in: visual neurosciences (l. chalupa and j. werner,...

Organization of Visual Areas in Macaque and Human Cerebral CortexDavid C. Van Essen

In: Visual Neurosciences (L. Chalupa and J. Werner, eds.)

In Press 8/15/03 -- Proof version

Introduction.The mammalian visual system contains

numerous visual areas that collectively occupy alarge fraction of cerebral cortex. For corticalcartographers interested in vision, a fundamentalset of objectives is to identify in key species ofinterest the overall extent of visual cortex, thetotal number of visual areas, the identities ofthese areas, and their location in relation to oneanother and to various gyral and sulcallandmarks. Over the past three decades there hasbeen much progress in this endeavor for anumber of primate and non-primate species.However, the task remains far from complete.Numerous qualitatively different partitioningschemes abound, even for the most intensivelystudied species. Our fragmentary and rapidlyevolving understanding is reminiscent of thesituation faced by cartographers of the earth'ssurface many centuries ago, when maps werereplete with uncertainties and divergentportrayals of most of the planet's surface.

The primary objective of this chapter is tosummarize our current understanding of visualcortical organization in two primate species, themacaque monkey and the human. The macaqueis the most intensively studied nonhumanprimate and has been charted using a widevariety of approaches. Human visual cortex,largely terra incognita until the past decade, isnow accessible thanks to modern neuroimagingmethods, especially functional magneticresonance imaging (fMRI; see Chapter 79, TheVentral Visual Object Pathway in Humans:Evidence brainnn fMRI). A secondary objective,more methodological in nature, is to illustrate theutility of computerized surface-based atlases inelucidating visual cortical organization. In brief,surface-based atlases offer many advantages overconventional atlases (e.g., stereotactic atlases andpictorial representations). These include theability to (i) visualize the cortical surface inmultiple configurations, including smoothed andflattened maps, (ii) view any number ofpartitioning schemes and open-ended amounts of

complex data in a convenient and electronically-accessible format; (iii) represent various types ofspatial uncertainty that are associated with realexperimental data; (iv) compensate for individualvariability and (v) make objective interspeciescomparisons of cortical organization.

Visual areas in the macaque monkey.

Figure 1 shows the estimated extent of visualcortex in the macaque and its relationship toother sensory modalities and to motor cortex.This is displayed on a surface-based atlas of theright cerebral hemisphere that was generatedfrom a high-resolution structural MRI imagevolume (Van Essen et al., 2002; Van Essen,2002; see legend to Fig. 1 for details). The toppanels show lateral and medial views,respectively, of the fiducial (three-dimensional)configuration; the lower left panel (Fig. 1C) is aflat map that shows the entire surface in a singleview.

The dotted lines on the flat map represent theestimated boundary between regions dominatedby different modalities, based on the analysis ofFelleman and Van Essen (1991). Theseboundaries are not sharply defined, as there isconsiderable intermixing of function intransitional regions between modalities. Theblending of colors on the maps in Figure 1qualitatively reflects this functional overlap.Cortex that is predominantly or exclusivelyvisual (blue shading) occupies about half (52%)of the cortical surface area (as measured on thefiducial surface rather than on the flat map,which contains significant distortions). Thisgreatly exceeds the amount devoted to othermodalities: somatosensory (green, 10%),auditory (red, 3%), motor (magenta, 8%), andolfactory (brown, 1%). Unassigned cortex (gray,25%) is mostly cognitive or emotional infunction, but is not subdivided along these linesin the figure.

Figure 1. Visual cortex and other functional modalities mapped onto a surface-based atlas of macaquecerebral cortex. The atlas was generated from a high-resolution (0.5 mm3 voxels) structural MRI volumegenerously provided by N. Logothetis (Case F99UA1, M. mulatta), using the SureFit segmentation methodfor surface reconstruction and Caret software for surface manipulation and flattening (Van Essen et al.,2001a). This atlas has many advantages over its predecessors, which include manually generated maps(Van Essen and Maunsell, 1980; Felleman and Van Essen, 1991) and surface-based atlases from ahemisphere that lacked corresponding structural MRI data (Van Essen et al., 2001a). A. Lateral view. B.Medial view. C. Flat map. Surface coloring represents different functional modalities, as identified on theflat map; darker shading represents cortex buried in sulci. D. Lateral view of the atlas spherical map, withlatitude and longitude isocontours. By convention, the lateral pole is set at the ventral tip of the centralsulcus. E. Latitude and longitude isocontours displayed on the flat map. Data for Figures 1-3 can beaccessed via http://brainmap.wustl.edu:8081/sums/archivelist.do?archive_id=448857.

Figure 1 also shows latitude and longitudeisocontours that are determined on a sphericalmap (Panel D) and projected to the flat map(Panel E). As with earth maps, sphericalcoordinates provide a concise and objective wayto specify precise locations on the map (Drury etal, 1999; Fischl et al., 1999a,b; Van Essen et al.,2001a).The identification of distinct visual areas isgenerally based on finding reliable differences inone or more characteristics related to: (i)architecture, (ii) connectivity, (ii) visualtopography, and/or (iv) functional characteristics(Felleman and Van Essen, 1991, Kaas, 1997).Using various combinations of these criteria,numerous partitioning schemes for visual cortexin the macaque monkey have been published overthe past century. Figure 2 shows 10 such schemesthat were mapped to the atlas using a surface-

based registration method (Van Essen et al., 1998,2001b; see legend to Fig 2 for details). Panels A-C illustrate three schemes that encompass most orall of the visual cortex. The Felleman and VanEssen (1991) and Ungerleider and Desimone(1986) schemes are based on anatomical andphysiological data from many sources. The Lewisand Van Essen (2000a) scheme is based on anarchitectonic analysis of multiple hemispheres,with the atlas map generated via surface-basedregistration of a particular individual map. PanelD shows several schemes that cover morerestricted regions, including a connectivity-basedanalysis of occipital cortex (Lyon and Kaas, 2002)and architectonic analyses of temporal andparietal cortex (Seltzer and Pandya, 1978, 1980,1986). Panel E shows two additional architectonicschemes covering temporal (Baylis et al., 1987)and parietal (Preuss and Goldman-Rakic, 1991)

Van Essen 3Organization of Visual Cortex

regions, plus a visuotopic mapping analysis ofdorsal occipital cortex (Galletti et al 1999). Whilefar from an exhaustive compilation, Figure 2includes most of the partitioning schemes incurrent use that have been reported in a formatsuitable for registration to the atlas.

Although there are many similarities, thesepartitioning schemes differ in many ways, forreasons that reflect various technicalimpediments faced by cortical cartographers. (i)Subtle boundaries. The distinctions betweenneighboring regions are often subtle, even whenevaluated with the most sensitive anatomical andphysiological techniques available. (ii) Internalheterogeneity. Many (perhaps most) visual areasare internally heterogeneous. This heterogeneitymay be manifested by modularity (repetitiveorganization at a finer scale than the overall arealdimensions); asymmetries (differences betweenthe representations of the upper (superior) andlower (inferior) visual fields; or internalgradients (gradual shifts in characteristics ratherthan discrete modularity). (iii) Individualvariability. The overall size of well-definedvisual areas such as V1 and MT can vary two-fold or more from one individual to the next(Van Essen et al., 1984; Maunsell and VanEssen, 1987). This is compounded bysubstantial variability in the exact pattern ofconvolutions and in the location of arealboundaries relative to gyral and sulcal landmarks

A compelling case for areal identification entailsfinding region-specific characteristics that arerobust, consistent across multiple approaches, andreplicated by multiple laboratories. The diversityamong partitioning schemes signifies that aconsensus has been achieved for only a minority ofthe visual areas illustrated in Figure 2. Several well-defined areas (V1, V2, V4, and MT) are shown bydifferent colors in Figure 2; others are included aspart of a regional coloring pattern that includes sixclusters discussed below.

The differences among partitioning schemes canbe categorized along four lines: Terminologicalequivalence. Some differences are essentiallyterminological, in that different labels areassigned to what is fundamentally the samevisual area. For example, area 17 is equivalentto area V1; MT (Fig. 2A-C) is equivalent to V5(Shipp and Zeki, 1985);, and PO (Fig. 2A-C) isequivalent to V6 (Fig. 2F). Lumping vs.Splitting. Some regions are considered a singlearea by some investigators (the “lumpers”) but as

two separate areas by other investigators (the“splitters”). This is an issue, for example, forsubdivisions V3d/V3v, V4d/V4v, andLIPd/LIPv. In some cases it can be helpful touse the term “zone” to describe a consistentlyidentifiable region whose status as a distinct areais uncertain, ambiguous, or contentious (Lewisand Van Essen, 2000a). The term “subdivision”can then encompass both zones and well-definedcortical areas. Boundary uncertainty. Evenwhen there is a consensus on the identity of anarea and the main criteria for its identification,the location and extent of any particular area onthe atlas map vary substantially across schemes,(cf. V2 and MT in Figure 2A-D). Thesedifferences may reflect (i) the choice of criteriaor emphasis among different criteria availablefor delineating boundaries; (ii) variability in thesize and location of areas in the individualsstudied, (iii) inaccuracies in portraying arealboundaries on a summary diagram in the originalpublication; and (iv) inaccuracies or distortionsarising when registering data to the atlas.Genuine incompatibility. In some regions,partitioning schemes differ more profoundly thancan be explained by the factors just mentioned.For example, in inferotemporal cortex (blue)there is rather little correlation between the arealboundaries in panel A vs. E; hence the schemesare largely incompatible.

Figure 2. Ten partitioning schemes for macaque visual cortex registered to the atlas and displayed on flat map views.See abbreviation list for full names of areas. Data were registered to the atlas using a surface-based registration methodin which geographic (gyral and sulcal) landmarks were used to constrain the registration (Van Essen et al., 2001b).Depending on the data source, this method was applied to computerized maps (spherical or flat maps) and to scannedimages of manually generated flat maps or drawings of the hemispheric surface and of schematically opened sulci.Thus, there are substantial differences in the fidelity of the published representations and in the distortions anduncertainties involved in registering to the atlas, but visualization on a common substrate nonetheless remainsadvantageous. A. Felleman and Van Essen (1991) partitioning scheme for visual areas. Areal boundaries wereoriginally charted on a physical model of an individual hemisphere (case 79O). They were transferred to acomputerized surface reconstruction of the same hemisphere and then were registered to the Case F99UA1 atlas usingspherical maps of each hemisphere. B. Ungerleider and Desimone (1986) scheme (their Figure 1, as modified in Fig. 2of Desimone and Ungerleider, 1989). Registration was achieved using geographic landmarks on a manually generatedflat map. C. Lewis and Van Essen (2001a) scheme from Case 95DR (their Figure 14) registered from thecomputerized flat maps. D. A composite map of partitioning schemes for occipital cortex (Lyon and Kaas, 2002, theirFigure 4), parietal cortex (Preuss and Goldman-Rakic, 1991, their Figure 4C) and temporal cortex (Baylis et al., 1987,their Figures 2 and 3). The Lyon and Kaas map was based on a visuotopic analysis of V1 projections as displayed onsections of physically flattened cortex. The Preuss and Goldman-Rakic maps were derived from their illustrations ofschematically partially unfolded sulci; the Baylis et al. maps were based on cortex flattened using a “straight-line”unfolding technique. E. A composite map of dorso-medial cortex (Galetti et al., 1999, their Figure 17), and parietaland temporal cortex (Seltzer and Pandya, 1978, 1980, 1986), all illustrated on schematically unfolded sulci. Data canbe accessed via http://brainmap.wustl.edu:8081/sums/archivelest.do?archive_id=448857.

Occipital visual areas. V1 and V2 are bothlarge, well-defined areas, with V1 occupying13% and V2 occupying 10% of total corticalsurface area (12.6 cm2) in the atlas righthemisphere. V1 and V2 have a mirror-symmetric visuotopic organization, with thevertical meridian represented along theircommon boundary, and with upper fieldsrepresented ventrally and lower fields dorsally ineach area. In addition, both areas haveprominent internal modularity related to theprocessing streams that course through theseareas (Felleman and Van Essen 1991; Van Essenand Gallant, 1994; Chapter 34, this volume)).Interestingly, there are significant asymmetriesbetween dorsal V2 (V2d) and ventral V2 (V2v):V2v is notably wider than V2d (Figure 2A-D),and the two subregions differ in the globalpattern of thick stripes, thin stripes, and inter-stripes (Olavarria and Van Essen, 1997).

Area V3 was originally identified as a strip ofcortex that adjoins V2 and has mirror-symmetricvisuotopic organization (Zeki, 1969). Subsequentstudies confirmed this visuotopic organizationbut revealed that the dorsal and ventralsubdivisions are physically separated from oneanother by the interposition of area V4 (cf. Fig.2A-C). More significantly, evidence forpronounced dorso-ventral asymmetries inconnectivity (especially with V1),myeloarchitecture, and physiological propertiesprompted the classification of these dorsal andventral subdivisions as distinct visual areas: VP(or V3v) and V3 (or V3d), each containing apartial representation of the visual field (cf.Burkhalter et al., 1986). In contrast, Lyon andKaas (2002) reported relatively symmetricprojections of V1 using more sensitive tracers,and they support Zeki's original proposal thatV3d and V3v are subdivisions of a single areaV3. A sensible interim strategy is to designatethese subdivisions as “zones” V3d and V3vwhile awaiting additional data on the overallmagnitude and nature of V3d/V3v asymmetries,along with insights regarding the asymmetriesencountered in other regions and other species(see below). Independent of this terminologicaldebate, it is noteworthy that V3d and V3v varyconsiderably in location and size among thevarious maps shown in Figure 2.

V4 is a moderately-sized area whose lower-field(V4d) and upper-field (V4v) representations arecontiguous with one another, in contrast to thephysical separation of V3d and V3v. The

visuotopic organization of dorsal V4 appears tobe more complex and variable across individualsthan that of ventral V4 (Maquire and Baizer,1984; Gattas et al., 1988; Van Essen et al., 1990;Boussaud et al., 1991). Because analogous butmore pronounced dorso-ventral asymmetrieshave been reported for the corresponding regionof human cortex (see below), Tootell andHadjikhani (2001) have suggested that macaqueV4d and V4v might themselves constitutedistinct visual areas.

Five additional areas adjoin or closely approachV2 along its dorso-medial and ventro-medialboundaries. The dorso-medial cluster (magentain Fig. 2) includes areas V3A, PIP, and PO, eachof which includes an upper-field as well as alower-field representation (Colby et al., 1988;Felleman and Van Essen, 1991; Lyon and Kaas,2002). Area PO as charted by Colby et al.(1988) corresponds to area V6 of Galletti et al.(1999). The ventro-medial cluster (brown in Fig.2) includes areas TF and TH (near the bottom ofthe flat map) both of which receive visual inputs(see Felleman and Van Essen, 1991). Theposterior portion of TF, identified as VTF byBoussaud et al. (1991), is visually responsive buthas at best a crude visuotopic organization.

Dorsal temporal and posterior parietal cortex. The “dorsal stream” of visual areas ( Chapter 34,Ventral and Dorsal Cortical Processing Streams)includes cortex in and near the intraparietalsulcus, plus the dorsal part of the superiortemporal sulcus. Area MT, the most extensivelystudied area in the dorsal stream, contains acomplete visuotopic map, but with a bias oflower versus upper visual fields (Maunsell andVan Essen, 1987). Though MT is well-definedby several criteria (including a high incidence ofdirection-selective cells), its precise location andextent on different summary maps variessignificantly (cf. Fig. 2A-D; see also Desimoneand Ungerleider, 1986). Adjoining MT on itslateral side is a narrow strip that has beenidentified as V4t (Ungerleider and Desimone,1986, Felleman and Van Essen, 1991) or MTc(Lyon and Kaas 2002). Within V4t,architectonically distinct zones V4ta and V4tphave been described (Lewis and Van Essen,2000a)

A major target of MT is the MST complex(orange in Fig. 2), which lies dorsal and medialto MT and is implicated in higher-order motionanalysis. MST is heterogeneous both


anatomically and physiologically, but it remainsunclear whether there are two subdivisions(MSTd and MSTl; of Komatsu and Wurtz 1988a,1988b and Felleman and Van Essen, 1991;MSTc and MSTp of Boussaud et al., 1990) orthree (MSTdp, MSTm, and MSTl of Lewis andVan Essen, 2000a) and whether these constitutedistinct areas or zones within a larger MSTcomplex. Area FST lies ventral to the MSTcomplex and medial to MT, but its positiondiffers markedly in different partitioningschemes (Fig. 2A versus 2B,C).

Posterior parietal visual cortex (yellow in Fig. 2)includes several elongated areas in and near theintraparietal sulcus, plus additional areas in moreposterior regions that are represented in someschemes. The most fine-grained scheme (Lewisand Van Essen, 2000a; Figure 2C) is based onimmunohistochemical as well as cyto and myelo-architecture and includes seven distinct areas (7a,LIPd, LIPv, VIP, MIP, MDP, and DP) plusadditional architectonic zones. In the regionpreviously described as area LIP (Blatt et al.,1990), subdivisions LIPd and LIPv differ fromone another in architecture, connectivity, andphysiological characteristics and are thus likelyto constitute separate visual areas (cf. Lewis andVan Essen, 2000a, 2000b). Area VIP, along thefundus of the intraparietal sulcus, contains lateral(VIPl) and medial (VIPm) architectonic zones,but these are not considered distinct areas on thebasis of current evidence (Lewis and Van Essen,2000a, 2000b). Areas LIPd, LIPv, and VIP ofLewis and Van Essen (2000a) largely correspondwith POa-e, POa-i, and IPd of Seltzer andPandya (1980, 1986) except that they are morerestricted antero-posteriorly. The relationshipswith other schemes are somewhat confusingbecause of "cross-talk" in the terminology: areaVIP* of Ungerleider and Desimone correspondsto LIPv of Lewis and Van Essen; areas LIP andVIP of Felleman and Van Essen correspond toLIPd and LIPv/VIPl, respectively, of Lewis andVan Essen.

A second group of areas, near the posterior endof the intraparietal sulcus, includes areas MDP,MIP, and DP, plus zone LOP (Fig. 2C). AreaMDP corresponds to V6A of Galetti et al.(1999). Zone LOP may correspond to the cIPSsubdivision identified physiologically by Taira etal., (2000) based on surface orientationselectivity.

Ventral temporal areas. Cortex ventral to area MTand anterior to V4 is generally considered part of theventral processing stream (cf. Chapter 34, Ventraland Dorsal Cortical Processing Streams). Thisregion includes a cluster of inferotemporal areas(blue in Figure 2) that are implicated mainly inpattern recognition and form analysis (Desimoneand Ungerleider, 1989; Tanaka, 1997). Anothercluster of ventral-STS areas (dark green in Fig. 2)includes polysensory regions and regions involvedin both form and motion processing (Cusick, 1997;Oram and Perrett, 1996). The five schemes in Figure2 subdivide ventral temporal cortex along bothantero-posterior and dorso-ventral axes, but thenumber of identified subdivisions ranges from fourto ten and the location of areal boundaries varieswidely as well.

The simplest scheme (Ungerleider and Desimone,1986, Fig. 2B) includes a visuotopically organizedarea TEO that contains a lower-field and an upper-field representation (see also Boussaud et al.,(1990)), plus three areas (TEc, TEr, and TEm) thatlack clear visuotopic organization. The Fellemanand Van Essen (1991) scheme, based mainly ontopographic and connectional data, includes threeareas (VOT, PITd, and PITv) in the regioncorresponding to TEO of Ungerleider andDesimone. VOT contains only an upper-fieldrepresentation, whereas PITd and PITv are reportedto each contain a crude topography with lower-fieldand upper-field inputs (Van Essen et al., 1990).Areas CITd and CITv of Felleman and Van Essen(1991) together correspond approximately to TEc ofUngerleider and Desimone (1986) but aredistinguished from one another by differentialconnections. More anteriorly on the atlas map, there


Figure 3. A-C. Lateral, medial, and flat map views of a composite map obtained by superimposing the datafrom Figure 2. Although the specific areal assignments at each location cannot be ascertained by viewingthis image, they can be readily obtained using a node-identification option in the Caret visualizationsoftware. See Abbreviations list for full names. See Fig. 1 legend for data access information.

is reasonable correspondence between AITd andTEr in the two schemes but poor correspondencebetween AITv and TEm.

The Seltzer and Pandya (1978) architectonicscheme (Fig. 2E) includes five inferotemporalareas (TEa, TEm, TE1, TE2, TE3), plus fouradditional areas in the superior temporal sulcus(TAa, TPO, PGa, and IPa). The Baylis et al.(1987) scheme (Fig. 2D) uses the same criteriaand terminology as Seltzer and Pandya (1978),but the areal boundaries differ significantly onthe atlas map. The Lewis and Van Essen scheme(2000a), like that of Cusick (1997), identifiesthree subdivisions within TPO (TPOc, TPOi,TPOr). In inferotemporal cortex the Lewis andVan Essen (2000a) scheme does not discriminateamong TE1, TE2, and TE3 but does identifydorso-ventral subdivisions TE1-3d and TE1-3v.The latter correspond approximately tosubdivisions TEad and TEav of Yukie et al.(1990) and Saleem and Tanaka (1996).

Frontal areas. Felleman and Van Essenclassified areas 8 (FEF) and 46 as part of visualcortex. Areas 8 and 46 have both beenpartitioned into multiple subdivisions, includingeight zones (8A, 8Am, 8Ar, 46d, 46v, 46dr,46vr, and 46r) by Preuss and Goldman-Rakic(1991b), and zones 8Ac, 46p, and 46v by Lewisand Van Essen (2000a).

It remains unclear which of the aforementionedschemes for inferotemporal and parietal cortexbest reflect the underlying neurobiologicalreality. Indeed, alternative possibilities worthbearing in mind are that much of inferotemporaland frontal cortex might contain gradualgradients of properties rather than sharplydefined areas, or else irregular clustering whosearrangement varies markedly from oneindividual to the next.

Figure 3 shows a composite map, in which all ofthe 10 schemes represented in the precedingpanels are superimposed and displayed in lateral(Fig. 3A), medial (Fig. 3B) and flat map (Fig.3C) views. Besides the individually coloredareas, the composite map includes the sixclusters discussed in preceding sections: thedorso-medial occipital complex (DMOcx),posterior parietal complex (PPcx), MST complex(MSTcx), ventral superior temporal complex(VSTcx), inferotemporal complex (ITcx), andthe TF/TH cluster.

How many visual subdivisions are these? It isnaturally of interest to have a current estimate ofthe total number of cortical areas andsubdivisions associated with visual processing.Given the diversity among partitioning schemes,it is impractical to arrive at a definitive singlenumber. Altogether, there is substantialevidence for more than 40 anatomically and/or


functionally distinct subdivisions of visuallyresponsive cortex, but for some the evidencedoes not warrant identification as separate areas.A conservative "lumper" can argue that thenumber of convincing visual areas is only abouttwo dozen. A more generous "splitter" can makea credible case for at least three dozen distinctareas. The number of areas that show clearvisuotopic organization is also difficult todetermine precisely, but is in the range of 10 –12, depending on designation of zones vs. areas.

Coping with multiple schemes, arealuncertainties, and individual variability. Severalgeneral observations emerge from the precedingdiscussion. First, a multiplicity of competingpartitioning schemes will likely persist for yearsto come, because many of the issues remaininherently difficulty to resolve with currentlyavailable techniques. Second, it is becomingincreasingly important to have objective methodsfor quantifying and visualizing the uncertaintiesassociated with charting areal boundaries and thevariability associated with individual differencesin cortical organization. This leads to the notionof probabilistic surface-based maps of corticalorganization. The composite map in Figure 3constitutes one step in this direction, as itincludes many different schemes in a commoncoordinate system. Another important aspect ofa probabilistic approach is to incorporateinformation about individual variability, byregistering maps of many individuals onto theatlas (Van Essen et al., 2001a).

Another important issue involves the options foraccessing and extracting information from surface-based atlases. The fundamental challenge is thatexisting atlases already contain far moreinformation than can be easily gleaned from staticpictorial images such as those shown in the presentchapter. Moreover, the amount of informationrepresented on such atlases is likely to growexponentially over the next decade. An attractivealternative is to use computerized visualizationsoftware to access atlas data more efficiently andflexibly. For the atlases illustrated here, this can bedone by downloading specific data sets (using

hyperlinks included in the figure legends) andviewing the maps using the freely available Caretsoftware (Van Essen et al. 2001b;http://brainmap.wustl.edu/caret). Existingvisualization options in Caret include: zooming inon regions of interest; rapid toggling betweendifferent partitioning schemes; overlaying onescheme directly over another; listing arealidentities for multiple partitioning schemes whenclicking on locations of interest; specifyinglocation by latitude and longitude (cf. Fig. 1E);encoding uncertainty limits for each boundary; andencoding variability by combining maps fromdifferent individuals.

Human visual cortex. The analysis of human visualcortex has benefited greatly from the advent ofstructural and functional MRI methods that can beroutinely carried out on normal subjects. In the tophalf of Figure 4, the extent of visual cortex andother functional modalities is charted on the righthemisphere of a surface-based atlas (the"Human.Colin" atlas) that was generated fromhigh-resolution structural MRI of a particularindividual (Van Essen, 2002; Van Essen et al.,2002; Holmes et al., 1998). The surface displaysinclude lateral and medial views of the fiducialsurface (Fig. 4A, B) and the inflated surface (Fig.4C, D), plus a flat map (Fig. 4E). The assignmentof different functional modalities was estimatedmainly from functional neuroimaging data thatwere mapped onto the atlas using a combination ofmethods applied to a number of published datasets (see the legend to Fig. 4). Based on theseprovisional assignments, cortex that ispredominantly visual in function occupies about27% of the total extent of cerebral cortex (950 cm2)in the right hemisphere of the atlas. Bycomparison, about 8% of cortex is predominantlyauditory, 7% somatosensory, and 7% motor. Theremaining half (51%) includes major domainsassociated with cognition, emotion, and language.

Human area V1 (area 17) has a well-definedarchitectonic boundary that runs near the marginsof the calcarine sulcus but with considerableindividual variability (Rademacher et al., 1993).The estimated surface area of V1 on the atlas map


Figure 4. Visual cortex and other functional modalities mapped onto a surface-based atlas of human cerebralcortex. The atlas was generated from a high-resolution structural MRI volume provided by A. Toga (CaseHuman.colin), using SureFit and Caret software (cf. Fig. 1). This atlas (Van Essen et al., 2002) is higher inquality and supercedes the Visible Man surface-based atlas previously published (Van Essen and Drury,1997; Van Essen et al., 2001a). Modality assignments were based on (i) stereotaxic mapping of fMRIvolume data onto the atlas surface from the studies of Corbetta et al. (1998); Lewis and DeYoe, 2000; Lewiset al., 2001) (ii) stereotaxic projection of published Talairach coordinates of activation focus centers (Ishai etal., 1999, Kanwisher et al., 1997; Van Essen and Drury, 1997); (iii) manually transposed boundaries relatedto local geographic and/or functional landmarks from surface maps published by (Press et al., 2001, andTootell & Hadjikhani, 2001; Burton and Sinclair, 2000. Data for Figures 4 and 5 can be downloaded viahttp://brainmap.wustl.edu:8081/sums/archivelist.do?archive_id=449900

(charted using the most likely boundary in theRademacher et al. study) is 21 cm2, or 2.2% ofcerebral cortex. This is about one-sixth of itsfractional occupancy on the macaque atlas.

Neuroimaging studies have revealed numerousvisuotopically organized extrastriate areas inhuman occipital cortex, in an arrangement thatshows many similarities to the pattern found inthe macaque. Corresponding areas that havefundamentally similar visuotopic organization inthe two species include V1, V2, V3 (V3d), VP(V3v), V3A, and V4v (Sereno et al., 1995;DeYoe et al., 1996; Hadjikhani et al., 1998). Inaddition, tests for motion-related activation haveconsistently demonstrated a prominent focus inor near the posterior inferotemporal sulcus. Thisfocus is generally presumed to correspond tomacaque MT plus part of the MST complex and

has therefore been identified as human MT+(Tootell et al., 1995) or as V5 (Watson et al.,1993).

Figure 5 includes many visuotopic areas thatwere mapped onto the human atlas using surface-based registration of an individual case fromHadjikhani et al. (1998). For technical reasonsthese maps do not include the representation ofthe fovea or far periphery, so the extent of theextrastriate areas is likely to be modestlyunderestimated. Interestingly, the sizes of V3d,V3v and V3A relative to V1 and V2 are allsubstantially greater in humans than in themacaque, suggesting a marked evolutionarydivergence in the relative sizes of nearby corticalareas. In the region adjoining dorsal V3, Smithet al. (1998) and Press et al. (2001) foundevidence for two representations, V3A and V3B,


instead of a single V3A, with V3B being locatedmore posterior (lower on the flat map). Area V7(Press et al., 2001; Tootell and Hadjikhani, 2001)is a visuotopically organized area that liesanterior to V3A; its location and extent isdisplayed on the atlas using dotted boundaries tosignify greater uncertainty.

Human area V4v lies antero-lateral to VP/V3vand contains a mirror-symmetric upper-fieldrepresentation. Interestingly, cortex lateral anddorsal to V4v, identified as LO (Van Oostende etal., 1997) or the LOC/LOP complex (Tootell andHadjikhani 2001), evidently lacks acomplementary lower-field representationequivalent to that described for macaque V4d.Instead, the LOC/LOP region represents bothupper and lower fields, but with an irregular andinconsistent map of polar angle and an apparentdiscontinuity in the transition between centraland peripheral eccentricities. LO, as described byGrill-Spector etal. (1998a,b; 2001), includesmost of LOC/LOP but extends further ventrallyand anteriorly (down and to the right on the flatmap). Area V8 lies anterior to V4v and containsa complete visuotopic map with a fovealrepresentation near its anterior margin to theright on the flat map (Hadjikhani et al., 1998, butsee Wade et al., 2002).

Tests using a variety of stimuli and behavioralparadigms besides those just discussed haverevealed several additional regions of functionalspecialization. Ventral occipito-temporal cortexcontains a region preferentially activated byobject versus non-object stimuli. Based onpublished stereotactic (Talairach) coordinates,

foci involved in analysis of faces, houses, andchairs are concentrated in a region (red dottedoutline in Fig. 5E) that partially overlaps V8 onthe atlas map but extends more anteriorly(Kanwisher et al., 1997; Ishai et al., 1999; Haxbyet al., 1999). This region has been proposed toinclude a fusiform face area (FF) and aparahippocampal place area (PP) (Kanwisher etal., 1997; Epstein and Kanwisher, 1998) and isaccordingly identified as FF/PP in Figure 5E.Other studies suggest that these may notconstitute distinct areas but rather a functionalgradient within a larger subdivision (Haxby etal., 2001).

In the parietal lobe, visually-related activationshave been reported in a large swath of cortex inand near the intraparietal sulcus, dorsal andanterior to the known visuotopic areas.Paradigms effective in activating this regioninclude shifting visual attention, target-directedeye movements, visual motion, and spatialanalyses (Haxby et al., 1994; Corbetta et al.,1998; Lewis and DeYoe, 2000; Lewis et al.,2001). This region presumably includes anumber of functionally distinct areas orsubdivisions that have not been clearlydiscriminated using existing paradigms andanalysis methods.

Macaque-Human comparisons.

While there are many striking similarities invisual cortical organization between macaqueand human, there are numerous differences aswell. Some of the differences are in relative sizeand in the geographic location of areas, but

Figure 5 Identified visual areas on the Human.colin surface-based atlas. See Abbreviations list for full names. Theboundary of MT+ on the atlas map was estimated by projecting the motion-related activation foci tabulated by VanEssen and Drury (1997) onto the atlas surface. The visuotopic map from Figure 5A of Tootell and Hadjikhani. (2001)was then registered to the atlas using the V1/V2 boundary and the posterior boundary of MT+ as landmarks. Additionalareas LO and V7 were drawn manually onto the atlas, based respectively on the studies of Tootell and Hadjikhani(2001) and Press et al. (2001). A. Lateral view B. Medial view. C. Inflated lateral view. D. Inflated medial view. E.Flat map view. The Red dotted contour represents the main cluster activation focus center involved in face and placeanalysis (see text).others presumably reflect fundamentaldifferences in the existence of areas or in theirtopological relationships to one another. Auseful general strategy for examining theserelationships and candidate homologies is to usesurface-based registration between species (VanEssen et al., 1998, 2001a). While neither provingnor disproving any particular homology,interspecies registration of surfaces provides agood testbed for exploring any particular set ofproposed homologies implied for therelationships among areas in intervening regions.

In Figure 6, the macaque and human maps wereregistered to one another using explicitlandmarks that are likely to reflect genuinehomologies. These landmarks (colored contoursin Fig. 6) include the fundus of the central sulcus(near the boundary between somatosensory and

motor cortex); the fundus of the Sylvian fissure(near the boundary between somatosensory andauditory cortex); the boundaries of V1, V2, andMT+; and the boundaries of neocortex along themedial wall (Fig. 6A, B). To avoid confoundsassociated with artificial cuts on the flat maps,the landmarks were first projected to macaqueand human spherical maps (not shown); theregistration was applied to the spherical maps;and the deformed visual areas were thenprojected back to the flat maps. This is shown inFigure 6D for the human visual areas deformedto the shape of the macaque flat map (andsuperimposed on the macaque sulcal map). InFigure 6D, the corresponding relationships areshown with the macaque visual areas deformedto the shape of the human flat map (andsuperimposed on the human sulcal map) Themacaque map (before and after deformation)


includes the composite of all ten partitioningschemes painted onto the map, plus the Lewisand Van Essen partitioning scheme (blackcontours). The human map includes the samevisuotopic areas delineated in Figure 5.

The deformation between species necessarilyinvolves highly nonlinear distortions, mainlybecause V1 and V2 are much smaller (relative tooverall cortical size) in humans vs. macaques,and also because the location of MT (relative tofoveal V2 and to the Sylvian fissure) is moreposterior and ventral in the human versus themacaque map. Consequently, in Figure 6D,there is considerably more expansion of parietalareas than inferotemporal areas on the deformedmacaque map. The parietal lobe as defined byconventional geographic landmarks is slightlylarger in the human atlas compared to themacaque (21% versus 19% of total neocorticalsurface area on the fiducial surface), whereas thesize of the region bounded by V2, MT, and thefundus of the central sulcus is substantiallylarger in humans (27% versus 21% ofneocortex). The species difference is even largerin the frontal lobe, which occupies 36% ofhuman neocortex but only 25% in the macaque).

Several potential homologies can be evaluatedby comparing individual areas and clusters ofareas in the deformed macaque visual areas inFigure 6D to the human map in Fig. 6B (or,equivalently, comparing the deformed humanareas in Fig. 6D to the macaque map in Fig. 6A).One particular issue of interest is the relationshipbetween macaque areas V4 and TEO/VOT onthe one hand and human areas V4v, LOC/LOP,and V8 on the other hand. Deformed macaqueV4v overlaps extensively with human V4v, anddeformed macaque V4d overlaps with humanLOC/LOP, consistent with the proposedhomologies for these areas. In contrast,deformed macaque V4 differs greatly in size andlocation compared to human V8. As emphasizedby Tootell and Hadjikhani (2001) these and otherdifferences argue strongly against a homologybetween macaque V4 and human V8, asproposed by Zeki et al. (1998).

Based on its location just anterior to V4v,human V8 is a candidate for homology with areaTEO in the Ungerleider and Desimone schemeand with VOT in the Felleman/Lewis/Van Essenschemes. However, the visuotopic organization

of human V8 is not in accord with that reportedfor either TEO or VOT, making a homologyimplausible on those grounds. For human V7, itslocation just anterior to V3A makes areas DPand zone LOP the most plausible candidates forhomologues in the macaque, but a visuotopicmap consistent with that in V7 has not beenreported in this region.

Parietal visual cortex in the deformed macaquemap overlaps extensively with human parietalvisual cortex but is shifted somewhat morelateral (lower on this part of the map). Candidatehomologies have been suggested betweenmacaque LIP and human parietal areas involvedin attention and eye movements (e.g., Corbetta etal., 1998; Sereno et al., 2001). These and othercandidate homologies can be used as additionalconstraints to test for mappings that bring the

Figure 6. Comparisons between macaque and human visual cortex using interspecies surface-basedregistration. A. Macaque atlas flat map showing the composite map of visual areas (same as Figure 3C)plus the boundaries of the Lewis and Van Essen scheme (same contours as in Figure 2C) and the landmarksused to constrain the registration. B. Human atlas flat map showing visuotopic and functionally definedareas plus the landmarks used to constrain the registration. C. Deformed human visual areas overlaid onthe macaque flat map. D. Deformed macaque visual areas overlaid on the human flat map. Data can beaccessed via http://brainmap.wustl.edu:8081/sums/archivelist.do?archive_id=450135

overall parietal regions into closer register andmay suggest additional homologies.

Deformed macaque inferotemporal and ventralsuperior temporal areas (blue and green in Fig.4D) lie well anterior (to the right on the flat map)to the known visually responsive regions ofhuman occipito-temporal cortex. One possibleexplanation for this discrepancy is that humanvisual cortex extends farther anterior in thetemporal lobe than previously recognized.Alternatively, the homologues of the macaqueinferotemporal complex may lie within currentlydesignated human visual cortex, anterior to V8and/or flanking it. If so, this would signify aneven more pronounced over-emphasis on parietalvisual areas and under-emphasis oninferotemporal visual areas in humans comparedto macaques.

Other species. Although the focus of thischapter has been on the macaque and human,there is an enormous amount to be gained byobtaining a better understanding of visual cortex

in other primate and non-primate species. Therehas been substantial progress in elucidatingvisual cortical organization in other nonhumanprimates, most notably the owl monkey but alsoseveral other species as well (Kaas, 1997; Rosa,1997). In brief, these reveal similar patterns,especially for occipital visual areas, but alsomany indications of significant differences.

Rodents, particularly the mouse, are likely tobecome increasingly important as model systemsfor studying many aspects of corticalorganization. Studies of the rat and mouse haverevealed a primary visual area surrounded by amodest number of extrastriate visual areas(Wagor et al., 1980; Coogan and Burkhalter,1990). However, the magnitude of differences inthe overall number and layout of visual areasfrom species in different orders remains to bedetermined. A mouse surface-based atlas, akinto those for the macaque and human illustratedhere, has recently been generated (Van Essen etal., 2002) and should aid in charting the detailedorganization of mouse visual cortex.


Concluding remarks.Progress in elucidating visual cortical

organization is likely to accelerate markedly inthe next few years, particularly with the use offMRI and other imaging methods that can beapplied to monkeys (Logothetis et al., 1999;Vanduffel et al. 2001 ) and to rodents as well asto humans. Because these data are representeddigitally from the outset, registering such data tosurface-based atlases should be easier and moreaccurate than for many of the data sets illustratedin this chapter. As the richness and complexityof such atlases and associated databases grow,the ways in which neuroscientists routinelyaccess the data will likely evolve to beprogressively more web-based, analogous to howmolecular biologists use search engines and largedatabases to access an increasingly large fractionof the information they use in their research.


AbbreviationsCortical Areas:DP dorsal prelunate areaFST floor of superior temporal areaIPa area IPa from Cusick et al., (1995)LIPd lateral intraparietal (dorsal)LIPv lateral intraparietal (ventral)MDP medial dorsal parietal areaMIP medial intraparietal areaMST medial superior temporal areaMT middle temporal areaPIP posterior intraparietal areaPO parietal-occipital areaTAa area TAa from Cusick et al., (1995)TEad antero-dorsal division of TETEav antero-ventral division of TETF temporal area FTH temporal area HTpt temporo-parietal areaTPOc temporal parietal occipital (caudal)TPOi temporal parietal occipital (intermediate)TPOr temporal parietal occipital (rostral)VIP ventral intraparietalVIP* heavily myelinated subdivision of VIPV1 visual area 1V2 visual area 2V3 visual area 3V3A visual area V3AV4 visual area 4V4t V4 transitional areaVOT ventral occipitotemporal areaVP ventral posterior area7a visual area 7a46 visual area 46

Cortical ZonesLOP lateral occipital parietalMST medial superior temporal areaMSTd dorsal subdivision of MSTMSTl lateral subdivision of MSTMSTda dorso-anterior subdivision of MSTMSTdp dorso-posterior subdivision of MSTMSTm medial subdivision of MSTVIPl lateral subdivision of VIPVIPm medial subdivision of VIPV4ta V4 transitional area (anterior)V4tp V4 transitional area (posterior)

7al lateral area 7aDMOcx Dorso-medial occipitalcomplexIPdITcx Inferotemporal complexMSTcx Medial Superior temporalcomplexMTc caudal to Middle TemporalOAaPGaPOa-e external division of areaPOaPOa-i internal division of area POaPPcx Posterior parietal complexTE1 subdivision 1 of TETE1-3d dorsal subdivision of TE1-3TE1-3v ventral subdivision of TE1-3TE2 subdivision 2 of TETE3 subdivision 3 of TETEa/m subdivisions a and m of TETEm medial division of TETPO temporo-pareital-occipitalareaV2d dorsal division of V2V2v ventral division of V2V3d dorsal division of V3V3v ventral diivision of V3V6 visual area 6V6A Visual area 6AVSTcx Ventral superior temporalcomplex


REFERENCESBaylis, G.C., E.T. Rolls, and C.M. Leonard (1987)

Functional subdivisions of the temporal lobeneocortex. J. Neurosci. 7(2):330-342.

Blatt, G.J., R.A. Andersen, and G.R. Stoner (1990)Visual receptive field organization andcortico-cortical connections of the lateralintraparietal area (Area LIP) in theMacaque. J. Comp. Neurol. 299:421-445.

Boussaud, D., Ungerleider, L.C. and Desimone, R.(1990) Pathways for motion analysis:Cortical connections of the medial superiortemporal and fundus of the superiortemporal visual areas in the macaque. J.Comp. Neurol. 296: 462-495.

Boussaud, D., Desimone, R. and Ungerleider, L.G.(1990)) Visual topography of area TEO inthe macaque. J. Comp. Neurol. 306: 554-575.

Burton H, Sinclair RJ. Attending to and rememberingtactile stimuli: a review of brain imagingdata and single-neuron responses. J ClinNeurophysiol. 2000 Nov;17(6):575-91.Review.

Colby, C.L., Gattass, R., Olson, C.R. and Gross, C.G.(1988) Topographic organization of corticalafferents to extrastriate visual area PO in themacaque: a dual tracer study. J. Comp.Neurol., 269: 392-413.

Coogan, T.A. and Burkhalter, A. (1990) Conservedpatterns of corticocortical connectionsdefine areal hierarchy in rat visual cortex.Exp. Brain Res. 80: 49-53.

Corbetta, M., Akbudak, E., Conturo, T.E., Snyder,A.Z , Ollinger, J.M.,Drury, H.A.,Linenweber, M.R., Raichle, M.E., VanEssen, D.C. Petersen, S.E and Shulman,G.L. (1998) A common network offunctional areas for attention and eyemovements. Neuron 21, 761-773.

Cusick, C.G. (1997) The superior temporalpolysensory region in monkeys. In: CerebralCortex, Volume 12, Extrastriate Cortex inPrimates, (Rockland KS, Kaas JH, andPeters A, eds), New York, Plenum Press, pp.435-468.

Desimone, R. and Ungerleider, L.B. (1986) Multiplevisual areas in the caudal superior temporalsulcus of the macaque. J. Comp. Neurol.248: 164-189.

Desimone, R. and Ungerleider (1989) Neuralmechanisms of visual processing inmonkeys. Handbook of Neuropsychology,Vol. 2 In: Boller, F. and Grafman, J., eds.,pp. 267-299, Elsevier.

DeYoe, E.A., Carman, G., Bandetinni, P., Glickman,S., Wieser, J., Cox, R., Miller, D., and Neitz,J. (1996) Mapping striate and extrastriate

visual areas in human cerebral cortex. Proc.Natl. Acad. Sci. USA 93:2382-2386.

Drury, H.A., Van Essen, D.C., Corbetta, M., &Snyder, A.Z. (1999) Surface-based analysesof the human cerebral cortex. In: BrainWarping, San Diego A.Toga et al., eds.,Academic Press, pp. 337-363.

Epstein, R. and Kanwisher, N. (1998) A corticalrepresentation of the local visualenvironment. Nature 392: 598-601.

Felleman, D.J. and Van Essen, D.C. (1991)Distributed hierarchical processing inprimate cerebral cortex, Cerebral Cortex, 1:1-47.

Fischl, B., Sereno, M.I. & Dale, A.M. (1999a) Corticalsurface-based analysis. II: Inflation,flattening, and a surface-based coordinatesystem. NeuroImage 9:195-207.

Fischl B, Sereno MI, Tootell RB, & Dale AM(1999b) High-resolution intersubjectaveraging and a coordinate system for thecortical surface. Hum Brain Mapp.1999;8(4):272-84.

Galletti, C., P. Fattori, M Gamberini, and D.F. Kutz(1999) The cortical visual area V6: Brainlocation and visual topography. Eur. J.Neurosci. 11:3922-3936.

Gattass, R., A.P.B. Sousa, and C.G. Gross (1988)Visuotopic organization and extent of V3and V4 of the macaque. J. Neurosci.8(6):1831-1845.

Grill-Spector K., T. Kushnir, S. Edelman, Y. Itzchak,R. Malach, 1998a Cue-Invariant

Activation in Object-Related Areas of theHuman Occipital Lobe, Neuron, 21: 191-202.

Grill-Spector K., T. Kushnir, T. Hendler, S. Edelman,Y. Itzchak, R. Malach, 1998b A

Sequence of Object-Processing StagesRevealed by fMRI in the Human OccipitalLobe, Human Brain Mapping 6:316-328

Grill-Spector K., Z. Kourtzi, and N. Kanwisher (2001)The lateral occipital complex and its role inobject recognition. Vis. Res. 41: 1409-1422.

Hadjikhani, N., Liu, A.K., Dale, A.M., Cavanagh, P.& Tootell, R.B.H. (1998) Retinotopy andcolor sensitivity in human visual corticalarea V8. Nature Neuroscience 1:235-241.

Haxby, J.V., Ungerleider, L.G., Clark, V.P., Schouten,J.L., Hoffman, E.A. and Martin, A. (1999) Theeffect of face inversion on activity in humanneural systems for face and object perception.Neuron 22: 189-199.

Haxby JV, Horwitz B, Ungerleider LG, Maisog JM,Pietrini P Grady CL (1994) The functionalorganization of human extrastriate cortex: APET-rCBF study of selective attention tofaces and locations. J Neurosci 14:6336-6353.


Haxby JV, Gobbini MI, Furey ML, Ishai A, SchoutenJL, Pietrini P. Distributed and overlappingrepresentations of faces and objects inventral temporal cortex. Science. 2001293(5539):2425-30.

Holmes, C.J., Hoge, R., Collins, L., Woods, R., Toga,A.W. and Evans, A.C. (1998) Enhancementof MR images using registration for signalaveraging. J. Comp. Asst. Tomag. 22: 324-333.

Ishai, A., Ungerleider, L.G., Martin, A., Schouten,J.L., Haxby, J.V. (1999) Distributedrepresentation of objects in the human ventralvisual pathway. Proc. Natl. Acad. Sci. USA 96:9379-9384.

Kaas, J.H. (1997) Theories of visual cortexorganization in primates. In: Cerebral Cortex,Volume 12, Extrastriate Cortex in Primates,(Rockland KS, Kaas JH, and Peters A, eds), NewYork, Plenum Press, pp. 91-125.

Kanwisher, N., McDermottk, J. and Chun, MM (1997)The fusiform face area: A module in humanextrastriate cortex specialized for faceperception. J. Neurosci. 17: 4302-4311.

Komatsu, H., and R.H. Wurtz (1988) Relation ofcortical areas MT and MST to pursuit eyemovements. I. Localization and visual propertiesof neurons. J. Neurophys. 60(2):580-603.

Komatsu, H. and Wurtz, R.H. (1988b) Relation ofcortical areas MT and MST to pursuit eyemovements. III. Interaction with full-field visualstimulation. J. Neurophysiol., 60: 621-644.

Lewis JW, and DeYoe EA. (2000) A Comparison ofVisual and Auditory Motion Processing inHuman Cerebral Cortex. Cerebral Cortex10:873-888.

Lewis, J.W. and Van Essen, D.C. (2000a)Architectonic parcellation of parieto-occipital cortex and interconnected corticalregions in the Macaque monkey. J. Comp.Neurol. 428: 79-111.

Lewis, J.W. and Van Essen, D.C. (2000b) Cortico-cortical connections of visual, sensorimotor,and multimodal processing areas in theparietal lobe of the Macaque monkey. J.Comp. Neurol. 428: 112-137.

Lewis JW, Wightman, FL., Junion Dienger JL, DeYoeEA (2001) FMRI Activation in response tothe identification of natural sounds. Soc.Neurosci. Abstr. 27, Program #512.9

Logothetis, N.K., Guggenberger, H., Peled, S., andPauls, J. (1999) Functional imaging of themonkey brain, Nat. Neurosci. 6:555-562.

Lyon DC, Kaas JH. Evidence for a modified v3 withdorsal and ventral halves in macaquemonkeys. Neuron. 2002 Jan 31;33(3):453-61.

Maguire, W.M. and Baizer, J.S. (1984) Visuotopicorganization of the prelunate gyrus inRhesus monkey. J. Neurosci. 4: 1690-1704.

Maunsell, J.H.R., and D.C. Van Essen (1987)Topographical organization of the middletemporal visual area in the macaquemonkey: Representational biases and therelationship to callosal connections andmyeloarchitectonic boundaries. J. Comp.Neurol. 266:535-555.

Olavarria,, J.F. and Van Essen, D.C. (1997) Theglobal pattern of cytochrome oxidase stripesin visual area V2 of the macaque monkey.Cerebral Cortex 7: 395-404.

Oram and Penett 1996. Integration of form andmotion in the anterior superior temporalpolysensory area (STPa) of the macaquemonkey. J. Neurophysiol., 76: 109-129.

Press WA, Brewer AA, Dougherty RF, Wade AR,Wandell BA. Visual areas and spatialsummation in human visual cortex. VisionRes. 2001;41(10-11):1321-

Preuss, T.M., and P.S. Goldman-Rakic (1991b)Architectonics of the parietal and temporalassociation cortex in the strepsirhine primategalago compared to the anthropoid primatemacaca. J. Comp Neurol. 310:475-506.

Rademacher, J., Caviness Jr, V.S., Steinmetz, H., &Galaburda, A. M. (1993). Topographicalvariation of the human primary cortices:Implications for neuroimaging, brainmapping, and neurobiology.” CerebralCortex 3: 313-329.

Rosa, M.G.P. (1997) Visuotopic organization ofprimate extrastriate cortex. In: CerebralCortex, Volume 12, Extrastriate Cortex inPrimates, (Rockland KS, Kaas JH, andPeters A, eds), New York, Plenum Press, pp.127-203.

Saleem, K.S., and K. Tanaka (1996) Divergentprojections from the anterior inferotemporal areaTE to the perirhinal and entorhinal cortices in themacaque monkey. J. Neurosci. 16(15):4757-4775.

Seltzer, B., and D.N. Pandya (1978) Afferent corticalconnections and architectonics of thesuperior temporal sulcus and surroundingcortex in the rhesus monkey. Brain Res.149:1-24.

Seltzer, B., and D.N. Pandya (1980) Convergingvisual and somatic sensory cortical input tothe intraparietal sulcus of the rhesusmonkey. Brain Res. 192:339-351.

Seltzer, B., and D.N. Pandya (1986) Posterior parietalprojections to the intraparietal sulcus of therhesus monkey. Exp. Brain. Res. 62:459-469.

Sereno MI, Dale AM, Reppas JB, Kwong KK,Belliveau JW, Bardy TJ, Rosen BR, TootellRBH (1995) Borders of multiple visual areasin humans revealed by functional magneticresonance imaging. Science 268:889-893.


Sereno MI, Pitzalis S, Martinez A. Mapping ofcontralateral space in retinotopic coordinatesby a parietal cortical area in humans.Science. 2001 294(5545):1350-4.

Shipp, S. and Zeki, S. (1985) Segregation of pathwaysleading from V2 to areas V4 and V5 ofmacaque monkey visual cortex. Nature,315: 322-325.

Smith, A.T., Grenlee, M.W., Singh, K.D., Kraemer,F.M. and Hennig, J. (1998) The processingof first- and second-order motion in humanvisual cortex assessed by functionalmagnetic resonance imaging (fMRI). J.Neurosci. 18: 3816-3830.

Taira M, Tsutsui KI, Jiang M, Yara K, Sakata H.Parietal neurons represent surfaceorientation from the gradient of binoculardisparity. J Neurophysiol. 2000May;83(5):3140-6.

Tanaka, K. (1997) Columnar organization in theinferotemporal cortex. In: Cerebral Cortex,Volume 12, Extrastriate Cortex in Primates,(Rockland KS, Kaas JH, and Peters A, eds),New York, Plenum Press, pp. 469-495.

Tootell, RBH, Reppas JB, Kwong, KK, Malach, R.,Born, RT, Brady TJ, Rosen BR andBelliveau JW (1195) Functional analysis ofhuman MT and related visual cortcial areasusing magnetic resonance imaging. J.Neurosci. 15: 3215-3230.

Tootell, R.B.H. & Hadjikhani, N. (2001) Where is'dorsal V4' in human visual cortex?Retinotopic, topographic and functionalevidence. Cerebral Cortex (in press).

Ungerleider, L.G., and R. Desimone (1986) Corticalconnections of visual area MT in themacaque. J. Comp. Neurol. 248:190-22.

Van Essen, D.C. & Drury, H.A (1997) Structural andfunctional analyses of human cerebral cortexusing a surface-based atlas. J. Neuroscience17: 7079-7102.

Van Essen, D.C. and Gallant, J.L. (1994) Neuralmechanisms of form and motion processingin the primate visual system. Neuron, 13:1-10

Van Essen, D.C. (2002) Windows on the brain. Theemerging role of atlases and databases inneuroscience. Curr. Op. Neurobiol. 12:574-579

Van Essen, D.C., Newsome, W.T. & Maunsell, J.H.R.(1984) The visual field representation instriate cortex of the macaque monkey:asymmetries, anisotropies and individualvariability. Vision Res. 24: 429-448.

Van Essen, D.C., Felleman, D.F., DeYoe, E.A.,Olavarria, J.F. and Knierim, J.J. (1990)Modular and hierarchical organization ofextrastriate visual cortex in the macaquemonkey, Cold Spring Harbor Symp. Quant.Biol., 55: 679-696.

Van Essen, D.C., Drury, H.A., Joshi, S., & Miller,M.I. (1998) Functional and structuralmapping of human cerebral cortex:Solutions are in the surfaces. Proc Natl.Acad. Sci. USA 95:788-795.

Van Essen, D.C. Lewis, J.W,. Drury, H.A.,Hadjikhani, N., Tootell, R.B.H.,Bakircioglu, M. and Miller, M.I. 2001a.Mapping visual cortex in monkeys andhumans using surface-based atlases. VisionResearch 41: 1359-1378.

Van Essen, D.C., Dickson, J., Harwell, J., Hanlon, D.,Anderson, C.H. and Drury, H.A. 2001b. AnIntegrated Software System for Surface-based Analyses of Cerebral Cortex. Journalof American Medical InformaticsAssociation . 8:443-459.

Van Essen, D.C. Harwell, J., Hanlon, D., Dickson, J.,Snyder, A. and Cox, RW (2002) Mappingfunctional activation patterns onto cerebraland cerebellar surface-based atlases.NeuroImage ( (URL:http://www.academicpress.com/journals/hbm2002/14798.html).

Van Oostende S, Sunaert, S. Van Hecke, P., MarchalG., and Orban, GA (1997) The kineticoccipital (KO) region in man: an fMRIstudy. Cereb Cortex 7: 690-701.

Vanduffell W, Fize, D., Mandeville, J.B., Nelissen, K.,Van Hecke, P., Rosen, B.R., Tootell, R.B.,and Organ, G.A. (2001) Visual motionprocessing investigated using contrast agent-enhanced fMRI in awake behavingmonkeys. Neuron 32: 565-577.

Wade, A.R., Brewer, A.A., Rieger, J.W. and Wandell,B.A. (2002) Functional measurements ofhuman ventral occipital cortex: Retinotopyand color. Phil. Trans of the Royal Society(in press).

Wagor, E., Mangini, N.J., Pearlman, A.L. (1980)Retinotopic organization of striate andextrastriate visual cortex in the mouse. J.Comp. Neurol. 193: 187-202.

Watson JDG, Myers R, Frackowiak RSJ, Hajnal JV,Woods RP, Mazziotta JC, Shipp S, Zeki S(1993) Area V5 of the human brain:Evidence from a combined study usingpositron emission tomography and magneticresonance imaging. Cerebral Cortex 3:37-94.

Yukie, M., Takeuchi, H., Hasegawa, Y. and Iwai, E.(1990) Differential connectivity ofinferotemporal area TE with the amygdalaand the hippocampus in the monkey. In:Vision, Memory, and the Temporal Lobe(Iwai, E, Mishkin, M., eds), pp. New York:Elsevier.

Zeki, S.M. (1969) Representations of central visualfields in prestriate cortex of monkey. BrainRes. 14: 271-291.


Zeki, S., McKeefry, D. J., Bartels, A., & Frackowiak,R. S. J. (1998) Has a new color beendiscovered? Nature Neuroscience 1: 335-336.

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