Convolutional neural networks (CNNs) were inspired by early findings in the study of
biological vision. They have since become successful tools in computer vision and state-of …

Neuroscience research is undergoing a minor revolution. Recent advances in machine
learning and artificial intelligence research have opened up new ways of thinking about …

In order to better understand how the brain perceives faces, it is important to know what
objective drives learning in the ventral visual stream. To answer this question, we model …

Biological intelligence is remarkable in its ability to produce complex behaviour in many
diverse situations through data efficient, generalisable and transferable skill acquisition. It is …

Much of the controversy evoked by the use of deep neural networks as models of biological
neural systems amount to debates over what constitutes scientific progress in neuroscience …

Centered Kernel Alignment (CKA) was recently proposed as a similarity metric for
comparing activation patterns in deep networks. Here we experiment with the modified RV …

The distribution of retinal ganglion cells in primate visual systems portrays a densely
distributed central region, with an incrementally decreasing cell density as the angle of …

Recent advances in computer vision have enabled machines to have high performance in
labeling objects in natural scenes. However, object labeling constitutes only a small fraction …

Recent advances in computer vision have enabled machines to have high performance in
labeling objects in natural scenes. However, object labeling constitutes only a small fraction …

any of the debates surrounding the use of deep neural networks (DNNs) as models of
biological neural networks amount to debates over what constitutes scientific progress in …