1. fMRI and neural encoding models: Voxel receptive fields (continued)

2. A voxel receptive field model of visual cortex: Kay et al, Nature, 2008

3. A voxel receptive field model of visual cortex: Kay et al, Nature, 2008

4. A voxel receptive field model of visual cortex: Kay et al, Nature, 2008

5. A specific voxel’s receptive field

6. Generative and discriminative models
From Christopher Bishop book:
Pattern Recongition and Machine Learning

7. Huth et al. (2012) Semantic space in cortex

8. Principal Components Analysis (PCA)

9. Representing categories in WordNet

10. Representing multiple semantic principal components

11. A closer look at semantic space

12. What do the components mean?

13. Highly distributed representations

14. How much of each region’s activation does the model explain?

15. Summary: Voxel receptive field models
Generative model of neural activation, as opposed to a discriminative model
Often called encoding models vs. decoding models
Useful for synthesising (generating) inferred inputs, e.g. the image someone was seeing
Still leaves lots of neural function unexplained, but a very useful step forward nonetheless