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Reward and Attentional Control in Visual Search

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The Influence of Attention, Learning, and Motivation on Visual Search

Part of the book series: Nebraska Symposium on Motivation ((NSM))

Abstract

It has long been known that the control of attention in visual search depends both on voluntary, top-down deployment according to context-specific goals, and on involuntary, stimulus-driven capture based on the physical conspicuity of perceptual objects. Recent evidence suggests that pairing target stimuli with reward can modulate the voluntary deployment of attention, but there is little evidence that reward modulates the involuntary deployment of attention to task-irrelevant distractors. We report several experiments that investigate the role of reward learning on attentional control. Each experiment involved a training phase and a test phase. In the training phase, different colors were associated with different amounts of monetary reward. In the test phase, color was not task-relevant and participants searched for a shape singleton; in most experiments no reward was delivered in the test phase. We first show that attentional capture by physically salient distractors is magnified by a previous association with reward. In subsequent experiments we demonstrate that physically inconspicuous stimuli previously associated with reward capture attention persistently during extinction—even several days after training. Furthermore, vulnerability to attentional capture by high-value stimuli is negatively correlated across individuals with working memory capacity and positively correlated with trait impulsivity. An analysis of intertrial effects reveals that value-driven attentional capture is spatially specific. Finally, when reward is delivered at test contingent on the task-relevant shape feature, recent reward history modulates value-driven attentional capture by the irrelevant color feature. The influence of learned value on attention may provide a useful model of clinical syndromes characterized by similar failures of cognitive control, including addiction, attention-deficit/hyperactivity disorder, and obesity.

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References

  • Anderson, B. A., & Folk, C. L. (2010). Variations in the magnitude of attentional capture: Testing a two-process model. Attention, Perception, & Psychophysics, 72, 342–352.

    Article  Google Scholar 

  • Anderson, B. A., Laurent, P. A., & Yantis, S. (2011a). Value-driven attentional capture. Proceedings of the National Academy of Sciences U S A, 108, 10367–10371.

    Article  Google Scholar 

  • Anderson, B. A., Laurent, P. A., & Yantis, S. (2011b). Learned value magnifies salience-based attentional capture. PLoS One, 6(11), e27926.

    Google Scholar 

  • Anderson, B. A., Laurent, P. A., & Yantis, S. (2012). Generalization of value-based attentional priority. Visual Cognition, 20, 647–658.

    Google Scholar 

  • Belopolsky, A. V., Schreij, D., & Theeuwes, J. (2010). What is top-down about contingent capture? Attention, Perception, &Psychophysics, 72, 326–341.

    Article  Google Scholar 

  • 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, 309–369.

    Article  PubMed  Google Scholar 

  • Bisley, J. W., & Goldberg, M. E. (2010). Attention, intention, and priority in the parietal lobe. Annual Review of Neuroscience, 33, 1–21.

    Article  PubMed  Google Scholar 

  • Braver, T. S., Cole, M. W.,& Yarkoni, T. (2010). Vive les differences! Individual variation in neural mechanisms of executive control. Current Opinion in Neurobiology, 20, 242–250.

    Article  PubMed  Google Scholar 

  • Bundesen, C. (1990). A theory of visual attention. Psychological Review, 97, 523–547.

    Article  PubMed  Google Scholar 

  • Bush, G. (2010). Attention-deficit/hyperactivity disorder and attention networks. Neuropsychopharmacology, 35, 278–300.

    Article  PubMed  Google Scholar 

  • Christ, S. E., & Abrams, R. A. (2006). Abrupt onsets cannot be ignored. Psychonomic Bulletin & Review, 13, 875–880.

    Article  Google Scholar 

  • Corbetta, M., & Shulman, G.L. (2002). Control of goal-directed and stimulus driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215.

    Article  PubMed  Google Scholar 

  • Davis, C. (2010). Attention-deficit/hyperactivity disorder: associations with overeating and obesity. Current Psychiatry Reports, 12, 389–395.

    Article  PubMed  Google Scholar 

  • Della Libera, C., & Chelazzi, L. (2006). Visual selective attention and the effects of monetary reward. Psychological Science, 17, 222–227.

    Article  PubMed  Google Scholar 

  • Della Libera, C., & Chelazzi, L. (2009). Learning to attend and to ignore is a matter of gains and losses. Psychological Science, 20, 778–784.

    Article  PubMed  Google Scholar 

  • Dickman, S. J., & Meyer, D. E. (1988) Impulsivity and speed-accuracy tradeoffs in information processing. Journal of Personality & Social Psychology, 54, 274–290.

    Article  Google Scholar 

  • Duncan, J., Ward, R., & Shapiro, K. (1994). Direct measurement of attentional dwell time in human vision. Nature, 369, 313–315.

    Article  PubMed  Google Scholar 

  • Egeth, H. E., &Yantis, S. (1997). Visual attention: Control, representation, and time course. Annual Review of Psychology, 48, 269–297.

    Article  PubMed  Google Scholar 

  • Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & Psychophysics, 16, 143–149.

    Article  Google Scholar 

  • Everitt, B. J., Dickinson, A., & Robbins, T. W. (2001).The neuropsychological basis of addictive behaviour. Brain Research Reviews, 36, 129–138.

    Article  PubMed  Google Scholar 

  • Field, M., & Cox, W. M. (2008). Attentional bias in addictive behaviors: A review of its development, causes, and consequences. Drug and Alcohol Dependence, 97, 1–20.

    Article  PubMed  Google Scholar 

  • Folk, C. L., & Remington, R. W. (1998). Selectivity in distraction by irrelevant featural singletons: Evidence for two forms of attentional capture. Journal of Experimental Psychology: Human Perception & Performance, 24, 847–858.

    Article  Google Scholar 

  • Folk, C.L., Remington, R. W., & Johnston, J. C. (1992). Involuntary covert orienting is contingent on attentional control settings. Journal of Experimental Psychology: Human Perception & Performance, 18, 1030–1044.

    Article  Google Scholar 

  • Folk, C. L., Remington, R. W., Wu, S. C. (2009). Additivity of abrupt onset effects supports nonspatial distraction, not the capture of spatial attention. Attention Perception & Psychophysics, 71, 308–313.

    Article  Google Scholar 

  • Fukuda, K., & Vogel, E. K. (2009). Human variation in overriding attentional capture. Journal of Neuroscience, 29, 8726–8733.

    Article  PubMed  Google Scholar 

  • Fukuda, K., & Vogel, E. K. (2011). Individual differences in recovery time from attentional capture. Psychological Science, 22, 361–368.

    Article  PubMed  Google Scholar 

  • Garavan, H., & Hester, R. (2007). The role of cognitive control in cocaine dependence. Neuropsychological Review, 17, 337–345.

    Article  Google Scholar 

  • Groman, S. M., James, A. S., Jentsch, J. D. (2008). Poor response inhibition: at the nexus between substance abuse and attention deficit/hyperactivity disorder. Neuroscience & Biobehavioral Reviews, 33, 690–698.

    Article  Google Scholar 

  • Hickey, C., Chelazzi, L., & Theeuwes, J. (2010a). Reward changes salience in human vision via the anterior cingulate. Journal of Neuroscience, 30, 11096–11103.

    Article  Google Scholar 

  • Hickey, C., Chelazzi, L., & Theeuwes, J. (2010b). Reward guides vision when it’s your thing: Trait reward-seeking in reward-mediated visual priming. PLOS One, 5, e14087.

    Google Scholar 

  • Hollerman J. R., Tremblay L., Schultz W. (1998). Influence of reward expectation on behavior-related neuronal activity in primate striatum. Journal of Neurophysiology, 80, 947–963.

    PubMed  Google Scholar 

  • Itti, L., & Koch, C. (2001). Computational modelling of visual attention. Nature Reviews Neuroscience, 2, 194–203.

    Article  PubMed  Google Scholar 

  • Koob, G. F., & Le Moal, M. (1997). Drug abuse: Hedonic homeostatic dysregulation. Science, 278, 52–58.

    Article  PubMed  Google Scholar 

  • Krebs, R. M., Boehler, C. N., & Woldorff, M. G. (2010). The influence of reward associations on conflict processing in the Stroop task. Cognition, 117, 341–347.

    Article  PubMed  Google Scholar 

  • Kyllingsbaek, S., Schneider, W. X., & Bundesen, C. (2001). Automatic attraction of attention to former targets in visual displays of letters. Perception & Psychophysics, 63, 85–98.

    Article  Google Scholar 

  • Lien, M.-C., Ruthruff, E., & Johnston, J. V. (2010). Attentional capture with rapidly changing attentional control settings. Journal of Experimental Psychology: Human Perception & Performance, 36, 1–16.

    Article  Google Scholar 

  • Lin, J. Y., Murray, S. O., & Boynton, G. M. (2009). Capture of attention to threatening stimuli without perceptual awareness. Current Biology, 19, 1118–1122.

    Article  PubMed  Google Scholar 

  • Moran, J., & Desimone, R. (1985). Selective attention gates visual processing in the extrastriate cortex. Science, 229, 782–784.

    Article  PubMed  Google Scholar 

  • McClure, S. M., Berns, G. S., & Montague, P. R. (2003). Temporal prediction errors in a passive learning task activate human striatum. Neuron, 38, 339–346.

    Article  PubMed  Google Scholar 

  • Navalpakkam, V., Koch, C., Rangel, A., & Perona, P. (2010). Optimal reward harvesting in complex perceptual environments. Proceedings of the National Academy of Sciences U S A, 107, 5232–5237.

    Article  Google Scholar 

  • O’Doherty, J. P., Dayan, P., Friston, K., Critchley, H., & Dolan, R. J. (2003). Temporal difference models and reward-related learning in the human brain. Neuron, 38, 329–337.

    Article  PubMed  Google Scholar 

  • Parkhurst, D., Law, K., & Niebur, E. (2002). Modeling the role of salience in the allocation of overt visual attention. Vision Research, 42, 107–123.

    Article  PubMed  Google Scholar 

  • Pashler, H. (Ed.). (1998). Attention. London: Psychology Press.

    Google Scholar 

  • Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the barratt impulsiveness scale. Journal of Clinical Psychology, 51, 768–774.

    Article  PubMed  Google Scholar 

  • Peck, C. J., Jangraw, D. C., Suzuki, M., Efem, R., & Gottlieb, J. (2009). Reward modulates attention independently of action value in posterior parietal cortex. Journal of Neuroscience, 29, 11182–11191.

    Article  PubMed  Google Scholar 

  • Pessoa, L., & Engelmann, J. B. (2010). Embedding reward signals into perception and cognition. Frontiers in Neuroscience, 4(17).doi: 10.3389/fnins.2010.00017

    Google Scholar 

  • Platt, M. L., & Glimcher, P. W. (1999). Neural correlates of decision variables in parietal cortex. Nature, 400, 233–238.

    Article  PubMed  Google Scholar 

  • Raymond, J. E., & O’Brien, J. L. (2009). Selective visual attention and motivation: The consequences of value learning in an attentional blink task. Psychological Science, 20, 981–988.

    Article  PubMed  Google Scholar 

  • Rescorla, R. A. (1999). Partial reinforcement reduces the associative change produced by nonreinforcement. Journal of Experimental Psychology: Animal Behavior Processes, 25, 403–414.

    Article  Google Scholar 

  • Robinson, T. E., & Berridge, K. C. (2003). Addiction. Annual Review of Psychology, 54, 25–53.

    Article  PubMed  Google Scholar 

  • Robinson, T. E., & Berridge, K. C. (2008). The incentive sensitization theory of addiction: some current issues. Philosophical Transactions of the Royal Society: B Biological Sciences, 363, 3137–3146.

    Article  Google Scholar 

  • Schultz, W., Dayan, P., and Montague, P. R. (1997). A neural substrate of prediction and reward. Science, 275, 1593–1599.

    Article  PubMed  Google Scholar 

  • Serences, J. T. (2008). Value-based modulations in human visual cortex. Neuron, 60, 1169–1181.

    Article  PubMed  Google Scholar 

  • Serences, J. T., & Saproo, S. (2010). Population response profiles in early visual cortex are biased in favor of more valuable stimuli. Journal of Neurophysiology, 104, 76–87.

    Article  PubMed  Google Scholar 

  • Sheppard, B., Chavira, D., Azzam, A., Grados, M. A., Umaña, P., Garrido, P., & Mathews, C. A. (2010). ADHD prevalence and association with hoarding behaviors in childhood onset OCD. Depression & Anxiety, 27, 667–674.

    Article  Google Scholar 

  • Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing II: Perceptual learning, automatic attending, and general theory. Psychological Review, 84, 127–190.

    Article  Google Scholar 

  • Shuler, M. G., & Bear, M. F. (2006). Reward timing in the primary visual cortex. Science, 311, 1606–1609.

    Article  PubMed  Google Scholar 

  • Simen, P., Contreras, D., Buck, C., Hu, P., Holmes, P.,& Cohen, J.D. (2009). Reward rate optimization in two-alternative decision making: empirical tests of theoretical predictions. Journal of Experimental Psychology: Human Perception & Performance, 35, 1865–1897.

    Article  Google Scholar 

  • Sugrue, L. P., Corrado, G. S., & Newsome, W. T. (2005). Choosing the greater of two goods: neural currencies for valuation and decision making. Nature Reviews Neuroscience, 6, 363–375.

    Article  PubMed  Google Scholar 

  • Sutton, R. S., & Barto, A. G. (1998).Reinforcement learning: An introduction. Cambridge: MIT Press.

    Google Scholar 

  • Theeuwes, J. (1992). Perceptual selectivity for color and form. Perception & Psychophysics, 51, 599–606.

    Article  Google Scholar 

  • Theeuwes, J. (2010). Top-down and bottom-up control of visual selection. Acta Psychologica, 135, 77–99.

    Article  PubMed  Google Scholar 

  • Theeuwes, J., & Godijn, R. (2002). Irrelevant singletons capture attention: Evidence from inhibition of return. Perception & Psychophysics, 64, 764–770.

    Article  Google Scholar 

  • Yantis, S. (1993).Stimulus-driven attentional capture. Current Directions in Psychological Science, 2, 156–161.

    Article  Google Scholar 

  • Yantis, S. (2000). Goal-directed and stimulus-driven determinants of attentional control. In S. Monsell, & J. Driver (Eds.), Attention and performance (Vol. 18, pp. 73–103). Cambridge: MIT Press.

    Google Scholar 

  • Yantis, S. (2008). Neural basis of selective attention: Cortical sources and targets of attentional modulation. Current Directions in Psychological Science, 17, 86–90.

    Article  PubMed  Google Scholar 

  • Yantis, S., & Hillstrom, A. P. (1994). Stimulus-driven attentional capture: Evidence from equiluminant visual objects. Journal of Experimental Psychology: Human Perception & Performance, 20, 95–107.

    Article  Google Scholar 

  • Yantis, S., & Jonides, J. (1984). Abrupt visual onsets and selective attention: Evidence from visual search. Journal of Experimental Psychology: Human Perception & Performance, 10, 350–374.

    Article  Google Scholar 

  • Yantis, S., & Jonides, J. (1990). Abrupt visual onsets and selective attention: Voluntary versus automatic allocation. Journal of Experimental Psychology: Human Perception & Performance, 16, 121–134.

    Article  Google Scholar 

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Acknowledgements

We thank H. Egeth, J. Flombaum, L. Gmeindl, P. Holland, D. E. Meyer, and J. Serences for fruitful discussions and suggestions. The experiments reported here were supported by US National Institutes of Health grant R01-DA013165 to S.Y.

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Correspondence to Steven Yantis .

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Yantis, S., Anderson, B., Wampler, E., Laurent, P. (2012). Reward and Attentional Control in Visual Search. In: Dodd, M., Flowers, J. (eds) The Influence of Attention, Learning, and Motivation on Visual Search. Nebraska Symposium on Motivation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4794-8_5

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