The ability to silently hear music in the mind has been argued to be fundamental to musicality. Objective measurements of this subjective imagery experience are needed if this link between imagery ability and musicality is to be investigated. However, previous tests of musical imagery either rely on self-report, rely on melodic memory, or do not cater in range of abilities. The Pitch Imagery Arrow Task (PIAT) was designed to address these shortcomings; however, it is impractically long. In this paper, we shorten the PIAT using adaptive testing and automatic item generation. We interrogate the cognitive processes underlying the PIAT through item response modelling. The result is an efficient online test of auditory mental imagery ability (adaptive Pitch Imagery Arrow Task: aPIAT) that takes 8 min to complete, is adaptive to participant's individual ability, and so can be used to test participants with a range of musical backgrounds. Performance on the aPIAT showed positive moderate-to-strong correlations with measures of non-musical and musical working memory, self-reported musical training, and general musical sophistication. Ability on the task was best predicted by the ability to maintain and manipulate tones in mental imagery, as well as to resist perceptual biases that can lead to incorrect responses. As such, the aPIAT is the ideal tool in which to investigate the relationship between pitch imagery ability and musicality.
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http://dx.doi.org/10.1007/s00426-020-01322-3 | DOI Listing |
Int Health
January 2025
Max Nader Center for Rehabilitation Technologies and Outcome Research, Shirley Ryan Ability Lab, 355 East Erie Street, Chicago, IL 60611, USA.
Low-and middle-income countries experience 77% of the world's premature deaths caused by non-communicable diseases, and their underlying health determinant data are often scarce and inaccurate. Improving satellite imagery data literacy worldwide is an integral step toward using the vast amount of publicly available data collected via satellites, such as air pollution, green space and light at night-all determinants of non-communicable diseases. Existing machine learning-based algorithms enable automated analysis of satellite imagery data, but health officials and scientists must know where to find and how to apply these algorithms to measure risk and target interventions.
View Article and Find Full Text PDFSci Rep
January 2025
School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK.
As marine heatwaves and mass coral bleaching events rise in frequency and severity, there is an increasing need for high-resolution satellite products that accurately predict reef thermal environments over large spatio-temporal scales. Deciding which global sea surface temperature (SST) dataset to use for research or management depends in part on the desired spatial resolution. Here, we evaluate two SST datasets - the lower-resolution CoralTemp v3.
View Article and Find Full Text PDFSci Rep
January 2025
Computer Vision Center, Universitat Autònoma de Barcelona, Barcelona, 08193, Spain.
In this study, we explore an enhancement to the U-Net architecture by integrating SK-ResNeXt as the encoder for Land Cover Classification (LCC) tasks using Multispectral Imaging (MSI). SK-ResNeXt introduces cardinality and adaptive kernel sizes, allowing U-Net to better capture multi-scale features and adjust more effectively to variations in spatial resolution, thereby enhancing the model's ability to segment complex land cover types. We evaluate this approach using the Five-Billion-Pixels dataset, composed of 150 large-scale RGB-NIR images and over 5 billion labeled pixels across 24 categories.
View Article and Find Full Text PDFBackground: Pain-related symptoms are thought to affect motor imagery abilities adversely.
Primer Study Objective: The study aimed to examine motor imagery ability and its association with pain, functional status, neck awareness, and depression in individuals with chronic neck pain.
Design And Setting: A cross-sectional study, single-center.
Acta Psychol (Amst)
December 2024
School of Psychology, University College Dublin, Ireland. Electronic address:
Background: Motor imagery (MI) can be an effective strategy for learning and enhancing movement or as an alternative training modality when physical practice is compromised. Individual differences in MI ability are widely documented but the role of experience in different activities in influencing MI is not well understood. The present study examined how experience in activities associated with the use of MI influences implicit and explicit MI.
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