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Interval timing, the ability to perceive and estimate durations between events, is essential for many animal behaviors. In mammals, it is linked to specific cortical and sub-cortical brain regions, but its neural basis in birds remains unclear. We trained two male carrion crows on a time estimation task using visual stimuli, cueing them to wait for a minimum duration of 1500 ms, 3000 ms, or 6000 ms before responding to receive a reward. During the task, we recorded activity from single neurons in the nidopallium caudolaterale (NCL), the avian executive telencephalon. Many neurons showed tuning to specific durations, suggesting that time intervals are encoded as abstract magnitudes along an ordered scale. Population-level decoding revealed that NCL activity predicted the crows' intended wait time, independent of the sensory properties of the cues. These findings show that abstract time estimation can emerge from neural architectures different from the mammalian neocortex.
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http://dx.doi.org/10.1038/s41467-025-63820-5 | DOI Listing |
JMIR Biomed Eng
August 2025
Cardiovascular Center and Divisions of Cardiology and Hospital Medicine, Department of Internal Medicine, National Taiwan University Hospital, No.7, Chung Shan S Rd, Taipei, 100225, Taiwan, 886 2-2312-3456.
Background: Photoplethysmography (PPG) signals captured by wearable devices can provide vascular age information and support pervasive and long-term monitoring of personal health condition.
Objective: In this study, we aimed to estimate brachial-ankle pulse wave velocity (baPWV) from wrist PPG and electrocardiography (ECG) from smartwatch.
Methods: A total of 914 wrist PPG and ECG sequences and 278 baPWV measurements were collected via the smartwatch from 80 men and 82 women with average age of 63.
Drug Alcohol Rev
September 2025
The Prescription Drug Misuse Education and Research (PREMIER) Center, University of Houston, Houston, Texas, USA.
Introduction: Buprenorphine is effective for opioid use disorder (OUD), yet adherence remains suboptimal. This study aimed to identify adherence trajectories, explore their predictors, and assess their association with opioid overdose risk and healthcare costs.
Methods: A retrospective cohort study was conducted using the Merative MarketScan Commercial Database, which includes a nationally representative sample of individuals with private, employer-sponsored health insurance in the United States.
Int J Cosmet Sci
September 2025
Department of Materials, School of Natural Sciences, The University of Manchester, Manchester, UK.
Objectives: Machine-based cyclic combing of hair tresses under dry conditions is a proven method for evaluating hair strength and the impact of treatments. Recent advancements in image analysis allow for a detailed review of hair fragment lengths and quantities produced after specific combing cycles. Our aim is to provide an in-depth analysis of the kinetics of hair fragment formation.
View Article and Find Full Text PDFBiom J
October 2025
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Accelerated failure time (AFT) models offer an attractive alternative to Cox proportional hazards models. AFT models are collapsible and, unlike hazard ratios in proportional hazards models, the acceleration factor-a key effect measure in AFT models-is collapsible, meaning its value remains unchanged when adjusting for additional covariates. In addition, AFT models provide an intuitive interpretation directly on the survival time scale.
View Article and Find Full Text PDFBehav Res Methods
September 2025
Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Cybernetics, Prague, Czech Republic.
Automatic markerless estimation of infant posture and motion from ordinary videos carries great potential for movement studies "in the wild", facilitating understanding of motor development and massively increasing the chances of early diagnosis of disorders. There has been a rapid development of human pose estimation methods in computer vision, thanks to advances in deep learning and machine learning. However, these methods are trained on datasets that feature adults in different contexts.
View Article and Find Full Text PDF