Humans possess a numerical intuition that allows them to manipulate large non-symbolic quantities. This ability has been broadly assessed with the help of number comparison tasks involving simultaneously displayed arrays. Many authors pointed out that the manipulation (or the lack thereof) of non-numerical features deeply impacts performance in these tasks, but the specific nature of this influence is not clear. This study investigates the interaction between numerical and non-numerical quantity judgement tasks. Adult participants performed five distinct comparison tasks, each based on a target dimension: numerosity, total area, dot size, convex hull, and mean occupancy. We manipulated the relation between the target and the other dimensions to measure their respective influence on task performance. Results showed that total area and convex hull substantially affected numerosity comparisons. The number of dots conversely acted as an informative dimension when participants had to make a decision based on the total area or the convex hull. Our results illustrate that adults flexibly use non-target dimensions as visual cues to perform comparison judgements. Overall, this suggests that the influence found in numerical comparison tasks is explicit and deliberate rather than due to implicit visual integration processes.
Although individual differences in children's moral self-concept emerge during early childhood and predict future behavioral outcomes, the cognitive skills underlying the development of the moral self have received little attention. We addressed this gap with a longitudinal sample of 106 children (M = 52.78 months, SD = 6.
Omics techniques, such as proteomics, contain crucial data for understanding biological processes, but they remain underutilized due to their high dimensionality. Typically, proteomics research focuses narrowly on using a limited number of datasets, hindering cross-study comparisons, a problem that can potentially be addressed by machine learning. Despite this potential, machine learning has seen limited adoption in the field of proteomics.
Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researchers aimed to fuse these techniques in a novel rehabilitation system. Moreover, these models utilized the biomedical signals acquired from the human body's particular organ, cells, or tissues.
Background: Individuals with autism spectrum disorder (ASD) exhibit persistent deficits in social interaction and communication in adulthood. Pioneering studies have suggested that these difficulties arise from a lack of immediate, spontaneous mentalizing (i.e.
Department of General Psychology, University of Padova, via Venezia 8, 35131 Padova, Italy; Padova Neuroscience Center, University of Padova, via Orus 2/B, 35129 Padova, Italy. Electronic address:
The impacting research on emotions of the last decades was carried out with different methods. The most popular was based on the use of a validated sample of slides, the International Affective Pictures System (IAPS), divided mainly into pleasant, neutral and unpleasant categories, and on fMRI as a measure of brain activation induced by these stimuli. With the present coordinate-based meta-analysis (CBMA) based on ALE approach, we aimed to unmask the main brain networks involved in the contrast of pleasant vs.
