Results 11 to 20 of about 379,465 (333)
Bayesian population receptive field modelling [PDF]
NeuroImage, 2016 We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated
Aponte +40 more
core +9 more sources
Shifting Receptive Fields [PDF]
Neuron, 2001 The very notion of a receptive field implies a defined, static region of sensitivity—for visual neurons, a region in retinotopic space. Other factors besides retinal stimulation (such as attentional state) may modulate neural responses, but the shape and position of the receptive field should remain fixed, permanently constrained by anatomical ...
Charles E. Connor
openalex +3 more sources
DFMA: an improved DeepLabv3+ based on FasterNet, multi-receptive field, and attention mechanism for high-throughput phenotyping of seedlings. [PDF]
Front Plant SciJia L +6 more
europepmc +3 more sources
The Role of Population Receptive Field Sizes in Higher-Order Visual Dysfunction. [PDF]
Curr Neurol Neurosci RepElul D, Levin N.
europepmc +3 more sources
Multi-Scale Receptive Field Detection Network
IEEE Access, 2019 Deep convolutional neural networks have contributed much to various computer vision problems including object detection. However, there are still many problems to be solved.
Haoren Cui, Zhihua Wei
doaj +1 more source
Perisaccadic remapping and rescaling of visual responses in macaque superior colliculus. [PDF]
PLoS ONE, 2012 Visual neurons have spatial receptive fields that encode the positions of objects relative to the fovea. Because foveate animals execute frequent saccadic eye movements, this position information is constantly changing, even though the visual world is ...
Jan Churan +2 more
doaj +1 more source
Auto-Selecting Receptive Field Network for Visual Tracking
IEEE Access, 2019 Recently, Convolutional Neural Networks (CNNs) have shown tremendous potential in the visual tracking community. It is well-known that the receptive field is a critical factor for CNN affecting performance.
Junfei Zhuang +4 more
doaj +1 more source
Dilated Deep Residual Network for Image Denoising [PDF]
, 2017 Variations of deep neural networks such as convolutional neural network (CNN) have been successfully applied to image denoising. The goal is to automatically learn a mapping from a noisy image to a clean image given training data consisting of pairs of ...
Hu, Kaoning +2 more
core +3 more sources
Information Optimization in Coupled Audio-Visual Cortical Maps [PDF]
, 2002 Barn owls hunt in the dark by using cues from both sight and sound to locate their prey. This task is facilitated by topographic maps of the external space formed by neurons (e.g., in the optic tectum) that respond to visual or aural signals from a ...
A. Zee +10 more
core +3 more sources
Developmental sensory experience balances cortical excitation and inhibition. [PDF]
, 2010 Early in life, neural circuits are highly susceptible to outside influences. The organization of the primary auditory cortex (A1) in particular is governed by acoustic experience during the critical period, an epoch near the beginning of postnatal ...
Barker, Alison J +4 more
core +3 more sources