The influences of velocity on texture motion and bar motion were compared in complex cells from cat's striate cortex. Velocity preference and bandwidth were invariably higher for texture motion than for bar motion. Bar tuning profiles were essentially velocity-invariant; texture tuning profiles were unimodal at low velocity, increasingly bimodal at higher velocities, with depressed sensitivity in directions optimal for bar stimuli. Velocity tuning was generally similar for each monocular input, except for one instance of opposite preferred directions through each eye for rapid texture motion. Implications for cortical wiring are discussed.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/0304-3940(80)90279-7 | DOI Listing |
J Oral Facial Pain Headache
March 2024
Department of Oral and Maxillofacial Surgery, Peking University School of Stomatology, 100081 Beijing, China.
Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysiology and developing effective analgesics. However, pain assessment methods for TN mouse models have not been widely studied, resulting in a critical gap in our understanding of TN. With the rapid advancement of deep learning, numerous pain assessment methods based on deep learning have emerged.
View Article and Find Full Text PDFMed Phys
December 2024
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, China.
Background: Due to the low signal-to-noise ratio (SNR) and the limited number of b-values, precise parameter estimation of intravoxel incoherent motion (IVIM) imaging remains an open issue to date, especially for brain imaging where the relatively small difference between D and D easily leads to outliers and obvious graininess in estimated results.
Purpose: To propose a synthetic data driven supervised learning method (SDD-IVIM) for improving precision and noise robustness in IVIM parameter estimation without relying on real-world data for neural network training.
Methods: On account of the absence of standard IVIM parametric maps from real-world data, a novel model-based method for generating synthetic human brain IVIM data was introduced.
PNAS Nexus
December 2024
Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Ferroelectric nematic (N) liquid crystals present a compelling platform for exploring topological defects in polar fields, while their structural properties can be significantly altered by ionic doping. In this study, we demonstrate that doping the ferroelectric nematic material RM734 with cationic polymers enables the formation of polymeric micelles that connect pairs of half-integer topological defects. Polarizing optical microscopy reveals that these string defects exhibit butterfly textures, featured with a 2D polarization field divided by Néel-type kink walls into domains exhibiting either uniform polarization or negative splay and bend deformations.
View Article and Find Full Text PDFSensors (Basel)
November 2024
School of Comuputer Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Focusing on the issue of the low recognition rates achieved by traditional deep-information-based action recognition algorithms, an action recognition approach was developed based on skeleton spatial-temporal and dynamic features combined with a two-stream convolutional neural network (TS-CNN). Firstly, the skeleton's three-dimensional coordinate system was transformed to obtain coordinate information related to relative joint positions. Subsequently, this relevant joint information was encoded as a color texture map to construct the spatial-temporal feature descriptor of the skeleton.
View Article and Find Full Text PDFSensors (Basel)
November 2024
School of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China.
Magnetic Barkhausen noise (MBN) is one of the most effective methods for determining the easy axis of ferromagnetic materials and for evaluating texture and residual stress in a nondestructive manner. MBN signals from multiple angles and different magnetization sections can be used to characterize magnetic anisotropy caused by various magnetization mechanisms. This paper reviews the development and application of magnetic anisotropy detection technology, and the MBN anisotropy models that take into account domain wall motion and magnetic domain rotation are analyzed thoroughly.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!