This study aimed to identify the neural basis of probabilistic reasoning, a type of inductive inference that aids decision making under conditions of uncertainty. Eight normal subjects performed two separate two-alternative-choice tasks (the balls in a bottle and personality survey tasks) while undergoing functional magnetic resonance imaging (fMRI). The experimental conditions within each task were chosen so that they differed only in their requirement to make a decision under conditions of uncertainty (probabilistic reasoning and frequency determination required) or under conditions of certainty (frequency determination required). The same visual stimuli and motor responses were used in the experimental conditions. We provide evidence that the neo-cerebellum, in conjunction with the premotor cortex, inferior parietal lobule and medial occipital cortex, mediates the probabilistic inferences that guide decision making under uncertainty. We hypothesise that the neo-cerebellum constructs internal working models of uncertain events in the external world, and that such probabilistic models subserve the predictive capacity central to induction.
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http://dx.doi.org/10.1016/j.cogbrainres.2003.12.009 | DOI Listing |
Otolaryngol Head Neck Surg
January 2025
Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, Michigan, USA.
Objective: Evaluate inpatient audiometry on clinical decision-making. Assess stakeholder perspectives on the practice of inpatient audiometry and financial impact.
Study Design: This is a mixed methods study utilizing retrospective chart review, a focus group, and financial analyses.
Genes Chromosomes Cancer
January 2025
Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Medical Research Center Oulu and Biocenter Oulu, University of Oulu, Oulu, Finland.
Myelodysplastic neoplasia with complex karyotype (CK-MDS) poses significant clinical challenges and is associated with poor survival. Detection of structural variants (SVs) is crucial for diagnosis, prognostication, and treatment decision-making in MDS. However, the current standard-of-care (SOC) cytogenetic testing, relying on karyotyping, often yields ambiguous results in cases with CK.
View Article and Find Full Text PDFBMC Anesthesiol
January 2025
Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA, 94612, USA.
Background: Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data.
Methods: Patients 65-years and older undergoing urgent or emergency non-cardiac surgery within 21 hospitals 2017-2021 were used to develop the model (randomly split: 80% training, 20% test).
BMC Health Serv Res
January 2025
Bihar Rural Livelihoods Promotion Society (BRLPS) "JEEVIKA", Patna Bihar, India.
Background: Rural populations in Bihar, India, face significant healthcare access challenges due to geographical, infrastructural, and financial barriers. The Swasthya Mitra program, initiated by the Bihar Rural Livelihood Promotion Society in collaboration with local and international partners, aims to mitigate these challenges by employing trained community members to navigate patients through the healthcare system.
Methods: This qualitative study employed in-depth interview and thematic analysis to evaluate the Swasthya Mitra program in the Bhagalpur and Jamui districts in Bihar, India.
Sci Rep
January 2025
Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, 95616, USA.
This study utilizes an integrated Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach to perform Solar Power Plant Site Selection (SPPSS) in Kermanshah Province, Iran. It introduces a novel group weighting method, the Dempster-based Best-Worst Method (DBWM), which combines weights vectors derived from experts' opinions. The study also conducts a comprehensive sensitivity analysis comparing four GIS-based models for SPPSS.
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