Bistability occurs when two alternative percepts can be derived from the same physical stimulus. To identify the neural correlates of specific subjective experiences we used a bistable auditory stimulus and determined whether the two perceptual states could be distinguished electrophysiologically. Fourteen participants underwent magnetoencephalography while reporting their perceptual experience while listening to a continuous bistable stream of auditory tones. Participants reported bistability with a similar overall proportion of the two alternative percepts (52% vs 48%). At the individual level, sensor space electrophysiological discrimination between the percepts was possible in 9/14 participants with canonical variate analysis (CVA) or linear support vector machine (SVM) analysis over space and time dimensions. Classification was possible in 14/14 subjects with non-linear SVM. Similar effects were noted in an unconstrained source space CVA analysis (classifying 10/14 participants), linear SVM (classifying 9/14 subjects) and non-linear SVM (classifiying 13/14 participants). Source space analysis restricted to a priori ROIs showed discrimination was possible in the right and left auditory cortex with each classification approach but in the right intraparietal sulcus this was only apparent with non-linear SVM and only in a minority of particpants. Magnetoencephalography can be used to objectively classify auditory experiences from individual subjects.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5772671 | PMC |
http://dx.doi.org/10.1038/s41598-018-19287-0 | DOI Listing |
Front Artif Intell
January 2025
CONAHCYT-Instituto Potosino de Investigación Científica y Tecnológica, A.C. División de Geociencias Aplicadas, San Luis Potosí, Mexico.
This systematic review provides a state-of-art of Artificial Intelligence (AI) models such as Machine Learning (ML) and Deep Learning (DL) development and its applications in Mexico in diverse fields. These models are recognized as powerful tools in many fields due to their capability to carry out several tasks such as forecasting, image classification, recognition, natural language processing, machine translation, etc. This review article aimed to provide comprehensive information on the Machine Learning and Deep Learning algorithms applied in Mexico.
View Article and Find Full Text PDFDrug Dev Ind Pharm
December 2024
Department of Pharmaceutical Technology, Ramanbhai Patel College of Pharmacy, Charotar University of Science and Technology (CHARUSAT), CHARUSAT Campus, Changa, Gujarat, India.
Objective: The objective of this study is to create predictive models utilizing machine learning algorithms, including Artificial Neural Networks (ANN), k-nearest neighbor (kNN), support vector machines (SVM), and linear regression, to predict critical quality attributes (CQAs) such as hardness, friability, and disintegration time of fast disintegrating tablets (FDTs).
Methods: A dataset of 864 batches of FDTs was generated by varying binder types and amounts, disintegrants, diluents, punch sizes, and compression forces. Preprocessing steps included normalizing numerical features based on industry standards, one-hot encoding for categorical variables, and addressing outliers to ensure data consistency.
Front Comput Neurosci
November 2024
School of Information Science and Engineering, Linyi University, Linyi, China.
Background: The methods used to detect epileptic seizures using electroencephalogram (EEG) signals suffer from poor accuracy in feature selection and high redundancy. This problem is addressed through the use of a novel multi-domain feature fusion and selection method (PMPSO).
Method: Discrete Wavelet Transforms (DWT) and Welch are used initially to extract features from different domains, including frequency domain, time-frequency domain, and non-linear domain.
J Environ Manage
December 2024
School of Resources and Safety Engineering, Central South University, Changsha, Hunan, 410083, PR China.
Peak particle velocity (PPV) serves as a critical metric in assessing the appropriateness of blasting design parameters. However, existing methods for accurately measuring PPV remain insufficient. To develop a robust PPV prediction model, this study integrates the Extreme Gradient Boosting (XGBoost) algorithm with four distinct optimization techniques: Runge Kutta Optimizer (RUN), Equilibrium Optimizer (EO), Gradient-Based Optimizer (GBO), and Reptile Search Algorithm (RSA).
View Article and Find Full Text PDFBiosens Bioelectron
January 2025
Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture and Rural Affairs, Beijing, 100093, PR China. Electronic address:
The contamination of mycotoxins is a serious problem around the world. It has detrimental effects on human beings and leads to tremendous economic loss. It is essential to develop a rapid and non-destructive method for contamination recognition particularly for early alarm.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!