AIMC Topic: Visual Cortex
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Predicting Single Neuron Responses of the Primary Visual Cortex with Deep Learning Model.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 13, 2024
Modeling neuron responses to stimuli can shed light on next-generation technologies such as brain-chip interfaces. Furthermore, high-performing models can serve to help formulate hypotheses and reveal the mechanisms underlying neural responses. Here ...
There is a fundamental, unbridgeable gap between DNNs and the visual cortex.
The Behavioral and brain sciences
Dec 6, 2023
Deep neural networks (DNNs) are not just inadequate models of the visual system but are so different in their structure and functionality that they are not even on the same playing field. DNN units have almost nothing in common with neurons, and, unl...
Robot-assisted implantation of a microelectrode array in the occipital lobe as a visual prosthesis: technical note.
Journal of neurosurgery
Oct 27, 2023
The prospect of direct interaction between the brain and computers has been investigated in recent decades, revealing several potential applications. One of these is sight restoration in profoundly blind people, which is based on the ability to elici...
Learnable latent embeddings for joint behavioural and neural analysis.
Nature
May 3, 2023
Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neu...
MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex.
PLoS computational biology
Sep 6, 2022
Convolutional neural networks trained on object recognition derive inspiration from the neural architecture of the visual system in mammals, and have been used as models of the feedforward computation performed in the primate ventral stream. In contr...
A self-supervised domain-general learning framework for human ventral stream representation.
Nature communications
Jan 25, 2022
Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general ...
Attention modulates neural representation to render reconstructions according to subjective appearance.
Communications biology
Jan 11, 2022
Stimulus images can be reconstructed from visual cortical activity. However, our perception of stimuli is shaped by both stimulus-induced and top-down processes, and it is unclear whether and how reconstructions reflect top-down aspects of perception...
NeuroGen: Activation optimized image synthesis for discovery neuroscience.
NeuroImage
Dec 20, 2021
Functional MRI (fMRI) is a powerful technique that has allowed us to characterize visual cortex responses to stimuli, yet such experiments are by nature constructed based on a priori hypotheses, limited to the set of images presented to the individua...
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 ...
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