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

This article develops the Synchronous Matching Adaptive Resonance Theory (SMART)
neural model to explain how the brain may coordinate multiple levels of thalamocortical and …

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 study of biorealistic neuron circuits has been limited by the efficiency of digital
implementations. Efficient digital approaches generally use I&F variants, losing important …

Abstract Brain-chip-interfaces (BCHIs) are hybrid entities where chips and nerve cells
establish a close physical interaction allowing the transfer of information in one or both …

Rapid advances in neuronal probe technology for multisite recording of brain activity have
posed a significant challenge to neuroscientists for processing and analyzing the recorded …

How spiking neurons cooperate to control behavioral processes is a fundamental problem in
computational neuroscience. Such cooperative dynamics are required during visual …

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