1. The Visual System: Feature Detection Model Lesson 17

2. Cortical Mechanisms n Primary Visual Cortex - V1 l Striate or calcarine cortex n Hubel and Wiesel - Nobel Prize l Single cell recording n Feature detection model l simple stimuli  complex perceptions ~

3. Feature Detection Model n Visual perception of objects l detection of simple features l points, lines, corners, curves n Convergence of information l retina  LGN  V1 n Primary Visual Cortex (V1) l Simple cells l complex cells l hypercomplex cells ~

4. Simple Cells n Detect lines & edges l not center-surround n Best stimulus l bar of light or line l particular orientation l particular location ~

5. Simple Cells n LGN neurons RF l center-surround l converge onto simple cells (V1) n Bar of light l  APs in simple cell ~

6. Simple Cell Simple Cells n wrong location or angle l doesn’t affect simple cell ~ LGN V1 Wrong location Wrong angle

7. Complex Cells n In V1 & V2 (secondary visual cortex) n Convergence l of LGN & simple cells l responds to movement n Best stimulus l line or bar l Fixed angular orientation l Location not as important l preferred direction of movement ~

8. S1S2S3 Complex Cell Complex Cells V1 V1/V2

9. Hypercomplex Cells n V1 & V2 l Complex cells converge l Hypercomplex cells n Best stimulus l lines of specific length l Detect Corners ~

10. Feature Detection Theory n Features = lines & corners l Can it represent a curve?