Visual modularity

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In cognitive neuroscience, visual modularity is an organizational concept concerning how vision works. The way in which the primate visual system operates is currently under intense scientific scrutiny. One dominant thesis is that different properties of the visual world (colour, motion, form and so forth) require different computational solutions which are implemented in anatomically/functionally distinct regions that operate independently – that is, in a modular fashion (Calabretta & Parisi, 2005).

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[edit] Motion processing

Akinetopsia is an intriguing condition brought about by damage to the extra-striate area hMT+ that renders humans and monkeys unable to perceive motion (Zihl et al., 1983, 1991) and indicates that there might be a “motion centre” in the brain. Of course, such data can only indicate that this area is at least necessary to motion perception, not that it is sufficient; however, other evidence has shown the importance of this area to primate motion perception. Specifically, physiological, neuroimaging, perceptual, electrical- and transcranial magnetic stimulation evidence (Table 1) all come together on the area V5/hMT+. Converging evidence of this type is supportive of a module for motion processing. However, this view is likely to be incomplete: other areas are involved with motion perception, including V1 (Orban et al., 1986; Movshon & Newsome, 1996, Born and Bradley, 2005), V2 and V3a (see Grill-Spector and Malach, 2004) and areas surrounding V5/hMT+ (Table 2). A recent fMRI study put the number of motion areas at twenty-one (Stiers et al., 2006:83). Clearly a stream of diverse anatomical areas subserves motion perception. However, the extent to which this is ‘pure’ is in question: with Akinetopsia come severe difficulties in obtaining structure from motion (Rizzo, Nawrot, Zihl, 1995). V5/hMT+ has since been implicated in this function (Grunewald, Bradley & Andersen, 2002) as well as determining depth (DeAngelis, Cumming and Newsome, 1998). Thus the current evidence suggests that motion processing occurs in a modular stream, although with a role in form and depth perception at higher levels.

Table 1 | Evidence for a “motion centre” in the primate brain

Methodology Finding Source
Physiology (single cell recording) Cells directionally and speed selective in MT/V5 Zeki 1974; Van Essen et al. 1981; Maunsell & Van Essen 1983; Felleman & Kaas 1984
Neuroimaging Greater activation for motion information than static information in MT/V5 Buchel et al., 1998; Culham et al., 1998 ; Stiers et al., 2006
Electrical-stimulation & perceptual Following electrical stimulation of MT/V5 cells perceptual decisions are biased towards the stimulated neuron’s direction preference Salzman et al., 1992
Magnetic-stimulation Motion perception is also briefly impaired in humans by a strong magnetic pulse over the corresponding scalp region to hMT+ Hotson et al., 1994; Beckers and Zeki, 1995; Walsh and Cowey., 1998
Psychophysics Perceptual asynchrony among motion, color and orientation. Moutoussis and Zeki (1997); Viviani & Aymoz (2001)

Table 2 | Evidence for a motion processing surrounding V5

Methodology Finding Source
Physiology (single cell recording) Complex motion involving contraction/expansion and rotation found to activate neurons in medial superior temporal area (MST) Tanaka and Saito, 1989
Neuroimaging Biological motion activated superior temporal sulcus Grossman et al., 2000
Neuroimaging Tool use activated middle temporal gyrus and inferior temporal sulcus Beauchamp, Lee, Haxby and Martin, 2003

[edit] Color processing

Similar converging evidence suggests modularity for color. Beginning with Gowers’ (1888) finding that damage to the fusiform/lingual gyri in occipitotemporal cortex correlates with a loss in color perception (achromatopsia) the notion of a “color centre” in the primate brain has had growing support (e.g. Meadows, 1974; Sacks and Wasserman, 1987; Zeki, 1990; Grüsser and Landis, 1991). Again, such clinical evidence only implicates that this region is critical to color perception and nothing more. Other evidence, however, including neuroimaging (Bartels and Zeki, 2005; Bartels and Zeki, 2000; Stiers et al., 2006) and physiology (Wachtler et al. 2003; Kusunoki, Moutoussis & Zeki, 2006) converges on V4 as necessary to color perception. A recent meta-analysis has also shown a specific lesion common to achromats corresponding to V4 (Bouvier and Engel, 2006). From another direction altogether it has been found that when synaesthetes experience color by a non-visual stimulus V4 is active (Rich et al., 2006; Sperling et al., 2006). On the basis of this evidence it would seem that color processing is modular. However, as with motion processing it is likely that this conclusion is inaccurate. Other evidence shown in Table 3 implicates different areas’ involvement with color. It may thus be more instructive to consider a multistage color processing stream from the retina through to cortical areas including at least V1, V2, V4, PITd and TEO. Consonant with motion perception there appear to be a constellation of areas drawn upon for color perception. In addition, V4 may have a special but not exclusive role. For example, single cell recording has shown only V4 cells respond to the color of a stimuli rather than its waveband, whereas other areas involved with color do not (Wachtler et al. 2003; Kusunoki, Moutoussis & Zeki, 2006).

Table 3 | Evidence against a “color centre” in the primate brain

Other areas involved with color/Other functions of V4 Source
Wavelength sensitive cells in V1 and V2 Livingstone & Hubel, (1984); DeYoe & Van Essen, (1985)
anterior parts of the inferior temporal cortex Zeki & Marini, (1998); Beauchamp et al., (2000)
posterior parts of the superior temporal sulcus (PITd) Conway & Tsao, (2006)
Area in or near TEO Tootell, Nelissen Vanduffel Orban, (2004)
Shape detection Pasupathy, (2006); David, Hayden, Gallant, (2006)
Link between vision, attention and cognition Chelazzi, Miller, Duncan, & Desimone (2001)

[edit] Form processing

Another clinical case that would a priori suggest a module for modularity in visual processing is visual agnosia. The well studied patient DF is unable to recognize or discriminate objects (Mishkin, Ungerleider and Macko, 1983) owing to damage in areas of the lateral occipital cortex (James et al., 2003) although she can see scenes without problem – she can literally see the forest but not the trees (Steeves et al. 2006). Neuroimaging of intact individuals reveals strong occipito-temporal activation during object presentation and greater activation still for object recognition (see Grill-Spector, 2003). Of course, such activation could be due to other processes, such as visual attention. However, other evidence that shows a tight coupling of perceptual and physiological changes (Sheinberg and Logothetis, 2001) suggests activation in this area does underpin object recognition. Within these regions are more specialized areas for face or fine grained analysis (Gauthier, Skudlarski, Gore and Anderson, 2000), place perception (Epstein & Kanwisher, 1998) and human body perception (Downing, Jiang, Shuman and Kanwisher, 2001). Perhaps some of the strongest evidence for the modular nature of these processing systems is the double dissociation between object- and face (prosop-) agnosia (e.g. Moscowitch, Winocur and Behrmann, 1997). However, as with color and motion, early areas (see Pasupathy, 2006 for a comprehensive review) are implicated too lending support to the idea of a multistage stream terminating in the inferotemporal cortex rather than an isolated module.

[edit] Functional modularity

One of the first uses of the term "module" or "modularity" occurs in the influential book "Modularity of Mind" by the Philosopher Jerry Fodor (1983). A detailed application of this idea to the case of vision was published by Pylyshyn (1999), who argued that there is a significant part of vision that is not responsive to beliefs and is "cognitively impenetrable."

Much of the confusion concerning modularity exists in neuroscience because there is evidence for specific areas (e.g. V4 or V5/hMT+) and the concomitant behavioral deficits following brain insult (thus taken as evidence for modularity). In addition, evidence shows other areas are involved and that these areas subserve processing of multiple properties (e.g. V1: see Leventhal et al, 1995) (thus taken as evidence against modularity). That these streams have the same implementation in early visual areas, like V1 is not inconsistent with a modular viewpoint: to adopt the canonical analogy in cognition, it is possible for different software to run on the same hardware. A consideration of psychophysics and neuropsychological data would suggest support for this. For example, psychophysics has shown that percepts for different properties are realized asynchronously (Moutoussis & Zeki 1997, Viviani & Aymoz, 2001). In addition, although achromats experience other cognitive defects (Gegenfurtner, 2003) they do not have motion or form deficits when their lesion is restricted to V4 (Zeki, 2005). Relatedly, Zihl and colleagues’ (1983) Akinetopsia patient shows no deficit to color or object perception (although deriving depth and structure from motion is problematic, see above) and object agnostics do not have damaged motion or color perception, making the three disorders triply dissociable. Taken together this evidence suggests that even though distinct properties may employ the same early visual areas they are functionally independent. Furthermore, that the intensity of subjective perceptual experience (e.g. color) correlates with activity in these specific areas (e.g. V4) (Bartels and Zeki, 2005), the recent evidence that synaesthetes show V4 activation during the perceptual experience of color, as well as the fact that damage to these areas results in concomitant behavioral deficits (the processing may be occurring but perceivers do not have access to the information) are all evidence for visual modularity. Ashlee

[edit] References

Bartels, A & Zeki, S. (2000). The architecture of the human color centre: new results and a review. European Journal of Neuroscience, 12(1), 172-193.

Bartels, A. & Zeki, S. (2005). Brain dynamics during natural viewing conditions - a new guide for mapping connectivity in vivo. NeuroImage, 24(2), 339-349.

Beauchamp, M.S., Haxby, J.V., Rosen, A.C. & DeYoe, E.A.A. (2000). MRI functional case study of acquired cerebral dyschromatopsia. Neuropsychologia, 38, 1170–1179.

Beauchamp, M.S., Lee, K.E., Haxby, J.V., & Martin, A. (2003) FMRI responses to video and point-light displays of moving humans and manipulable objects. Journal of Cognitive Neuroscience, 15, 991-1001.

Beckers, G. & Zeki, S. 1995 The consequences of inactivating areas V1 and V5 on visual motion perception. Brain, 118, 49–60.

Born, R. T. & Bradley, D. C. (2005) Structure and function of visual area MT. Annual Review of Neuroscience, 28,157-89.

Bouvier, S.E. & Engel, S.A. (2006). Behavioral Deficits and Cortical Damage Loci in Cerebral Achromatopsia. Cerebral Cortex, 16(2),183-191.

Büchel, C., Josephs, O., Rees, G. Turner, R., Frith, C. D., & Friston, K. J. (1998). The functional anatomy of attention to visual motion. A functional MRI study. Brain, 121(7), 1281-94.

Calabretta, R. & Parisi, D. (2005). Evolutionary Connectionism and Mind/Brain Modularity. In W. Callabaut & D. Rasskin-Gutman , Modularity. Understanding the development and evolution of complex natural systems (pp. 309-330). Cambridge, MA: MIT Press.

Chelazzi, L., Miller, E. K., Duncan, J., & Desimone, R. (2001). Responses of neurons in macaque area V4 during memory-guided visual search. Cerebral Cortex, 11, 761-772.

Conway, B.R., Tsao, D.Y. (2006). Color architecture in alert macaque cortex revealed by fMRI. Cerebral Cortex, 16, 1604–1613.

Culham, J.C., Brandt, S.A., Cavanagh, P., Kanwisher, N.G., Dale, A.M., & Tootell, R.B.H. (1998) Cortical fMRI activation produced by attentive tracking of moving targets. Journal of Neurophysiology, 80, 2657–2670.

DeAngelis, G.C., Cumming, B.G., & Newsome, W.T. (1998) A new role for cortical area MT: The perception of stereoscopic depth. Nature, 394, 677-680.

DeYoe, E.A. & Van Essen, D.C. (1985). Segregation of efferent connections and receptive field properties in visual area V2 of the macaque. Nature, 317, 58−61.

Downing, P., Jiang, Y., Shuman, M., & Kanwisher, N. (2001). A Cortical Area Selective for Visual Processing of the Human Body. Science, 293, 2470-2473.

Epstein, N., & Kanwisher, N. (1998). A cortical representation of the local visual environment. Nature, 392(6676), 598-601.

Felleman, D.J. & Kaas, J.H. (1984). Receptive field properties of neurons in middle temporal visual area (MT) of owl monkeys. Journal of Neurophysiology, 52, 488-513.

Fodor, J. A. (1983). The Modularity of Mind: An Essay on Faculty Psychology. Cambridge, Mass.: MIT Press, a Bradford Book.

Gauthier, I., Skudlarski, P., Gore, J. C., & Anderson, A. W. (2000). Expertise for cars and birds recruits brain areas involved in face recognition. Nature Neuroscience, 3(2), 191-197.

Gegenfurtner, K.R. (2003) Cortical mechanisms of color vision. Nature Reviews Neuroscience, 4, 563-572.

Gowers, W. (1888) A manual of diseases of the brain. London: J. & A. Churchill.

Grill-Spector, K. & Malach, R. (2004). The human visual cortex. Annual Review of Neuroscience, 7, 649-677.

Grill-Spector, K. (2003). The neural basis of object perception. Current Opinion in Neurobiology, 13(3), 399-399.

Grossman, E., Donnelly, M., Price, R., Pickens, D., Morgan, V., Neighbor, G., & Blake, R. (2000) Brain areas involved in perception of biological motion. Journal of Cognitive Neuroscience, 12(5), 711-20.

Grunewald, A, Bradley, D.C., & Andersen, R.A. (2002). Journal of Neuroscience, 22, 6195-6207.

Grüsser, O.J., & Landis, T. (1991) The splitting of ‘‘I’’ and ‘‘me’’: Heautoscopy and related phenomena. In: Visual agnosias and other disturbances of visual perception and cognition. Amsterdam: MacMillan: 297–303.

Hotson, J., Braun, D., Herzberg, W., & Boman, D. (1994). Transcranial magnetic stimulation of extrastriate cortex degrades human motion direction discrimination. Vision Research, 34(16), 2115-23.

Kusunoki, M., Moutoussis, K., Zeki, S. (2006) Effect of background colors on the tuning of color-selective cells in monkey area v4. Journal of Neurophysiology, 95(5), 3047-3059.

Leventhal, A.G., Thompson, K.G., Liu, D., Zhou, Y., & Ault, S.J. (1995). Concomitant sensitivity to orientation, direction, and color of cells in layers 2, 3, and 4 of monkey striate cortex. Journal of Neuroscience, 15, 1808–1818.

Livingstone, M.S. & Hubel, D.H. (1984). Anatomy and physiology of a color system in the primate visual cortex. Journal of Neuroscience, 4, 309–356.

Maunsell, J.H.R. & Van Essen, D.C. (1983). Functional properties of neurons in middle temporal visual area of the macaque. Selectivity for stimulus direction, speed and orientation. Journal of Neurophysiology, 49, 1127-1147.

Meadows, J. C. (1974) Disturbed perception of colours associated with localized cerebral lesions. Brain, 97, 615–632.

Mishkin, M., Ungerleider, L., & Macko, K. (1983), Object vision and spatial vision: Two cortical pathways. Trends in Neuroscience, 6, 414-417.

Moscovitch, M., Winocur, G., Behrmann, M. (1997). What is special about face recognition? Nineteen experiments on a person with visual object agnosia and dyslexia but normal face recognition. Journal of Cognitive Neuroscience, 9, 555–604.

Moutoussis, K., & Zeki, S. (1997). A direct demonstration of perceptual asynchrony in vision. Proceedings of the Royal Society of London. Series B, 264(1380), 393–399.

Movshon, J.A., & Newsome, W.T. 1996. Visual response properties of striate cortical neurons projecting to area MT in macaque monkeys. Journal of Neuroscience, 16(23), 7733-41.

Orban, G.A., Kennedy, H., & Bullier, J. (1986). Velocity sensitivity and direction selectivity of neurons in areas V1 and V2 of the monkey: influence of eccentricity. Journal of Neurophysiology, 56(2), 462-80.

Pasupathy, A. (2006). Neural basis of shape representation in the primate brain. In: Visual Perception (Part 1): Progress in Brain Research, Martinez-Conde, Macknik, Martinez, Alonso & Tse, Eds.

Pylyshyn, Z. W. (1999). Is vision continuous with cognition? The case for cognitive impenetrability of visual perception. Behavioral and Brain Sciences, 22(3), 341-423.

Rich, A.N., Williams, M.A., Puce, A., Syngeniotis, A., Howard, M.A., McGlone, F., Mattingley, J.B. (2006). Neural correlates of imagined and synaesthetic colours. Neuropsychologia, 44(14), 2918-25.

Rizzo, M., Nawrot, M., & Zihl, J. (1995) Motion and shape perception in cerebral akinetopsia. Brain, 118,1105-27.

Sacks, O., & Wasserman, R. L. (1987). The painter who became color blind. New York Review of Books, 34, 25-33.

Salzman, C.D., Murasugi, C.M., Britten, K.H., & Newsome, W.T. (1992) Microstimulation in visual area MT: effects on direction discrimination performance. Journal of Neuroscience, 12, 2331-2356.

Sheinberg, D.L., & Logothetis, N. K. (2001). Noticing Familiar Objects in Real World Scenes: The Role of Temporal Cortical Neurons in Natural Vision. Journal of Neuroscience, 21(4), 1340 – 1350.

Sperling, J.M., Prvulovic, D., Linden, D.E., Singer, W., & Stirn, A. (2006). Neuronal correlates of colour-graphemic synaesthesia: an fMRI study. Cortex, 42(2), 295-303

Steeves, J.K.E., Culham, J.C., DuChaine, B.C., C. Cavina Pratesi, Valyear, K., Schindler, I., Humphrey, G.K., Milner, A.D. & Goodale, M.A. (2006). The fusiform face area is not sufficient for face recognition: evidence from a patient with dense prosopagnosia and no occipital face area. Neuropsychologia, 44(4), 596-609.

Stephen V. David, S.V., Hayden, B.Y., & Gallant, J.L (2006) Spectral Receptive Field Properties Explain Shape Selectivity in Area V4. Journal of Neurophysiology, 96, 3492-3505.

Stiers, P., Peeters, R., Lagae, L., Van Hecke, P., & Sunaertc, S. (2006) Mapping multiple visual areas in the human brain with a short fMRI sequence. NeuroImage, 29, 74 – 89.

Tanaka, K. & Saito, H.A. (1989) Analysis of motion of the visual field by direction, expansion/contraction, and rotation cells clustered in the dorsal part of the medial superior temporal area of the macaque monkey. Journal of Neurophysiology, 62, 626–641.

Tootell, R., Nelissen, K., Vanduffel, W., & Orban, G. (2004). Search for color 'center(s)' in macaque visual cortex. Cerebral Cortex, 14, 353-363

Van Essen D.C., Maunsell, J.H.R., & Bixby, J.L. (1981). The middle temporal visual area in the macaque: myeloarchitecture, connections, functional properties and topographic organization. Journal of Comparative Neurology, 199, 293–326.

Viviani, P., & Aymoz, C. (2001). Color, form and movement are not perceived simultaneously. Vision Research, 41(22), 2909–2918.

Wachtler, T., Sejnowski, T. J., & Albright, T. D. (2003) Representation of color stimuli in awake macaque primary visual cortex. Neuron, 37, 681–691.

Wade, A.R. & Wandell B.A. (2002). Chromatic Light Adaptation Measured using Functional Magnetic Resonance Imaging. Journal of Neuroscience, 22(18):8148-8157.

Walsh, V., & Cowey, A. (1998). Magnetic stimulation studies of visual cognition. Trends in Cognitive Sciences, 2, 103–110.

Zeki S. (2005). The Ferrier Lecture 1995 behind the seen: The functional specialization of the brain in space and time. Philos. Trans. R. Soc. Lond. B. Biol. Sci., 360, 1145-83.

Zeki, S. (1990) Parallelism and functional specialization in human visual cortex. Quant. Biol. 55, 651–661.

Zeki, S. M. (1974) Functional organization of a visual area in the posterior bank of the superior temporal sulcus of the rhesus monkey. Journal of Neurophysiology, 236, 549–573.

Zeki, S.M. & Marini, L (1998). Three cortical stages of color processing in the human brain. Brain, 121, 1669–1685.

Zihl, J., von Cramon D., Mai, N., & Schmid, C. (1991). Disturbance of movement vision after bilateral posterior brain damage. Further evidence and follow up observations. Brain, 114, 2235–52.

Zihl, J., von Cramon, D., & Mai, N. (1983). Selective disturbances of movement vision after bilateral brain damage. Brain, 106, 313–40.

[edit] See also