Non-recurrent deep convolutional neural networks (CNNs) are currently the best at modeling
core object recognition, a behavior that is supported by the densely recurrent primate …

Distributed neural population spiking patterns in macaque inferior temporal (IT) cortex that
support core object recognition require additional time to develop for specific, "late-solved" …

The internal representations of early deep artificial neural networks (ANNs) were found to
be remarkably similar to the internal neural representations measured experimentally in the …

Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object
classification tasks such as ImageNet. Further, they are quantitatively accurate models of …

INTRODUCTION The pattern of light that strikes the eyes is processed and re-represented
via patterns of neural activity in a “deep” series of six interconnected cortical brain areas …

Primates, including humans, can typically recognize objects in visual images at a glance
despite naturally occurring identity-preserving image transformations (eg, changes in viewpoint)…

Deep convolutional artificial neural networks (ANNs) are the leading class of candidate
models of the mechanisms of visual processing in the primate ventral stream. While initially …

Faces are among the most important visual stimuli that humans perceive in everyday life.
While extensive literature has examined emotional processing and social evaluations of faces, …

Optogenetics has revolutionized neuroscience in small laboratory animals, but its effect on
animal models more closely related to humans, such as non-human primates (NHPs), has …

Transcranial electrical stimulation (tES) is a promising therapeutic tool for a range of neurological
diseases. Understanding how the small currents used in tES spread across the scalp …