AIMC Topic: Visual Cortex

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Early Emergence of Solid Shape Coding in Natural and Deep Network Vision.

Current biology : CB Oct 22, 2020
Area V4 is the first object-specific processing stage in the ventral visual pathway, just as area MT is the first motion-specific processing stage in the dorsal pathway. For almost 50 years, coding of object shape in V4 has been studied and conceived...
Neurons Photic Stimulation Macaca mulatta Deep Learning Models, Neurological Electroencephalography Visual Pathways Intravital Microscopy Microscopy, Fluorescence, Multiphoton Visual Cortex Electrodes, Implanted Form Perception Animals Male
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Comparing biological and artificial vision systems: Network measures of functional connectivity.

Neuroscience letters Sep 24, 2020
Advances in Deep Convolutional Neural Networks (DCNN) provide new opportunities for computational neuroscience to pose novel questions regarding the function of biological visual systems. Some attempts have been made to utilize advances in machine le...
Models, Neurological Data Interpretation, Statistical Neurons Neural Networks, Computer Animals Mice Visual Cortex Recognition, Psychology
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Infrared and visible image fusion method of dual NSCT and PCNN.

PloS one Sep 18, 2020
To solve the problem that the details of fusion images are not retained well and the information of feature targets is incomplete, we proposed a new fusion method of infrared (IR) and visible (VI) image-IR and VI image fusion method of dual non-subsa...
Image Processing, Computer-Assisted Artificial Intelligence Humans Nerve Net Cats Neural Networks, Computer Algorithms Visual Cortex Infrared Rays Animals
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Motion opponency examined throughout visual cortex with multivariate pattern analysis of fMRI data.

Human brain mapping Sep 2, 2020
This study explores how the human brain solves the challenge of flicker noise in motion processing. Despite providing no useful directional motion information, flicker is common in the visual environment and exhibits omnidirectional motion energy whi...
Adult Brain Mapping Support Vector Machine Magnetic Resonance Imaging Motion Perception Humans Multivariate Analysis Visual Cortex
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A recurrent circuit implements normalization, simulating the dynamics of V1 activity.

Proceedings of the National Academy of Sciences of the United States of America Aug 25, 2020
The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model's defining characteristic is that the response of each neuron is divided by a factor that includes a weighte...
Animals Computational Biology Models, Neurological Neurons Visual Cortex Neural Networks, Computer
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Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference.

Nature neuroscience Aug 10, 2020
Sensory cortices display a suite of ubiquitous dynamical features, such as ongoing noise variability, transient overshoots and oscillations, that have so far escaped a common, principled theoretical account. We developed a unifying model for these ph...
Haplorhini Visual Cortex Visual Pathways Neural Networks, Computer Animals Models, Neurological Humans
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A Comparative Analysis of Visual Encoding Models Based on Classification and Segmentation Task-Driven CNNs.

Computational and mathematical methods in medicine Aug 1, 2020
Nowadays, visual encoding models use convolution neural networks (CNNs) with outstanding performance in computer vision to simulate the process of human information processing. However, the prediction performances of encoding models will have differe...
Databases, Factual Visual Perception Functional Neuroimaging Humans Neural Networks, Computer Visual Cortex Magnetic Resonance Imaging Image Processing, Computer-Assisted Artificial Intelligence Models, Neurological Algorithms Photic Stimulation
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Improved object recognition using neural networks trained to mimic the brain's statistical properties.

Neural networks : the official journal of the International Neural Network Society Jul 29, 2020
The current state-of-the-art object recognition algorithms, deep convolutional neural networks (DCNNs), are inspired by the architecture of the mammalian visual system, and are capable of human-level performance on many tasks. As they are trained for...
Neural Networks, Computer Animals Models, Neurological Pattern Recognition, Automated Haplorhini Pattern Recognition, Visual Visual Cortex
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Depth in convolutional neural networks solves scene segmentation.

PLoS computational biology Jul 24, 2020
Feed-forward deep convolutional neural networks (DCNNs) are, under specific conditions, matching and even surpassing human performance in object recognition in natural scenes. This performance suggests that the analysis of a loose collection of image...
Visual Cortex Recognition, Psychology Signal Processing, Computer-Assisted Visual Perception Pattern Recognition, Visual Female Reproducibility of Results Young Adult Adult Male Adolescent Humans Neural Networks, Computer Brain
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A Modeling Study of the Emergence of Eye Position Gain Fields Modulating the Responses of Visual Neurons in the Brain.

Frontiers in neural circuits May 26, 2020
The responses of many cortical neurons to visual stimuli are modulated by the position of the eye. This form of gain modulation by eye position does not change the retinotopic selectivity of the responses, but only changes the amplitude of the respon...
Visual Perception Visual Cortex Visual Fields Normal Distribution Photic Stimulation Neural Networks, Computer Eye Movements Neurons Humans
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