. The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer's decision-making is a crucial issue. Yet the neural substrate of the proposer's decision behavior, especially from the resting-state network perspective, remains unclear.. In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers' unfair offer rates in the ultimatum game.The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors.. Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.
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http://dx.doi.org/10.1088/1741-2552/acf61e | DOI Listing |
Clin Neuropsychol
December 2024
Northwell Health, New Hyde Park, NY, USA.
As the field of neuropsychology continues expanding efforts to better recruit providers and serve individuals from diverse populations, understanding the training and practice experiences of neuropsychologists from diverse backgrounds is crucial. Given the diversity of Asian populations, the experiences of Asian neuropsychologists offer a unique opportunity to reflect on the progress made in addressing issues related to diversity, equity, and inclusion (DEI). This information will help address challenges related to education, training, and clinical practice, particularly in meeting growing demands for neuropsychological evaluations among Asian populations and addressing unique challenges.
View Article and Find Full Text PDFJ Sleep Res
December 2024
Institute of Child and Adolescent Psychiatry and Psychotherapy, Centre for Integrative Psychiatry, School of Medicine, University Medical Centre Schleswig-Holstein- Campus Kiel, Kiel, Germany.
Children and adults have been shown to benefit from sleep with regard to the consolidation of declarative memories. Especially during childhood, the generalisation of information from social and non-social contexts is important for adaptable behaviour in new situations and might show specific features in children. Here, we investigated whether adults (n = 18) and children (n = 19) differ in their generalisation of features assessed in wake and sleep conditions.
View Article and Find Full Text PDFPLoS One
December 2024
Padova Neuroscience Center, University of Padova, Padova, Italy.
An affective variant of the Stop-Signal task was used to study the interaction between emotion and response inhibition (RI) in healthy young participants. The task involved the covert presentation of emotional faces as go stimuli, as well as a manipulation of motivation and affect by inducing a negative mood through the assignment of unfair punishment. In the literature on emotion and RI, there are contrasting findings reflecting the variability in the method used to calculate the RI latency, namely the Stop-Signal Reaction Time (SSRT).
View Article and Find Full Text PDFJMIR Form Res
December 2024
Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada.
Background: While deep learning classifiers have shown remarkable results in detecting chest X-ray (CXR) pathologies, their adoption in clinical settings is often hampered by the lack of transparency. To bridge this gap, this study introduces the neural prototype tree (NPT), an interpretable image classifier that combines the diagnostic capability of deep learning models and the interpretability of the decision tree for CXR pathology detection.
Objective: This study aimed to investigate the utility of the NPT classifier in 3 dimensions, including performance, interpretability, and fairness, and subsequently examined the complex interaction between these dimensions.
Psychoneuroendocrinology
January 2025
Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin, Humboldt, Universitaet zu Berlin, and Berlin Institute of Health, Hindenburgdamm 30, Berlin 12203, Germany; DZPG (German Center for Mental Health), Berlin, Germany. Electronic address:
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