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 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 ~

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

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

Simple Cells LGN V1 wrong location or angle doesn’t affect simple cell ~

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 ~

Complex Cells S1 S2 S3 V1 V1/V2 Complex Cell

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

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