Grid and place cells typically fire at progressively earlier phases within each cycle of the theta rhythm as rodents run across their firing fields, a phenomenon known as theta phase precession. Here, we report theta phase precession relative to turning angle in theta-modulated head direction cells within the anteroventral thalamic nucleus (AVN). As rodents turn their heads, these cells fire at progressively earlier phases as head direction sweeps over their preferred tuning direction. The degree of phase precession increases with angular head velocity. Moreover, phase precession is more pronounced in those theta-modulated head direction cells that exhibit theta skipping, with a stronger theta-skipping effect correlating with a higher degree of phase precession. These findings are consistent with a ring attractor model that integrates external theta input with internal firing rate adaptation-a phenomenon we identified in head direction cells within AVN. Our results broaden the range of information known to be subject to neural phase coding and enrich our understanding of the neural dynamics supporting spatial orientation and navigation.
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Hippocampus
March 2025
UCL Institute of Cognitive Neuroscience, University College London, London, UK.
Grid and place cells typically fire at progressively earlier phases within each cycle of the theta rhythm as rodents run across their firing fields, a phenomenon known as theta phase precession. Here, we report theta phase precession relative to turning angle in theta-modulated head direction cells within the anteroventral thalamic nucleus (AVN). As rodents turn their heads, these cells fire at progressively earlier phases as head direction sweeps over their preferred tuning direction.
View Article and Find Full Text PDFACS Omega
March 2025
Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, U.K.
Traditional poly(ether sulfone) (PES) filters, widely used for sterile, viral, and ultrafiltration, often exhibit restrictions in their selectivity-permeability profile due to their heterogeneous pore size distribution. This limitation has sparked interest in developing novel isoporous membrane materials and fabrication techniques. Among promising candidates, block copolymer (BCP) membranes produced via self-assembly and nonsolvent-induced phase separation (SNIPS) offer significant advantages, including tunable pore size, narrow pore size distribution, high porosity, and enhanced mechanical flexibility.
View Article and Find Full Text PDFPhys Rev Lett
February 2025
Xi'an Jiaotong University, Ministry of Education Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, Shaanxi Province Key Laboratory of Quantum Information and Quantum Optoelectronic Devices, School of Physics, Xi'an 710049, China.
Spin rotation is central for the spin manipulation of lepton beams which, in turn, plays an important role in investigation of the properties of spin-polarized lepton beams and the examination of spin-dependent interactions. However, realization of compact and ultrafast spin rotation of lepton beams, between longitudinal and transverse polarizations, still faces significant challenges. Here, we put forward a novel method for ultrafast (picosecond timescale) spin rotation of a relativistic lepton beam via employing a moderate-intensity terahertz (THz) wave in a dielectric-lined waveguide (DLW).
View Article and Find Full Text PDFCommun Chem
March 2025
Department of Materials, The University of Manchester, Oxford Road, M13 9PL, Manchester, UK.
High entropy metal chalcogenides are an emergent class of materials that have shown exceptional promise in applications such as energy storage, catalysis, and thermoelectric energy conversion. However, the stability of these materials to factors other than temperature are as yet unknown. Here we set out to assess the stability of the high entropy metal sulfide (MnFeCuAgZnCd)S with high pressure (up to 9 GPa), compared to an enthalpically stabilised AgCuS, and a quasi-stable (MnFeZnCd)S.
View Article and Find Full Text PDFComput Biol Med
March 2025
Shaanxi International Innovation Center for Transportation-Energy-Information Fusion and Sustainability, Chang'an University, Xi'an 710064, China; IVR Low-Carbon Research Institute, School of Energy and Electrical Engineering, Chang'an University, Xi'an 710064, China. Electronic address:
Recent advancements in cardiac imaging have been significantly enhanced by integrating deep learning models, offering transformative potential in early diagnosis and patient care. The research paper explores the application of hybrid deep learning methodologies, focusing on the roles of Autoencoders, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) in enhancing cardiac image analysis. The study implements a comprehensive approach, combining traditional algorithms such as Sobel, Watershed, and Otsu's Thresholding with advanced deep learning models to achieve precise and accurate imaging outcomes.
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