1. Ψ
Sensation
&
Perception

2. Ψ -Discussion Section- Session 4 – Visual Cortex I
Icecube (Hubel & Wiesel)
Pinwheel (Issa & Stryker)

3. Administrative stuff

4. Presentation 1: Receptive fields and functional architecture of monkey striate cortex (1968) presented by John Scott-Railton
Presentation 2: Spatial Frequency Maps in Cat Visual Cortex (2000) presented by Jasmine Kwong

5. Next week Week 7: 11/08/2004 Higher visual perception: Contours
Paper 1 (Classic): von der Heydt et al., 1984 (Perla)
Paper 2 (Modern): Bakin et al., (?)

6. BACKGROUND

7. This weeks issue:

8. How can one effectively represent 6 stimulus dimensions on a 2
How can one effectively represent 6 stimulus dimensions on a 2.5 dimensional sheet?
Orientation
Ocular dominance
Spatial frequency
Motion
Depth
Color

9. Essentially a mathematical optimization problem
Similarly:
How to put as much of the sheet as possible into a sphere? (Cortex into skull)
Solution?
Folding!

10. That’s why cortex is folded
It optimizes area while minimizing volume
So far, so good.
But what about the basic functional unit of cortex organization?
How to represent all stimulus dimensions effectively in all locations?

11. Two proposals:

12. 1. The “Iceblock” model (Hypercolumns)
David H. Hubel
Torsten N. Wiesel
Nobel prize in Physiology, 1981

14. 2. The “Pinwheel” model
Naoum P. Issa
(UofC)
Michael P. Stryker

16. Optical imaging Rationale:
Deoxygenated blood is darker than oxygenated blood.
This is particularly true in the range of red light.
Active neurons use up more oxygen than neurons that are less active.
This leads to a local, spatial distribution of blood saturation levels.
 Regions of active neurons should appear darker.

17. Optical Imaging

18. Pro and Con Pro Con Very high spatial resolution
Allows to visualize large scale activity patterns
Relatively direct link to electrical activity of neurons
Better time course than fMRI
Con
Still relatively bad time course (linked to oxygen dynamics)
Invasive
Very low signal to noise  need to average many, many trials to see signal.
Hemodynamics indirect, nonlinear.

19. BOLD time course

20. The case for spatial frequency
Orientation
Ocular dominance
Spatial frequency
Motion
Depth
Color

21. Picture representation in V1

22. The concept Luminance Space Amplitude = Contrast
Wavelength = Spatial Frequency
Amplitude = Contrast
Space

23. Looks like:

24. Fouriers theorem
EVERY waveform can be decomposed into simple sine-waves with the right amplitude and frequency.
EVERY waveform can be synthesized by adding sine-waves with the right amplitude and frequency.

26. V1 neurons are apt to represent sine waves of different frequency

28. Philosophical implication
The representation of the visual world by neurons in V1 is VERY different from our phenomenological experience. Each neuron only represents a tiny slice of oriented spatial frequency!