1. Read this article for Friday Oct 21! Trends in Neuroscience (2000) 23, 571 - 579 Hint #1: there are at least 3 ways of getting this article Hint #2: none of them are “wait till Matt sends it to me”

2. Some comments on your theories: Remember that a theory is a proposed answer to a question: –E.g. “How is the visual system tuned to detect edges?”…”My theory is that visual neurons receive excitatory input from the centre of their receptive fields but inhibitory input from the surrounding region.”

3. Some comments on your theories: Remember that predictions follow from theories –E.g. “My theory is that visual neurons receive excitatory input from the centre of their receptive fields but inhibitory input from the surrounding region” –My theory predicts if I record spike trains from visual neurons while presenting visual stimuli at different locations around its receptive field, I will see a pattern of decreased spike rate when the stimulus is off centre and increased spike rate when the stimulus is on centre.

4. Some comments on your theories: Don’t send a neuroscientist to do a psychologist’s job: –My theory is that we can measure memory ability using fMRI NO! You measure memory ability with a battery of memory tasks, a clipboard and a stopwatch. Propose a theory ABOUT HOW THE BRAIN WORKS

5. Some comments on your theories: Assignment for next week: make a prediction –My theory is…… –My prediction is….

6. The Role of “Extrastriate” Areas Different visual cortex regions contain cells with different tuning properties

7. The Role of “Extrastriate” Areas Consider two plausible models: 1.System is purely hierarchical: –each area performs some elaboration on the input it is given and then passes on that elaboration as input to the next “higher” area 2.System is analytic and parallel: –different areas elaborate on different features of the input

8. The Role of “Extrastriate” Areas Functional imaging (PET) investigations of motion and colour selective visual cortical areas suggests analytical and parallel organization Zeki et al. Subtractive Logic –stimulus alternates between two scenes that differ only in the feature of interest (i.e. colour, motion, etc.)

9. The Role of “Extrastriate” Areas Identifying colour sensitive regions Subtract Voxel intensities during these scans… …from voxel intensities during these scans …etc. Time ->

10. The Role of “Extrastriate” Areas result –voxels are identified that are preferentially selective for colour –these tend to cluster in anterior/inferior occipital lobe

11. The Role of “Extrastriate” Areas similar logic was used to find motion-selective areas Subtract Voxel intensities during these scans… …from voxel intensities during these scans …etc. Time -> MOVING STATIONARY MOVING STATIONARY

12. The Role of “Extrastriate” Areas result –voxels are identified that are preferentially selective for motion –these tend to cluster in superior/dorsal occipital lobe near TemporoParietal Junction –Akin to Human V5

13. The Role of “Extrastriate” Areas Thus PET studies doubly-dissociate colour and motion sensitive regions Bilateral V5 Bilateral V4

14. The Role of “Extrastriate” Areas V4 and V5 are doubly-dissociated in lesion literature:

15. The Role of “Extrastriate” Areas V4 and V5 are doubly-dissociated in lesion literature: –achromatopsia (color blindness): there are many forms of color blindness cortical achromatopsia arises from lesions in the area of V4 singly dissociable from motion perception deficit - patients with V4 lesions have other visual problems, but motion perception is substantially spared

16. The Role of “Extrastriate” Areas V4 and V5 are doubly-dissociated in lesion literature: –akinetopsia (motion blindness): bilateral lesions to area V5 (extremely rare) severe impairment in judging direction and velocity of motion - especially with fast-moving stimuli visual world appeared to progress in still frames similar effects occur when M-cell layers in LGN are lesioned in monkeys

17. Visual Neuron Responses Edges are important because they are the boundaries between objects and the background or objects and other objects

18. Visual Neuron Responses This conceptualization of the visual system was “static” - it did not take into account the possibility that visual cells might change their response selectivity over time –Logic went like this: if the cell is firing, its preferred line/edge must be present and… –if the preferred line/edge is present, the cell must be firing We will encounter examples in which these don’t apply! Representing boundaries must be more complicated than simple edge detection!

19. Visual Neuron Responses Boundaries between objects can be defined by color rather than brightness

20. Visual Neuron Responses Boundaries between objects can be defined by texture

21. Visual Neuron Responses Boundaries between objects can be defined by motion and depth cues