Although previous studies have explored the brain mechanism by which an individual independently accomplishes task switching or rule shifting with different hierarchical structures, electrophysiological evidence indicating that two actors cooperate to complete the hierarchical rule shift remains unclear. This study adopts a modified joint hierarchical rule shifting paradigm in which one actor judged the parity task and the other decided the magnitude task. Results demonstrated that cues in high- and low-shift conditions elicited larger P2 amplitudes and that low-shift had a larger P3 amplitude than high-shift. Results further indicated that participants required more attention resources to ascertain who would make a judgment for the current trial and that low hierarchical features were superior in reconfiguring changed rules. Regarding the target, the high-shift condition evoked smaller P2 and larger N2 amplitudes when compared to low-shift and repeat conditions, whereas when compared to high- and low-shifts, the repeat condition elicited a larger P3 amplitude. The findings revealed that participants required more control resources to process the varied features and that repeat condition required the least cognitive resources to update rules. Thus, participants had different process patterns between cues and targets when cooperating with their co-actors.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/WNR.0000000000001600 | DOI Listing |
Brief Bioinform
November 2024
Department of Translational Research, Dasman Diabetes Institute, Dasman 15462, Kuwait City, Kuwait.
In response to distinct cellular stresses, the p53 exhibits distinct dynamics. These p53 dynamics subsequently control cell fate. However, different stresses can generate the same p53 dynamics with different cell fate outcomes, suggesting that the integration of dynamic information from other pathways is important for cell fate regulation.
View Article and Find Full Text PDFJ Educ Eval Health Prof
January 2025
Department of the History of Medicine and Medical Humanities, Seoul National University College of Medicine, Seoul, Korea.
The introduction of modern Western medicine in the late 19th century, notably through vaccination initiatives, marked the beginning of governmental involvement in medical licensure, with the licensing of doctors who performed vaccinations. The establishment of the national medical school "Euihakkyo" in 1899 further formalized medical education and licensure, granting graduates the privilege to practice medicine without additional examinations. The enactment of the Regulations on Doctors in 1900 by the Joseon government aimed to define doctor qualifications, including modern and traditional practitioners, comprehensively.
View Article and Find Full Text PDFEntropy (Basel)
December 2024
Institute of Mathematics, University of Mannheim, 68131 Mannheim, Germany.
All characterizations of the Shannon entropy include the so-called chain rule, a formula on a hierarchically structured probability distribution, which is based on at least two elementary distributions. We show that the chain rule can be split into two natural components, the well-known additivity of the entropy in case of cross-products and a variant of the chain rule that involves only a single elementary distribution. The latter is given as a proportionality relation and, hence, allows a vague interpretation as self-similarity, hence intrinsic property of the Shannon entropy.
View Article and Find Full Text PDFCogn Neurodyn
December 2024
School of Systems Science, Beijing Normal University, Beijing, 100875 China.
Adaptive mechanisms of learning models play critical roles in interpreting adaptive behavior of humans and animals. Different learning models, varying from Bayesian models, deep learning or regression models to reward-based reinforcement learning models, adopt similar update rules. These update rules can be reduced to the same generalized mathematical form: the Rescorla-Wagner equation.
View Article and Find Full Text PDFJ Comput Neurosci
December 2024
Computational Neuroscience Group, Centre de Recerca Matemàtica, Campus de Bellaterra, Edifici C, 08193, Bellterra, Spain.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!