Visual cortex

Visual cortex is the term applied to both the primary visual cortex (also known as striate cortex or "V1") and upstream visual cortical areas also known as extrastriate cortical areas (V2, V3, V4, V5). The primary visual cortex is anatomically equivalent to Brodmann area 17, or BA17. Brodmann areas are based on a histological map of the human brain created by Korbinian Brodmann.

Introduction

The primary visual cortex, V1, is the koniocortex (sensory type) located in and around the calcarine fissure in the occipital lobe. It is the one that receives information directly from the lateral geniculate nucleus.To this have been added later as many as thirty interconnected (secondary or tertiary) visual areas. At the present time there is fair agreement for only 3 of these areas, V2, V3 and MT (aka V5).

The first cortical visual area, transmits information to two primary pathways, called the ventral stream and the dorsal stream:

The ventral stream begins with V1, goes through Visual area V2, then through Visual area V4, and to the inferior temporal lobe. The ventral stream, sometimes called the "What Pathway", is associated with form recognition and object representation. It is also associated with storage of long-term memory.

The dorsal stream begins with V1, goes through Visual area V2, then to Visual area V3, Visual area MT (also known as V5) and to the inferior parietal lobule. The dorsal stream, sometimes called the "Where Pathway" or the "How Pathway", is associated with motion, representation of object locations, and control of the eyes and arms, especially when visual information is used to guide saccades or reaching.

The dichotomy of the dorsal/ventral pathways (also called the "what/where" or "action/perception" streams) was proposed (among others) by Goodale and Milner (1992) and is still contentious among vision scientists and psychologists. It is probably an over-simplification of the true state of affairs in visual cortex. It is based on the findings that visual illusions such as the Ebbinghaus illusion may distort judgements of a perceptual nature, but when the subject responds with an action, such as grasping, no distortion occurs. However, recent work (Franz et al, 2005) suggests that the both the action and perception systems are equally fooled by such illusions.

Neurons in the visual cortex fire action potentials when visual stimuli appear within their receptive field. A receptive field is a small region within the entire visual field. Any given neuron only responds to a subset of stimuli within its receptive field. This property is called tuning. In the earlier visual areas, neurons have simpler tuning. For example, a neuron in V1 may fire to any vertical stimulus in its receptive field. In the higher visual areas, neurons have complex tuning. For example, in the inferior temporal cortex (IT), a neuron may only fire when a certain face appears in its receptive field.

The visual cortex receives its blood supply primarily from the calcarine branch of the posterior cerebral artery.

Primary visual cortex (V1)

The primary visual cortex is the best studied visual area in the brain. It is the part of the cerebral cortex that is responsible for processing visual stimuli. It is the simplest, earliest cortical visual area. It is highly specialized for processing information about static and moving objects and is excellent in pattern recognition.

The functionally defined primary visual cortex is approximately equivalent to the anatomically defined striate cortex. The name "striate cortex" is derived from the stria of Gennari, a distinctive stripe visible to the naked eye that represents myelinated axons from the lateral geniculate body terminating in layer 4 of the gray matter.

The primary visual cortex is divided into six functionally distinct layers, labelled 1 through 6. Layer 4, which receives most visual input from the lateral geniculate nucleus (LGN), is further divided into 4 layers, labelled 4A, 4B, 4Cα, and 4Cβ. Sublamina 4Cα receives most magnocellular input from the LGN, while layer 4Cβ receives input from parvocellular pathways.

Function

V1 has a very well-defined map of the spatial information in vision. For example, in humans the upper bank of the calcarine sulcus responds strongly to the lower half of visual field (below the center), and the lower bank of the calcarine to the upper half of visual field. Conceptually, this retinotopy mapping is a transformation of the visual image from retina to V1. The correspondence between a given location in V1 and in the subjective visual field is very precise: even the blind spots are mapped into V1. Evolutionally, this correspondence is very basic and found in most animals that possess a V1. In human and animals with a fovea in the retina, a large portion of V1 is mapped to the small, central portion of visual field, a phenomenon known as cortical magnification. Perhaps for the purpose of accurate spatial encoding, neurons in V1 have the smallest receptive field size of any visual cortex regions.

Individual V1 neurons have strong tuning to a small set of stimuli. That is, the neuronal responses can discriminate small changes in visual orientations, spatial frequencies and colors. Furthermore, individual V1 neurons in human and animals with binocular vision have ocular dominance, namely tuning to one of the two eyes. In V1, and primary sensory cortex in general, neurons with similar tuning properties tend to cluster together as cortical columns. David Hubel and Torsten Wiesel proposed the classic ice-cube organization model of cortical columns for two tuning properties: ocular dominance and orientation. However, this model cannot accommodate the color, spatial frequency and many other features to which neurons are tuned. The exact organization of all these cortical columns within V1 remains a hot topic of current research.

Current consensus seems to be that V1 consists of tiled sets of selective spatiotemporal filters. In the spatial domain, the functioning of V1 can be thought of as similar to many spatially local, complex Fourier transforms. Theoretically, these filters together can carry out neuronal processing of spatial frequency, orientation, motion, direction, speed (thus temporal frequency), and many other spatiotemporal features. Experiments of V1 neurons substantiate these theories, but also raise new questions.

The visual information relayed to V1 is not coded in terms of spatial (or optical) imagery, but rather as the local contrast. As an example, for an image comprising half side black and half side white, the divide line between black and white has strongest local contrast and is encoded, while few neurons code the brightness information (black or white per se). As information is further relayed to subsequent visual areas, it is coded as increasingly non-local frequency/phase signals. Importantly, at these early stages of cortical visual processing, spatial location of visual information is well preserved amid the local contrast encoding.

Current research

Research on the primary visual cortex can involve recording action potentials from electrodes within the brain of cats, ferrets, mice, or monkeys, or through recording intrinsic optical signals from animals or fMRI signals from human and monkey V1.

One recent discovery about V1 is that signals measured by fMRI show very large attentional modulation. This result strongly contrasts with macaque physiology research showing very small changes (or no changes) in firing associated with attentional modulation.

Other current work on V1 seeks to fully characterize its tuning properties, and to use it as a model area for the canonical cortical circuit.

Lesions to primary visual cortex usually lead to a scotoma, or hole in the visual field. Interestingly, patients with scotomas are often able to make use of visual information presented to their scotomas, despite being unable to consciously perceive it. This phenomenon, called blindsight, is widely studied by scientists interested in the neural correlate of consciousness.

V2

Visual area V2 is the second major area in the visual cortex, and first region within the visual association area. It receives strong feedforward connections from V1 and sends strong connections to V3, V4, and V5. It also sends strong feedback connections to the V1.

Anatomically, V2 is split into four quadrants, a dorsal and ventral representation in the left and the right hemispheres. Together these four regions provide a complete map of the visual world. Functionally, V2 has many properties in common with V1. Cells are tuned to simple properties such as orientation, spatial frequency, and color. The responses of many V2 neurons are also modulated by more complex properties, such as the orientation of illusory contours and whether the stimulus is part of the figure or the ground (Qiu and von der Heydt, 2005).

Recent research has shown that V2 cells show a small amount of attentional modulation (more than V1, less than V4), are tuned for moderately complex patterns, and may be driven by multiple orientations at different subregions within a single receptive field.

V3

Visual area V3 is a part of the dorsal stream, receiving inputs from V2 and primary visual areas. It projects to the posterior parietal cortex. It may be anatomically located in Brodmann area 19. Debate exists as to whether there are also adjacent areas 3A and 3B. Recent work with fMRI has suggested that area V3/V3A may play a role in the processing of global motion (Braddick, 2001).

V4

Visual area V4 is one of the visual areas in the extrastriate visual cortex of the macaque monkey. It is located anterior to V2 and posterior to visual area PIT. It comprises at least four regions (left and right V4d, left and right V4v), and some groups report that it contains rostral and caudal subdivisions as well. It is unknown what the human homologue of V4 is, and this issue is currently the subject of much scrutiny.

V4 is the third cortical area in the ventral stream, receiving strong feedforward input from V2 and sending strong connections to the posterior inferotemporal cortex (PIT). It also receives direct inputs from V1, especially for central space. In addition, it has weaker connections to V5 and visual area DP (the dorsal prelunate gyrus).

V4 is the first area in the ventral stream to show strong attentional modulation. Most studies indicate that selective attention can change firing rates in V4 by about 20%. A seminal paper by Moran and Desimone characterizing these effects was the first paper to find attention effects anywhere in the visual cortex (see .

Like V1, V4 is tuned for orientation, spatial frequency, and color. Unlike V1, it is tuned for object features of intermediate complexity, like simple geometric shapes, although no one has developed a full parametric description of the tuning space for V4. Visual area V4 is not tuned for complex objects such as faces, as areas in the inferotemporal cortex are.

The firing properties of V4 were first described by Semir Zeki in the late 1970s, who also named the area. Before that, V4 was known by its anatomical description, the prelunate gyrus. Originally, Zeki argued that the purpose of V4 was to process color information. Work in the early 1980s proved that V4 was as directly involved in form recognition as earlier cortical areas. This research supported the Two Streams hypothesis, first presented by Ungerleider and Mishkin in 1982.

Recent work has shown that V4 exhibits long-term plasticity, encodes stimulus salience, is gated by signals coming from the frontal eye fields, shows changes in the spatial profile of its receptive fields with attention, and encodes hazard functions.

V5

Visual area V5, also known as visual area MT (middle/medial temporal), is a region in the extrastriate cortex that appears to process complex visual motion stimuli. It contains many neurons selective for the motion of complex visual features (line ends, corners). Much work has been carried out on this region as it appears to integrate local visual motion signals into the global motion of complex objects (Movshon et al, 1985).

There is still much controversy over the exact form of the computations carried out in area MT (Wilson et al, 1992) and some research suggests that feature motion is in fact already available at lower levels of the visual system such as V1 (Tinsley et al, 2003).

References

Braddick, OJ, O'Brian, JMD, et al (2001) Brain areas sensitive to visual motion. Perception, 30, 61-72
Franz VH, Scharnowski F, Gegenfurtner (2005) Illusion effects on grasping are temporally constant not dynamic. J Exp Psychol Hum Percept Perform. 31(6), 1359-78
Goodale & Milner (1992) Separate pathways for perception and action. Trends in Neuroscience, 15, 20-25.
Peters, Alan (ed), and Kathleen S. Rockland (ed). 1994. Cerebral Cortex: Primary Visual Cortex in Primates v. 10 (Cerebral Cortex). Kluwer Academic / Plenum Publishers
Peters, Alan (ed) and Bertram Payne (ed). 2001. The Cat Primary Visual Cortex Academic Press.
Moran & Desimone. Selective Attention Gates Visual Processing in the Extrastriate Cortex. Science 229(4715), 1985.
Tinsley, C.J., Webb, B.S., Barraclough, N.E., Vincent, C.J., Parker, A., & Derrington, A.M. (2003). The nature of V1 neural responses to 2D moving patterns depends on receptive-field structure in the marmoset monkey. J Neurophysiol, 90 (2), 930-937.
Qiu FT, von der Heydt R. Figure and ground in the visual cortex: v2 combines stereoscopic cues with gestalt rules. Neuron. 2005 Jul 7;47(1):155-66.
Movshon, J.A., Adelson, E.H., Gizzi, M.S., & Newsome, W.T. (1985). The analysis of moving visual patterns. In: C. Chagass, R. Gattass, & C. Gross (Eds.), Pattern recognition mechanisms (pp. 117-151), Rome: Vatican Press.
Wilson, H.R., Ferrera, V.P., & Yo, C. (1992). A psychophysically motivated model for two-dimensional motion perception. Vis Neurosci, 9 (1), 79-97.

External links

The Primary Visual Cortex by Matthew Schmolesky
Architecture of the Visual Cortex, by David Hubel
For Neuroanatomy of the striate area 17 visit BrainInfo
For Neuroanatomy and Internal Structure of Brodmann area 17 in guenon visit BrainInfo
Histochemical Images of the Visual Cortex
Computational Maps in the Visual Cortex
Simulator for computational modeling of visual cortex maps

Gourt Home::Gourt :: Visual cortex