Tononi . claim that their integrated information theory of consciousness makes testable predictions. This article discusses two of the more startling predictions, which follow from the theory's claim that conscious experiences are generated by inactive as well as active neurons. The first prediction is that a subject's conscious experience at a time can be affected by the disabling of neurons that were already inactive at that time. The second is that even if a subject's entire brain is "silent," meaning that all of its neurons are inactive (but not disabled), the subject can still have a conscious experience. A few authors have noted the implausibility of these predictions-which I call the disabling prediction and the silent brain prediction-but none have considered whether they are testable. In this article, I argue that they are not. In order to make this case, I first try to clarify the distinction between active, inactive (i.e. silent), and inactivated (i.e. disabled) neurons. With this clarification in place, I show that, even putting aside practical difficulties, it is impossible to set up a valid test of either the disabling prediction or the silent brain prediction. The conditions of the tests themselves are conditions under which a response from the subject could not reasonably be interpreted as evidence of consciousness or change in consciousness.
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http://dx.doi.org/10.1093/nc/niac015 | DOI Listing |
Am J Chin Med
January 2025
School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine (NJUCM), Nanjing, Jiangsu, P. R. China.
Colorectal cancer, characterized by its high incidence, concealed early symptoms, and poor prognosis at advanced stages, ranks as the third leading cause of cancer-related deaths worldwide. (AM) refers to the dried roots of (Fisch.) Bge.
View Article and Find Full Text PDFAnal Chim Acta
March 2025
Artificial Intelligence Research Center, Chang Gung University, Taoyuan, 333323, Taiwan; Department of Artificial Intelligence, College of Intelligent Computing, Chang Gung University, Taoyuan, 333323, Taiwan. Electronic address:
Background: In recent years, employing deep learning methods in the biosensing area has significantly reduced data analysis time and enhanced data interpretation and prediction accuracy. In some SPR fields, research teams have further enhanced detection capabilities using deep learning techniques. However, the application of deep learning to spectroscopic surface plasmon resonance (SPR) biosensors has not been reported.
View Article and Find Full Text PDFBMJ Open
January 2025
Southern Medical University Institute for Global Health, Dermatology Hospital of Southern Medical University, Guangzhou, Guangdong, China
Introduction: Traditional Chinese medicine (TCM) is commonly used alongside Western medicine for stroke management in China. However, there is significant variation in TCM practice, and the utilisation of evidence-based clinical practice guidelines is inadequate. This study aims to evaluate the effectiveness of three popular frameworks-Consolidated Framework for Implementation Research (CFIR), Theoretical Domains Framework (TDF) and Normalization Process Theory (NPT)-in improving implementation outcomes for the integrated TCM and Western medicine clinical practice guideline for stroke management.
View Article and Find Full Text PDFJ Colloid Interface Sci
January 2025
National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics, Research Institute of Aero-Engine, Beihang University, Beijing 100191, China. Electronic address:
Hypothesis: Complex emulsions usually consist of aqueous phases, like oil-in-water-in-oil (o/w/o) and water-in-oil-in-water (w/o/w), serving foundational roles in colloid science. Oil-in-oil-oil (o/o/o) emulsions offer new avenues for non-aqueous reagents but face challenges in balancing the forces between multiple organic phases.
Experiments: In this work, we generate o/o/o emulsions by integrating an AC electric field with a double cross-junction microchannel.
J Acoust Soc Am
January 2025
Key Laboratory of Modern Acoustics (MOE), School of Physics, Collaborative Innovation Centre of Advanced Microstructures, Nanjing University, Nanjing 210093, China.
In thermal therapies, accurate estimation of in-tissue power deposition density (PDD) is essential for predicting temperature distributions over time or regularizing temperature imaging. Based on our previous work on ultrasound thermometry, namely, multi-thread thermal strain imaging (MT-TSI), this work develops an in vivo PDD estimation method. Specifically, by combining the TSI model infinitesimal echo strain filter with the bio-heat transfer theory (the Pennes equation), a finite-difference time-domain model is established to allow online extraction of the PDD.
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