myDoes the Brain Have So Many Visual Areas?
Jon H. Kaas Department of Psychology Vanderbilt University, Nashville Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021
Introduction vision, but there are varying opinions about the nature of these different aspects, and about what is gained by The visual system of an advanced mammal, such as a increasing the numbers of visual areas. The present paper macaque monkey, includes a number of subcortical and considers what is a visual area, how species vary in cortical centers (see Kaas & Huerta, 1988 for review). The numbers of visual areas, and the possible advantages of retina projects to the suprachiasmatic nucleus, the pregen- having larger numbers of visual areas. iculate nucleus, the lateral geniculate nucleus, nuclei of the accessory optic system, the pretectal nuclei, and the 1. WhatLaVLualArea? superior colliculus. Most of the very large pulvinar com- BrodmaM (1909) regarded cortical areas as the “organs” plex, which includes at least 7 or 8 nuclei, is also involved of the brain, with specific functions or sets of functions. in vision. Parts of the reticular nucleus, the basal ganglia, Because of their functional distinctiveness,the “organs”of pons, and cerebellum are predominately visual in func- the brain were expected to differ in histological structure, tion, and the parabigeminal nucleus and oculomotor and Brodmann used architectural differences in the brains nuclei of the brain stem are visual centers. But much of of humans and a wide-range of other mammils to parcel visual processing, especially processing related to con- cortex into areas of presumed functional significance. scious aspects of vision, occurs in visual cortex, where Eight decades of subsequent research support Brodmann’s some 15-30 visual areas partikipate. An obvious question, assumption that cortex is sharply divided into a mosaic of given this multiplicity, is why so many areas? functionally distinct areas or fields. However, the architec- Of course an obvious question is not often new. tonic method, when used by itself, is often unreliable. Cowey (198l), for example, titled a paper ‘Why are there Because the architectonic method and other ap- so many visual areas?” Kaas (1982) subtitled a paper “Why proaches all have the potential for error, cortical areas are do sensory systems have so many subdivisions?”, and most reliably defined by multiple criteria. If cortical areas Barlow (1986) recently asked “Why have multiple cortical are functionally distinct subdivisions of the brain, areas are areas?”. Cowey (1981) noted that “the answer to the likely to differ along a number of parameFers including question . . . is not clear” and “that is why it is worth histological structure, connections, and neuron properties discussing.” The general consensus is that the different (see Kaas, 1982). In addition, areas in sensory systems visual areas are specialized to mediate different aspects of often systematically represent a sensory surface. If a region
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Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 terpreted so that parts of areas can be considered to be A. Proposed subdlvlslons of cortex In squirrels. complete areas, a single area can be incorporated into several different fields, several fields can be incorrectly n combined (e.g., borders misidentified), and identified subdivisions can be incorrectly homologized across spe- cies (see Kaas, 1982). Brodmann, because of the extent of his studies, and the number of species considered, has had great and lasting impact, even though his brain maps correctly identified only a few sensory areas of the cortex. For visual cortex, Brodmann usually, but not always, Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 identified the primary field, V-I (his area 17), sometimes located the second field, V-I1 (his area 181, but failed to identlfv any of the other of the currently recognized visual fields (with the possible exception of “area 19as V-I11 in 8. Classical subdlvklons of Brodmann(’09). cats). In proposing subdivisions of cortex in squirrels (Fig. lB), Brodmann (1909) correctly identified part of the primary field, V-I or area 17, but incorrectly identified the less developed medial portion of area 17 that is devoted to monocular vision as the second field, area 18 W-11). No primary somatosensory field (area 3b) or primary auditory - field (area 41) was found, and only part of the primary motor field (area 4) was identified. Most other proposed subdivisionshave little relationship to present understand- ings of cortical organization. The point is not to devalue the contributions of Brodmann and other earlier investiga- tors, but to stress the potential for error when only one method is used to subdivide the brain. The older, highly inaccurate maps are part of our scientific legacy, but Figure 1. Current (A) and classical
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Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 further investigation can and should mod* and improve the map. Similarly, in other mammals such as cats and I HEDGEHOG various monkeys, the evidence for proposed subdivisions varies area by area.
2. Are There! Many Visual Areas? The question of number of visual areas is part of a larger issue of how many areas of cortex exist. Until recently, one could be a “lumper”or a “divider”and propose that there 1c-Olfoclor are few or many brain areas, since there was no unequivo- Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 cal way to evaluate the various proposals based on architectonic appearance. The two major contributors to theories of cortical organization, Brodmann (1909) and von Economo (1929) agreed that the number is species variable, an increase represents an advance in evolution, and that the human brain has on the order of 50 or more areas. Other estimates for the human brain were of over 200 areas. Lashley, in contrast, argued that there was little Figure 2. Proposed areas of neomrtex in hedgehogs, an reason to believe that rats and humans differ in number of insecrtvore with proportionately little neomrtex and few fields, and that the brains of both contain about ten areas cortical areas. pnlmary (V-I) and secondary (V-II) visual areas, primary (S-0 and secondary @II) (e.g., Lashley & Clark, 1946). We now have strong evi- areas, amotorfield(M-I)andandtoryregionhavebeen dence that primitive mammals with small brains and identified, and there is little room for additional areas. limited behavioral range have few cortical areas, perhaps Whiktempmalcortexcaudaltotheauditoryregionmay be visual, the hedgehog ap to have only a few (3-5) as few as 10-15, while advanced mammals with large visual areas. Ad~moLofthe brain. Modifid brains and considerable behavioral range have many from Kaas, 1987. cortical areas (50-100 or more). The common European hedgehog, an insectivore, is an example of a mammal with very few cortical areas of neocortex can be easily removed, flattened between (Figure 2). The brain is small, and it has very little glass plates, sectioned parallel to the surface, and stained neocortex, no more than a cap on the rest of the forebrain to reveal myeloarchitectonic fields that have been previ- and about the same amount as the first mammals, as ously related to sensory representations (Figure 3; see suggested from endocasts of the brain cavity. In hedge- Kaas et al., 1989b; Krubitzeret al., 1986,for review). Again, hogs, microelectrode recordings and stimulations have the conclusion is clear. Mice have few cortical areas, on the demonstrated first and second visual areas, motor cortex, order of 10-15, and at best 3-5 visual areas (Wagor et al., first and second somatosensory areas, and an auditory 1980; however see Montero et al., 1973). region (see has, 1987a). The auditory region may contain Behaviorally advanced mammals with larger brains two or more fields, there is mom in temporal cortex for one certainly have more fields. The best examples come from or two additional visual fields, a taste area remains to be the domestic cat, several species of New World monkeys, identified, a supplementary motor field may exist medi- and Old World macaque monkeys where considerableex- ally, there appear to be several orbitofrontal and midline perimental evidence has been gathered (see Kaas, 198% limbic fields, and transitional cortex is found along the for review). Cats appear to have as many as 10-15 visual rhinal fissure. Altogether, hedgehogs get along just fine areas, five somatosensoryareas, and at least eight auditory with probably 10-15 cortical areas, as Lashley supposed areas. Monkeys also have large numbers of cortical areas, for all mammals. Of course hedgehogs do this without especially visual areas, and it is probable that higher pri- being tremendously flexible in behavior. They wander mates including humans have even more. about appearing to find carrion and other helpless food Much of our research on the organization of cortex has largely by accident, and escape danger by rolling into a been on the relatively small-brained New World monkey, ball of spines. Thus, the Greek poem from about 680-640 the night or owl monkey (Aotus). In this monkey, the B.C. “The fox knows many tricks, the hedgehog only one. cortex can be removed and flattened, much as in the One good one!” mouse, by placing a cut in primary visual cortex (area 17) The upper limit on the number of cortical areas in so it can spread out (Figure 4). In this form, all of neocortex hedgehogs can be deduced from the strong evidence for can be viewed as a single, flat sheet with only slight the location and existence of some areas and the fact that distortions produced by flattening. Fiber stains and other there isn’t much cortex in addition to these fields. Another histological procedures provide landmarks sq that experi- example is the cortex of the common mouse, where we mentally determined fields can be superimposed on the have some concept of cortical organization based on flattened cortex with considerable accuracy. experimental data from mice and rats. The small amount The caudal half of the cortex in owl monkeys contains
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Piriform Cortex
Figure 3. Some of the suixlivhsions of neocortex in a mouse. The drawing is based on architectonic distribu- tions apparent in cortex that has been separated &om the biain, unfolded, flattened between glas!3 plates, and cut parallel to the surke. sOmatosemmy5elds (SI or pri- marysomatosemmycoitex,s-IIorsecondarysomatosen- soiycortexandWor~-ventral),thevisual5e~(V- 1or primary visual, V-II or secondary visual), motor 5eld (M-I),and auditory fields (primary or AI, mstd or R, temporal anterior or TA) have been identifled in micro- electrode mapping studies where results were +elated to architestwe in rodents (see Krubitzer et at, 1986;Luethke, et aL, 1988; Kaas et aL, 1989 for reviews). Because of the fla- cortex of the medial wall including limbic cortex is to the top and parts of piriformcortex are at the bottom. The olEactorybuIbs are miss@& Rostralis left.
a large number of visual areas (see Kaas, 1986 and 1989a Figure 4. coitical areas superimposed on an outline of a for review). The experimental support is extensive for the sectionfromcortexthathasbeenremoved, flattenedand existence, location and extent of the primary field (V-I or cut parallel to the surhce for aNew World owl monkey. A area 171, the secondary field (V-I1 or area 181, and the dorsolateral view of the brain with reference areas is on the upper rlght. The opened lateral (Sylvian) sulcus and middle temporal visual area (M'l9. Other proposed subdi- superior temporal sulcus (S'I'S) are markedwith dashed visions have less compelling and varying amounts of lines. The co callosum (CC) and limbic cortex have experimental support. Thus it is likely that the present beenUllfOZfrom the medialwallof the cerebralhemi- sphere.Thevisual,somatic,auditoiyandmotorareasare scheme will be modified, qnd given the history of progress &om published reports on owl monkeys (see Kaas, 1982; in this type of research, several of the larger fields will 1988 for review and references). A dashed line on the prove to be composed of more than one visual area. outline of the intact brain (upper rlght) and the shaded region on the flattened cortex (below) indicates the ap However, there is now evidence for about 15 visual areas proximate extent ofvisualcortex. This inchlde!s primary in caudal neocortex and at least 3 visuomotor areas in the (V-I)and secondary (V-II) 5elds, the middle temporal frontal lobe. Similar numbers of visual areas have been proposed for macaque monkeys, where different groups the dorsomedlat afea (DM), the medial area 8,theven- of investigators have produced somewhat different sum- tropostedorcVp)andvenrrrwnterlor(VA)areas,thesupe- maries and use partially different terminologies (Figure 5; rim temporal area (ST), the area of the fundus of the see Van Essen, 1985; Desimone L? Ungerleider, 1986). The clear conclusion, however, is that these advanced mam- mals, cats and monkeys, have on the order of 15-30 visual areas. theeyeregionofthesupplementaryraotorarea 124 Journal of Cognitive Neuroscience Volume 1, Number 2 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 luman Area I7 = 3000mm2 A. Van Essen, 1985 Uacaque = 1200 Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 Mouse = 4.5 profiles (see Baker et al., 1981; Zeki, 1978). The point of disagreement is what these differences in responsiveness suggest for theories of processing in the visual system. One view is that neurons that are apparently responding best to a particular stimulus feature are in fact signaling that the feature is present. Neurons detect stimulus features and by doing so participate in the function of object identification. An extension of this view is that greater specificity occurs B. Ungerleider and Desimone, 1986 over stages of processing so that at higher stations only a small subset of neurons are activated, and their activity signals the presence of a specific object, such as a face (see Barlow, 1972). The obvious problem with this line of reasoning is that the proposal ultimately seems unwork- able because too many classes of very specific neurons would be needed at the highest levels. Others hold that neurons, though responding best to certain stimulus features, are encoding multidimensional properties of visual stimuli (e.g., Optican & Richmond, 1987). Accord- ing to some holding this view (e.g., Desimone et al., 1989, the response characteristicsof neurons become less spedfic and more abstract in reflecting stimulus features in the higher stages of processing. According to this concept, large numbers of neurons participate in all perceptual tasks and individual neurons are active during many perceptual tasks. In support of this view, network models have demonstrated that problems can be solved when activity is distributedacross an array of elements and when the nature of the task is not obvious from the activity profiles of the individual elements (e.g., Andersen & Zipser, 1988, Hopfield & Tank, 1986). Remarkably, the same sorts of response profiles for neurons in different areas of visual cortex have been used as evidence for both types of theories. In ,one view, the "best response" is the key, and other responsiveness is "noise." In the other view, all responses of neurons, even at low rates, are significant. While the basic issue is not 125 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 easily resolved, Marrocco (1986) has critically reviewed the evidence for what he terms “attribute-specificareas” with attribute-specific neurons, and provides guidelines for evaluating visual areas for specificity. Marrocco (1986) concludes that the weight of the evidence is against the theory that neuronsjn each field are devoted to a single stimulus attribute (as suggested in Figure 7). 4. WhyNotHaveJustOneBigVisualArea? Reptiles appear to get along with only one visual “area”in Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 dorsal or general cortex (neocortex; see Kaas, 1987b; Ulinski and Mulligan, 19871, with much of the visual pro- cessing being done in the optic tectum (superior collicu- lus) of the midbrain. The optic tectum is extremelywell dif- ferentiated into layers in some species, but the structure is not subdivided horizontally into a number of areas. Mammals appear to have addressed the problem of increasing visual abilities largely by increasing the number of visual areas, rather than the size of a single field such as V-I. An increase in number rather than just size isn’t a result of some unknown factor that limits size. Area 17 varies greatly in size across species, with larger brains having a larger area 17. For example, area 17 can be as much as lo00 times larger in the human than the mouse brain (Figure 6j, so areas can be increased greatly in size. To some extent, some mammals probably do enhance or specialize their visual abilities by enlarging and differ- entiating an existing visual area or areas. An extreme in Figufe7.Oneconceptofse!rialpiocessingindsuat~ specialization where a single visual area is emphasized in maca~wIllonlreys. A-ce OfdsualslffaS @-1- V-5) success- compute and add difkrent fe;rtures (attrib- may be the tarsier, where area 17 is very large, extending utes) of the visual array to result in object vision. The over the caudal third of the cerebral hemisphere and more pro~stressesserialpiocessingandthes~ons differentiated into layers (and sublayers) than any other of vlsualafeas #or the detecclon of stimulus ?ttnlbutes, but does not recognk the known complexityof the system. mammal (e.g., Hassler, 1966; Woolard, 1925). The large M&ed hmYoung, 1978. size and sharp laminar distinctions of area 17 in tarsiers are reminiscent of the optic tectum of highly visual birds, and indeed there may be further similarities in function. evidence for distinct classes of modules is available only Tarsiers are specialized as visual predators (Polyak, 19571, for area 17 and 18 of monkeys. In area 17, there is evidence and need to be extremely proficient in detecting and for separate laminar systems relating to processing infor- tracking prey, but there is little evidence for varied or mation from the parvocellular and magnocellular genicu- complex visual behavior. late layers, and for separate vertical systems for the In a sense, laminar specializations such as that seen in cytochrome oxidase KO) blob and interblob regions, area 17 of tarsiers and the optic tectum of some birds are devoted to different aspects of the parvocellular inputs equivalent to producing more visual areas by stacking (perhaps stimulus orientation and color, respectively, see representations one on top of the other. The potential of Livingstone & Hubel, 1988). In area 18, three types of this method of increasing visual abilities is limited, how- vertical bands of cells, the M stripe, the P stripe, and the ever, by restrictions on the thickness of cortex, which interstripe regions form three fractionated maps of the varies only slightly across species. visual hemifield, each processing a different type of Another way of creating multiple representations information from area 17 (Figure 9; see Livingstone & within a single visual area is to have a mosaic of vertical Hubel, 1988 for review). In principle, the number of frac- arrays of neurons (local processing modules), with each tionated representations within a single visual area could location in visual space repeated in several types of arrays. increase to any number, providing an alternative to Thus, rather than containing a single representation with increasing the number of separately located and internally continuous change across the surface, an area can have coherent visual areas. That the number appearsto be small repetitions and local discontinuities to produce several suggests that there are major disadvantages to increasing fractionated, interdigitated representations, each with its the number of dispersals of functionally distinct process- own functions (see bas, 1989b).To some extent, all visual ing modules within a field. The most obvious disadvantage areas may multiply functions in this way, but dear is that as the number increases, interactions between 126 Journal of Cognitive Neuraecimct Volume I, Number 2 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 in theories of cortical organization (e.g., Hubel & Wiesel, Parietal 1965). Another concept, that of parallel processing, has become increasingly discussed in terms of cortical function. Pathway More recently, the complexities of cortical processing have been described in terms of a network of interconnected areas. These concepts are discussed and related to current information on the interconnections of visual areas below. Sa. serfat Processing Across Visual heaa Serial pro- cessing is certainly an important feature of the visual system. Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 In an overly simple view of visual cortex as a single chain of visual areas, the significance of multiple visual areas is that each area represents a successive step in a serial chain of processing. Such a restricted view of visual processing is no longer common, but it is suggested by some of the terminology in current use. The early and long-standing use of terms such as V-I and V-11, S-I and S-11, and A-I and A-11, implies serial processing (although Woolsey introduced the . terms to indicate order of discovery). The subsequent use of the term “V-111” by Hubel and Wiesel(1965) further implies a serial model, although it wasn’t clear from the reported data on single neurons that serial processing across fields accomplished much more than the serial processing within V-I (simple to complex to hypercomplex). A chain of processing areas also is implied, intended or not, by the more recent use of the terms V1, V2, V3, V4, V5 and V6 for proposed visual areas (e.g., Zeki, 1978; Figure 7). While modules of the same set and between modules of different Ungerleider and Mishkin (1982) argue for the alignment of sets become dependent on longer connections. Thus, the visual areas in two parallel streams (see below), only one problem of interconnections within a field may be the stream is considered important in the recognition of visual major limit on multiplying function within a field (Cowey, stimuli. According to this view, the areas in the object 1981; Kaas, 1977; see below). Thus, limits on cortical thick- recognition system are “primarily organized in a serial ness and therefore numbers of functionally distinct layers, hierarchy,” although parallel processing may occur within and limits on numbers of functionally distinct vertical a field (Desimone et al., 1985). modules mean that major advances in visual processing cannot result by simply increasing the size of one visual 5b. parallel Processing Across Visual Amaa Parallel area. processing streams within visual systems appear to address the problem of the basic slowness of strictly serial systems. 5. Concepts of How Multiple Areas are Modern views of parallel processing in the mammalian Jlltel-COMeCted visual system stem from the discoveries that three broad In the classical view of the visQal system, there was a categories of ganglion cells of the retina of cats, the X, Y, and simple hierarchy of only two or three functionally distinct W cells, project in parallel to the lateral geniculate nucleus subdivisions of cortex (see Menenich & Kaas, 1980 for where the inputs remain largely segregated and project review). Thus, a primary “visuosensory”area (area 17 or separately to cortex. One hypothesis for cats is that V-I, V- striate cortex) activated a secondary “visuopsychic”area I1 and V-111, rather than being successive stages in a hierar- (Bolton, 1900, Campbell, 1905) divided into two sequen- chy, are three end targets for the parallel pathways, with V- tial bands, areas 18 and 19 of BrodmaM (1909) or the I being devoted to X cells, V-I1 devoted to Y cells, and V-111 parastriate and peristriate areas of Elliot-Smith (1906). devoted to W cells (Stone et al., 1979). In primates, where Visuopsychic cortex then fed into bimodal or multimodal the W (koniocellular) cell system is typically reduced, and association cortex (“interpretive cortex”). Even relatively the geniculate projection is almost exclusively restricted to recent proposals for the organization of visual cortex in V-I (see Kaas & Huerta, 19881, there is evidence instead for humans added to these early views only by allowing parallel processing of X (parvocellular) and Y (magnocellu- several functional subdivisions of interpretive cortex (e.g., lar) cell information within V-I and V-11 (Figure 9, see Kaas, Konorski, 1967). For mammals with large numbers of 1986; Livingstone & Hubel, 1988). In addition, Ungerleider visual areas, these early to more recent views are obviously and Mishkin (1982) present evidence for a divergence of too simple (see Figures 4 & 5). Yet, the concept of serial outflow from V-I into two parallel hierarchies of areas, with processing along a chain of visual areas remains important one sequence of fields ending in the temporal lobe and 127 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 Processing Hierarchy of Visual Cortex in Owl Monkeys Figure 9. A pracesshg bkrarchy for visual areas in owl monkeys The sim lltied outline includes major fedfor- wPrd(A4and Van Essen, 1983) connections, does not consider all fedback or “inmnxdbte”connec- tions, anddoes not inchuie allvisualareas. Also, the many ~andcallosalconnectionsarenotshown.Scrlal and parallel processing components are evident. In addl- tion, a given visual such typically Ipcefve8 area as MT Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 inputs from several levels in the system. Thus, higher levels of the sequence may be dewdbed by “network” concepts(seetext~.~ctionallydisthctclassesofcellsin theretina(X,Y,andWprojectto~,magnocel- lular, and interlaminar (m) Wns of the lateral genicu- late nucleus (LGN), which in turn ectto neurons inV- Ithatrewto o ut neurons insx-ws 1% termin~logy),b%s or interblob regions. subgeqwnt re- laysareofthemagmewb to the M stripes, and one pamxduk @lob) to the P stripes and the other (interblob) totheinterstripe regions of v-II (area 18). rayer X neurons also project dhdyto the middle temporalvisual area 0,which also 811 input fnnn the M stripes Of V-IL MT projects to cortexinthe fundus of the superior temporal sulcus (IS“) and the superior temporal area (a,which reJay to posterior PQiaetal cortex as part of a subsystem \ specializedfordsualattentkmands ielaeaons(see \ Ungerleider and Mishkin, 1982 fot c).Most of the ourputOf V-II is dhddto the dOI’SOMvisual area (DL orv-4of macaque monlup), where fnfwmattonis relayed over sequence of fields in faferlor temporal (rn COiQx (note c=W c, togtral, r, and polat, p, 4medial, m, ~ions).Higherlevelsan?essdngulate~pffsuma- bly for mothtiom4 components, the hippocan amygddafotmechdsmsrebtedtothestongeo memo- ries, andvhomomr centers (frontalventral,frontaleye LQN fMd, supplementary motor area) in the frontal Eobe (see Kaas, 1986; 1988 for derenca and details). YW X RETINA mediating object vision and the other sequence of fields activate the neurons in the higher stations and provide ending in posterior parietal cortex and mediating visual inputs for further computations. The significance of the attention and spatial vision (Figure 8). While more elabo- feedback connections is less certain, but presumably rate hierarchies have been subsequently proposed (e.g., feedback connectionsmodulate the activity of the neurons Figure 9, Ungerleider & Desimone, 1986; Maunsell & Van at the lower level. For areas 17 and 18 of monkeys, the hen, 1983; Weller & bas, 1987), patterns of connec- feedback from MT, which is in the Y cell or M stream, tions support the view that many of the visual areas largely distributes across all three processing streams (Krubitzer & belong to one or the other of the two major streams in both bas, 1988). Therefore one function of feedback may be New and Old World monkeys. More recent evidence (see to integrate processing across the semi-independent par- Livingstone & Hubel, 1988) suggests that the X (parvocel- allel pathways. lular) stream subdivides into two parallel streams in V-I, which remain segregated in V-11, and project in parallel to 5c. Networks: A number of models of how neuronal DL 074) (Figure 9). Thus, at least the early stages of systems function have employed large numbers of simu- processing in visual cortex of primates are characterized lated neurons that are widely interconnected. Such models by three parallel streams of sequences of modules con- may have stages of processing, but they are basically nected across several visual areas. concerned with the outcomes (emergent properties) of Within the parallel streams in primates, and within the multiple interactions at the neuronal level (e.g., Andersen overall hierarchy o€visual areas, there are “feedforward & Zipser, 1988; Hopfield & Tank, 1986; Linsker, 1986 1. In projections from lower to higher levels, and “feedback addition, the term “network has been used, especially projections from higher to lower levels (Maunsell8 Van recently, in another way to refer to a collection of cortical Essen 1983). The feedforward projections presumably areas, presumably functioningtogether, that are intercon- 128 ]ournal of Cognitive Neuroscience Volume 1, Number 2 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 nected in a manner that is not obviously hierarchical, or at connections. An understanding of the details of connec- least in a manner where hierarchical processing across tions, how they form and how they are maintained, can areas is not the dominant feature. For example, Mesulam contribute to understanding what visual areas do by (1981) and Goldman-Rakic (1988) describe a collection of placing constraints, by making theories more or less likely. interconnected fields in the frontal, parietal, and temporal The idea that connections can be guided to very lobes of macaque monkeys as a “network.”While feedfor- specific and predetermined targets, even over consider- ward and feedback types of connections clearly exist, able distances, has been with us for some time (e.g., many of the connections of visual cortex are of interme- Sperry’s chemospecificity theory - see Sperry, 1945). diate types that do not clearly identify areas as “higher”or However, the bulk of the evidence now suggests that only “lower”(see Maunsell & Van Essen, 1983; Weller & Kaas, the crude outlines of patterns of connections are formed Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 19811, supporting the viewpoint that, in some sense, there by such guidance. Selection among many possibilities for is validity in describing the organization of visual cortex as synaptic targets and synaptic strength provides the details a “network”of areas. However, a notion embedded in the of the connection pattern during development, and main- concept of a network, whether at the level of neurons or tains and modifies local connections in adults (see Kaas, cortical areas, is that widespread interconnectionsprovide 1988;Merzenich et al., 1988for reviews). The critical point widespread accessability of components to each other of this theory, which has the concept of the “Hebbian” (e.g., Hopfield & Tank, 1986). The cortical areas are not so synapse (Hebb, 1949) as its cornerstone, is that synaptic broadly interconnected. If extremely sparse and variable inputs are selected (reinforced) on their ability to be connections are not considered, then cortical areas typi- correlated in their activity patterns to the extent that they cally have interconnections with 3-6 fields of the same are active together when the activity is powerful enough hemisphere, 2 or 3 fields of the opposite hemisphere, and to result in the discharging of the target neuron (see with 2-3 thalamic nuclei (see Cusick & Kaas, 1986; Changuex & Danchin, 1976;Willshaw & Von der Malsburg, Merzenich & Kaas, 1980). Only some of these connec- 1976). If this is the way that the nervous system constructs tions have a major. activating role, and most of the major and maintains itself, then certain connection patterns and connections can be classified as feedforward or feedback- therefore modes of functioning seem more likely than ward across series of fields. Thus, the term “network”can others. be misleading. Since much of the processing in a sensory system has a hierarchical component, within and across areas, it is 5d. A Manifold System Clearly the visual systems of instructive to imagine what the selection of inputs with advanced mammals are capable of performing many correlated activity would do at successive stages in the different functions at once, and include a large number of visual system. Some of the functional implications of parts with complex patterns of interconnections. Figure 9 current concepts of the development of connections is a greatly oversimplified diagram of how visual cortex is within and across sensory areas have been reviewed and interconnected in owl monkeys. Cortical visual areas are outlined elsewhere (Kaas, 1988). not arranged in a single hierarchy for processing from One implication is that selection for correlated activity sensation to perception. Rather, each visual area is inter- would tend to create and preserve retinotopic andvisuotopic connected with 3-6 other visual areas with the inclusion organization (see for example, Constantine-Paton, 1982). of serial, parallel, recurrent, and network-like compo- Obviously, a powerful factor in correlating neural activity nents. In addition, each visual area directly accesses a is retinal location. Neurons in the same retinal location are number of subcortical regions and receives inputs from likely to fire together, both initially because they are likely parts of the pulvinar complex (see Kaas & Huerta, 1988). to be interrelated by local, perhaps initially random, inter- In general, current theories of visual system organization connections, and later in development because they have and function do not adequately address the complexities a high probability of being activated together by the same of the connectional framework, which suggests that visual stimuli. Selection for activity correlated by retinal position processing is manifold in nature (Kaas, 1977), with wide would counter the divergences and convergences of regions of cortex including many cortical fields interacting potential connections across stations, and retinotopic during even simple visual tasks. Furthermore, the outputs organization would tend to be preserved across stations. from many visual areas, via subcortical connections, have After vision starts, the alignment of the eyes would allow the potential to directly influence behavior. Perhaps it is stimuli to activate matched locations in the two eyes, so the multitude of possible influences on neurons in the that in late maturing connections, inputs from the two eyes motor system that allows the flexibility in behavior that merge and create visuotopic Organization, the systematic occurs in advanced mammals. representation of visual space. Another implication is that neurons will become less 6. Haw Do Connection patterns Develop and How selective at higher processing levels. Because it is difficult areTheyMaintained? to precisely preserve the timing of neural discharges across Obviously what any visual area does, that is the compu- multiple relays, each station in the relay will accept, in tations that occur in an area, depends on inputs and local order to maintain synaptic density, inputs with a greater KnaS 129 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 range in correlations. One consequence is that the recep- visual system seem to be making center-surround or local- tive fields get bigger. Thus, whatever functions neurons in global comparisons (see Allman et al., 1989, and the higher stations perform, they must do it with larger modulatory inputs may be very important in providing the receptive fields. Neurons in early stations are more likely surround or global effects. Providing more global effects is to be activated by spatially local events, neurons in higher a consequence of broader connections across cell classes stations are more likely to be activated by more global and across more visual space as a result of degraded events. Of course, the amount of selectivity for correlation correlations. within a given field may be modifiable in evolution, so that receptive fields for neurons in area 17, for example, may 7. wherpillpiocessingHierarchiesdovisual~ vary in size from species to species, and area 17 may have GetAdded? Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 a role in more global or more local functions accordingly. All mammals appear to have the primary (area 17 or V-I) An advantage of more cortical areas is that this could and secondary (area 18 or V-11) visual fields (Kaas, 1980) provide a greater range of levels of local to global process- and the end stations of visual processing, such as entorhi- ing. nal cortex, the amygdala and hippocampus, related to A third implication is that parallel paths will occur and object identification and visual memories (Mishkin, 19821, increase in number across higher stations. Location on the the medial limbic cortex, related to visual attention and receptor sheet is only one way to influence correlations. motivation (Mesulam, 198l), and the motor and visuomo- Another is through neural transductions and computa- tor fields and subcorticalstructures mediating motor behav- tions. The different sensitivities of adjacent receptors dis- ior. The simple hierarchies of visual areas, with little more correlates the activity of some of the neurons with inputs than beginning and end stations, that characterize the from the same retinal location and decreases the probabil- brains of mice and hedgehogs become complex hierar- ity that they will synapse on the same neuron at the next chies, like those of monkeys and cats, by the addition of station. This tends to create local populations of neurons new visual areas in the middle stages of processing. As a that are interconnected and computing on the basis of result, a change occurs from the situation where the first stimulus progrties related to the transduction process, as cortical station, area 17, directly accesses some of the end well as to stimulus location. Post-receptor processing or near end cortical stations in frontal and limbic cortex, as mechanisms, such as those that create the X, Y and W cell in rats and mice (e.g., Miller & Vogt, 198-9,to where area classes in the retina, would tend to create parallel path- 17 relates to only early stages of a lengthy hierarchy, as in ways across visual areas and semi-isolated processing monkeys (Figure 6). modules (columns) within areas. Moreover, the construc- tion of any new cell classes (in terms of response proper- 8. Theories of Why Multiple Visual Areas Exist ties) at higher stations would tend to increase the number Several proposals have been made for the advantages of parallel paths at higher levels in a hierarchy. However, provided by having larger rather than smaller numbers of the tendency for an increase in parallel paths would be areas in visual cortex. The proposals, to some extent, countered somewhat if higher neurons are more broadly address different issues, and are, to a large extent, mutually tuned for correlation. Thus, a merging of parallel paths compatible. The Fvst proposals are different versions of the would occur to some extent. Because of a probable basic theme that visual areas are specialized for analyzing relaxation of the correlation requirements, higher areas, by different aspects of the visual world, and that having more merging streams, would be expected to more closely visual area allows the analysis of more aspects. resemble a broadly interconnected network, and the processing would less closely resemble the predominately 8a. IncreaslngtheNumberofvtsualAreasIncreascs hierarchical processing at early levels. Thus, connection the Number of vie\uil Abilities This widespread as- patterns between higher areas would be less clearly sumption seems valid, though poorly supported. Clearly feedforward or feedback. there is an overall relationship between the magnitude of If the requirements for correlation become more re- brain development and abilities. To consider extremes, the laxed across stations,a fourth implication is that feedback visual capabilities of some fish seem to be so limited that connections would be more promiscuous but less effec- they select prey on the basis of retinal image size (see tive than feedforward connections. Neurons within a Wetterer & Bishop, 1985) rather than real size (which can system clearly have synaptic contacts that range in effec- be determined only with information in addition to image tiveness. The highly correlated feedforwad inputs would size), while human vision includes complex and varied acquire the most synaptic strength, and be the most inferences about the visual world that allow, for example, powerful. Because the neurons providing feedback, cal- mental rotations of objects, accurate predictions about 104, and widespread intrinsic connections are less corre- where obscured moving objects will appear, and the rapid lated in activity than those providing the feedforward identification(categorization) of a wide range of objects. By inputs, the feedback, callosal, and widespread intrinsic being less extreme and considering only mammals, no connections would be less effective and have modulatory doubt mammals with few visual areas, such as hedgehogs roles on neural activity. However, neurons throughout the and mice, have visual capacities vastly inferior to those of 130 Journal of Cognitive Neuroscimce Volume 1, Number 2 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 mammals with many visual areas, such as cats, monkeys, visual space. However, associations that do not depend on and presumably humans. Of course there are several proximity in space are psychologically important, and nagging concerns. Mammals with more visual areas also non-topographic maps or transformations, according to have larger brains (relative to body size), and its not certain Barlow, would seem better suited for most detections. that number of areas rather than brain size is important. Somewhat differently, Desimone et al. (19851, argue that There probably is an interaction, but it would be difficult object vision depends on the flow of information along a to evaluate the relative contributions of brain size and pathway from striate cortex to the temporal lobe, where number of fields. Another problem is that studies of animal processing is serial, yet multidimensional and increas- behavior have concentrated on species with simple nerv- ingly abstract at each stage. According to this view, having ous systems, and we do not have a comprehensive more, rather than fewer, visual areas would allow more Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/1/2/121/1755569/jocn.1989.1.2.121.pdf by guest on 18 May 2021 understanding of how visual abilities vary in mammals. complex processing that would enrich perception and Finally, we have an understanding of the broad outlines of reduce perceptual errors. cortical organization and these outlines are available for Multiple areas also provide more links to motor only a few species. Presently, we can’t be precise about the outputs. Each visual area projects to approximately 5-15 number of visual areas for any species. For these reasons, subcortical structures and nuclei (e.g., Graham et al., it is unlikely that we will have strong evidence in the near 1979, and many of these structures are closely related to future for the assumption that increases in numbers of motor performance. Most of these structures have inputs areas leads to increased abilities. from a number of visual areas, although the pattern of Opinions differ on how having more visual areas subcortical targets is different for each visual area. Creutzfeldt increases visual abilities. A common view is that visual (1985) has emphasized that there may be behavioral information is distributed to a number of visual areas advantages to having such multiple links between the where each visual area processes different “attributes” sensory organ and the motor output. One possible advan- (contrast, spatial frequency, orientation, movement, reti- tage may be that more possible influences on motor nal disparity, size, color) of a complex visual stimulus outputs increases behavioral flexibility. (Cowey, 1979; Young, 1978; Zeki, 1978). According to Zeki (1974; 19781, for example, multiple visual areas are 8b. Multiple Areas Simplify the Problem of Intercon- for the “division of labor” and “simultaneousanalysis” of necting Functionally Related Groups of Neurom different components of vision. Different functions are Cowey (1979; 198l), and others (i.e., Barlow, 1986; Kaas, emphasized in different cortical areas. More specifically 1977) have argued that having multiple visual areas is an according to this view, V1 emphasizes the analysis of effectiveway of allowing neurons to have the connections stimulus contours, V2 relates to depth, V4 (DL) is devoted needed for their roles in perception. Cowey (1979) starts to color, and V5 ~MTlis critical for detecting movement. with the premise that the different visual areas are con- However, most mammals, including some with the fewest cerned with “different aspects of the visual world” (attrib- visual areas, are sensitive to these basic attributes of visual utes). Most areas have retinotopic maps because the stimuli. Thus, species differences in numbers of areas are interactions between neurons with similarly located re- not explained, unless one holds that other (unspwiAed) ceptive fields that create selectivity for specific attributes stimulus features are analysed by advanced but not by of a complex stimulus depend on connections that are best primitive mammals. short and local and would be “cumbersomeor impossible” Another approach is to be less specific about what if long. Cowey (1979) also supposes that it is genetically identified visual areas do, but simply propose that having easier ta program local rather than far-reaching connec- more visual areas allows more siimulus parameters to be tions. Thus, within visual areas “the retina is topographi- considered. Thus, Ballard (1986) concludes that neurons cally mapped in order to keep inmcortical connections within any field have “multimodal” responses, but the short and to simplify developmental specificity.”Multiple number of parameters that can be handled by any topo- visual areas exist “forthe same reasons.”More specifically, graphic representation is limited (on the order of 5-15]. the local connections that would be needed to sharpen the Given that it is beneficial to compute a large number of tuning of individual neurons for one of the many attributes parameters, multiple areas are needed. A related concept (see above) of a complex stimulus would be long if is that multiple visual areas allow the system to detect neurons for all the different attributes were in the same “suspicious coincidences” along more stimulus parame- visual area. Having many retinotopic maps allows most of ters. According to Barlow (1986), the primary and other the computing to be done with short local connections, areas distribute information to a number of visual areas, although the receiving and sending information would each organized to detect different “suspicious coinci- require long connections between areas and subcortical dences” or “linking factors” (e.g., attributes such as structures. Most visual areas are semiretinotopic; that is, at orientation, direction of motion, or color) of the stimulus the global level there is a retinotopic map, but locally other (also see Phillips et al., 1984). Topographic representa- features of organization dominate. In the development of tions preserve neighborhood relations, and therefore are the brain, crude guidance could set up the long COM~C- useful in detecting coincidences in restricted regions of tions that interrelate these separate maps, and the order of KaaS 131 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn.1989.1.2.121 by guest on 23 September 2021 these connections, including aspects important for retino- Aclulow~ts topic and local features, could be refined by rules for re- This manuscript is based on an invited presentation given at the in 3rd Annual Meeting of the American Academy of Clinical Neu- inforcing correlated activity (see above). Neurons these rology. I thank R. Blake, J. Bullier, P. Garraghty, S. Florence, L. visual areas seem to be connected in ways that allow com- Krubitzer, and M. Powers for comments on the manuscript. parisons between more local and more global features of the stimulus (see Allman et al., 1985). 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