Background: Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain.
Method: We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors.
Results: The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted.
Comparison With Existing Methods: Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales.
Conclusions: This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.
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http://dx.doi.org/10.1016/j.jneumeth.2018.10.002 | DOI Listing |
Front Neurorobot
January 2025
College of Engineering, Qufu Normal University, Rizhao, China.
Brain-computer interfaces (BCIs) have garnered significant research attention, yet their complexity has hindered widespread adoption in daily life. Most current electroencephalography (EEG) systems rely on wet electrodes and numerous electrodes to enhance signal quality, making them impractical for everyday use. Portable and wearable devices offer a promising solution, but the limited number of electrodes in specific regions can lead to missing channels and reduced BCI performance.
View Article and Find Full Text PDFFront Plant Sci
January 2025
School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou, China.
Tea is an important economic product in China, and tea picking is a key agricultural activity. As the practice of tea picking in China gradually shifts towards intelligent and mechanized methods, artificial intelligence recognition technology has become a crucial tool, showing great potential in recognizing large-scale tea picking operations and various picking behaviors. Constructing a comprehensive database is essential for these advancements.
View Article and Find Full Text PDFJ Cheminform
January 2025
School of Systems Biomedical Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, 06978, Seoul, Republic of Korea.
G protein-coupled receptors (GPCRs) play vital roles in various physiological processes, making them attractive drug discovery targets. Meanwhile, deep learning techniques have revolutionized drug discovery by facilitating efficient tools for expediting the identification and optimization of ligands. However, existing models for the GPCRs often focus on single-target or a small subset of GPCRs or employ binary classification, constraining their applicability for high throughput virtual screening.
View Article and Find Full Text PDFNature
January 2025
German Centre for Cardiovascular Research (DZHK), Partner Site Lower Saxony, Göttingen, Germany.
Cardiomyocytes can be implanted to remuscularize the failing heart. Challenges include sufficient cardiomyocyte retention for a sustainable therapeutic impact without intolerable side effects, such as arrhythmia and tumour growth. We investigated the hypothesis that epicardial engineered heart muscle (EHM) allografts from induced pluripotent stem cell-derived cardiomyocytes and stromal cells structurally and functionally remuscularize the chronically failing heart without limiting side effects in rhesus macaques.
View Article and Find Full Text PDFMed Image Anal
January 2025
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Recently, a multi-scale representation attention based deep multiple instance learning method has proposed to directly extract patch-level image features from gigapixel whole slide images (WSIs), and achieved promising performance on multiple popular WSI datasets. However, it still has two major limitations: (i) without considering the relations among patches, thereby possibly restricting the model performance; (ii) unable to handle retrieval tasks, which is very important in clinic diagnosis. To overcome these limitations, in this paper, we propose a novel end-to-end MIL-based deep hashing framework, which is composed of a multi-scale representation attention based deep network as the backbone, patch-based dynamic graphs and hashing encoding layers, to simultaneously handle classification and retrieval tasks.
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