The retina and primary visual cortex (V1) both exhibit diverse neural populations sensitive to
diverse visual features. Yet it remains unclear how neural populations in each area partition …

Deep artificial neural networks (ANNs) play a major role in modeling the visual pathways of
primate and rodent. However, they highly simplify the computational properties of neurons …

Background The performance of machine learning classification methods relies heavily on
the choice of features. In many domains, feature generation can be labor-intensive and …

How well do deep neural networks fare as models of mouse visual cortex? A majority of
research to date suggests results far more mixed than those produced in the modeling of …

The integration and interaction of cross-modal senses in brain neural networks can facilitate
high-level cognitive functionalities. In this work, we proposed a bioinspired multisensory …

The latest advances in artificial intelligence technology have opened doors to the video
analysis of complex behaviours. In light of this, ethologists are actively exploring the …

Not only have deep networks become standard in machine learning, they are increasingly of
interest in neuroscience as models of cortical computation that capture relationships …

Despite their immense success as a model of macaque visual cortex, deep convolutional
neural networks (CNNs) have struggled to predict activity in visual cortex of the mouse …

Recent advances in machine learning have led to revolutionary breakthroughs in computer
games, image and natural language understanding, and scientific discovery. Foundation …

Under difficult viewing conditions, the brain's visual system uses a variety of recurrent
modulatory mechanisms to augment feedforward processing. One resulting phenomenon is …