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Related Articles from SNS
SC-TauPath: A Structural Connectivity Attribution Framework for Mapping Tau Propagation Pathways in Alzheimer's Disease
arXiv:2606.04066v1 Announce Type: cross Abstract: Understanding how structural connections are associated with tau propagation in Alzheimer's disease (AD) remains a central open question, yet existing computational models either rely heavily on biophysical assumptions or lack neurobiologically interpretable pathway maps. We present SC-TauPath, a structural connectivity (SC) attribution framework that maps tau propagation pathways from in vivo neuroimaging data. SC-TauPath combines a Network...
Structural Connectivity Between the Zinc Linchpin Motif, the cluster, and the active site orchestrates DNA repair in MUTYH
The DNA glycosylase MUTYH protects genomic integrity by excising adenine mispaired with 8-oxoguanine (OG), which initiates base excision repair (BER). The [4Fe-4S] cluster DNA binding domain and Zn linchpin motif of MUTYH are hotspots for inherited cancer associated variants (CAVs) highlighting their critical functions in DNA repair. Here, we present three full-length human MUTYH crystal structures bound to DNA across three catalytic states, representing early and late transition states and...
Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability
new Abstract: Many striking phenomena in deep learning, such as linear mode connectivity and the structured behavior of training dynamics, are closely tied to parameter symmetries: transformations that leave the realized function unchanged. Despite growing attention to parameter symmetries, the exact interplay between parameters, data, and representations remains underexplored. To investigate this, we develop a theoretical framework of effective function classes, i.e., the set of functions a...
Identifying Connectivity Distributions from Neural Dynamics Using Flows
arXiv:2603.26506v2 Announce Type: replace-cross Abstract: Connectivity structure shapes neural computation, but inferring this structure from population recordings is degenerate: multiple connectivity structures can generate identical dynamics. Recent work uses low-rank recurrent neural networks (lrRNNs) to infer low-dimensional latent dynamics and connectivity from observed activity, enabling a mechanistic interpretation of the dynamics. However, standard approaches for training lrRNNs can...
From Boundary Crossings to Global Connectivity: A Minimal Mechanism in Structured Agent-Based Landscapes
arXiv:2606.07344v1 Announce Type: new Abstract: This study investigates a minimal mechanism through which local mobility heterogeneity produces global reconfiguration in structured agent-based systems. Agents move in a multi-attractor landscape, where a small fraction exhibits higher-mobility exploratory dynamics while the remainder remain locally constrained. By comparing random-walk exploration, interface-sensitive dynamics, novelty-biased exploration, and a flat-landscape control, I...
A prognostic human brain network for diffuse midline glioma
Abstract Diffuse midline gliomas (DMGs) are near-universally lethal tumours of the childhood central nervous system1,2. In animal models, DMGs form brain-wide integrated networks through neuron-to-glioma synapses3,4,5,6 and glioma-to-glioma gap junctional coupling3. This extensive connectivity robustly promotes the growth and invasion of DMG3,4,5,6,7,8,9 and other glial malignancies10,11,12 through paracrine mechanisms and direct neuron-to-glioma synapses.
Connectivity Logic of Dendritic Spines in Cortex: Increased Inputs and Ensemble Formation
Dendritic spines, small protrusions covering the dendrites of most neurons, are fundamental elements of synaptic connectivity, yet their network-level organization remains poorly understood. Here we leverage the large-scale MICrONS volumetric electron microscopy dataset of mouse primary visual cortex to explore the connectivity logic of dendritic spines across multiple spatial scales. Our analysis provides structural support for the ``connectivity and diversity'' hypothesis, showing that,...
Brain-Atlas-Guided Generative Counterfactual Attention for Explainable Cognitive Decline Diagnosis Using Multimodal Connectomes
new Abstract: Mild cognitive impairment (MCI) and subjective cognitive decline (SCD) are closely associated with the early Alzheimer's disease continuum, where accurate and explainable diagnosis is important for early risk assessment and intervention. Existing connectome-based deep learning models can improve classification performance but often provide limited insight into disease-related functional and structural connectivity changes. This paper proposes an atlas-knowledge-guided...
Orbital Networks in the Three-Body Problem
Announce Type: cross Abstract: Orbital transfers in multi-body systems are often studied as isolated trajectory design problems, making it difficult to identify the larger transport structure connecting families of periodic orbits, including which families act as hubs, gateways, relays, or persistently difficult-to-access regions. This work introduces a reachable-set-based framework for constructing orbital networks in the circular restricted three-body problem. Finite-$\Delta V$ and...
Multi-Column RBF Neural Network Using Adaptive and Non-Adaptive Particle Swarm Optimization
new Abstract: The radial basis function neural network (RBFN) trained with a gradient descending algorithm provides an effective fully connected structure in both shallow and deep networks. The error correction (ErrCor), a state-of-the-art gradient-based training method, selects optimal hidden units to improve accuracy. Alternatively, as a population-based algorithm, the particle swarm optimization algorithm (PSO) uses the swarm experience to optimize RBFN parameters, offering global search...