This lecture covers structured data, databases, federating neuroscience-relevant databases, ontologies.
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.
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.
This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.
This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.