Tootfinder

celegans_2019: Complete C. elegans neurons (2019)
Networks among neurons of both the adult male and adult hermaphrodite worms C. elegans, constructed from electron microscopy series, to include directed edges (chemical) and undirected (gap junction), and spanning including nodes for muscle and non-muscle end organs.
This network has 585 nodes and 1755 edges.
Tags: Biological, Connectome, Weighted

Isaiah Bond, Quinshon Judkins clear of charges nearing NFL debuts; Michigan awaits NCAA sign-stealing decision

https://www.cbssports.com/nfl/news/isaiah…

🧠 Electro-optical Mott neurons made of niobium dioxide created for brain-inspired computing
https://techxplore.com/news/2025-08-electro-optical-mott-neurons-niobium.html

Electro-optical Mott neurons made of niobium dioxide created for brain-inspired computing
Over the past decades, engineers have introduced a wide range of computing systems inspired by the human brain or designed to emulate some of its functions. These include devices that artificially reproduce the behavior of brain cells (e.g., neurons), by processing and transmitting signals in the form of electrical pulses.

Optimal trace norms for Helmholtz problems
Benedikt Gr\"a{\ss}le
https://arxiv.org/abs/2506.11944 https://arxiv.org/pdf/2506.119…

Optimal trace norms for Helmholtz problems
The natural $H^1(Ω)$ energy norm for Helmholtz problems is weighted with the wavenumber modulus $σ$ and induces natural weighted norms on the trace spaces $H^{\pm1/2}(Γ)$ by minimial extension to $Ω\subset\mathbb R^n$. This paper presents a rigorous analysis for these trace norms with an explicit characterisation by weighted Sobolev-Slobodeckij norms and scaling estimates, highlighting their dependence on the geometry of the extension set $Ω\subset\mathbb R^n$ and the weight $σ$. The anal…

Recurrent pattern completion drives the neocortical representation of sensory inference (in mice) https://www.nature.com/articles/s41593-025-02055-5 "neurons that encode sensory inference are specialized for receiving and locally broadcasting top-down information"

Recurrent pattern completion drives the neocortical representation of sensory inference - Nature Neuroscience
Neurons that respond emergently to illusory contours drive pattern completion in V1. Pattern completion in lower cortical areas may therefore mediate perceptual inference by selectively reinforcing activity patterns that match prior expectations.

MindGrab for BrainChop: Fast and Accurate Skull Stripping for Command Line and Browser
Armina Fani (Tri-Institutional Center for Translational Research in Neuroimaging and Data Science), Mike Doan (Tri-Institutional Center for Translational Research in Neuroimaging and Data Science), Isabelle Le (Tri-Institutional Center for Translational Research in Neuroimaging and Data Science), Alex Fedorov (Emory University), Malte Hoffmann (Harvard University), Chris Rorden (University of South C…

MindGrab for BrainChop: Fast and Accurate Skull Stripping for Command Line and Browser
We developed MindGrab, a parameter- and memory-efficient deep fully-convolutional model for volumetric skull-stripping in head images of any modality. Its architecture, informed by a spectral interpretation of dilated convolutions, was trained exclusively on modality-agnostic synthetic data. MindGrab was evaluated on a retrospective dataset of 606 multimodal adult-brain scans (T1, T2, DWI, MRA, PDw MRI, EPI, CT, PET) sourced from the SynthStrip dataset. Performance was benchmarked against Synth…

Solarbetriebener Roboter bekämpft Unkraut mit KI und Hacke
Herbizide gegen Unkraut belasten die Nahrungsmittel, sind in der Landwirtschaft aber unerlässlich. Wirklich? Roboter können Unkraut umweltfreundlich beseitigen.

Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs
Yixiao Zhou, Ziyu Zhao, Dongzhou Cheng, zhiliang wu, Jie Gui, Yi Yang, Fei Wu, Yu Cheng, Hehe Fan
https://arxiv.org/abs/2509.10377

Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs
Sparse Mixture-of-Experts (SMoE) architectures are widely used in large language models (LLMs) due to their computational efficiency. However, though only a few experts are activated for each token, SMoE still requires loading all expert parameters, leading to high memory usage and challenges in deployment. Previous work has tried to reduce the overhead by pruning and merging experts, but primarily focused on expert-level operations, leaving neuron-level structure underexplored. We propose DERN…

Complexity of mixed Schatten norms of quantum maps
Jan Kochanowski, Omar Fawzi, Cambyse Rouz\'e
https://arxiv.org/abs/2507.08358 https://

Complexity of mixed Schatten norms of quantum maps
We study the complexity of computing the mixed Schatten $\|Φ\|_{q\to p}$ norms of linear maps $Φ$ between matrix spaces. When $Φ$ is completely positive, we show that $\| Φ\|_{q \to p}$ can be computed efficiently when $q \geq p$. The regime $q \geq p$ is known as the non-hypercontractive regime and is also known to be easy for the mixed vector norms $\ell_{q} \to \ell_{p}$ [Boyd, 1974]. However, even for entanglement-breaking completely-positive trace-preserving maps $Î…

fly_larva: Drosophila larva brain (2023)
A complete synaptic map of the brain connectome of the larva of the fruit fly Drosophila melanogaster. Nodes are neurons, and edges are synaptic connections, traced individually from brain image sections using three-dimensional electron microscopy–based reconstruction. Node metadata include the neuron hempisphere, hemispherical homologue, cell type, annotations, and inferred cluster. Edge metadata include the type of interaction (`'aa'`,…