Publikationsserver der Universitätsbibliothek Marburg
Titel:Eye movements and the maximization of value
Autor:Wolf, Christian
Weitere Beteiligte: Schütz, Alexander C. (Prof. Dr.)
Veröffentlicht:2017
URI:https://archiv.ub.uni-marburg.de/diss/z2018/0080
DOI: https://doi.org/10.17192/z2018.0080
URN: urn:nbn:de:hebis:04-z2018-00802
DDC:150 Psychologie
Titel (trans.):Augenbewegungen und die Maximierung von Wert
Publikationsdatum:2018-02-12
Lizenz:https://creativecommons.org/licenses/by-nc-sa/4.0

Dokument

Schlagwörter:
Latenz, decision making, Hochschulschrift, motivation, expected value, reaction time, eye movement, Entscheidungsfindung, Augenbewegung, Motivation, Erwarteter Wert, trans-saccadic integration, Sakkade, Reaktionszeit, latency, Trans-sakkadische Integration, information, saccade, Information

Summary:
Only the central region of the retina, the fovea, can provide us with high-acuity details of our visual environment. In the periphery however, resolution fades away with increasing eccentricity. As a consequence, humans and other animals with a foveated visual system move their eyes to redirect their gaze towards objects of interest. And with each saccadic eye movement, we choose a different region of the visual field for high-acuity processing. In the recent decades, the eye movement system has thus evolved as a role model to study decision making (Glimcher, 2003), which is also because the oculomotor system is sensitive to valuation processes. Moreover, our eye movements are tightly linked to visual perception, because where we look determines what we see and every eye movement poses a major challenge to the visual system as it shifts the whole visual image on the retina. In three studies, this dissertation project examined whether the eye movement system can adjust saccade latencies to maximize informational and motivational value and whether the visual system can maximize all the information available despite making eye movements. The first study investigated whether the eye movement system is sensitive to the information that can be gained by executing an eye movement. Participants saccaded to a peripherally appearing target and perform a perceptual task. By exchanging the target while the saccade was in flight, we could independently manipulate the pre-saccadic peripheral and the post-saccadic foveal visibility and thus create conditions where participants either lost or gained information by making an eye movement. In the loss condition, the probability of correctly identifying the target increased with saccade latency because participant could benefit longer from high resolution peripheral vision. The opposite pattern was observed in the gain condition. However, eye movement latencies did not differ no matter whether participants could gain or lose information and thus could not maximize the all the information available. Instead, latencies decreased with the probability that visual information at the saccade target was task-relevant, suggesting that saccade eye movements are influenced by the motivation to foveate task-relevant information, but not by the information that can be gained by saccade execution. In Study II, we tested whether the visual system is able to integrate pre-saccadic peripheral and post-saccadic foveal information and whether it weighs the incoming visual information according to its reliability, that is, according to how well something can be seen. This optimal integration would minimize the perceptual uncertainty and thus maximize all the information available to the visual system. For every individual, we separately measured discrimination performance in the fovea and the periphery. Using maximum-likelihood integration (Ernst & Bülthoff, 2004), we predicted the optimal weight given to peripheral information as well as the optimal uncertainty associated with the trans-saccadic percept. Both, in terms of weighting and uncertainty, trans-saccadic performance was not distinguishable from optimality. We thus could show that the visual system is able to integrate information across saccades and that it is close to optimal in doing so. This highlights that the visual system is able to maximize all the visual information available despite making eye movements. Study III investigated whether the influence of expected motivational value on saccades (Milstein & Dorris, 2007, 2011) can only be found in contexts where participants additionally have to choose between multiple rewarded targets. We recorded saccade latencies to rewarded targets differing in reward and manipulated the proportion of interleaved choices within one block. In choice-trials, two targets were displayed and participants could choose between the two to obtain the corresponding reward. Without choices present, we found no evidence for single target saccades to be affected by reward. When choices were interleaved, latencies to less rewarded targets were delayed and the magnitude of this delay increased with the proportion of choices. This delay was elicited by the expectation of an upcoming choice-trial as well as inter-trial priming: After a choice, saccadic reactions to the non-chosen target were delayed. We thus could show that there is no direct relationship between expected motivational value on the one hand and saccade latencies on the other hand. Rather, this relationship only persists in contexts where humans can maximize their reward outcome by preferring one target over the other. In sum, the present dissertation shows that there is no direct relationship between saccade latencies on the one hand and motivational value (Study III) or informational value (Study I) on the other hand. Instead, saccade latencies are sensitive to the probability that information acquired at the saccade target becomes task-relevant (Study I) and the preference of one target over the other (Study III). For perception we could show that the visual system can optimally integrate information about saccades and thus that vision does not correspond to disconnected snapshots, but rather to an integrated stream of continuous information (Study II).

Bibliographie / References

  1. von Holst, E., & Mittelstaedt, H. (1950). Das Reafferenzprinzip -Wechselwirkungen zwischen Zentralnervensystem und Peripherie. Die Naturwissenschaften, 37(20), 464-476. doi: 10.1007/BF00622503
  2. Takikawa, Y., Kawagoe, R., Itoh, H., Nakahara, H., & Hikosaka, O. (2002). Modulation of saccadic eye movements by predicted reward outcome. Experimental Brain Research, 142(2), 284-291. doi: 10.1007/s00221-001-0928-1
  3. Cherkasova, M. V., Manoach, D. S., Intriligator, J. M., & Barton, J. J. (2002). Antisaccades and task- switching: Interactions in controlled processing. Experimental Brain Research, 144(4), 528-537. doi: 10.1007/s00221-002-1075-z
  4. Ipata, A. E., Gee, A. L., Bisley, J. W., & Goldberg, M. E. (2009). Neurons in the lateral intraparietal area create a priority map by the combination of disparate signals. Experimental Brain Research, 192(3), 479-488. doi: 10.1007/s00221-008-1557-8
  5. Xu-Wilson, M., Zee, D. S., & Shadmehr, R. (2009). The intrinsic value of visual information affects saccade velocities. Experimental Brain Research, 196(4), 475-481. doi: 10.1007/s00221-009-1879-1
  6. Weiler, J., & Heath, M. (2012). The prior-antisaccade effect influences the planning and online control of prosaccades. Experimental Brain Research, 216(4), 545-552. doi: 10.1007/s00221-011-2958-7
  7. Guyader, N., Malsert, J., & Marendaz, C. (2010). Having to identify a target reduces latencies in prosaccades but not in antisaccades. Psychological Research, 74(1), 12-20. doi: 10.1007/s00426- 008-0218-7
  8. Irwin, D. E. (1991). Information integration across saccadic eye movements. Cognitive Psychology, 23(3), 420-456. doi: 10.1016/0010-0285(91)90015-G
  9. Zuber, B. L., & Stark, L. (1966). Saccadic suppression: Elevation of visual threshold associated with saccadic eye movements. Experimental Neurology, 16(1), 65-79. doi: 10.1016/0014- 4886(66)90087-2
  10. Bahill, A. T., Clark, M. R., & Stark, L. (1975). The main sequence, a tool for studying human eye movements. Mathematical Biosciences, 24, 191-204. doi: 10.1016/0025-5564(75)90075-9
  11. Findlay, J. M. (1982). Global visual processing for saccadic eye movements. Vision Research, 22(8), 1033-1045. doi: 10.1016/0042-6989(82)90040-2
  12. Jonides, J., Irwin, D. E., & Yantis, S. (1982). Integrating visual information from successive fixations. Science. doi: 10.1016/0042-6989(83)90198-0
  13. Deubel, H., Schneider, W. X., & Bridgeman, B. (1996). Postsaccadic target blanking prevents saccadic suppression of image displacement. Vision Research, 36(7), 985-996. doi: 10.1016/0042- 6989(95)00203-0
  14. Tanaka, Y., & Shimojo, S. (1996). Location vs feature: Reaction time reveals dissociation between two visual functions. Vision Research, 36(14), 2125-2140. doi: 10.1016/0042-6989(95)00272-3
  15. Carpenter, R. H. S. (2004). Contrast, probability, and saccadic latency: Evidence for independence of detection and decision. Current Biology, 14, 1576-1580. doi: 10.1016/j.cub.2004.08.058
  16. Melcher, D. (2005). Spatiotopic transfer of visual-form adaptation across saccadic eye movements. Current Biology, 15(19), 1745-1748. doi: 10.1016/j.cub.2005.08.044
  17. Hickey, C., & van Zoest, W. (2012). Reward creates oculomotor salience. Current Biology, 22(7), R219- R220. doi: 10.1016/j.cub.2012.02.007
  18. Manohar, S. G., Chong, T. T., Apps, M. A. J., Jarman, P. R., Bhatia, K. P., Husain, M., … Stamelou, M. (2015). Reward Pays the Cost of Noise Reduction in Motor and Cognitive Control. Current Biology, 25(13), 1707-1716. doi: 10.1016/j.cub.2015.05.038
  19. Valsecchi, M., & Gegenfurtner, K. R. (2016). Dynamic Re-calibration of Perceived Size in Fovea and Periphery through Predictable Size Changes. Current Biology, 26, 1-5. doi: 10.1016/j.cub.2015.10.067
  20. Noorani, I., & Carpenter, R. H. S. (2016). The LATER model of reaction time and decision. Neuroscience and Biobehavioral Reviews, 64, 229-251. doi: 10.1016/j.neubiorev.2016.02.018
  21. Gottlieb, J. (2007). From Thought to Action: The Parietal Cortex as a Bridge between Perception, Action, and Cognition. Neuron, 53(1), 9-16. doi: 10.1016/j.neuron.2006.12.009
  22. Kable, J. W., & Glimcher, P. W. (2009). The Neurobiology of Decision: Consensus and Controversy. Neuron, 63(6), 733-745. doi: 10.1016/j.neuron.2009.09.003
  23. Gottlieb, J. (2012). Attention, Learning, and the Value of Information. Neuron, 76(2), 281-295. doi: 10.1016/j.neuron.2012.09.034
  24. Campana, G., Cowey, A., Casco, C., Oudsen, I., & Walsh, V. (2007). Left frontal eye field remembers "where" but not "what." Neuropsychologia, 45(10), 2340-2345. doi: 10.1016/j.neuropsychologia.2007.02.009
  25. Ernst, M. O., & Bülthoff, H. H. (2004). Merging the senses into a robust percept. Trends in Cognitive Sciences, 8(4), 162-169. doi: 10.1016/j.tics.2004.02.002
  26. Serences, J. T., & Yantis, S. (2006). Selective visual attention and perceptual coherence. Trends in Cognitive Sciences, 10(1), 38-45. doi: 10.1016/j.tics.2005.11.008
  27. Fecteau, J. H., & Munoz, D. P. (2006). Salience, relevance, and firing: a priority map for target selection. Trends in Cognitive Sciences. doi: 10.1016/j.tics.2006.06.011
  28. Awh, E., Belopolsky, A. V., & Theeuwes, J. (2012). Top-down versus bottom-up attentional control: A failed theoretical dichotomy. Trends in Cognitive Sciences, 16(8), 437-443. doi: 10.1016/j.tics.2012.06.010
  29. Ludwig, C. J. H., Gilchrist, I. D., & McSorley, E. (2004). The influence of spatial frequency and contrast on saccade latencies. Vision Research, 44(22), 2597-2604. doi: 10.1016/j.visres.2004.05.022
  30. Navalpakkam, V., & Itti, L. (2005). Modeling the influence of task on attention. Vision Research, 45(2), 205-231. doi: 10.1016/j.visres.2004.07.042
  31. Trottier, L., & Pratt, J. (2005). Visual processing of targets can reduce saccadic latencies. Vision Research, 45(11), 1349-1354. doi: 10.1016/j.visres.2004.12.007
  32. Montagnini, A., & Chelazzi, L. (2005). The urgency to look: Prompt saccades to the benefit of perception. Vision Research, 45(27), 3391-3401. doi: 10.1016/j.visres.2005.07.013
  33. Kristjánsson, Á., & Driver, J. (2008). Priming in visual search: Separating the effects of target repetition, distractor repetition and role-reversal. Vision Research, 48(10), 1217-1232. doi: 10.1016/j.visres.2008.02.007
  34. Demeyer, M., De Graef, P., Wagemans, J., & Verfaillie, K. (2010). Parametric integration of visual form across saccades. Vision Research, 50(13), 1225-1234. doi: 10.1016/j.visres.2010.04.008
  35. Stigchel, S. (2010). Recent advances in the study of saccade trajectory deviations. Vision Research, 50(17), 1619-1627. doi: 10.1016/j.visres.2010.05.028
  36. Theeuwes, J., & Belopolsky, A. V. (2012). Reward grabs the eye: Oculomotor capture by rewarding stimuli. Vision Research, 74, 80-85. doi: 10.1016/j.visres.2012.07.024
  37. Hickey, C., & van Zoest, W. (2013). Reward-associated stimuli capture the eyes in spite of strategic attentional set. Vision Research, 92, 67-74. doi: 10.1016/j.visres.2013.09.008
  38. Bucker, B., Silvis, J. D., Donk, M., & Theeuwes, J. (2015). Reward modulates oculomotor competition between differently valued stimuli. Vision Research, 108, 103-112. doi: 10.1016/j.visres.2015.01.020
  39. Itti, L., & Koch, C. (2000). A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Research, 40, 1489-1506. doi: 10.1016/S0042-6989(99)00163-7
  40. Kusunoki, M., Gottlieb, J., & Goldberg, M. E. (2000). The lateral intraparietal area as a salience map: The representation of abrupt onset, stimulus motion, and task relevance. Vision Research, 40, 1459-1468. doi: 10.1016/S0042-6989(99)00212-6
  41. Thompson, K. G., & Bichot, N. P. (2005). A visual salience map in the primate frontal eye field. Progress in Brain Research. doi: 10.1016/S0079-6123(04)47019-8
  42. Berridge, K. C., & Robinson, T. E. (1998). What is the role of dopamine in reward: Hedonic impact, reward learning, or incentive salience? Brain Research Reviews, 28(3), 309-369. doi: 10.1016/S0165-0173(98)00019-8
  43. Leon, M. I., & Shadlen, M. N. (1999). Effect of expected reward magnitude on the response of neurons in the dorsolateral prefrontal cortex of the macaque. Neuron, 24(2), 415-425. doi: 10.1016/S0896- 6273(00)80854-5
  44. Leon, M. I., & Shadlen, M. N. (1999). Effect of expected reward magnitude on the response of neurons in the dorsolateral prefrontal cortex of the macaque. Neuron, 24(2), 415-425. doi: 10.1016/S0896-6273(00)80854-5
  45. Ikeda, T., & Hikosaka, O. (2003). Reward-dependent gain and bias of visual responses in primate superior colliculus. Neuron, 39(4), 693-700. doi: 10.1016/S0896-6273(03)00464-1
  46. McCoy, A. N., Crowley, J. C., Haghighian, G., Dean, H. L., & Platt, M. L. (2003). Saccade Reward Signals in Posterior Cingulate Cortex. Neuron, 40(5), 1031-1040. doi: 10.1016/S0896-6273(03)00719-0
  47. Alais, D., & Burr, D. C. (2004). The Ventriloquist Effect Results from Near-Optimal Bimodal Integration. Current Biology, 14(3), 257-262. doi: 10.1016/S0960-9822(04)00043-0
  48. Klein, R. M. (2000). Inhibition of return. Trends in Cognitive Neuroscience, 4(4), 138-147. doi: 10.1016/S1364-6613(00)01452-2
  49. Bridgeman, B., van der Heijden, A. H. C., & Velichkovsky, B. M. (1994). A theory of visual stability across saccadic eye movements. Behavioral and Brain Science, 17(2), 247-258. doi: 10.1017/S0140525X00034361
  50. Tanaka, Y., & Shimojo, S. (2000). Repetition priming reveals sustained facilitation and transient inhibition in reaction time. Journal of Experimental Psychology. Human Perception and Performance, 26(4), 1421-1435. doi: 10.1037/0096-1523.26.4.1421
  51. Rodriguez, M. L., & Logue, A. W. (1988). Adjusting delay to reinforcement: comparing choice in pigeons and humans. Journal of Experimental Psychology: Animal Behavior Processes, 14(1), 105-117. doi: 10.1037/0097-7403.14.1.105
  52. Herwig, A., & Schneider, W. X. (2014). Predicting object features across saccades: Evidence from object recognition and visual search. Journal of Experimental Psychology. General, 143(5), 1903-22. doi: 10.1037/a0036781
  53. Tatler, B. W., Brockmole, J. R., & Carpenter, R. H. S. (2017). LATEST : A Model of Saccadic Decisions in Space and Time. Psychological Review, 124(3), 267-300. doi: 10.1037/rev0000054
  54. Kawagoe, R., Takikawa, Y., & Hikosaka, O. (1998). Expectation of reward modulates cognitive signals in the basal ganglia. Nature Neuroscience, 1(5), 411-416. doi: 10.1038/1625
  55. Platt, M. L., & Glimcher, P. W. (1999). Neural correlates of decision variables in parietal cortex. Nature, 400(6741), 233-238. doi: 10.1038/22268
  56. Harris, C. M., & Wolpert, D. M. (1998). Signal-dependent noise determines motor planning. Nature, 394(6695), 780-4. doi: 10.1038/29528
  57. Newsome, W. T., Britten, K. H., & Movshon, J. A. (1989). Neuronal correlates of a perceptual decision. Nature, 341(6237), 52-54. doi: 10.1038/341052a0
  58. Stuphorn, V., Taylor, T. L., & Schall, J. D. (2000). Performance monitoring by the supplementary eye field. Nature, 408, 857-860. doi: 10.1038/35048576
  59. Gottlieb, J., Kusunoki, M., & Goldberg, M. E. (1998). The representation of visual salience in monkey parietal cortex. Nature, 391(6666), 481-4. doi: 10.1038/35135
  60. Schall, J. D., & Hanes, D. P. (1993). Neural basis of saccade target selection in frontal eye field during visual search. Nature, 366(6454), 467-469. doi: 10.1038/366467a0
  61. Schlag-Rey, M., Amador, N., Sanchez, H., & Schlag, J. (1997). Antisaccade performance predicted by neuronal activity in the supplementary eye field. Nature, 390(6658), 398-401. doi: 10.1038/37114
  62. Burr, D. C., Morrone, M. C., & Ross, J. (1994). Selective suppression of the magnocellular visual pathway during saccadic eye movements. Nature, 371(6497), 511-3. doi: 10.1038/371511a0
  63. Carpenter, R. H. S., & Williams, M. L. (1995). Neural computation of log likelihood in control of saccadic eye movements. Nature, 377(6544), 59-62. doi: 10.1038/377059a0
  64. Ernst, M. O., & Banks, M. S. (2002). Humans integrate visual and haptic information in a statistically optimal fashion. Nature, 415(6870), 429-433. doi: 10.1038/415429a
  65. Lauwereyns, J., Watanabe, K., Coe, B., & Hikosaka, O. (2002). A neural correlate of response bias in monkey caudate nucleus. Nature, 418(JULY), 413-417. doi: 10.1038/nature00844.1.
  66. Sommer, M. A., & Wurtz, R. H. (2006). Influence of the thalamus on spatial visual processing in frontal cortex. Nature, 444(7117), 374-377. doi: 10.1038/nature05279
  67. Melcher, D., & Morrone, M. C. (2003). Spatiotopic temporal integration of visual motion across saccadic eye movements. Nat Neurosci, 6(8), 877-81. doi: 10.1038/nn1098
  68. Cox, D. D., Meier, P., Oertelt, N., & DiCarlo, J. J. (2005). "Breaking" position-invariant object recognition. Nature Neuroscience, 8(9), 1145-1147. doi: 10.1038/nn1519
  69. Stuphorn, V., & Schall, J. D. (2006). Executive control of countermanding saccades by the supplementary eye field. Nature Neuroscience, 9(7), 925-931. doi: 10.1038/nn1714
  70. Fecteau, J. H., & Munoz, D. P. (2003). Exploring the consequences of the previous trial. Nature Reviews Neuroscience, 4(6), 435-443. doi: 10.1038/nrn1114
  71. Heuer, A., Wolf, C., Schütz, A. C., & Schubö, A. (2017). The necessity to choose causes reward-related anticipatory biasing: Parieto-occipital alpha-band oscillations reveal suppression of low-value targets. Scientific Reports, 7:14318. doi: 10.1038/s41598-017-14742-w
  72. Land, M., Mennie, N., & Rusted, J. (1999). The roles of vision and eye movements in the control of activities of daily living. Perception, 28(11), 1311-1328. doi: 10.1068/p2935
  73. Ostendorf, F., Liebermann, D., & Ploner, C. J. (2010). Human thalamus contributes to perceptual stability across eye movements. Proceedings of the National Academy of Sciences of the United States of America, 107(3), 1229-34. doi: 10.1073/pnas.0910742107
  74. Barthelmé, S., & Mamassian, P. (2010). Flexible mechanisms underlie the evaluation of visual confidence. Proceedings of the National Academy of Sciences, 107(48), 20834-20839. doi: 10.1073/pnas.1007704107
  75. Schütz, A. C., Trommershäuser, J., & Gegenfurtner, K. R. (2012). Dynamic integration of information about salience and value for saccadic eye movements. Proceedings of the National Academy of Sciences, 109(19), 7547-7552. doi: 10.1073/pnas.1115638109
  76. Peterson, M. F., & Eckstein, M. P. (2012). Looking just below the eyes is optimal across face recognition tasks. Proceedings of the National Academy of Sciences, 109(48), E3314-23. doi: 10.1073/pnas.1214269109
  77. Ludwig, C. J. H., Davies, J. R., & Eckstein, M. P. (2014). Foveal analysis and peripheral selection during active visual sampling. Proceedings of the National Academy of Sciences, 111(2), E291-9. doi: 10.1073/pnas.1313553111
  78. Barkley-Levenson, E., & Galván, A. (2014). Neural representation of expected value in the adolescent brain. Proceedings of the National Academy of Sciences, 111(4), 1646-51. doi: 10.1073/pnas.1319762111
  79. Bucker, B., Belopolsky, A. V., & Theeuwes, J. (2015). Distractors that signal reward attract the eyes. Visual Cognition, 23(1-2), 1-24. doi: 10.1080/13506285.2014.980483
  80. Rolls, E. T., McCabe, C., & Redoute, J. (2008). Expected value, reward outcome, and temporal difference error representations in a probabilistic decision task. Cerebral Cortex, 18(3), 652-663. doi: 10.1093/cercor/bhm097
  81. Everling (Eds.), Oxford Handbook of Eye Movements (pp. 195-213). New York: Oxford University Press. doi: 10.1093/oxfordhb/9780199539789.013.0011
  82. Chen, L. L., Hung, L. Y., Quinet, J., & Kosek, K. (2013). Cognitive regulation of saccadic velocity by reward prospect. European Journal of Neuroscience, 38(3), 2434-2444. doi: 10.1111/ejn.12247
  83. Herwig, A., Weiß, K., & Schneider, W. X. (2015). When circles become triangular: How transsaccadic predictions shape the perception of shape. Annals of the New York Academy of Sciences, 1339(1), 97-105. doi: 10.1111/nyas.12672
  84. Sommer, M. A., & Wurtz, R. H. (2002). A Pathway in Primate Brain for Internal Monitoring of Movements. Science, 296(5572), 1480-1482. doi: 10.1126/science.1069590
  85. Hanes, D. P., & Schall, J. D. (1996). Neural control of voluntary movement initiation. Science, 274(5286), 427-30. doi: 10.1126/science.274.5286.427
  86. Bridgeman, B., & Mayer, M. (1983). Failure to integrate information from successive fixations. Bulletin of the Psychonomic Society, 21(4), 285-286. doi: 10.1126/science.6623072
  87. Sprague, N., Ballard, D., & Robinson, A. (2007). Modeling embodied visual behaviors. ACM Transactions on Applied Perception, 4(2), 1-23. doi: 10.1145/1265957.1265960
  88. Crapse, T. B., & Sommer, M. A. (2008). The frontal eye field as a prediction map. Progress in Brain Research, 171, 383-390. doi: 10.1146/annurev-immunol-032713-120240.Microglia
  89. Bisley, J. W., & Goldberg, M. E. (2010). Attention, Intention, and Priority in the Parietal Lobe. Annual Review of Neuroscience, 33(1), 1-21. doi: 10.1146/annurev-neuro-060909-152823
  90. Basso, M. A., & May, P. J. (2017). Circuits for Action and Cognition: A View from the Superior Colliculus. Annual Review of Vision Science, 3(1), annurev-vision-102016-061234. doi: 10.1146/annurev-vision-102016-061234
  91. Glimcher, P. W. (2003). The Neurobiology of Visual Saccadic Decision Making. Annu Rev Neurosci, 26, 133-79. doi: 10.1146/annurev.neuro.26.010302.081134
  92. Kersten, D., Mamassian, P., & Yuille, A. (2004). Object Perception as Bayesian Inference. Annual Review of Psychology, 55(1), 271-304. doi: 10.1146/annurev.psych.55.090902.142005
  93. Roesch, M. R., & Olson, C. R. (2003). Impact of expected reward on neuronal activity in prefrontal cortex, frontal and supplementary eye fields and premotor cortex. Journal of Neurophysiology, 90(3), 1766-89. doi: 10.1152/jn.00019.2003
  94. Belopolsky, A. V., & van der Stigchel, S. (2013). Saccades curve away from previously inhibited locations: evidence for the role of priming in oculomotor competition. Journal of Neurophysiology, 110(10), 2370-7. doi: 10.1152/jn.00293.2013
  95. So, N.-Y., & Stuphorn, V. (2010). Supplementary eye field encodes option and action value for saccades with variable reward. Journal of Neurophysiology, 104(5), 2634-2653. doi: 10.1152/jn.00430.2010
  96. Failing, M. F., Nissens, T., Pearson, D., Le Pelley, M. E., & Theeuwes, J. (2015). Oculomotor capture by stimuli that signal the availability of reward. Journal of Neurophysiology, 114(4), 2316-2327. doi: 10.1152/jn.00441.2015
  97. Itoh, H., Nakahara, H., Hikosaka, O., Kawagoe, R., Takikawa, Y., & Aihara, K. (2003). Correlation of Primate Caudate Neural Activity and Saccade Parameters in Reward-Oriented Behavior. Journal of Neurophysiology, 89(4), 1774-1783. doi: 10.1152/jn.00630.2002
  98. Sommer, M. A., & Wurtz, R. H. (2004). What the Brain Stem Tells the Frontal Cortex. II. Role of the SC- MD-FEF Pathway in Corollary Discharge. Journal of Neurophysiology, 91(3), 1403-1423. doi: 10.1152/jn.00740.2003
  99. Madelain, L., Champrenaut, L., & Chauvin, A. (2007). Control of sensorimotor variability by consequences. J Neurophysiol, 98(4), 2255-2265. doi: 10.1152/jn.01286.2006
  100. Posner, M. I., & Cohen, Y. (1984). Components of visual orienting. In H. Bouma & D. Bouwhuis (Eds.), Attention and Performance (10th ed., pp. 531-556). Erlbaum. doi: 10.1162/jocn.1991.3.4.335
  101. Yashar, A., & Lamy, D. (2010). Intertrial repetition affects perception: the role of focused attention. Journal of Vision, 10(14), 3. doi: 10.1167/10.14.3
  102. Murray, R. F. (2011). Classification images : A review. Journal of Vision, 11(5), 1-25. doi: 10.1167/11.5.2.
  103. Tatler, B. W., Hayhoe, M., Land, M. F., & Ballard, D. (2011). Eye guidance in natural vision: reinterpreting salience. Journal of Vision, 11(5), 1-23. doi: 10.1167/11.5.5
  104. Schütz, A. C., Braun, D. I., & Gegenfurtner, K. R. (2011). Eye movements and perception: A selective review. Journal of Vision, 11(5), 1-30. doi: 10.1167/11.5.9
  105. Sullivan, B. T., Johnson, L., Rothkopf, C. A., Ballard, D., & Hayhoe, M. (2012). The role of uncertainty and reward on eye movements in a virtual driving task. Journal of Vision, 12(13), 1-17. doi: 10.1167/12.13.19
  106. Ackermann, J. F., & Landy, M. S. (2013). Choice of saccade endpoint under risk. Journal of Vision, 13(3), 27. doi: 10.1167/13.3.27
  107. Schütz, A. C., Kerzel, D., & Souto, D. (2014). Saccadic adaptation induced by a perceptual task. Journal of Vision, 14(5), 4. doi: 10.1167/14.5.4
  108. Ganmor, E., Landy, M. S., & Simoncelli, E. P. (2015). Near-optimal integration of orientation information across saccades. Journal of Vision, 15(16), 1-12. doi: 10.1167/15.16.8
  109. Meermeier, A., Gremmler, S., & Lappe, M. (2016). The influence of image content on oculomotor plasticity. Journal of Vision, 16(8), 1-12. doi: 10.1167/16.8.17
  110. Tong, M. H., Zohar, O., & Hayhoe, M. M. (2017). Control of gaze while walking: Task structure, reward, and uncertainty. Journal of Vision, 17(1), 28. doi: 10.1167/17.1.28
  111. Meermeier, A., Gremmler, S., & Lappe, M. (2017). New is always better: Novelty modulates oculomotor learning. Journal of Vision, 17(11), 1-7. doi: 10.1167/17.11.13
  112. Hayhoe, M. M., Shrivastava, A., Mruczek, R., & Pelz, J. B. (2003). Visual memory and motor planning in a natural task. Journal of Vision, 3(1), 49-63. doi: 10.1167/3.1.6
  113. Najemnik, J., & Geisler, W. S. (2005). Optimal eye movement strategies in visual search. Nature, 434(7031), 387-391. doi: 10.1167/5.8.778
  114. Rothkopf, C. A., Ballard, D. H., & Hayhoe, M. M. (2007). Task and context determine where you look. Journal of Vision, 7(14), 1-20. doi: 10.1167/7.14.16
  115. Renninger, L. W., Verghese, P., & Coughlan, J. (2007). Where to look next? Eye movements reduce local uncertainty. Journal of Vision, 7(3), 1-17. doi: 10.1167/7.3.6
  116. Wittenberg, M., Bremmer, F., & Wachtler, T. (2008). Perceptual evidence for saccadic updating of color stimuli. Journal of Vision, 8(14), 1-9. doi: 10.1167/8.14.9
  117. Najemnik, J., & Geisler, W. S. (2008). Eye movement statistics in humans are consistent with an optimal search strategy. Journal of Vision, 8(3), 1-14. doi: 10.1167/8.3.4
  118. Zhang, L., Tong, M. H., Marks, T. K., Shan, H., & Cottrell, G. W. (2008). SUN: A Bayesian framework for saliency using natural statistics. Journal of Vision, 8(7), 1-20. doi: 10.1167/8.7.32
  119. Demeyer, M., De Graef, P., Wagemans, J., & Verfaillie, K. (2009). Transsaccadic identification of highly similar artificial shapes. Journal of Vision, 9(4), 1-14. doi: 10.1167/9.4.28.
  120. Belopolsky, A. V. (2015). Common Priority Map for Selection History, Reward and Emotion in the Oculomotor System. Perception, 44(8-9), 920-933. doi: 10.1177/0301006615596866
  121. Ptak, R. (2012). The Frontoparietal Attention Network of the Human Brain. The Neuroscientist, 18(5), 502-515. doi: 10.1177/1073858411409051
  122. Barthelmé, S., & Mamassian, P. (2009). Evaluation of Objective Uncertainty in the Visual System. PLoS Computational Biology, 5(9), 1-8. doi: 10.1371/journal.pcbi.1000504
  123. Morvan, C., & Maloney, L. T. (2012). Human visual search does not maximize the post-saccadic probability of identifying targets. PLoS Computational Biology, 8(2). doi: 10.1371/journal.pcbi.1002342
  124. Bieg, H. J., Bresciani, J. P., Bülthoff, H. H., & Chuang, L. L. (2012). Looking for Discriminating Is Different from Looking for Looking's Sake. PLoS ONE, 7(9). doi: 10.1371/journal.pone.0045445
  125. Collins, T. (2012). Probability of Seeing Increases Saccadic Readiness. PLoS ONE, 7(11), 1-5. doi: 10.1371/journal.pone.0049454
  126. Weiler, J., Mitchell, T., & Heath, M. (2014). Response suppression delays the planning of subsequent stimulus-driven saccades. PLoS ONE, 9(1). doi: 10.1371/journal.pone.0086408
  127. Altering Spatial Priority Maps via Reward-Based Learning. Journal of Neuroscience, 34(25), 8594- 8604. doi: 10.1523/JNEUROSCI.0277-14.2014
  128. Haith, A. M., Reppert, T. R., & Shadmehr, R. (2012). Evidence for hyperbolic temporal discounting of reward in control of movements. Journal of Neuroscience, 32(34), 11727- 36. doi: 10.1523/JNEUROSCI.0424-12.2012
  129. Milstein, D. M., & Dorris, M. C. (2007). The influence of expected value on saccadic preparation. Journal of Neuroscience, 27(18), 4810-4818. doi: 10.1523/JNEUROSCI.0577-07.2007
  130. Knutson, B., Taylor, J., Kaufman, M., Peterson, R., & Glover, G. (2005). Distributed Neural Representation of Expected Value. Journal of Neuroscience, 25(19), 4806-4812. doi: 10.1523/JNEUROSCI.0642-05.2005
  131. Oostwoud Wijdenes, L., Marshall, L., & Bays, P. M. (2015). Evidence for Optimal Integration of Visual Feature Representations across Saccades. Journal of Neuroscience, 35(28), 10146-53. doi: 10.1523/JNEUROSCI.1040-15.2015
  132. Cavanaugh, J., Berman, R. A., Joiner, W. M., & Wurtz, R. H. (2016). Saccadic Corollary Discharge Underlies Stable Visual Perception. Journal of Neuroscience, 36(1), 31-42. doi: 10.1523/JNEUROSCI.2054-15.2016
  133. Reppert, T. R., Lempert, K. M., Glimcher, P. W., & Shadmehr, R. (2015). Modulation of Saccade Vigor during Value-Based Decision Making. Journal of Neuroscience, 35(46), 15369-15378. doi: 10.1523/JNEUROSCI.2621-15.2015
  134. Bremmer, F., Kubischik, M., Hoffmann, K.-P., & Krekelberg, B. (2009). Neural Dynamics of Saccadic Suppression. Journal of Neuroscience, 29(40), 12374-12383. doi: 10.1523/JNEUROSCI.2908- 09.2009
  135. Marshall, T. R., O'Shea, J., Jensen, O., & Bergmann, T. O. (2015). Frontal Eye Fields Control Attentional Modulation of Alpha and Gamma Oscillations in Contralateral Occipitoparietal Cortex. Journal of Neuroscience, 35(4), 1638-1647. doi: 10.1523/JNEUROSCI.3116-14.2015
  136. Gottlieb, J., Hayhoe, M., Hikosaka, O., & Rangel, A. (2014). Attention, Reward, and Information Seeking. Journal of Neuroscience, 34(46), 15497-15504. doi: 10.1523/JNEUROSCI.3270-14.2014
  137. Teichert, T., Yu, D., & Ferrera, V. P. (2014). Performance monitoring in monkey frontal eye field. Journal of Neuroscience, 34(5), 1657-71. doi: 10.1523/JNEUROSCI.3694-13.2014
  138. Markowitz, D. A., Wong, Y. T., Gray, C. M., & Pesaran, B. (2011). Optimizing the Decoding of Movement Goals from Local Field Potentials in Macaque Cortex. Journal of Neuroscience, 31(50), 18412-22. doi: 10.1523/JNEUROSCI.4165-11.2011
  139. Coren, S., & Hoenig, P. (1972). Effect of non-target stimuli upon length of voluntary saccades. Perceptual & Motor Skills, 34, 499-508. doi: 10.2466/pms.1972.34.2.499
  140. Schütz, A. C., & Souto, D. (2015). Perceptual task induces saccadic adaptation by target selection. Frontiers in Human Neuroscience, 9(October), 566. doi: 10.3389/fnhum.2015.00566
  141. Milstein, D. M., & Dorris, M. C. (2011). The relationship between saccadic choice and reaction times with manipulations of target value. Frontiers in Neuroscience, 5, 1-12. doi: 10.3389/fnins.2011.00122
  142. Chen, L. L., Chen, Y. M., Zhou, W., & Mustain, W. D. (2014). Monetary reward speeds up voluntary saccades. Frontiers in Integrative Neuroscience, 8(June), 48. doi: 10.3389/fnint.2014.00048
  143. Dunne, S., Ellison, A., & Smith, D. T. (2015). Rewards modulate saccade latency but not exogenous spatial attention. Frontiers in Psychology, 6, 1080. doi: 10.3389/fpsyg.2015.01080
  144. Kumada, T., & Humphreys, G. W. (2002). Cross-dimensional interference and cross-trial inhibition. Perception & Psychophysics, 64(3), 493-503. doi: 10.3758/BF03194720
  145. Cornelissen, F. W., Peters, E. M., & Palmer, J. (2002). The Eyelink Toolbox: Eye tracking with MATLAB and the Psychophysics Toolbox. Behavior Research Methods, Instruments, & Computers, 34(4), 613-617. doi: 10.3758/BF03195489
  146. Rayner, K., & Pollatsek, A. (1983). Is visual information integrated across saccades? Perception & Psychophysics, 34(1), 39-48. doi: 10.3758/BF03205894
  147. Maljkovic, V., & Nakayama, K. (1994). Priming of pop-out: I. Role of features. Memory & Cognition, 22(6), 657-672. doi: 10.3758/BF03209251
  148. McLaughlin, S. C. (1967). Parametric adjustment in saccadic eye movements. Perception & Psychophysics, 2(8), 359-362. doi: 10.3758/BF03210071
  149. Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16(2), 225- 237. doi: 10.3758/PBR.16.2.225
  150. Feldmann-Wüstefeld, T., & Schubö, A. (2016). Intertrial priming due to distractor repetition is eliminated in homogeneous contexts. Attention, Perception, & Psychophysics, 78(7), 1935- 1947. doi: 10.3758/s13414-016-1115-6
  151. Failing, M. F., & Theeuwes, J. (2017). Selection history: How reward modulates selectivity of visual attention. Psychon Bull Rev. doi: 10.3758/s13423-017-1380-y
  152. Bichot, N. P., & Schall, J. D. (2002). Priming in macaque frontal cortex during popout visual search: feature-based facilitation and location-based inhibition of return. Journal of Neuroscience, 22(11), 4675-4685. doi: 20026410
  153. Coe, B., Tomihara, K., Matsuzawa, M., & Hikosaka, O. (2002). Visual and anticipatory bias in three cortical eye fields of the monkey during an adaptive decision-making task. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 22(12), 5081-90. doi: 22/12/5081 [pii]
  154. Irwin, D. E., Yantis, S., & Jonides, J. (1983). Evidence against visual integration across saccadic eye movements. Perception & Psychophysics, 34(1), 49-57.
  155. Robinson, D. A., & Fuchs, A. F. (1969). Eye Movements Evoked by Stimulation of Frontal Eye Fields. Journal of Neurophysiology, 32(5), 637-648.
  156. Schlag-Rey, M., Schlag, J., & Dassonville, P. (1992). How the frontal eye field can impose a saccade goal on superior colliculus neurons. Journal of Neurophysiology, 67(4), 1003-1005.
  157. Dorris, M. C., Taylor, T. L., Klein, R. M., & Munoz, D. P. (1999). Influence of previous visual stimulus or saccade on saccadic reaction times in monkey. Journal of Neurophysiology, 81(5), 2429-2436.
  158. Neill, W. T. (1977). Inhibitory and Facilitatory Processes in Selective Attention. Journal of Experimental Psychology: Human Perception and Performance, 3(3), 444-450.
  159. O'Regan, J. K., & Lévy-Schoen, A. (1983). Integrating visual information from successive fixations: does trans-saccadic fusion exist? Vision Research, 23(8), 765-768.
  160. Schlag, J., Dassonville, P., & Schlag-Rey, M. (1998). Interaction of the two frontal eye fields before saccade onset. Journal of Neurophysiology, 79(1), 64-72.
  161. Burnham, K. ., & Anderson, D. R. (2002). Model Selection and Multimodal Inference (Second Edi). New York: Springer.
  162. Watanabe, K., Lauwereyns, J., & Hikosaka, O. (2003). Neural Correlates of Rewarded and Unrewarded Eye Movements in the Primate Caudate Nucleus. Journal of Neuroscience, 23(31), 10052-10057.
  163. Watanabe, K., Lauwereyns, J., & Hikosaka, O. (2003). Neural Correlates of Rewarded and Unrewarded Eye Movements in the Primate Caudate Nucleus. Journal of Neuroscience, 23(31), 10052-10057.
  164. Everling, S., & Munoz, D. P. (2000). Neuronal correlates for preparatory set associated with pro-saccades and anti-saccades in the primate frontal eye field. Journal of Neuroscience, 20(1), 387-400.
  165. Carpenter, R. H. S. (1981). Oculomotor procrastination. In D. F. Fisher, R. A. Monty, & J. W. Senders (Eds.), Eye movements: Cognition and Visual Perception (pp. 237-246). Hillsdale, NJ: Lawrence Erlbaum Associates.
  166. Goldberg, M. E., & Bruce, C. J. (1990). Primate frontal eye fields. III. Maintenance of a spatially accurate saccade signal. Journal of Neurophysiology, 64(2), 489-508.
  167. Sato, M., & Hikosaka, O. (2002). Role of primate substantia nigra pars reticulata in reward-oriented saccadic eye movement. Journal of Neuroscience, 22(6), 2363-73.
  168. Sato, M., & Hikosaka, O. (2002). Role of primate substantia nigra pars reticulata in reward- oriented saccadic eye movement. Journal of Neuroscience, 22(6), 2363-73.
  169. Dorris, M. C., & Munoz, D. P. (1998). Saccadic probability influences motor preparation signals and time to saccadic initiation. Journal of Neuroscience, 18(17), 7015-7026.
  170. Umeno, M. M., & Goldberg, M. E. (1997). Spatial Processing in the Monkey Frontal Eye Field . I . Predictive Visual Responses. Journal of Neurophysiology, 78, 1373-1383.
  171. Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10(4), 433-436.
  172. White, B. J., & Munoz, D. P. (2011). The superior colliculus. In S. Liversedge, I. D. Gilchrist, & S.
  173. Duhamel, J.-R., Colby, C. L., & Goldberg, M. E. (1992). The Updating of the Representation of Visual Space in Parietal Cortex by Intended Eye Movements. Science, 255, 90-92.
  174. Schall, J. D., Morel, A., & Kaas, J. H. (1993). Topography of supplementary eye field afferents to frontal eye field in macaque: Implications for mapping between saccade coordinate systems. Visual Neuroscience, 10, 385-393.

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