Prediction, context, and competition in visual recognition

Annals of the New York Academy of Sciences

Volumn 1339, Issue 1, 2015, Pages 190-198

  Trapp, Sabrina ^a   Bar, Moshe ^b  

^a MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

^b BAR ILAN UNIVERSITY   (Israel)

Author keywords

Biased competition; Expectations; Object recognition; Orbitofrontal cortex; Perceptual hypothesis; Perceptual task; Top down

Indexed keywords

ARTICLE; ASSOCIATION; BRAIN; BRAIN FUNCTION; COMPETITION; CONCEPTUAL FRAMEWORK; FRONTAL CORTEX; HUMAN; HYPOTHESIS; INFORMATION PROCESSING; LEARNING; MAGNETOENCEPHALOGRAPHY; NERVE CELL; NONHUMAN; NOVEL OBJECT RECOGNITION TEST; ORBITAL CORTEX; PERCEPTION; PREDICTION; REINFORCEMENT; SENSORY STIMULATION; SIGNAL PROCESSING; VISION; VISUAL CORTEX; VISUAL INFORMATION; VISUAL MEMORY; VISUAL SYSTEM; FORECASTING; FRONTAL LOBE; PATTERN RECOGNITION; PHOTOSTIMULATION; PHYSIOLOGY; PROCEDURES;

FORECASTING; FRONTAL LOBE; HUMANS; PATTERN RECOGNITION, VISUAL; PHOTIC STIMULATION;

EID: 84925356710     PISSN: 00778923     EISSN: 17496632     Source Type: Book Series    
DOI: 10.1111/nyas.12680     Document Type: Article

References (74)

1. Kok, P., M. Failing & F.P. de Lange. 2013. Prior expectations evoke stimulus templates in the primary visual cortex. J. Cogn. Neurosci. 26: 1546-1554.
2. Summerfield, C. & E. Koechlin. 2008. A neural representation of prior information during perceptual inference. Neuron 59: 336-347.
3. Rao, R.P. & D.H. Ballard. 1999. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat. Neurosci. 2: 79-87.
4. Lee, T.S. & D. Mumford. 2003. Hierarchical Bayesian inference in the visual cortex. J. Opt. Soc. Am. A. 20: 1434-1448.
5. Bar, M. 2003. A cortical mechanism for triggering top-down facilitation in visual object recognition. J. Cogn. Neurosci. 15: 600-609.
6. Desimone, R. & J. Duncan. 1995. Neural Mechanisms of selective visual-attention. Annu. Rev. Neurosci. 18: 193-222.
7. Moran, J. & R. Desimone, 1985. Selective attention gates visual processing in the extrastriate cortex. Science 229: 782-784.
8. Kastner, S., P. De Weerd, R. Desimone & L.G. Ungerleider. 1998. Mechanisms of directed attention in the human extrastriate cortex as revealed by functional MRI. Science 282: 108-111.
9. Kastner, S., M.A. Pinsk, P. De Weerd, et al. 1999. Increased activity in human visual cortex during directed attention in the absence of visual stimulation. Neuron 4: 751-761.
10. Leopold, D. & N.K. Logothetis. 1999. Multistable phenomena: changing views in perception. Trends Cogn. Sci. 3: 254-264.
11. Leopold, D.A. & N.K. Logothetis. 1996. Activity changes in early visual cortex reflect monkeys' percepts during binocular rivalry. Nature 379: 549-553.
12. Sundareswara, R. & P.R. Schrater. 2008. Perceptual multistability predicted by search model for Bayesian decisions. J. Vis. 8(5): 12, 1-19.
13. van Ee, R., W.J. Adams & P. Mamassian. 2003. Bayesian modeling of cue interaction: bistability in stereoscopic slant perception. J. Opt. Soc. Am. A. 20: 1398-1406.
14. Ratcliff, R. & G. McKoon. 2008. The diffusion decision model: theory and data for two-choice decision tasks. Neural Comput. 20: 873-922.
15. Voss, A., M. Nagler & V. Lerch. 2013. Diffusion models in experimental psychology: a practical introduction. Exp. Psychol. 60: 385-402.
16. Mulder, M.J., E.J. Wagenmakers, R. Ratcliff, et al. 2012. Bias in the brain: a diffusion model analysis of prior probability and potential payoff. J. Neurosci. 32: 2335-2343.
17. Hanks, T.D., M.E. Mazurek, R. Kiani, et al. 2011. Elapsed decision time affects the weighting of prior probability in a perceptual decision task. J. Neurosci. 31: 6339-6352.
18. Cisek, P. 2007. Cortical mechanisms of action selection: the affordance competition hypothesis. Philos. Trans. R. Soc. Lond. B 362: 1585-1599.
19. Cisek, P. & J.F. Kalaska. 2005. Neural correlates of reaching decisions in dorsal premotor cortex: specification of multiple direction choices and final selection of action. Neuron 45: 801-814.
20. Bar, M & S. Ullman. 1996. Spatial context in recognition. Perception 25: 343-352.
21. Bar, M. 2004. Visual objects in context. Nat Rev. Neurosci. 5: 617-629.
22. Boyce S.J., A. Pollatsek & K. Rayner. 1989. Effect of background information on object identification. J. Exp. Psychol. Hum. Percept. Perform. 15: 556-566.
23. Davenport, J.L. & M.C. Potter. 2004. Scene consistency in object and background perception. Psychol. Sci. 15: 559-564.
24. Chun, M.M. & Y. Jiang. 1998. Contextual cueing: Implicit learning and memory of visual context guides spatial attention. Cogn. Psychol. 36: 28-71.
25. Palmer, S.E. 1975. The effects of contextual scenes on the identification of objects. Mem. Cogn. 3: 519-526.
26. Biederman, I., A.L. Glass & E.W. Stacy. 1973. Searching for objects in real-world scenes. J. Exp. Psychol. Gen. 97: 22-27.
27. Gilbert, C.D. & W. Li. 2013. Top-down influences on visual processing. Nat. Rev. Neurosci. 14: 350-363.
28. Dawson, M.R. 1987. Moving contexts do affect the perceived direction of apparent motion in motion competition displays. Vision Res. 27: 799-809.
29. Sobel, K.V. & R. Blake. 2002. How context influences predominance during binocular rivalry. Perception 31: 813-824.
30. Orban, G.A., D. Van Essen & W. Vanduffel. 2004. Comparative mapping of higher visual areas in monkeys and humans. Trends Cogn. Sci. 8: 315-324.
31. Bar, M. & E. Aminoff. 2003. Cortical analysis of visual context. Neuron 38: 347-358.
32. Aminoff, E.M., N. Gronau & M. Bar. 2007. The parahippocampal cortex mediates spatial and nonspatial associations. Cereb. Cortex 17: 1493-1503.
33. Aminoff, E.M., K. Kveraga & M. Bar. 2013. The role of the parahippocampal cortex in cognition. Trends Cogn. Sci. 17: 379-390.
34. Sakai, K. 2008. Task set and prefrontal cortex. Annu. Rev. Neurosci. 31: 219-245.
35. Sakagami, M. & K. Tsutsui. 1999. The hierarchical organization of decision making in the primate prefrontal cortex. Neurosci. Res. 34: 79-89.
36. Sakai, K. & R.E. Passingham. 2003. Prefrontal interactions reflect future task operations. Nat. Neurosci. 6: 75-81.
37. Barbas, H. 2000. Connections underlying the synthesis of cognition, memory, and emotion in primate prefrontal cortices. Brain Res. Bull. 52: 319-330.
38. Cavada, C., T. Company, J. Tejedor, et al. 2000. The anatomical connections of the macaque monkey orbitofrontal cortex. A review. Cereb. Cortex 10: 220-242.
39. Kringelbach, M.L. & E.T. Rolls. 2004. The functional neuroanatomy of the human orbitofrontal cortex: Evidence from neuroimaging and neuropsychology. Progress Neurobiol. 72: 341-372.
40. Dikker, S. & L. Pylkkänen. 2013. Predicting language: MEG evidence for lexical preactivation. Brain Lang. 127: 55-64.
41. Freeman, J.B., Y. Ma, M. Barth, et al. 2015. The neural basis of contextual influences on face categorization. Cereb. Cortex Advanced Online Publication. 25: 415-422.
42. Oliva, A. & A. Torralba. 2001. Modeling the shape of a scene: a holistic representation of the spatial envelope. Int. J. Comput. Vision 42: 145-175.
43. Kihara, K. & Y. Takeda. 2010. Time course of the integration of spatial frequency-based information in natural scenes. Vision Res. 50: 2158-2162.
44. De Cesarei, A. & G.R. Loftus. 2011. Global and local vision in natural scene identification. Psychon. Bull. Rev. 18: 840-847.
45. Mu, T. & S. Li. 2013. The neural signature of spatial frequency-based information integration in scene perception. Exp. Brain Res. 227: 367-377.
46. Musel, B., C. Bordie, M. Dojat, et al. 2013. Retinotopic and lateralized processing of spatial frequencies in human visual cortex during scene categorization. J. Cogn. Neurosci. 25: 1315-1331.
47. Schyns, P.G. & A. Oliva. 1994. From blobs to boundary edges: evidence for time- and spatial- dependent scene recognition. Psychol. Sci. 5: 195-200.
48. Bar, M., K.S. Kassam, A.S. Ghuman, et al. 2006. Top-down facilitation of visual recognition. Proc. Natl. Acad. Sci. U.S.A. 1032: 449-454.
49. Kveraga, K., J. Boshyan & M. Bar. 2007 Magnocellular projections as the trigger of top-down facilitation in recognition. J Neurosci. 27: 13232-13240.
50. Kaplan, E. 2004. "The M, P, and K pathways of the primate visual system." In The Visual Neuroscience. L. M. Chalupa & J. S. Werner, Eds.: 481-494. Cambridge, MA: The MIT Press.
51. Kaplan, E. & R.M. Shapley. 1986. The primate retina contains two types of ganglion cells, with high and low contrast sensitivity. Proc. Natl. Acad. Sci. U.S.A. 83: 2755-2757.
52. Wiesel, T.N. & D.H. Hubel. 1966. Spatial and chromatic interactions in the lateral geniculate body of the rhesus monkey. J. Neurophysiol. 29: 1115-1156.
53. Wassle, H. & B.B. Boycott. 1991. Functional architecture of the mammalian retina. Physiol. Rev. 71: 447-480.
54. Chaumon, M., K. Kveraga, L.F. Barrett & M. Bar. 2014. Visual predictions in the orbitofrontal cortex rely on associative content. Cereb. Cortex 24: 2899-2907.
55. Li, F.F., R. VanRullen, C. Koch & P. Perona. 2002. Rapid natural scene categorization in the near absence of attention. Proc. Natl. Acad. Sci. U.S.A. 99: 9596-9601.
56. Thorpe, S.J., D. Fize & C. Marlot. 1996. Speed of processing in the human visual system. Nature 381: 520-522.
57. Breitmeyer, B.G. 1975. Simple reaction time as a measure of the temporal response properties of the transient and sustained channels. Vision Res. 15: 1411-1412.
58. Bullier, J. 2001. Integrated model of visual processing. Brain Res. Rev. 36: 96-107.
59. Van Essen, D.C. & E.A. Deyoe. 1995. "Concurrent processing in the primate visual cortex." In The Cognitive Neurosciences M. Gazzaniga, Ed.: 383-400. Cambridge: Bradford Book.
60. Bar, M., R. Tootell, D. Schacter, et al. 2001. Cortical mechanisms of explicit visual object recogntion. Neuron 29: 529-535.
61. Shenhav, A., L.F. Barrett & M. Bar. 2012. Affective value and associative processing share a cortical substrate. Cogn. Affect. Behav. Neurosci. 13: 46-59.
62. Gottfried, J.A., J. O'Doherty & J.R. Dolan. 2003. Encoding predictive reward value in human amygdala and orbitofrontal cortex. Science 301: 1104-1107.
63. Kahnt, K., J. Heinzle, S.Q. Park & J.D. Haynes. 2010. The neural code of reward anticipation in human orbitofrontal cortex. Proc. Natl. Acad. Sci. U.S.A. 107: 6010-6015.
64. Takahashi, Y.K., C.Y. Chang, F. Lucantonio, et al. 2013. Neural estimates of imagined outcomes in the orbitofrontal cortex drive behavior and learning. Neuron 16: 507-518.
65. O'Shea, J. & V. Walsh. 2006. Cognitive Neuroscience: trickle-down theories of vision. Curr. Biol. 166: 206-209.
66. Horr, N.K., C. Braun & K.G. Volz. 2014. Feeling before knowing why: the role of the orbitofrontal cortex in intuitive judgments-an MEG study. Cogn. Affect. Behav. Neurosci. 14: 1271-1285.
67. Hsu, M., R. Bhatt, D. Adolphs, et al. 2005. Neural systems responding to degrees of uncertainty in human decision making. Science 210: 1680-1683.
68. Volz, K.G., R. Rübsamen & D.Y. von Cramon. 2008. Cortical regions activated by the subjective sense of perceptual coherence of environmental sounds: a proposal for a neuroscience of intuition. Cogn. Affect. Behav. Neurosci. 8: 318-328.
69. Wilson, R.C., Y.K. Takahashi, G. Schoenbaum & Y. Niv. 2014. Orbitofrontal cortex as a cognitive map of task space. Neuron 81: 267-279.
70. Schoenbaum, G. & B. Setlow. 2001. Integrating orbitofrontal cortex into prefrontal theory: common processing themes across species and subdivision. Learn Mem. 8: 134-147.
71. Duncan, J. & A.M. Owen. 2000. Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends Neurosci. 23: 475-483.
72. Miller, E.K. & J.D. Cohen. 2001. An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24: 167-202.
73. Kveraga, K., A.S. Ghuman, K.S. Kassam, et al. 2011. Early onset of neural synchronization in the contextual associations network. Proc. Natl. Acad. Sci. U.S.A. 108: 3389-3394.
74. Friston, K. 2005. A theory of cortical responses. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360: 815-836.