A key goal of computational neuroscience is to link brain mechanisms to behavioral
functions. The present article describes recent progress towards explaining how laminar …

A full understanding of consciousness requires that we identify the brain processes from
which conscious experiences emerge. What are these processes, and what is their utility in …

Sensory processing of visual, auditory, and other sensor information (eg, visual imagery,
LIDAR, RADAR) is conventionally based on “stovepiped,” or isolated processing, with little …

Abstract Lifelong Deep Neural Network (L-DNN) technology revolutionizes Deep Learning
by enabling fast, post-deployment learning without extensive training, heavy computing …

Sensory processing of visual, auditory, and other sensor information (eg, visual imagery,
LIDAR, RADAR) is conventionally based on “stovepiped,” or isolated processing, with little …

The systems and methods disclosed herein include a path integration system that calculates
optic flow, infers angular velocity from the flow field, and incorporates this velocity estimate …

The functional role of synchronous oscillations in various brain processes has attracted a lot
of experimental interest. Berke et al.(2008) reported beta oscillations during the learning of …

Today, artificial neural networks are trained on large sets of manually tagged images.
Generally, for better training, the training data should be as large as possible. Unfortunately …

Making use of very detailed neurophysiological, anatomical, and behavioral data to build
biologically-realistic computational models of animal behavior is often a difficult task. Until …

Sensory processing of visual, auditory, and other sensor information (eg, visual imagery,
LIDAR, RADAR) is conventionally based on “stovepiped,” or isolated processing, with little …