In this paper we demonstrate how the Nengo neural modeling and simulation libraries
enable users to quickly develop robotic perception and action neural networks for simulation …

We expand our existing spiking neuron model of decision making in the cortex and basal
ganglia to include local learning on the synaptic connections between the cortex and …

Dynamical systems are universal computers. They can perceive stimuli, remember, learn
from feedback, plan sequences of actions, and coordinate complex behavioural responses …

Methods, systems and apparatus that provide for perceptual, cognitive, and motor behaviors
in an integrated system implemented using neural architectures. Components of the system …

Building large-scale brain models is one method used by theoretical neuroscientists to
understand the way the human brain functions. Researchers typically use either a bottom-up …

Deep learning has demonstrated remarkable success in a variety of fields in the past
decade and experienced remarkable developments. Despite improved performance, the …

The amygdala (AMY) is widely implicated in fear learning and fear behaviour, but it remains
unclear how the many biological components present within AMY interact to achieve these …

We present research in the modeling of neurons within Drosophila (fruit fly) olfaction. We
describe the process from data collection, to model creation, and spike generation. Our …

Current state-of-the-art approaches to computational speech recognition and synthesis are
based on statistical analyses of extremely large data sets. It is currently unknown how these …

In this thesis I present the Recurrent Error-driven Adaptive Control Hierarchy (REACH); a
large-scale spiking neuron model of the motor cortices and cerebellum of the motor control …