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.

This lecture will highlight our current understanding and recent developments in the field of neurodegenerative disease research, as well as the future of diagnostics and treatment of neurodegenerative diseases.

2nd part of the lecture. This lecture will highlight our current understanding and recent developments in the field of neurodegenerative disease research, as well as the future of diagnostics and treatment of neurodegenerative diseases.

This lecture will provide an overview of neuroimaging techniques and their clinical applications

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

The lecture focuses on rationale for employing neuroimaging methods for movement disorders

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.