Noise as a Network Regulator: Unexpected Dynamics in Neural Circuits
![The study demonstrates how the dynamics of neuronal firing rates-specifically, the mean firing rate and membrane potential-shift across regimes determined by the correlation of noise, with theoretical predictions aligning with simulations of quadratic integrate-and-fire neurons, and revealing a dependence on both the correlation coefficient and noise intensity as described by the deterministic component of [latex]Eq. (9)[/latex].](https://arxiv.org/html/2601.10032v1/x2.png)
New research reveals that correlated noise in networks of spiking neurons can surprisingly stabilize activity and induce unique states of metastability.
Science
Building Trustworthy AI: Combining Simple Models for Robust Performance
A new approach leverages mixtures of transparent local models to create interpretable machine learning systems with guaranteed performance bounds.
Can AI Truly Hear? Testing Audio Models in the Real World
A new benchmark reveals that current audio AI struggles with the complexities of everyday sound, often performing worse with common noise reduction techniques.
The Benefits of Being Forgetful: How AI Can Learn Like Humans
New research reframes forgetting in large language models as a crucial cognitive process, not a limitation, and demonstrates a method for leveraging this to improve reasoning abilities.
Taming the LSST Data Flood: Meet Alertissimo
The Vera C. Rubin Observatory’s LSST will generate an unprecedented deluge of astronomical alerts, and a new tool called Alertissimo is designed to help scientists manage and analyze this real-time stream.
Predicting Winter Surges: A New Alert System for Pediatric Respiratory Illness
![The study demonstrates a predicted hospitalization curve [latex] H_{\text{SIR}}(t) [/latex], revealing a peak magnitude [latex] h_{\text{SIR}} [/latex] occurring on day [latex] t_{\text{SIR}} [/latex], thereby establishing a quantifiable relationship between epidemiological parameters and peak healthcare demand.](https://arxiv.org/html/2601.09821v1/figs/ModelSIR.png)
Researchers have developed a forecasting model to anticipate peaks in pediatric respiratory infections, offering hospitals crucial time to prepare for increased demand.
Seeing is Understanding: AI Gains Smarter Vision for Roadside Assets
A new approach harnesses the power of artificial intelligence to accurately identify and analyze roadside infrastructure, paving the way for proactive maintenance and improved urban planning.
Decoding Nature’s Rhythms with Machine Learning
New data-driven methods are allowing scientists to unravel the complex dynamics of ecological and epidemiological systems with unprecedented accuracy.
Unlocking Black Box Time Series: A New Approach to Explainable AI
Researchers have developed a novel framework for dissecting complex time series models and revealing the underlying drivers of their predictions.
When AI Plays Doctor: Safety Advances in Child Health
New research reveals that large language models are becoming safer in simulated pediatric consultations, but bigger isn’t always better.