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The Visual System: Feature Detection Model

The Visual System: Feature Detection Model. Lecture 15. Cortical Mechanisms. Primary Visual Cortex - V1 Striate or calcarine cortex Hubel and Wiesel - Nobel Prize Single cell recording Feature detection model simple stimuli  complex perceptions ~. Feature Detection Model.

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The Visual System: Feature Detection Model

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  1. The Visual System:Feature Detection Model Lecture 15

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

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

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

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

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

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

  8. S1 S2 S3 Complex Cells V1 V1/V2 Complex Cell

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

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

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