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Found 8 papers, 4 papers with code
How to optimize neuroscience data utilization and experiment design for advancing primate visual and linguistic brain models?
In recent years, neuroscience has made significant progress in building large-scale artificial neural network (ANN) models of brain activity and behavior.
Identifying Shared Decodable Concepts in the Human Brain Using Image-Language Foundation Models
In the final section of our analysis, we localize shared decodable concepts in the brain using a voxel-masking optimization method to produce a shared decodable concept (SDC) space.
Improving the Accuracy and Robustness of CNNs Using a Deep CCA Neural Data Regularizer
As convolutional neural networks (CNNs) become more accurate at object recognition, their representations become more similar to the primate visual system.
Different Spectral Representations in Optimized Artificial Neural Networks and Brains
For convolutional networks, the best $\alpha$ values depend on the task complexity and evaluation metric: lower $\alpha$ values optimized validation accuracy and robustness to adversarial attack for networks performing a simple object recognition task (categorizing MNIST images of handwritten digits); for a more complex task (categorizing CIFAR-10 natural images), we found that lower $\alpha$ values optimized validation accuracy whereas higher $\alpha$ values optimized adversarial robustness.
Improved object recognition using neural networks trained to mimic the brain's statistical properties
To test this, we trained DCNNs on a composite task, wherein networks were trained to: a) classify images of objects; while b) having intermediate representations that resemble those observed in neural recordings from monkey visual cortex.
A Self-Organizing Memory Network
Information in working memory, however, is retained for tens of seconds, suggesting the question of how time-varying neural activities maintain stable representations.
Using deep learning to reveal the neural code for images in primary visual cortex
Moreover, even for the simple and complex cells-- the best-understood V1 neurons-- it is challenging to predict how they will respond to natural image stimuli.
Searching for modified growth patterns with tomographic surveys
In alternative theories of gravity, designed to produce cosmic acceleration at the current epoch, the growth of large scale structure can be modified.
