6 papers · ranked by Valyu relevance
Eun Joo Kim, Ji Hoon Jeong, June-Seek Choi, Jeansok J. Kim
A fundamental challenge for animals and humans is resolving competing survival demands under naturalistic threat, yet circuit-level mechanisms remain poorly understood. We developed a paradigm recapitulating a predator-prey encounter: Long-Evans rats emerged from a nest to forage in an open arena, choosing between…
Robert M. Hechler, Tianna Peller, Marie-Josée Fortin, Martin Krkosek
Population fluctuations are now empirically recognized to be nonlinear, but the governing attractors are poorly understood. Here we show that population dynamics of 457 marine fish stocks from 121 species worldwide are governed by a single attractor that partitions into three archetypes reflecting top predators…
Yuji Ikegaya
Among the human senses, hearing is distinguished by its high frequency resolution and sensitivity to spatiotemporal patterns. Accordingly, sonification—the rendering of neural activity as sound for direct perception—has a long history in neuroscience. Although sonification can facilitate exploration of the temporal…
Nivethigha Elango, Liza J. McCann, David M. Hughes
Childhood-onset rheumatic diseases including Juvenile Idiopathic Arthritis (JIA), Juvenile Systemic Lupus Erythematosus (jSLE), and Juvenile Dermatomyositis (JDM) could impact growth, but this is not well described within the UK population, particularly over the long term. This study aims to compare the growth patterns…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…
Panagiotis Douris, George Kodovazenitis
The integration of artificial intelligence (AI) into dentistry is reshaping clinical workflows, opening new possibilities for population-level public health monitoring. Machine learning approaches, such as convolutional neural networks and other deep learning architectures, are becoming more and more capable to exhibit…