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1
Introduction
2
Three Questions
3
Scanning
4
Cnnbased model
5
Does it work
6
Results
7
Image computable models
8
Predicted stimuli
9
What have we done
10
The Ideal Feature Space
11
Can Processing Stages Be Shared
12
What About a Larger Network
13
Behavioral RDMs
14
Summary
15
Questions
16
Is faces special
17
Is there a way to test this
18
Can we probe the network to generate optimal stimuli
19
Can we have three different models
20
Do we need specific functions
21
Face recognition
22
Spontaneous segregation
23
Longrange connectivity
Description:
Explore the concept of functional specificity in the human brain through this insightful one-hour lecture by MIT's Nancy Kanwisher. Delve into three key questions surrounding brain function, examining scanning techniques, CNN-based models, and image-computable models. Investigate the ideal feature space, shared processing stages, and the potential of larger networks. Analyze behavioral RDMs and discuss the specialization of face recognition, spontaneous segregation, and long-range connectivity. Engage with thought-provoking inquiries about optimal stimuli generation, multiple model comparisons, and the necessity of specific functions in brain processing.

Functional Specificity in the Human Brain - What, Whether, and Why?

MITCBMM
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