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Lesson type

Lesson title:

The probability of a hypothesis, given data.

Difficulty level: Beginner
Duration: 7:57
Speaker: : Barton Poulson
Lesson title:

Why math is useful in data science.

Difficulty level: Beginner
Duration: 1:35
Speaker: : Barton Poulson
Lesson title:

Why statistics are useful for data science.

Difficulty level: Beginner
Duration: 4:01
Speaker: : Barton Poulson
Lesson title:

Statistics is exploring data.

Difficulty level: Beginner
Duration: 2:23
Speaker: : Barton Poulson
Lesson title:

Graphical data exploration

Difficulty level: Beginner
Duration: 8:01
Speaker: : Barton Poulson
Lesson title:

Numerical data exploration

Difficulty level: Beginner
Duration: 5:05
Speaker: : Barton Poulson
Lesson title:

Simple description of statistical data.

Difficulty level: Beginner
Duration: 10:16
Speaker: : Barton Poulson
Lesson title:

Basics of hypothesis testing.

Difficulty level: Beginner
Duration: 06:04
Speaker: : Barton Poulson
Lesson title:

In this lecture, the speaker demonstrates Neurokernel's module interfacing feature by using it to integrate independently developed models of olfactory and vision LPUs based upon experimentally obtained connectivity information.

Difficulty level: Intermediate
Duration: 29:56
Speaker: : Aurel A. Lazar
Lesson title:

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

Difficulty level: Beginner
Duration: 1:32:17
Speaker: : Shih-Chii Liu
Lesson title:

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

Difficulty level: Beginner
Duration: 21:15
Speaker: : Tadashi Yamazaki
Lesson title:

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

Difficulty level: Beginner
Duration: 41:57
Speaker: : Giacomo Indiveri
Lesson title:

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

Difficulty level: Beginner
Duration: 20:39
Speaker: : Giacomo Indiveri
Lesson title:

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.

Difficulty level: Intermediate
Duration: 19:57
Lesson title:

This lecture covers computational principles that growth cones employ to detect and respond to environmental chemotactic gradients, focusing particularly on growth cone shape dynamics.

Difficulty level: Intermediate
Duration: 26:12
Speaker: : Geoff Goodhill
Lesson title:

In this lecture you will learn that in developing mouse somatosensory cortex, endogenous Btbd3 translocate to the cell nucleus in response to neuronal activity and oriented primary dendrites toward active axons in the barrel hollow.

Difficulty level: Intermediate
Duration: 27:32
Speaker: : Tomomi Shimogori
Lesson title:

In this presentation, the speaker describes some of their recent efforts to characterize the transcriptome of the developing human brain, and and introduction to the BrainSpan project.

Difficulty level: Intermediate
Duration: 30:45
Speaker: : Nenad Sestan
Lesson title:

How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.

Difficulty level: Beginner
Duration: 1:08:45
Speaker: : Clay Reid
Lesson title:

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.

Difficulty level: Beginner
Duration: 1:13:16
Speaker: : Clay Reid