Briefly describe the functional organisation of the visual

system; describe a computational problem the visual system

has to solve. How is this solution achieved in the nervous

system?

Dionne Angela Donnelly

Module Code: PSYC202

Word Count: 1545

The visual system (VS) consists of the eye, the lateral geniculate nucleus (LGN), the striate

cortex (visual cortex, VC) and the magno- (M), parvo- (P) and koniocellular (K) pathways which

connect them (Eysenck & Keane, 2005). The whole retina-geniculate-striate pathway is an

inverted retinotopic map, which means that neurons will have inverted positions relative to one

another in the brain that are the same as their positions in the retina (Eysenck & Keane, 2005).

One computational problem the VS must solve is the problem of depth perception, or how we

combine information from both eyes to create a single three-dimensional (3D) representation

from the two-dimensional (2D, proximal stimuli) images created on our retinas from the world

around us (the distal stimuli). The information we take from these images appear to be a variety

of cues to depth which work in varying degrees depending on the distance of the stimulus from

the observer (Goldstein, 1999). In an attempt to understand the resolution of this problem each

component of the VS in evaluated in order to understand the role it plays in our perception of

depth. From this it is seen that the amalgamation of cues our eyes receive from the outside world

in order to perceive depth probably occurs within the cortical areas of the brain involved in

higher order processing.

In everyday situations, depth perception is usually based on cues provided by movement

(Eysenck & Keane, 2005). The most important of these cues is motion parallax in which when

we move, objects nearest to us move quickly past us, but those objects furthest away are much

slower (Goldstein, 1999). Static cues are monocular and include: pictorial cues, of which several

examples are linear perspective, texture gradient, image blur and interposition/occlusion;

oculomotor cues consist of convergence and accommodation; the binocular cue is stereopsis,

which is due to disparity of the two retinal images (Eysenck & Keane, 2005, Goldstein, 1999).

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Disparity is the difference in the angle of the two images on the retinas. The further away details

are from the two fixation points (the parts of the image will fall on the foveas) the greater the

disparity (Goldstein, 1999). Disparity and consequently stereopsis is thought to play a major role

in our visual perception of depth.

Visual perception begins with the reception stage (Kalat, 1988) which involves the absorption of

light energy into the first component of the VS, the eye. Light travels in through the cornea and

passes through the pupil (a hole in the iris) to the lens (controlled by the ciliary muscle) which

focuses the light through the vitreous humour to the back of the eye – the retina (Eysenck &

Keane, 2005). The oculomotor cues originate within the eye: Convergence is when the eyes

move together to focus the fovea onto a nearby object and accommodation is when the lens

changes shape in order to change the level of focus on objects at different distances from the

observer (Eysenck & Keane, 2005, Goldstein, 1999). Convergence and accommodation are poor

cues to depth as they only provide information about stimuli between zero and two metres away

from the observer (Goldstein, 1999). Therefore they are not considered to contribute much to the

overall perception of depth.

The transduction stage takes place in the retina (Kalat, 1988), as the light energy is converted to

electrochemical signals by the photoreceptors – rods and cones. The level of coding is directly

dependent upon the intensity of the stimulus (Kalat, 1988). Firstly, light travels through four

layers of cells (the ganglion (G), amacrine (A), bipolar (B) and then horizontal (H) cells) to the

rods and cones. There are six million cones which are concentrated around the fovea (Eysenck &

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Keane, 2005) and are specialised for colour vision and more importantly for depth perception -

sharpness. Image blur is one of the pictorial cues to depth perception, if an image is sharper than

its surroundings then it is perceived as being closer to the observer (Eysenck & Keane, 2005).

Therefore, it can interpreted that cones play a role in our perception of depth. There are 125

million rods which are mainly located around the periphery and are specialised for motion

perception and seeing in dim light (Eysenck & Keane, 1995). From this, it could be that rods

play a role in everyday depth perception involving motion parallax. Most of the differences

between rods and cones are due to retinal convergence, as there are 130 million photoreceptors

which converge onto 20 million B cells, which then converge onto only one million G cells

meaning that rods converge many more times than cones, and some cones only converge onto

one G cell each (Goldstein, 1999). There are different kinds of G cell: the M-ganglion cell which

projects down the magnocellular (M) pathway, and the P-ganglion cell, which projects down the

parvocellular (P) pathway. These pathways travel to the brain via the optic nerve down the

retina-geniculate-striate pathway (Eysenck & Keane, 2005).

Upon entering the brain, the signals pass through the optic chiasma (where the pathways from

the two retinas cross and the outer halves of each retinal projection go to the ipsilateral

hemisphere) to the lateral geniculate nucleus (LGN) of the thalamus (Eysenck & Keane, 2005).

The LGN actually receives 80 per cent of its input from the VC but the reason for this is

unknown (Weurger, 2010). The LGN is retinotopic and has six layers. Layers 1, 4, and 6 receive

signals from the contralateral eye. Layers 2, 3, and 5 receive signals from the ipsilateral eye.

These layers are often referred to as ocular dominance columns (ODCs). Also, the layers

correspond to the different pathways, with layers 1 and 2 relating to the M pathway, in which the

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cells have large retinal fields (RFs) and large cell bodies, responding mainly to motion. This

pathway could therefore account for the transmission of depth information for moving objects.

Layers 3, 4, 5 and 6 relate to the P pathway, with small cell bodies. The P pathway is split into

two areas – blobs (high metabolic activity, respond to colour) and interblobs (low activity,

respond to location and orientation). As interblobs are sensitive to location and orientation it

could be that they too help to carry information regarding depth to the VC. Both pathways also

respond to contrast (Eysenck & Keane, 2005). Just ventral to each layer are the K cells, which

have very small cell bodies (Weurger, 2010), but apart from their association with colour, little is

known about these cells.

After passing through the LGN, the pathways arrive at the six layered VC in the occipital lobe

(Eysenck & Keane, 2005) and the axons mainly end in layer 4C in the primary VC (PVC, V1 or

Area 17) (Weurger, 2010). The mixing of the pathways of both eyes first occurs here, as in the

LGN they are completely segregated (Zigmond et al. 1999). The M pathway projects from the

LGN to layer 4Cα, the P pathway to layer 4Cβ, whilst the K pathway projects to layers 2 and 3

of the PVC (Weurger, 2010, see also Zigmond et al. 1999). More of these cortical neurones

receive information from the fovea than from the periphery (Goldstein, 1999). Zeki (1992, cited

in Eysenck & Keane, 2005) argued that the VC of the macaque monkey is organised into

different functional areas, and we generalise these to the human brain. He stated that the V1 and

V2 are mainly involved in early perception, whilst the V3 and V3A cells respond to form. The

V4 is mainly responsive to colour and line orientation and the V5 is dedicated to motion. The V5

(or middle temporal area) is thought to be involved in stereopsis (Eysenck & Keane, 2005) as

cells located in V2 which deal with disparity also project to V5 (Zeki, 1978, and Britten, 2004

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cited in Daw, 1995). In a test of this proposal, DeAngelis, Cumming and Newsome (1998, cited

in Eysenck & Keane, 2005) stimulated cell clusters in monkey V5 and found their depth

perception to be biased towards the disparity preferred by those cells. Bülthoff, Bülthoff and

Sinha (1998, cited in Eysenck & Keane, 2005) found that when stereoscopic information of

familiar objects was scrambled, subjects did not realise it was wrong. The researchers argued that

the stereoscopic information is overridden by their expectations of what the stimuli should look

like. This is supported by research by Bruce, Green and Georgeson (2003, cited in Eysenck &

Keane, 2005), who reversed information presented to the right and left eyes, they found that

depth was reversed when looking at random-dot stereograms (RDS) and wire-frame images. But,

this effect was not seen when using photographs, which suggests that other factors such as

expectation of size/shape etc., and other depth cues such as occlusion play a role in modifying

our perception of depth, especially in situations which conflict with our normal perception of

stimuli.

To conclude, it would seem the computational problem of depth perception is solved

predominantly in the VC, showing that resolution of so many different cues requires higher

cortical functioning to solve. However, it is not clearly understood how these cues are integrated

within the cortex nor why binocular cues are sometimes ignored in favour of other cues, such as

prior knowledge of objects and occlusion.

References

Daw, N. W. (1995). Visual Development (Second Ed.). NY: Springer.

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Eysenck, M. W. & Keane, M. T. (2005). Cognitive Psychology A Student’s Handbook (5th Ed.).

Hove: Psychology Press.

Goldstein, E. B. (1999). Sensation and Perception (5th Ed.). California: Brooks/Cole.

Kalat, J. W. (1998). Biological Psychology (5th Ed.). California: Wadsworth.

Weurger, S. M. (2010). Vision II: From the Retina to the Brain. PSYC202 Perception and

Memory Lecture Slides.

Zigmond, M. J., Bloom, F. E., Landis, S. C., Roberts, J. L. & Squire, L. R. (Eds.) (1999).

Fundamental Neuroscience. London: Academic Press.

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