There are aspects of schizophrenia that pose challenges for Clark's model. These include: (1) evidence for excitatory activity underlying self-organizing neural ensembles that support coordinating functions, and their impairment in schizophrenia; (2) evidence regarding hallucinations that suggest they are not due to excessive prediction error; and (3) the critical role of emotional factors as setting conditions for delusion formation.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1017/S0140525X12002221 | DOI Listing |
Heliyon
January 2025
Information Technology Department, Technical College of Informatics-Akre, Akre University for Applied Sciences, Kurdistan Regain, Iraq.
Deep Learning (DL) has significantly contributed to the field of medical imaging in recent years, leading to advancements in disease diagnosis and treatment. In the case of Diabetic Retinopathy (DR), DL models have shown high efficacy in tasks such as classification, segmentation, detection, and prediction. However, DL model's opacity and complexity lead to errors in decision-making, particularly in complex cases, making it necessary to estimate the model's uncertainty in predictions.
View Article and Find Full Text PDFFront Nutr
January 2025
Process Design and Engineering Cell, CSIR-Central Salt and Marine Chemicals Research Institute, Bhavnagar, Gujarat, India.
Objective: The study aimed to analyze the safety and effectiveness of the ProBC Plus ( LMG S-31876) supplement across various health parameters, including stress levels, immunoglobulin levels, biochemical parameters, and vital signs.
Methods: A randomized, double-blind, placebo-controlled clinical trial study was conducted involving 50 subjects diagnosed with ailments related to immune system dysfunction and stress related disorders. Patients were treated with ProBC Plus (2 billion colony-forming units [CFU]) along with a placebo capsule administered once daily for a period of 8 weeks.
Front Bioeng Biotechnol
January 2025
Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
Introduction: Accurate prediction of knee biomechanics during total knee replacement (TKR) surgery is crucial for optimal outcomes. This study investigates the application of machine learning (ML) techniques for real-time prediction of knee joint mechanics.
Methods: A validated finite element (FE) model of the lower limb was used to generate a dataset of knee joint kinematics, kinetics, and contact mechanics.
Front Big Data
January 2025
Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland.
Atmospheric ozone chemistry involves various substances and reactions, which makes it a complex system. We analyzed data recorded by Switzerland's National Air Pollution Monitoring Network (NABEL) to showcase the capabilities of machine learning (ML) for the prediction of ozone concentrations (daily averages) and to document a general approach that can be followed by anyone facing similar problems. We evaluated various artificial neural networks and compared them to linear as well as non-linear models deduced with ML.
View Article and Find Full Text PDFJ Neural Eng
January 2025
Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Transcranial ultrasound stimulation (TUS) presents challenges in ultrasound wave transmission through the skull, affecting study outcomes due to aberration and attenuation. While planning strategies incorporating 3D computed tomography (CT) scans help mitigate these issues, they expose participants to radiation, which can raise ethical concerns. A solution involves generating skull masks from participants' anatomical magnetic resonance imaging (MRI).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!