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.
How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.
Introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.
Introduction to neurons, synaptic transmission, and ion channels.
2nd part of the lecture. Introduction to cell receptors and signalling cascades
Introduction to the origin and differentiation of myelinating cell types, molecular mechanisms defining onset and progression of myelination, demyelination and remyelination after injury.
This lecture covers: integrating information within a network, modulating and controlling networks, functions and dysfunctions of hippocampal networks, and the integrative network controlling sleep and arousal.
This lecture focuses on the comprehension of nociception and pain sensation. It highlights how the somatosensory system and different molecular partners are involved in nociception and how nociception and pain sensation are studied in rodents and humans and the development of pain therapy.