= VL 6

What are the resulting graphs from convolution and correlation?

As the distance towards an object approaches infinity, its binocular disparity approaches zero.

Which of the following are reasons why the huaman visual system relies on processing binocular disapairy?
	- It supports accurate depth perception Yes
	- It enables steerospic 3D vision Yes
	- It aids in motion planning and interaction with objects such as reaching and grasping Yes
	- It enhances colour discrimination and sharpens visual activity Yes
	- It contributes to sound localisation through visual spatial integration Yes

What is a key advantage of using phase-based methods compared to traditional window-based cross-correlation?
	- Phase-based methods allow for faster and more biological plausible computation of image disparity Yes
	- Phase-based methods completly remove noise from the image data Yes/No
	- No, window-based cross-corrleation is preferred because it is computatinally more efficient No
	- phase-based mehtods require no infrmation about local image structure No

What are corrleations (cross or auto) used for
	- Determining the temporal relation between cell firing Yes
	- Measuring the self- similarity of cell firing Yes
	- Descritoi of network operation ssuch sas lateral inhibition No
	- Modeling tempral filter charactreristics of membranes No
	- Measuring the strenght of cell-to-cell connections Yes
	
Select the correct statements about correlation fucntions
	- The correlation $h (x) =  g (x) * f (x)$ is equal to $f (x) * g (x)$ mirrored at the Y-Axis Yes
	- Cross-correlation is sued to deterinme the spatioal realtion between two cells firing No
	- Cross corellatoin are used b ythe brain to determine motin and soud perception aspects Yes
	- Auto-correlatoin gives the similatity between bservations of a vairable and its time-shifted version Yes
	- auto correltaions always have their maximum peak at t=0 Yes
	- if the psike train has a period of tau then its autocorrletaio nfucntion ahs theirr maximum peak at $t =  tau$ No
	- Auto corrletaion are approcimatley even functions Yes
	- the presence of noise can overdamp the amplitude of the oscillations of a given autocorrleation function Yes
	- auto correlations always show oscillatory patterns No

Which crosscorrelatoin function represents to mutually activating neurons (activating each other)?

