Download Organization of the Visual System

Review of Visual System
We can’t go over every aspect of the visual system in a single lecture, so I’m going to assume
you have covered this in general in previous courses, and will review some elements that are
key to this course.
1) Anatomy, Lateralization, and Depth. Stimulation at the retina leads to activation of retinal
ganglion cells, which project to a part of the thalamus called the lateral geniculate nucleus
(LGN). Remember that the optics of the eye cause light from the right visual field to strike
the left retina and vice versa. Ganglion cells from the medial retinas (the parts close to the
nose) cross over to the opposite LGN. As a result, you have everything from the left visual
field activating the right LGN, and vice versa. But at this point, information from the two eyes
is not yet combined, but instead is separated in different layers of magnocellular (M) and
parvocellular (P) cells.. The right LGN then projects to the right side of the primary visual
cortex (V1), located along the calcarine fissure at the back of occipital cortex (and left to
left). Thus this lateralization remains in the cortex and is seen through higher levels of visual
cortex as well (thought question: so why don’t we see things backwards?). Information from
the left and right eyes is combined at the level of V1, giving rise to a form of depth
perception called binocular disparity. However, other monocular cues (e.g., occlusion,
parallax, size constancy, linear convergence and texture) are equally important.
2) Retinotopy. Because of the structure of the eye and the orderly way in which light falls on
the back of the eye, activation of cells in the retina likewise forms an orderly, i.e. topographic
map of space known as a retinotopic map. The map is over-represented (and color) at the
fovea, where cone cells are packed closely together, and under-represneted (and relatively
color instenstive) in the periphery where one has more scattered receptors, mainly of the rod
type. These project indirectly to local gangion cells, which we have seen already project to
the LGN. This distorted retinotopic map is preserved in LGN and V1, but starts to break
down at higher levels (V2, V3, V4) and its controversial if any retinotopy remains at the
highest levels (see below), except in terms of general lateralization. Retinotopy does not
exist so that we have a picture of the world in our heads, rather it may have several
advantages: if most connections between cells are local, then retinotopy reduces connection
lengths (and thus brain volume) while increasing speed of interactions. It may also play a
role in certain ‘wave’-like electrical phenomena that my coordinate activation across
populations of neurons. Such population phenomena are not so obvious when one records
action potentials, but are more evident when one records ‘local field potentials’ that reveal
the sum of local synaptic activity, or images visual cortex in other ways.
3) Receptive Fields (RF). The RF is the area in space where a stimulus can modulate activity
of a particular neuron. This activity is normally quantified by measuring the rate of action
potentials from a single neuron. This modulation could be either excitatory or inhibitory.
(There are also ‘non classical’ RFs: points in space where a stimulus will not change activity,
but will change the effect of a stimulus in the classic RF.) Visual RFs are generally located
in a particular part of retinotopic space and vary in size and shape. In the classic story,
Retinal Ganglion cells and LGN cells essentially have donut-like RFs with excitatory centres
and inhibitory surrounds, which are small near the fovea and bigger toward the periphery.
Hubel and Weisel won the Nobel Prize for showing that in V1, these RFs assume more
linear characteristics, e.g., ‘simple cells’ that respond to lines with a certain orientation in a
certain part of space, ‘complex cells’ that require the line to be moving one way or the other
othrogonal to its long axis, or hypercomplex cells that require a certain line length. Moder
techniques tend to be more computational, for example looking at frequency and principle
component analysis of the information contained in cells.
4) Functional Specialization. Even at the level of the retina, ganglion cells have different
functional properties, e.g. comparing p and m ganglion cells. Confusingly, p cells project to
M cells in the LGN and m cells project to P cells, where from hereon they are called the M
and P pathway (based on the LGN nomenclature). P cells tend to have smaller, colorsensitive receptive fields and less temporal resolution (and thus are thought to be good for
discriminating certain features of objects), whereas M cells have larger color-insensitive
receptive fields and are very temporally sensitive (and thus are thought to be more useful for
spatial perception and motion processing). This dichotomy tends to be preserved in cortex,
although in more abstract ways. Ungerleider and Mishkin pointed out that a ‘dorsal stream’
of vision, running from occipital cortex to parietal cortex, contained mostly spatiallyresponsive neurons with little feature responsiveness, whereas the ‘ventral stream’, running
from occipital cortex through temporal cortex has neurons that are highly sensitive to
features. Further as one goes further along this stream the features become more complex,
e.g. coding for rudimentary shape components like corners in V4 to (sometimes) specific
objects, independent of location, in IT (inferotemporal). An intermediate area in the human,
LO, seems particularly important for object analysis. This gave rise to the notion of a ‘where’
and ‘what’ pathways. Goodale and Milner revised this to ‘how’ and ‘what’ or action and
perception pathways. This is based on observations such as deficits in patients with these
areas, or the fact that many dorsal stream neurons also show action responses and motor
response fields for different parts of the body (we will return to this next week). The main
difference between these two accounts is that the first considers the type of visual input to
the stream, whereas the second considers the output: what this information is used for. Not
everything fits neatly within these schemes; for example V5 (MT, or MT+ in humans) is a
major motion sensitive area that contributes to both perception and action, so it might be
considered an input module to both. Further, each of the streams has many different
functional modules (some of which we will consider in this course), each having different
complex neuron types. Neverthless, the dorsal-ventral distinction has proven over the years
to be a powerful heuristic to understand the major aspects of high-level vision.