In this study, we introduce the importance of elevated membrane potentials (MPs) in the prefrontal cortex (PFC) compared to that in the posterior parietal cortex (PPC), based on new observations of different MP levels in these areas. Through experimental data and spiking neural network modeling, we investigated a possible mechanism of the elevated membrane potential in the PFC and how these physiological differences affect neural network dynamics and cognitive functions in the PPC and PFC. Our findings indicate that NMDA receptors may be a main contributor to the elevated MP in the PFC region and highlight the potential of using a modeling toolkit to investigate the means by which changes in synaptic properties can affect neural dynamics and potentiate desirable cognitive functions through population activities in the corresponding brain regions.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10372347 | PMC |
http://dx.doi.org/10.3389/fncel.2023.1153970 | DOI Listing |
Elife
December 2024
Otto-Creutzfeldt-Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany.
Speech production and perception involve complex neural dynamics in the human brain. Using magnetoencephalography, our study explores the interaction between cortico-cortical and cortico-subcortical connectivities during these processes. Our connectivity findings during speaking revealed a significant connection from the right cerebellum to the left temporal areas in low frequencies, which displayed an opposite trend in high frequencies.
View Article and Find Full Text PDFEnviron Monit Assess
December 2024
Faculty of Information Technology, University of Engineering and Technology, Vietnam National University Hanoi, E3 Building, 144 Xuan Thuy Street, Dich Vong Hau Ward, Cau Giay District, Ha Noi, 100000, Vietnam.
PM pollution is a major global concern, especially in Vietnam, due to its harmful effects on health and the environment. Monitoring local PM levels is crucial for assessing air quality. However, Vietnam's state-of-the-art (SOTA) dataset with a 3 km resolution needs to be revised to depict spatial variation in smaller regions accurately.
View Article and Find Full Text PDFInterdiscip Sci
December 2024
School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, 213164, China.
Cell-Penetrating Peptides (CPPs) are a crucial carrier for drug delivery. Since the process of synthesizing new CPPs in the laboratory is both time- and resource-consuming, computational methods to predict potential CPPs can be used to find CPPs to enhance the development of CPPs in therapy. In this study, EnDM-CPP is proposed, which combines machine learning algorithms (SVM and CatBoost) with convolutional neural networks (CNN and TextCNN).
View Article and Find Full Text PDFMol Divers
December 2024
Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, 211198, China.
Protein-ligand interactions are the molecular basis of many important cellular activities, such as gene regulation, cell metabolism, and signal transduction. Protein-ligand binding affinity is a crucial metric of the strength of the interaction between the two, and accurate prediction of its binding affinity is essential for discovering drugs' new uses. So far, although many predictive models based on machine learning and deep learning have been reported, most of the models mainly focus on one-dimensional sequence and two-dimensional structural characteristics of proteins and ligands, but fail to deeply explore the detailed interaction information between proteins and ligand atoms in the binding pocket region of three-dimensional space.
View Article and Find Full Text PDFACS Sens
December 2024
Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of Korea.
The increasing prevalence of obesity and metabolic disorders has created a significant demand for personalized devices that can effectively monitor fat metabolism. In this study, we developed an advanced breath analyzer system designed to provide real-time monitoring of exercise-induced fat burning by analyzing volatile organic compounds (VOCs) present in both oral and alveolar breath. Acetone in exhaled breath and β-hydroxybutyric acid (BOHB) in the blood are both biomarkers closely linked to the metabolic fat burning process occurring in the liver, particularly after exercise.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!