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Title
Abstract
Introduction
Methods Attentional Network Test
Results
Discussion
References
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Psychology
Cognitive Science

Human Attentional Networks: A Connectionist Model

Profile image of Hongbin WangHongbin Wang

2007, Journal of Cognitive Neuroscience

https://doi.org/10.1162/JOCN.2007.19.10.1678
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12 pages

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Abstract

Recent evidence in cognitive neuroscience has suggested that attention is a complex organ system subserved by at least three attentional networks in the brain, for alerting, orienting, and executive control functions. However, how these different networks work together to give rise to the seemingly unitary mental faculty of attention remains unclear. We describe a connectionist model of human attentional networks to explore the possible interplays among the networks from a computational perspective. This model is developed in the framework of leabra (local, error-driven, and associative, biologically realistic algorithm) and simultaneously involves these attentional networks connected in a biologically inspired way. We evaluate the model by simulating the empirical data collected on normal human subjects using the Attentional Network Test (ANT). The simulation results fit the experimental data well. In addition, we show that the same model, with a single parameter change that affect...

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References (51)

  1. Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrated theory of the mind. Psychological Review, 111, 1036-1060.
  2. Anderson, J. R., & Lebiere, C. (1998). The atomic components of thought. Hillsdale, NJ: Erlbaum.
  3. Anderson, J. R., & Lebiere, C. (2003). The Newell Test for a theory of cognition. Behavioral and Brain Science, 26, 587-637.
  4. Booth, J., Carlson, C. L., & Tucker, D. (2001). Cognitive inattention in the ADHD subtypes. Paper presented at the tenth scientific meeting of the International Society for Research in Child and Adolescent Psychopathology (ISRCAP), Vancouver, BC, Canada.
  5. Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108, 624-652.
  6. Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: An update. Trends in Cognitive Sciences, 8, 539-546.
  7. Braver, T. S., Barch, D. M., & Cohen, J. D. (1999). Cognition and control in schizophrenia: A computational model of dopamine and prefrontal function. Biological Psychiatry, 46, 312-328.
  8. Braver, T. S., & Cohen, J. D. (1999). Dopamine, cognitive control, and schizophrenia: The gating model. Progress in Brain Research, 121, 327-349.
  9. Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Sciences, 4, 215-222.
  10. Callejas, A., Lupianez, J., & Tudela, P. (2004). The three attentional networks: On their independence and interactions. Brain and Cognition, 54, 225-227.
  11. Churchland, P. S., & Sejnowski, T. J. (1992). The computational brain. Cambridge: MIT Press.
  12. Cohen, J. D., Dunbar, K., & McClelland, J. L. (1990). On the control of automatic processes: A parallel distributed processing account of the Stroop effect. Psychological Review, 97, 332-361.
  13. Cohen, J. D., Romero, R. D., Servan-Schreiber, D., & Farah, M. J. (1994). Mechanisms of spatial attention: The relation of macrostructure to microstructure in parietal neglect. Journal of Cognitive Neuroscience, 6, 377-387.
  14. Cohen, J. D., & Tong, F. (2001). The face of controversy. Science, 293, 2405-2407.
  15. Colby, C. L., & Goldberg, M. E. (1999). Space and attention in parietal cortex. Annual Review of Neuroscience, 22, 319-349.
  16. Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193-222.
  17. Egeth, H. E., & Yantis, S. (1997). Visual attention: Control, representation, and time course. Annual Review of Psychology, 48, 269-297.
  18. Fan, J., Fossella, J. A., Sommer, T., Wu, Y., & Posner, M. I. (2003). Mapping the genetic variation of executive attention onto brain activity. Proceedings of the National Academy of Sciences, U.S.A., 100, 7406-7411.
  19. Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. Neuroimage, 26, 471-479.
  20. Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14, 340-347.
  21. Fan, J., & Posner, M. I. (2004). Human attentional networks. Psychiatrische Praxis, 31, s210-s214.
  22. Fan, J., Raz, A., & Posner, M. I. (2003). Attentional mechanisms. In M. J. Aminoff & R. B. Daroff (Eds.), Encyclopedia of neurological sciences (Vol. 1, pp. 292-299). San Diego, CA: Academic Press.
  23. Fan, J., Wu, Y., Fossella, J. A., & Posner, M. I. (2001). Assessing the heritability of attentional networks. BMC Neuroscience, 2, 14-20.
  24. Farah, M. J. (2000). The cognitive neuroscience of vision. Malden, MA: Blackwell.
  25. Fletcher, P., McKenna, P. J., Friston, K. J., Frith, C. D., & Dolan, R. J. (1999). Abnormal cingulate modulation of fronto- temporal connectivity in schizophrenia. Neuroimage, 9, 337-342.
  26. Fossella, J., Posner, M. I., Fan, J., Swanson, J. M., & Pfaff, D. W. (2002). Attentional phenotypes for the analysis of higher mental function. The Scientific World, 2, 217-223.
  27. Herd, S. A., Banich, M. T., & O'Reilly, R. C. (2006). Neural mechanisms of cognitive control: Integrative model of Stroop task performance and fMRI data. Journal of Cognitive Neuroscience, 18, 22-32.
  28. Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709.
  29. Konrad, K., Neufang, S., Hanisch, C., Fink, G. R., & Herpertz- Dahlmann, B. (2006). Dysfunctional attentional networks in children with attention deficit/hyperactivity disorder: Evidence from an event related functional magnetic resonance imaging study. Biological Psychiatry, 59, 643-651.
  30. MacLeod, C. M. (1991). Half a century of research on the Stroop effect: An integrative review. Psychological Bulletin, 109, 163-203.
  31. MacLeod, C. M., & MacDonald, P. A. (2000). Interdimensional interference in the Stroop effect: Uncovering the cognitive and neural anatomy of attention. Trends in Cognitive Sciences, 4, 383-391.
  32. Marr, D. (1982). Vision. San Francisco, CA: Freeman.
  33. Montague, P. R., Hyman, S. E., & Cohen, J. D. (2004). Computational roles for dopamine in behavioural control. Nature, 431, 760-767.
  34. Oberlin, B. G., Alford, J. L., & Marrocco, R. T. (2005). Normal attention orienting but abnormal stimulus alerting and conflict effect in combined subtype of ADHD. Behavioral Brain Research, 165, 1-11.
  35. O'Reilly, R. C. (1998). Six principles for biologically based computational models of cortical cognition. Trends in Cognitive Sciences, 2, 455-462.
  36. O'Reilly, R. C., & Munakata, Y. (2000). Computational explorations in cognitive neuroscience. Cambridge: MIT Press.
  37. Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3-25.
  38. Posner, M. I. (Ed.). (2004). Cognitive neuroscience of attention. New York: Guilford Press.
  39. Posner, M. I., & Dehaene, S. (2000). Attentional networks. In M. S. Gazzaniga (Ed.), Cognitive neuroscience: A reader. Malden, MA: Blackwell.
  40. Posner, M. I., & Fan, J. (in press). Attention as an organ system. In J. Pomerantz (Ed.), Neurobiology of perception and communication: From synapse to society. The IVth De Lange Conference. Cambridge, UK: Cambridge University Press.
  41. Posner, M. I., & Petersen, S. E. (1990). The attention systems of the human brain. Annual Review of Neuroscience, 13, 25-42.
  42. Posner, M. I., & Raichle, M. E. (1994). Images of mind. New York: Scientific American Library.
  43. Posner, M. I., Rothbart, M. K., Vizueta, N., Levy, K. N., Evans, D. E., Thomas, K. M., et al. (2002). Attentional mechanisms of borderline personality disorder. Proceedings of the National Academy of Sciences, U.S.A., 99, 16366-16370.
  44. Raz, A., & Buhle, J. (2006). Typologies of attentional networks. Nature Reviews Neuroscience, 7, 367-379.
  45. Rueda, M. R., Fan, J., McCandliss, B. D., Halparin, J. D., Gruber, D. B., Lercari, L. P., et al. (2004). Development of attentional networks in childhood. Neuropsychologia, 42, 1029-1040.
  46. Scerif, G., & Karmiloff-Smith, A. (2005). The dawn of cognitive genetics? Crucial developmental caveats. Trends in Cognitive Sciences, 9, 126-135.
  47. Ungerleider, L. G., & Mishkin, M. (1982). Two cortical visual systems. In D. J. Ingle, M. A. Goodale, & R. J. W. Mansfield (Eds.), Analysis of visual behavior. Cambridge, MA: MIT Press.
  48. Wang, H., Fan, J., & Johnson, T. R. (2004). A symbolic model of human attentional networks. Cognitive Systems Research, 5, 119-134.
  49. Wang, H., Fan, J., & Yang, Y. (2004). Toward a multilevel analysis of human attentional networks. In K. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the Twenty-Sixth Annual Meeting of the Cognitive Science Society (pp. 1428-1433). Mahwah, NJ: Erlbaum.
  50. Wang, H., Johnson, T. R., Sun, Y., & Zhang, J. (2005). Object-location memory: The interplay of multiple representations. Memory & Cognition, 33, 1147-1159.
  51. Wang, K., Fan, J., Dong, Y., Wang, C.-Q., Lee, T. M. C., & Posner, M. I. (2005). Selective impairment of attentional networks of orienting and executive control in schizophrenia. Schizophrenia Research, 78, 235-241.

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