This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network. 

Presentation of a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Presentation of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

The lecture covers a brief introduction to neuromorphic engineering, some of the neuromorphic networks that the speaker has developed, and their potential applications, particularly in machine learning.

This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies. 

2nd part of the lecture. Introduction to cell receptors and signalling cascades

GABAergic interneurons and local inhibition on the circuit level.

The ionic basis of the action potential, including the Hodgkin Huxley model. 

Introduction to the course Cellular Mechanisms of Brain Function.

The ionic basis of the action potential, including the Hodgkin Huxley model. 

Introduction to the course Cellular Mechanisms of Brain Function.

Ion channels and the movement of ions across the cell membrane.

Spatiotemporal dynamics of the membrane potential.

Action potentials, and biophysics of voltage-gated ion channels.

Voltage-gating kinetics of sodium and potassium channels.

The ionic basis of the action potential, including the Hodgkin Huxley model.

Action potential initiation and propagation.

Neurotransmitter release in the presynaptic specialization.

Synaptic modulation through diffusing neurotransmitters.