Remarkably, artificial neural networks (ANNs) have shown astounding success in almost all
aspects of artificial intelligence. Meanwhile, large scale experiments have gathered an …

Recent advances in neural network modeling have enabled major strides in computer vision
and other artificial intelligence applications. Human-level visual recognition abilities are …

Partially inspired by features of computation in visual cortex, deep neural networks compute
hierarchical representations of their inputs. While these networks have been highly …

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 …

Highlights•Artificial and biological neural networks can be analyzed using similar
methods.•Neural analysis has revealed similarities between the representations in artificial …

Artificial neural networks (ANNs) are essential tools in machine learning that have drawn
increasing attention in neuroscience. Besides offering powerful techniques for data analysis …

Convolutional neural networks trained on object recognition derive some inspiration from
the neuroscience of the visual system in primates, and have been used as models of the …

Over the last decade, we have witnessed tremendous successes of Artificial Neural
Networks (ANNs) on solving a wide range of Al tasks. However, there is considerably less …

Humans and animals excel at generalizing from limited data, a capability yet to be fully
replicated in artificial intelligence. This perspective investigates generalization in biological …

Significant progress in visual neuroscience has often followed somewhat serendipitous
discoveries of specific stimulus preferences of individual neurons. For instance, the …