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Long-term memory affects animal fitness, especially in social species. In these species, the memory of group members facilitates the acquisition of novel foraging skills through social learning when naïve individuals observe and imitate the successful foraging behavior. Long-term memory and social learning also provide the framework for cultural behavior, a trait found in humans but very few other animal species. In birds, little is known about the duration of long-term memories for complex foraging skills, or the impact of long-term memory on group members. We tested whether wild jays remembered a complex foraging task more than 3 years after their initial experience and quantified the effect of this memory on naïve jay behavior. Experienced jays remembered how to solve the task and their behavior had significant positive effects on interactions by naïve group members at the task. This suggests that natural selection may favor long-term memory of solutions to foraging problems to facilitate the persistence of foraging skills that are specifically useful in the local environment in social birds with long lifespans and overlapping generations.
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http://dx.doi.org/10.1038/s41598-023-46666-z | DOI Listing |
Anal Methods
September 2025
College of Science, Kunming University of Science and Technology, Kunming, 650500, China.
To address the technical challenges associated with determining the chronological order of overlapping stamps and textual content in forensic document examination, this study proposes a novel non-destructive method that integrates hyperspectral imaging (HSI) with convolutional neural networks (CNNs). A multi-type cross-sequence dataset was constructed, comprising 60 samples of handwriting-stamp sequences and 20 samples of printed text-stamp sequences, all subjected to six months of natural aging. Spectral responses were collected across the 400-1000 nm range in the overlapping regions.
View Article and Find Full Text PDFJ Neurol Neurosurg Psychiatry
September 2025
Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
Background: In Alzheimer's disease (AD), sensitive measures of cognitive decline prior to overt symptoms are urgently needed. Accelerated long-term forgetting (ALF), where new information is retained normally over conventional testing intervals but is then lost at an accelerated rate over the following days and weeks, has been identified cross-sectionally in presymptomatic autosomal dominant and sporadic AD cohorts. We aimed to assess whether ALF testing is predictive of proximity to future symptom onset.
View Article and Find Full Text PDFNeurosci Biobehav Rev
September 2025
Department of Psychology, Ludwig-Maximilians-University Munich. Munich, Germany.
The neuroscience of creativity has proposed that shared and domain-specific brain mechanisms underlie creative thinking. However, greater nuance is needed in characterizing these mechanisms, and limited neuroimaging analyses, especially regarding the relationship between the Alternative Uses Task (AUT) and other linguistic tasks, have so far prevented a comprehensive understanding of the neural basis of creativity. This paper offers to fill these gaps with a closer examination of the contributions of the specific domains and the deactivations associated with creativity.
View Article and Find Full Text PDFNanotechnology
September 2025
Beijing University of Technology, Key Laboratory of Optoelectronics Technology, School of Information Science and Technology., Beijing, 100124, CHINA.
The rapid advancements in the field of artificial intelligence have intensified the urgent need for low-power, high-speed artificial synaptic devices. Here, a near-infrared (NIR) artificial synaptic device is successfully realized based on pristine InGaAs nanowires (NWs), which achieves a paired-pulse facilitation (PPF) of up to 119%. Additionally, a postsynaptic current (PSC) in memory storage behavior has been implemented by applying different voltage pulses along with continuous illumination of 1064 nm NIR light due to the memristor characteristics of the device.
View Article and Find Full Text PDFComput Methods Programs Biomed
September 2025
eXiT Research Group, Universitat de Girona (UdG), EPS - Edifici P-IV, Carrer Universitat de Girona, 6, Girona, 17003, Catalunya, Spain.
Background And Objective: Hybrid forecasting methods aim to overcome the limitations of classical statistical approaches and deep learning models. While statistical methods provide interpretability, they often lack predictive power. Conversely, deep learning models achieve high accuracy but act as "black boxes.
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