Neuronal connections of eye-dominance columns in the cat cerebral cortex after monocular deprivation

Tire Defects Classification with Multi-Contrast Convolutional Neural Networks

The objective of this study is to improve the accuracy in tire defect classification with limited training samples under varying illuminations. We investigate an algorithm based on deep learning to achieve high accuracy with limited samples. First, image contrast normalizations and data augmentation were used to avoid overfitting problems of the network with a large number of parameters. Furthermore, multi-column CNN is proposed by combining several CNNs trained on differently preprocessed data into a multi-column CNN (MC-CNN), and then their predictions are averaged as the output of the proposed network. An average accuracy of 98.47% is achieved with the proposed CNN-based method. Experimental results show that our scheme receives satisfactory classification accuracy and outperforms state-of-the-art methods on the same tire defect dataset.

Erasing synapses in sleep: is it time to be SHY?

Converging lines of evidence strongly support a role for sleep in brain plasticity. An elegant idea that may explain how sleep accomplishes this role is the "synaptic homeostasis hypothesis (SHY)." According to SHY, sleep promotes net synaptic weakening which offsets net synaptic strengthening that occurs during wakefulness. SHY is intuitively appealing because it relates the homeostatic regulation of sleep to an important function (synaptic plasticity). SHY has also received important experimental support from recent studies in Drosophila melanogaster. There remain, however, a number of unanswered questions about SHY. What is the cellular mechanism governing SHY? How does it fit with what we know about plasticity mechanisms in the brain? In this review, I discuss the evidence and theory of SHY in the context of what is known about Hebbian and non-Hebbian synaptic plasticity. I conclude that while SHY remains an elegant idea, the underlying mechanisms are mysterious and its functional significance unknown.