Flexible cognitive resources: Competitive content maps for attention and memory

Trends in Cognitive Sciences

Volumn 17, Issue 3, 2013, Pages 134-141

  Franconeri, Steven L ^a   Alvarez, George A ^b   Cavanagh, Patrick ^c  

^a NORTHWESTERN UNIVERSITY   (United States)

^b HARVARD UNIVERSITY   (United States)

^c UNIVERSITÉ PARIS DESCARTES   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CAPACITY LIMIT; COGNITIVE CAPACITY; COGNITIVE RESOURCES; PROCESSING RESOURCES; REAL ESTATE; SHORT TERM MEMORY; VISUAL SPATIAL ATTENTION;

COGNITIVE SYSTEMS;

ATTENTION; BRAIN MAPPING; COGNITION; EYE MOVEMENT; FRONTAL EYE FIELD; HUMAN; INFORMATION; MEMORY; RECOGNITION; REVIEW; SHORT TERM MEMORY;

ATTENTION; BRAIN; BRAIN MAPPING; COGNITION; HUMANS; MEMORY; VISUAL PERCEPTION;

EID: 84875273398     PISSN: 13646613     EISSN: 1879307X     Source Type: Journal    
DOI: 10.1016/j.tics.2013.01.010     Document Type: Review

References (100)

1. Broadbent D. Perception and Communication 1958, Pergamon Press.
2. Norman D.A., Bobrow D.G. On data-limited and resource-limited processes. Cogn. Psychol. 1975, 7:44-64.
3. Posner M.I., et al. Attention and the detection of signals. J. Exp. Psychol. Gen. 1980, 109:160-174.
4. Mountcastle V.B. The columnar organization of the neocortex. Brain 1997, 120:701-722.
5. Desimone R., Duncan J. Neural mechanisms of selectivevisual attention. Annu. Rev. Neurosci. 1995, 18:193-222.
6. Reynolds J.H., et al. Competitive mechanisms subserve attention in macaque areas V2 and V4. J. Neurosci. 1999, 19:1736-1753.
7. Dehaene S., Cohen L. Cultural recycling of cortical maps. Neuron 2007, 56:84-98.
8. Tsotsos J.K., et al. Modeling visual attention via selective tuning. Artif. Intell. 1995, 78:507-547.
9. Scalf P., Beck D. Competition in Visual Cortex Impedes Attention to Multiple Items. J. Neurosci. 2010, 30:161-169.
10. Franconeri S.L., et al. Tracking multiple objects is limited only by object spacing, not speed, time, or capacity. Psychol. Sci. 2010, 21:920-925.
11. Stewart T.C., et al. Neural representations of compositional structures: Representing and manipulating vector spaces with spiking neurons. Connect. Sci. 2011, 23:145-153.
12. Bowers J. On the biological plausibility of grandmother cells: implications for neural network theories in psychology and neuroscience. Psychol. Rev. 2009, 116:220-251.
13. O'Reilly R.C. Six principles for biologically based computational models of cortical cognition. Trends Cogn. Sci. 1998, 2:455-462.
14. Franconeri S.L., et al. How many locations can you select?. J. Exp. Psychol. Hum. Percept. Perform. 2007, 33:1003-1012.
15. Zhang W., Luck S.J. Discrete fixed-resolution representations in visual working memory. Nature 2008, 453:233-235.
16. Awh E., et al. Visual working memory represents a fixed number of items regardless of complexity. Psychol. Sci. 2007, 18:622-628.
17. Raffone A., Wolters G. A cortical mechanism for binding in visual working memory. J. Cogn. Neurosci. 2001, 13:766-785.
18. Awh E., et al. Visual and oculomotor selection: links, causes and implications for spatial attention. Trends Cogn. Sci. 2006, 10:124-130.
19. Cavanagh P., et al. Visual stability based on remapping of attention pointers. Trends Cogn. Sci. 2010, 14:147-153.
20. Moore T., et al. Visuomotor origins of covert spatial attention. Neuron 2003, 40:671-683.
21. Müller J.R., et al. Microstimulation of the superior colliculus focuses attention without moving the eyes. Proc. Natl. Acad. Sci. U.S.A. 2005, 102:524-529.
22. Bahcall D.O., Kowler E. Attentional interference at small spatial separations. Vis. Res. 1999, 39:71-86.
23. Cave K.R., Zimmerman J.M. Flexibility in spatial attention before and after practice. Psychol. Sci. 1997, 8:399-403.
24. McCarley J.S., et al. Spatially mediated capacity limits in attentive visual perception. Acta Psychol. 2007, 126:98-119.
25. McCarley J.S., Mounts J.R. On the relationship between flanker interference and localized attentional interference. Acta Psychol. 2008, 12:102-109.
26. Mounts J.R. Evidence for suppressive mechanisms in attentional selection: Feature singletons produce inhibitory surrounds. Attent. Percept. Psychophys. 2000, 62:969-983.
27. Cutzu F., Tsotsos J.K. The selective tuning model of attention: psychophysical evidence for a suppressive annulus around an attended item. Vis. Res. 2003, 43:205-219.
28. Carlson T.A., et al. Quadrantic deficit reveals anatomical constraints on selection. Proc. Natl. Acad. Sci. U.S.A. 2007, 104:13496-13500.
29. Franconeri S.L., et al. Multiple object tracking is limited by crowding, but not speed. Psychon. Bull. Rev. 2008, 15:802-808.
30. Shim W.M., et al. Spatial separation between targets constrains maintenance of attention on multiple objects. Psychon. Bull. Rev. 2008, 15:390-397.
31. Franconeri, S.L. The nature and status of visual resources. In Oxford Handbook of Cognitive Psychology (Reisberg, D., ed.), Oxford University Press (in press).
32. Alvarez G.A., Franconeri S.L. How many objects can you track?: Evidence for a resource-limited tracking mechanism. J. Vis. 2007, 7:1-10.
33. Alvarez G.A., Cavanagh P. Independent resources for attentional tracking in the left and right visual fields. Psychol. Sci. 2005, 16:637-643.
34. Alvarez G.A., et al. Anatomical constraints on attention: hemifield independence is a signature of multifocal spatial selection. J. Vis. 2012, 12:1-20.
35. Torralbo A., Beck D.M. Perceptual load-induced selection as a result of local competitive interactions in visual cortex. Psychol. Sci. 2008, 19:1045-1050.
36. Gardner J.L., et al. Maps of visual space in human occipital cortex are retinotopic, not spatiotopic. J. Neurosci. 2008, 28:3988-3999.
37. Green C.S., Bevallier D. Action video game modifies visual selective mechanism. Nature 2003, 423:534-537.
38. Alvarez G.A., Cavanagh P. The capacity of visual short-term memory is set both by visual information load and by number of objects. Psychol. Sci. 2004, 15:106-111.
39. Balas B., et al. A summary statistic representation in peripheral vision explains visual crowding. J. Vis. 2009, 9:13.
40. Rosenholtz R., et al. A summary statistic representation in peripheral vision explains visual search. J. Vis. 2012, 12:14.
41. Fei-Fei L., et al. Why does natural scene categorization require little attention? Exploring attentional requirements for natural and synthetic stimuli. Vis. Cogn. 2005, 12:893-924.
42. Reddy L., VanRullen R. Spacing affects some but not all visual searches: implications for theories of attention and crowding. J. Vis. 2007, 7:3.
43. Parks N.A., et al. Steady-state signatures of visual perceptual load, multimodal distractor filtering, and neural competition. J. Cogn. Neurosci. 2011, 23:1113-1124.
44. McManis S.A., Somers D.C. Processing efficiency of divided spatial attention mechanisms in human visual cortex. J. Neurosci. 2005, 25:9444-9448.
45. Umemoto A., et al. A bilateral advantage for storage in visual working memory. Cognition 2010, 117:69-79.
46. Mathot S., et al. From reorienting of attention to biased competition. Attent. Percept. Psychophys. 2010, 72:651-657.
47. Ihssen N., et al. Improving visual short-term memory by sequencing the stimulus array. Psychon. Bull. Rev. 2010, 17:680-686.
48. Gorgoraptis N., et al. Dynamic updating of working memory resources for visual objects. J. Neurosci. 2011, 31:8502-8511.
49. Shapiro K.L., Miller C.E. The role of biased competition in visual short term memory. Neuropsychologia 2011, 49:1506-1517.
50. Bays M.P., et al. Temporal dynamics of encoding, storage, and reallocation of visual working memory. J. Vis. 2011, 11:6.
51. Curtis C.E., D'Esposito M. Persistent activity in the prefrontal cortex during working memory. Trends Cogn. Sci. 2003, 7:415-423.
52. Postle B.R. Working memory as an emergent property of the mind and brain. Neuroscience 2006, 139:23-28.
53. Funahashi S. Space representation in the prefrontal cortex. Prog. Neurobiol. 2012, 10.1016/j.pneurobio.2012.04.002.
54. Kastner S., et al. Topographic maps in human frontal cortex revealed in memory-guided saccade and spatial working-memory tasks. J. Neurophysiol. 2007, 97:3494-3507.
55. Funahashi S., et al. Dorsolateral prefrontal lesions and oculomotor delayed-response performance: evidence for mnemonic 'scotomas'. J. Neurosci. 1993, 13:1479-1497.
56. Kanwisher N. Functional specificity in the human brain: a window into the functional architecture of the mind. Proc. Natl. Acad. Sci. U.S.A. 2010, 107:11163-11170.
57. Chang E.F., et al. Categorical speech representation in human superior temporal gyrus. Nat. Neurosci. 2010, 13:1428-1432.
58. Peelen M.V., et al. Supramodal representations of perceived emotions in the human brain. J. Neurosci. 2010, 30:10127-10134.
59. Caramazza A., Mahon B.Z. The organization of conceptual knowledge: the evidence from category-specific semantic deficits. Trends Cogn. Sci. 2003, 7:354-361.
60. Anderson M.C., et al. Remembering can cause forgetting: retrieval dynamics in long term memory. J. Exp. Psychol. Learn. 1994, 20:1063-1087.
61. Carr T.H., Dagenbach D. Semantic priming and repetition priming from masked words: Evidence for a center-surround attentional mechanism in perceptual recognition. J. Exp. Psychol. 1990, 16:341-350.
62. Healey M.K., et al. Direct evidence for the role of inhibition in resolving interference in memory. Psychol. Sci. 2010, 21:1464-1470.
63. Schoner, G. et al. Dynamic Thinking: A Primer on Dynamic Field Theory, Oxford University Press (in press).
64. Johnson J.S., et al. Dynamic neural field model of visual working memory and change detection. Psychol. Sci. 2009, 20:568-577.
65. Buonomano D.V., Merzenich M.M. Cortical plasticity: from synapses to maps. Annu. Rev. Neurosci. 1998, 21:149-186.
66. Albright T.D., et al. Columnar organization of directionally selective cells in visual area MT of the macaque. J. Neurophysiol. 1984, 51:16-31.
67. Da Costa S., et al. Human primary auditory cortex follows the shape of Heschl's Gyrus. J. Neurosci. 2011, 31:14067-14075.
68. Atiani S., et al. Task difficulty and performance induce diverse adaptive patterns in gain and shape of primary auditory cortical receptive fields. Neuron 2009, 61:467-480.
69. Tanaka K. Columns for complex visual object features in the inferotemporal cortex: Clustering of cells with similar but slightly different stimulus selectivities. Cereb. Cortex 2003, 13:90-99.
70. Wang G., et al. Optical imaging of functional organization in the monkey inferotemporal cortex. Science 1996, 272:1665-1668.
71. Arzi A., Sobel N. Olfactory perception as a compass for olfactory neural maps. Trends Cogn. Sci. 2011, 15:537-545.
72. Auffarth B., et al. Continuous spatial representations in the olfactory bulb may reflect perceptual categories. Front. Syst. Neurosci. 2011, 5:82.
73. Knudsen E.I., et al. Computational maps in the brain. Annu. Rev. Neurosci. 1987, 10:41-65.
74. Gould H.J., et al. The relationship of corpus callosum connections to electrical stimulation maps of motor, supplementary motor, and the frontal eye fi{ligature}elds in owl monkeys. J. Comput. Neurol. 1986, 247:297-325.
75. Loach D., et al. An attentional mechanism for selecting appropriate actions afforded by graspable objects. Psychol. Sci. 2008, 19:1253-1257.
76. Purves D., et al. Iterated patterns of brain circuitry (or how the cortex gets its spots). Trends Neurosci. 1992, 15:362-368.
77. Kaas J.H. Topographic maps are fundamental to sensory processing. Brain Res. Bull. 1997, 44:107-112.
78. Knudsen E.I. Auditory and visual maps of space in the optic tectum of the owl. J. Neurosci. 1982, 2:1177-1194.
79. Luck S.J., Vogel E.K. The capacity of visual working memory for features and conjunctions. Nature 1997, 390:279-281.
80. Zhang W., Luck S.J. The number and quality of representations in working memory. Psychol. Sci. 2011, 22:1434-1441.
81. Wheeler M., Treisman A.M. Binding in short-term visual memory. J. Exp. Psychol. Gen. 2002, 131:48-64.
82. Fougnie D., et al. What are the units of storage in visual working memory?. J. Vis. 2010, 10:1-11.
83. Bays P.M., Husain M. Dynamic shifts of limited working memory resources in human vision. Science 2008, 321:851.
84. Bays P.M., et al. The precision of visual working memory is set by allocation of a shared resource. J. Vis. 2009, 9:1-11.
85. Wilken P., Ma W.J. A detection theory account of change detection. J. Vis. 2004, 4:1120-1135.
86. Xu Y., Chun M.M. Dissociable neural mechanisms supporting visual short-term memory for objects. Nature 2006, 440:91-95.
87. Brady T.F., et al. A review of visual memory capacity: beyond individual items and towards structured representations. J. Vis. 2011, 11:1-34.
88. Brady T.F., Tenenbaum J.B. Encoding higher-order structure in visual working memory: A probabilistic model. Proceedings of the 32nd Annual Conference of the Cognitive Science Society 2010, 411-416. Cognitive Science Society. S. Ohlsson, R. Catrambone (Eds.).
89. O'Reilly R.C., Rudy J.W. Conjunctive representations in learning and memory: principles of cortical and hippocampal function. Psychol. Rev. 2001, 108:311-345.
90. Treisman A.M., Gelade G. A feature-integration theory of attention. Cogn. Psychol. 1980, 12:97-136.
91. Gray C.M., Singer W. Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc. Natl. Acad. Sci. U.S.A. 1989, 86:1698-1702.
92. Bays P.M., et al. Storage and binding of object features in visual working memory. Neuropsychologia 2011, 49:1622-1631.
93. Fougnie D., Alvarez G.A. Object features fail independently in visual working memory: evidence for a probabilistic feature-store model. J. Vis. 2011, 11:1-12.
94. Randall L. Warped Passages: Unraveling the Mysteries of the Universe's Hidden Dimensions 2005, Ecco.
95. Wandell B.A., et al. Visual field maps in human cortex. Neuron 2007, 56:366-383.
96. Alvarez G.A. Representing multiple objects as an ensemble enhances visual cognition. Trends Cogn. Sci. 2011, 15:122-131.
97. Farah M. Why does the somatosensory homunculus have hands next to face and feet next to genitals: a hypothesis. Neural Comput. 1998, 10:1983-1985.
98. Konkle T., Oliva A. A real-world size organization of object responses in occipitotemporal cortex. Neuron 2012, 74:1114-1124.
99. Pylyshyn Z.W., Storm R.W. Tracking multiple independent targets: evidence for a parallel tracking mechanism. Spat. Vis. 1988, 3:179-197.
100. Konkle T., et al. Conceptual distinctiveness supports detailed visual long-term memory for real-world objects. J. Exp. Psychol. Gen. 2010, 139:558-578.