Connections between neurons can be found by checking whether synapses exist at points
of contact, which in turn are determined by neural shapes. Finding these shapes is a special …

Combining multi-modality brain data for disease diagnosis commonly leads to improved
performance. A challenge in using multi-modality data is that the data are commonly …

How does the mammalian retina detect motion? This classic problem in visual neuroscience
has remained unsolved for 50 years. In search of clues, here we reconstruct Off-type …

We use a simple modification to a conventional SLR camera to capture images of several
hundred scenes in colour (RGB) and near-infrared (NIR). We show that the addition of near …

Modern graphics cards contain hundreds of cores that can be programmed for intensive
calculations. They are beginning to be used for spiking neural network simulations. The goal …

Category-specificity has been demonstrated in the human posterior ventral temporal cortex
for a variety of object categories. Although object representations within the ventral visual …

The human visual system can rapidly recognize objects despite transformations that alter
their appearance. The precise timing of when the brain computes neural representations …

Deep convolutional neural networks (DCNNs) have attracted much attention recently, and
have shown to be able to recognize thousands of object categories in natural image …

Discovering the visual features and representations used by the brain to recognize objects is
a central problem in the study of vision. Recently, neural network models of visual object …

Large-scale numerical simulations of detailed brain circuit models are important for
identifying hypotheses on brain functions and testing their consistency and plausibility. An …