Many Gestalt phenomena have been described in terms of perception of a whole being not equal to the sum of its parts. It is unclear how these phenomena emerge in the brain. We used functional MRI to study the neural basis of the behavioral configural-superiority effect (i.e., visual search is more efficient when an odd element is part of a configuration than when it is presented by itself). We found that searching for the odd element in a display of four line segments (parts) was facilitated by adding two additional line segments to each of them (creating whole shapes). Functional MRI–based decoding of neural responses to the position of the odd element revealed a neural configural-superiority effect in shape-selective regions but not in low-level retinotopic areas, where decoding of parts was more pronounced. These results show how at least some Gestalt phenomena in vision emerge only at the higher stages of visual information processing and suggest that feed-forward processing might be sufficient to produce such phenomena.
AlbrightT. D.StonerG. R. (2002). Contextual influences on visual processing. Annual Review of Neuroscience, 25, 339–379.
2.
AltmannC. F.BülthoffH. H.KourtziZ. (2003). Perceptual organization of local elements into global shapes in the human visual cortex. Current Biology, 13, 342–349.
3.
AshM. G. (1995). Gestalt psychology in German culture, 1890–1967: Holism and the quest for objectivity. Cambridge, England: Cambridge University Press.
4.
BarM.KassamK. S.GhumanA. S.BoshyanJ.SchmidA. M.DaleA. M.. . . HalgrenE. (2006). Top-down facilitation of visual recognition. Proceedings of the National Academy of Sciences, USA, 103, 449–454.
5.
BiedermanI. (1987). Recognition-by-components: A theory of human image understanding. Psychological Review, 94, 115–147.
CraftE.SchutzeH.NieburE.von der HeydtR. (2007). A neural model of figure-ground organization. Journal of Neurophysiology, 97, 4310–4326.
8.
DesimoneR.AlbrightT.GrossC.BruceC. (1984). Stimulus-selective properties of inferior temporal neurons in the macaque. Journal of Neuroscience, 4, 2051–2062.
9.
FellemanD. J.Van EssenD. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1, 1–47.
10.
Grill-SpectorK.KushnirT.HendlerT.EdelmanS.ItzchakY.MalachR. (1998). A sequence of object-processing stages revealed by fMRI in the human occipital lobe. Human Brain Mapping, 6, 316–328.
11.
GrossbergS.MingollaE.RossW. D. (1997). Visual brain and visual perception: How does the cortex do perceptual grouping?Trends in Neurosciences, 20, 106–111.
12.
HankeM.HalchenkoY.SederbergP.HansonS.HaxbyJ.PollmannS. (2009). PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data. Neuroinformatics, 7, 37–53.
13.
HaxbyJ. V.GobbiniM. I.FureyM. L.IshaiA.SchoutenJ. L.PietriniP. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 2425–2430.
14.
HochsteinS.AhissarM. (2002). View from the top: Hierarchies and reverse hierarchies in the visual system. Neuron, 36, 791–804.
15.
KamitaniY.TongF. (2005). Decoding the visual and subjective contents of the human brain. Nature Neuroscience, 8, 679–685.
KogoN.StrechaC.Van GoolL.WagemansJ. (2010). Surface construction by a 2-D differentiation-integration process: A neurocomputational model for perceived border ownership, depth, and lightness in Kanizsa figures. Psychological Review, 117, 406–439.
18.
KourtziZ.KanwisherN. (2001). Representation of perceived object shape by the human lateral occipital complex. Science, 293, 1506–1509.
19.
KourtziZ.ToliasA. S.AltmannC. F.AugathM.LogothetisN. K. (2003). Integration of local features into global shapes: Monkey and human fMRI studies. Neuron, 37, 333–346.
20.
LammeV. A. F.RoelfsemaP. R. (2000). The distinct modes of vision offered by feedforward and recurrent processing. Trends in Neurosciences, 23, 571–579.
21.
MurrayS. O.BoyaciH.KerstenD. (2006). The representation of perceived angular size in human primary visual cortex. Nature Neuroscience, 9, 429–434.
22.
NikolaevA. R.GepshteinS.KubovyM.van LeeuwenC. (2008). Dissociation of early evoked cortical activity in perceptual grouping. Experimental Brain Research, 186, 107–122.
23.
Op de BeeckH. P.BrantsM.BaeckA.WagemansJ. (2010). Distributed subordinate specificity for bodies, faces, and buildings in human ventral visual cortex. NeuroImage, 49, 3414–3425.
24.
Op de BeeckH. P.TorfsK.WagemansJ. (2008). Perceived shape similarity among unfamiliar objects and the organization of the human object vision pathway. Journal of Neuroscience, 28, 10111–10123.
25.
OstwaldD.LamJ. M.LiS.KourtziZ. (2008). Neural coding of global form in the human visual cortex. Journal of Neurophysiology, 99, 2456–2469.
26.
PeirceJ. W. (2007). PsychoPy: Psychophysics software in Python. Journal of Neuroscience Methods, 162, 8–13.
PomerantzJ. R.SagerL. C.StoeverR. J. (1977). Perception of wholes and of their component parts: Some configural superiority effects. Journal of Experimental Psychology: Human Perception and Performance, 3, 422–435.
29.
RiesenhuberM.PoggioT. (1999). Hierarchical models of object recognition in cortex. Nature Neuroscience, 2, 1019–1025.
30.
SigmanM.GilbertC. D. (2000). Learning to find a shape. Nature Neuroscience, 3, 264–269.
31.
SpillmannL. (2009). Phenomenology and neurophysiological correlations: Two approaches to perception research. Vision Research, 49, 1507–1521.
32.
TanakaK.SaitoH.FukadaY.MoriyaM. (1991). Coding visual images of objects in the inferotemporal cortex of the macaque monkey. Journal of Neurophysiology, 66, 170–189.
33.
TanskanenT.SaarinenJ.ParkkonenL.HariR. (2008). From local to global: Cortical dynamics of contour integration. Journal of Vision, 8(7), Article 15. Retrieved from http://www.journalofvision.org/content/8/7/15
34.
TootellR.ReppasJ.KwongK.MalachR.BornR.BradyT.. . . BelliveauJ. W. (1995). Functional analysis of human MT and related visual cortical areas using magnetic resonance imaging. Journal of Neuroscience, 15, 3215–3230.
35.
Van EssenD. C.DruryH. A.DicksonJ.HarwellJ.HanlonD.AndersonC. H. (2001). An integrated software suite for surface-based analyses of cerebral cortex. Journal of the American Medical Informatics Association, 8, 443–459.
36.
VeceraS. P.O’ReillyR. C. (1998). Figure-ground organization and object recognition processes: An interactive account. Journal of Experimental Psychology: Human Perception and Performance, 24, 441–462.
37.
WagemansJ.WichmannF. A.Op de BeeckH. (2005). Visual perception I: Basic principles. In LambertsK.GoldstoneR. L. (Eds.), Handbook of cognition (pp. 3–47). London, England: Sage.
38.
WertheimerM. (1922). Untersuchungen zur Lehre von der Gestalt, I: Prinzipielle bemerkungen [Investigations of the principles of Gestalt, I: Fundamental remarks]. Psychologische Forschung, 1, 47–58.
39.
WilliamsM. A.BakerC. I.Op de BeeckH. P.Mok ShimW.DangS.TriantafyllouC.KanwisherN. G. (2008). Feedback of visual object information to foveal retinotopic cortex. Nature Neuroscience, 11, 1439–1445.
40.
WundtW. M. (1874). Grundzüge der physiologischen psychologie [Principles of physiological psychology]. Leipzig, Germany: W. Engelman.
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