Humans persist in their attempts to predict the future in spite of the fact that natural events often involve a fundamental element of uncertainty. The present study explored computational mechanisms underlying biases in prospective decision making by using a simple psychophysical task. Observers viewed a randomly moving Gabor target for T sec and anticipated its future position ΔT sec following stimulus offset. Applying reverse correlation analysis, we found that observer decisions focused heavily on the last part of target velocity and especially on velocity information following the last several direction reversals. If target random motion explicitly contained an additional linear trend, observers tended to utilize information of the linear trend as well. These behavioral data are well explained by a leaky-integrator model of perceptual decision making based on evidence accumulation with adaptive gain control. The results raise the possibility that prospective decision making toward future events follows principles similar to those involved in retrospective decision making toward past events.
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http://dx.doi.org/10.1038/s41598-019-40687-3 | DOI Listing |
JMIR Res Protoc
January 2025
Clinical Informatics and Health Outcomes Research Group, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
Background: There are gaps in our understanding of the clinical characteristics and disease burden of the respiratory syncytial virus (RSV) among community-dwelling adults. This is in part due to a lack of routine testing at the point of care. More data would enhance our assessment of the need for an RSV vaccination program for adults in the United Kingdom.
View Article and Find Full Text PDFCurr Treat Options Oncol
January 2025
Department of Respiratory Medicine, Huzhou Central Hospital, Affiliated Central Hospital, Huzhou University, Huzhou, Zhejiang, China.
Small-cell lung cancer accounts for about 15% of lung cancers with an extremely poor prognosis. The incorporation of immunotherapy to platinum-based chemotherapy offers sustained overall survival benefits and become the standard for the first-line setting of extensive-stage small-cell lung cancer. However, only a limited number of patients derive prolonged benefits.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Pharmaceutics, Datta Meghe College of Pharmacy, Datta Meghe Institute of Higher Education and Research (DU), Sawangi Meghe, Wardha, Maharashtra, 442001, India.
Liver cancer is one of the most challenging malignancies, often associated with poor prognosis and limited treatment options. Recent advancements in nanotechnology and artificial intelligence (AI) have opened new frontiers in the fight against this disease. Nanotechnology enables precise, targeted drug delivery, enhancing the efficacy of therapeutics while minimizing off-target effects.
View Article and Find Full Text PDFInterdiscip Sci
January 2025
Institute for Complexity Science, Henan University of Technology, Zhengzhou, 450001, China.
Artificial intelligence technology has demonstrated remarkable diagnostic efficacy in modern biomedical image analysis. However, the practical application of artificial intelligence is significantly limited by the presence of similar pathologies among different diseases and the diversity of pathologies within the same disease. To address this issue, this paper proposes a reinforced collaborative-competitive representation classification (RCCRC) method.
View Article and Find Full Text PDFLung
January 2025
Division of Pulmonary and Critical Care Medicine, Albany Medical College, 16 New Scotland Avenue, MC-91, Albany, NY, 12208, USA.
Purpose: The priorities and concerns of sarcoidosis patients in the United States (US) have not been well-described.
Methods: A survey constructed by sarcoidosis patients and doctors was administered to US sarcoidosis patients. The survey queried patients concerning their demographics, disease state, disease impact on health and well-being, health care priorities and impressions of sarcoidosis care.
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