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.

Introduction to the Mathematics chapter of Datalabcc's "Foundations in Data Science" series.

Primer on elementary algebra

Primer on linear algebra

Primer on systems of linear equations

Primer on calculus

How calculus relates to optimization

Big O notation

Basics of probability.

A basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.

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

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.

Long-range inhibitory connections in the brain, with examples from three different systems.

The "connectome" is a term, coined in the past decade, that has been used to describe more than one phenomenon in neuroscience. This lecture explains the basics of structural connections at the micro-, meso- and macroscopic scales.