Using Decoding to Understand Neural Algorithms

Explore the intricacies of neural decoding and its application in understanding neural algorithms through this comprehensive tutorial. Delve into the ventral visual pathway, examine the concept of information in neural systems, and learn about training methods for neural decoding. Investigate abstract representations and position invariance in neural networks, analyzing results from both invariant and non-invariant cases. Discover the impact of permutations on neural decoding and gain insights into the role of attention in neural processing. Presented by Ethan Meyers from Hampshire College and MIT, this 71-minute lecture from the BMM Summer Course 2018 offers a deep dive into cutting-edge neuroscience research techniques.

Introduction
Ventral Visual Pathway
Understanding Neural Algorithms
What is Information
Outline
Neural Decoding
Training
Abstract Representation
Position Invariance
Results
Invariant case
Noninvariant case
Permutations
Summary
Attention