AIMC Topic: Visual Cortex
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Noise-trained deep neural networks effectively predict human vision and its neural responses to challenging images.
PLoS biology
Dec 9, 2021
Deep neural networks (DNNs) for object classification have been argued to provide the most promising model of the visual system, accompanied by claims that they have attained or even surpassed human-level performance. Here, we evaluated whether DNNs ...
Visual prototypes in the ventral stream are attuned to complexity and gaze behavior.
Nature communications
Nov 18, 2021
Early theories of efficient coding suggested the visual system could compress the world by learning to represent features where information was concentrated, such as contours. This view was validated by the discovery that neurons in posterior visual ...
Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning.
NeuroImage
Oct 1, 2021
Whether it be in a single neuron or a more complex biological system like the human brain, form and function are often directly related. The functional organization of human visual cortex, for instance, is tightly coupled with the underlying anatomy ...
A strategy for mapping biophysical to abstract neuronal network models applied to primary visual cortex.
PLoS computational biology
Aug 16, 2021
A fundamental challenge for the theoretical study of neuronal networks is to make the link between complex biophysical models based directly on experimental data, to progressively simpler mathematical models that allow the derivation of general opera...
Unveiling functions of the visual cortex using task-specific deep neural networks.
PLoS computational biology
Aug 13, 2021
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We r...
Uncovering structured responses of neural populations recorded from macaque monkeys with linear support vector machines.
STAR protocols
Aug 12, 2021
When a mammal, such as a macaque monkey, sees a complex natural image, many neurons in its visual cortex respond simultaneously. Here, we provide a protocol for studying the structure of population responses in laminar recordings with a machine learn...
Face Recognition by Humans and Machines: Three Fundamental Advances from Deep Learning.
Annual review of vision science
Aug 4, 2021
Deep learning models currently achieve human levels of performance on real-world face recognition tasks. We review scientific progress in understanding human face processing using computational approaches based on deep learning. This review is organi...
Interrogating theoretical models of neural computation with emergent property inference.
eLife
Jul 29, 2021
A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or a patt...
A dual-channel language decoding from brain activity with progressive transfer training.
Human brain mapping
Jul 27, 2021
When we view a scene, the visual cortex extracts and processes visual information in the scene through various kinds of neural activities. Previous studies have decoded the neural activity into single/multiple semantic category tags which can caption...
Coordination of top-down influence on V1 responses by interneurons and brain rhythms.
Bio Systems
Jun 15, 2021
Top-down processing in neocortex underlies functions such as prediction, expectation, and attention. Visual systems have much feedback connection that carries information of behavioral context. Top-down signals along feedback pathways modulate the re...
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