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Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm.
Neural Comput
January 2025
Intelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, BT48 7JL Derry-Londonderry, Northern Ireland, U.K.
Decision formation in perceptual decision making involves sensory evidence accumulation instantiated by the temporal integration of an internal decision variable toward some decision criterion or threshold, as described by sequential sampling theoretical models. The decision variable can be represented in the form of experimentally observable neural activities. Hence, elucidating the appropriate theoretical model becomes crucial to understanding the mechanisms underlying perceptual decision formation.
View Article and Find Full Text PDFDesign and evaluation of a problem-based learning VR module for apparel fit correction training.
PLoS One
January 2025
Department of Human Centered Design, Cornell University, Ithaca, New York, United States of America.
The increased adoption of three-dimensional (3D) digital prototyping software programs makes it necessary to train novice designers to use these programs efficiently. However, existing studies spanning from engineering to design education indicate that students feel incompetent in understanding 3D digital prototypes and navigating the software, so there is a need to find effective training methods. In the current study, training modules were developed to teach participants fit correction skills through an iterative problem-based learning (PBL) approach.
View Article and Find Full Text PDFMultifaceted confidence in exploratory choice.
PLoS One
January 2025
Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
Our choices are typically accompanied by a feeling of confidence-an internal estimate that they are correct. Correctness, however, depends on our goals. For example, exploration-exploitation problems entail a tension between short- and long-term goals: finding out about the value of one option could mean foregoing another option that is apparently more rewarding.
View Article and Find Full Text PDFSeries expansion of a scalable Hermitian excitonic renormalization method.
J Chem Phys
December 2024
Department of Chemistry, University of the Pacific, Stockton, California 95204, USA.
Utilizing the sparsity of the electronic structure problem, fragmentation methods have been researched for decades with great success, pushing the limits of ab initio quantum chemistry ever further. Recently, this set of methods has been expanded to include a fundamentally different approach called excitonic renormalization, providing promising initial results. It builds a supersystem Hamiltonian in a second-quantized-like representation from transition-density tensors of isolated fragments, contracted with biorthogonalized molecular integrals.
View Article and Find Full Text PDFBackground: Dementia is a major public health problem affecting millions of people worldwide. Early diagnosis and intervention are essential to improve quality of life and reduce the burden of dementia. Recently, voice digital biomarkers have emerged as a promising approach for the early detection of dementia owing to its clinical utility and accessibility.
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