neural Circuitry Underlying Working Memory at the Faculty of Social Sciences? Check our vacancy!

🚨🧠🚨 POSTDOC POSITION 🚨🧠🚨 in my lab: www.ru.nl/en/working-a... Connectivity in Working Memory. Deadline 12 Nov! Apply via website; please repost.

View from your office onto Giessen and surrounding villages.

Please repost! I am looking for a PhD candidate in the area of Computational Cognitive Neuroscience to start in early 2026.

The position is funded as part of the Excellence Cluster "The Adaptive Mind" at @jlugiessen.bsky.social.

Please apply here until Nov 25:
www.uni-giessen.de/de/ueber-uns...

Connectivity Structure and Dynamics of Nonlinear Recurrent Neural Networks The structure of brain connectivity predicts collective neural activity, with a small number of connectivity features determining activity dimensionality, linking circuit architecture to network-level...

Now in PRX: Theory linking connectivity structure to collective activity in nonlinear RNNs!
For neuro fans: conn. structure can be invisible in single neurons but shape pop. activity
For low-rank RNN fans: a theory of rank=O(N)
For physics fans: fluctuations around DMFT saddle⇒dimension of activity

The missing half of the neurodynamical systems theory Bifurcations—an underexplored concept in neuroscience—can help explain how small differences in neural circuits give rise to entirely novel functions.

Timely by Xiao-Jing Wang

Bifurcations—an underexplored concept in neuroscience—can help explain how small differences in neural circuits give rise to entirely novel functions.

www.thetransmitter.org/neural-dynam...

Strongest data yet suggesting that repeated MDMA use causes deficits in declarative memory (e.g., memory for new information, words, etc). #psychedelicscience #MDMA

10.1093/brain/awaf391

A mean-field model of neural networks with PV and SOM interneurons reveals connectivity-based mechanisms of gamma oscillations Classic theoretical models of cortical oscillations are based on the interactions between two populations of excitatory and inhibitory neurons. Nevertheless, experimental studies and network simulatio...

Various theoretical properties derived for gamma oscillations based on canonical E-SOM-PV microcircuit connectivity using mean-field modelling, which moves beyond classic Wilson-Cowan models in important ways
biorxiv.org/content/10.1... - w. Farzin Tahvili & Matteo Di Volo

New #NeuroAI preprint on #ContinualLearning!

Continual learning methods struggle in mostly unsupervised environments with sparse labels (e.g. parents telling their child the object is an 'apple').
We propose that in the cortex, predictive coding of high-level top-down modulations solves this! (1/6)

Really interesting work by Bakhurin and colleagues challenging the reward prediction error hypothesis of dopamine:
www.nature.com/articles/s41...
I love this figure which both echoes and undermines the famous figure from Schultz et al. (1997).

PhD Position: Theory of Learning in Artificial and Biologically Inspired Neural Networks | Radboud University Do you want to work as a PhD candidate Theory of Learning in Artificial and Biologically Inspired Neural Network? Check our vacancy!

Please RT - Open PhD position in my group at the Donders Center for Neuroscience, Radboud University.

We're looking for a PhD candidate interested in developing theories of learning in neural networks.

Applications are open until October 20th.

For more info: www.ru.nl/en/working-a...

Can self supervised learning help understand how the brain learns to see the world?

Our latest study, led by Josephine Raugel (FAIR, ENS), is now out:

📄 arxiv.org/pdf/2508.18226
🧵 thread below

Now out in @cp-cellreports.bsky.social: PV and SOM cells play distinct causal roles in controlling network oscillations and stability

with Matteo di Volo and Farzin Tahvilli

www.cell.com/cell-reports...

Beyond Rate Coding: Surrogate Gradients Enable Spike Timing Learning in Spiking Neural Networks We investigate the extent to which Spiking Neural Networks (SNNs) trained with Surrogate Gradient Descent (Surrogate GD), with and without delay learning, can learn from precise spike timing beyond fi...

New preprint for #neuromorphic and #SpikingNeuralNetwork folk (with @pengfei-sun.bsky.social).

arxiv.org/abs/2507.16043

Surrogate gradients are popular for training SNNs, but some worry whether they really learn complex temporal spike codes. TLDR: we tested this, and yes they can! 🧵👇

🤖🧠🧪

To claim that sensory responses of visual cortical neurons are not prediction errors (based on the data the authors have) is unwarranted. There is ample evidence for stimulus surround and visuomotor prediction errors.

fully agreed!

Super! Congrats!

Direct entorhinal control of CA1 temporal coding Nature Communications - Temporal coding in the hippocampus is thought to be key for memory and predictions. Here, the authors show that blocking one entorhinal input affects two aspects of...

Our collaboration - from PhD work - examining input-specific (EC L3) contributions to rate and temporal coding in CA1 place cells is now out in @natcomms.nature.com 🔬🧠

rdcu.be/evWtz

The situation in Germany has also gotten more difficult with NHP experiments in several ways - I am curious if we are / will be seeing the same trend as in the Netherlands. Is Europe setting an example, or is it just relying on the convenient fact that NHP research will be done elsewhere anyway?

This should be bigger news - the Dutch parliament decided to strongly reduce non-human primates experiments. Subsidy for the large primate center - which includes important virology research unique in Europe - is gradually reduced to zero by 2030. Going towards the end of NHP research in NL...

Log-Normal Multiplicative Dynamics for Stable Low-Precision Training of Large Networks Studies in neuroscience have shown that biological synapses follow a log-normal distribution whose transitioning can be explained by noisy multiplicative dynamics. Biological networks can function sta...

Together with @repromancer.bsky.social, I have been musing for a while that the exponentiated gradient algorithm we've advocated for comp neuro would work well with low-precision ANNs.

This group got it working!

arxiv.org/abs/2506.17768

May be a great way to reduce AI energy use!!!

#MLSky 🧪

Agreed. And one seems like a useful distraction for the other ...

It’s ironic that amid huge cuts to science and education funding and enforcement of Dutch-only programs, extra money is spent attracting US scientists. I support international collaboration, but without investing in our own students and education, science can’t thrive.

www.nwo.nl/en/news/upda...

High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model Computation in recurrent networks of neurons has been hypothesized to occur at the level of low-dimensional latent dynamics, both in artificial systems and in the brain. This hypothesis seems at odds ...

The firing of neural populations is high-dim even if their subthreshold activity is low-dim! This work by @bio-emergent.bsky.social and @haydari.bsky.social shows how, with a solvable model, a data analysis technique, and data from mouse visual cortex: www.biorxiv.org/content/10.1...