Skip to main content

The Application of Large Scale Brain Systems to Practical “EF” Behavior: Revisiting the Introductory Examples

  • Chapter
  • First Online:
  • 1777 Accesses

Part of the book series: SpringerBriefs in Neuroscience ((TVOBTP))

Abstract

The introduction of this paper described numerous examples of decision making, or problem-solving. These examples warrant a close examination of the concept of cognitive control, how it differs in some of these examples, and how it is measured in neuropsychological evaluation. All examples required keeping information in mind for the ultimate purpose of guiding behavior. To reiterate, this is a task-dependent cognitive system, with a changing locus of control dependent on the task in question, an extension of the fronto-striatal motor control system [42, 51].

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Seger, C.A. and C.M. Cincotta, Dynamics of frontal, striatal, and hippocampal systems during rule learning. Cereb Cortex, 2006. 16(11): p. 1546-55.

    Article  PubMed  Google Scholar 

  2. Lezak, M.D., et al., Neuropsychological assessment. 5th ed. 2012, Oxford; New York: Oxford University Press. xxv, 1161 p.

    Google Scholar 

  3. Wasserman, T. and L.D. Wasserman, Toward an integrated model of executive functioning in children. Appl Neuropsychol Child, 2013. 2(2): p. 88-96.

    Article  PubMed  Google Scholar 

  4. Miller, R., A theory of basal ganglia and their disorders. 2008, Boca Raton: CRC Press.

    Google Scholar 

  5. Cromwell, H.C. and J. Panksepp, Rethinking the cognitive revolution from a neural perspective: how overuse/misuse of the term ‘cognition’ and the neglect of affective controls in behavioral neuroscience could be delaying progress in understanding the BrainMind. Neurosci Biobehav Rev, 2011. 35(9): p. 2026-35.

    Article  PubMed  Google Scholar 

  6. Hazy, T.E., M.J. Frank, and R.C. O’reilly, Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system. Philos Trans R Soc Lond B Biol Sci, 2007. 362(1485): p. 1601-13.

    Article  PubMed Central  PubMed  Google Scholar 

  7. Hazy, T.E., M.J. Frank, and R.C. O’Reilly, Banishing the homunculus: making working memory work. Neuroscience, 2006. 139(1): p. 105-18.

    Article  PubMed  Google Scholar 

  8. Castellanos, F.X. and E. Proal, Large-scale brain systems in ADHD: beyond the prefrontal-striatal model. Trends Cogn Sci, 2012. 16(1): p. 17-26.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Frank, M.J., A. Scheres, and S.J. Sherman, Understanding decision-making deficits in neurological conditions: insights from models of natural action selection. Philos Trans R Soc Lond B Biol Sci, 2007. 362(1485): p. 1641-54.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Wechsler, D., Wechsler Adult Intelligence Scale-III. 1997, San Antonio, TX: Psychological Corporation.

    Google Scholar 

  11. Gerton, B.K., et al., Shared and distinct neurophysiological components of the digits forward and backward tasks as revealed by functional neuroimaging. Neuropsychologia, 2004. 42(13): p. 1781-7.

    Article  PubMed  Google Scholar 

  12. Dengtang, L., X. Yifeng, and L. Zheng, Functional magnetic resonance imaging of backward digit span task in first-episode schizophrenia patients before and after treatment. Shanghai Archives of Psychiatry, 2004. 16(5).

    Google Scholar 

  13. Justus, T. and R.B. Ivry, The cognitive neuropsychology of the cerebellum. International Review of Psychiatry, 2001. 13: p. 276-282.

    Article  Google Scholar 

  14. Marvel, C.L. and J.E. Desmond, Functional topography of the cerebellum in verbal working memory. Neuropsychol Rev, 2010. 20(3): p. 271-9.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Ravizza, S.M., et al., Cerebellar damage produces selective deficits in verbal working memory. Brain, 2006. 129(Pt 2): p. 306-20.

    PubMed  Google Scholar 

  16. Takahashi, M., et al., White matter microstructure of the cingulum and cerebellar peduncle is related to sustained attention and working memory: a diffusion tensor imaging study. Neurosci Lett, 2010. 477(2): p. 72-6.

    Article  PubMed  Google Scholar 

  17. Shulman, G.L., et al., Interaction of stimulus-driven reorienting and expectation in ventral and dorsal frontoparietal and basal ganglia-cortical networks. J Neurosci, 2009. 29(14): p. 4392-407.

    Article  PubMed Central  PubMed  Google Scholar 

  18. Capotosto, P., et al., Frontoparietal cortex controls spatial attention through modulation of anticipatory alpha rhythms. J Neurosci, 2009. 29(18): p. 5863-72.

    Article  PubMed Central  PubMed  Google Scholar 

  19. Arnott, S.R. and C. Alain, The auditory dorsal pathway: orienting vision. Neurosci Biobehav Rev, 2011. 35(10): p. 2162-73.

    Article  PubMed  Google Scholar 

  20. Grant, E.R. and M.J. Spivey, Eye movements and problem solving: guiding attention guides thought. Psychol Sci, 2003. 14(5): p. 462-6.

    Article  PubMed  Google Scholar 

  21. Thomas, L.E. and A. Lleras, Moving eyes and moving thought: on the spatial compatibility between eye movements and cognition. Psychon Bull Rev, 2007. 14(4): p. 663-8.

    Article  PubMed  Google Scholar 

  22. Banich, M.T. and R.J. Compton, Cognitive neuroscience. 3rd ed. 2011, Belmont, CA: Wadsworth, Cengage Learning. xxiii, 595 p.

    Google Scholar 

  23. Naatanen, R., T. Kujala, and I. Winkler, Auditory processing that leads to conscious perception: a unique window to central auditory processing opened by the mismatch negativity and related responses. Psychophysiology, 2011. 48(1): p. 4-22.

    Article  PubMed  Google Scholar 

  24. Salmi, J., et al., Orienting and maintenance of spatial attention in audition and vision: an event-related brain potential study. The European journal of neuroscience, 2007. 25(12): p. 3725-33.

    Article  PubMed  Google Scholar 

  25. Johnson, J.S., et al., Implicit memory influences the allocation of attention in visual cortex. Psychon Bull Rev, 2007. 14(5): p. 834-9.

    Article  PubMed  Google Scholar 

  26. Li, R., et al., The neuronal correlates of digits backward are revealed by voxel-based morphometry and resting-state functional connectivity analyses. PLoS One, 2012. 7(2): p. e31877.

    Article  PubMed Central  PubMed  Google Scholar 

  27. Morton, J.B. and Y. Munakata, Active versus latent representations: a neural network model of perseveration, dissociation, and decalage. Dev Psychobiol, 2002. 40(3): p. 255-65.

    Article  PubMed  Google Scholar 

  28. Morton, J.B. and Y. Munakata, Are you listening? Exploring a developmental knowledge-action dissociation in a speech interpretation task. Developmental Science, 2002. 5(4): p. 435-440.

    Article  Google Scholar 

  29. Chatham, C.H., M.J. Frank, and Y. Munakata, Pupillometric and behavioral markers of a developmental shift in the temporal dynamics of cognitive control. Proc Natl Acad Sci U S A, 2009. 106(14): p. 5529-33.

    Article  PubMed Central  PubMed  Google Scholar 

  30. Tau, G.Z. and B.S. Peterson, Normal development of brain circuits. Neuropsychopharmacology, 2010. 35(1): p. 147-68.

    Article  PubMed Central  PubMed  Google Scholar 

  31. Brahmbhatt, S.B., T. McAuley, and D.M. Barch, Functional developmental similarities and differences in the neural correlates of verbal and nonverbal working memory tasks. Neuropsychologia, 2008. 46(4): p. 1020-31.

    Article  PubMed Central  PubMed  Google Scholar 

  32. Luna, B., A. Padmanabhan, and K. O’Hearn, What has fMRI told us about the development of cognitive control through adolescence? Brain Cogn, 2010. 72(1): p. 101-13.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Koziol, L.F., D.E. Budding, and D. Chidekel, Adaptation, expertise, and giftedness: towards an understanding of cortical, subcortical, and cerebellar network contributions. Cerebellum, 2010. 9(4): p. 499-529.

    Article  PubMed  Google Scholar 

  34. Shrager, Y., et al., Working memory and the organization of brain systems. J Neurosci, 2008. 28(18): p. 4818-22.

    Article  PubMed Central  PubMed  Google Scholar 

  35. Morton, J.B. and Y. Munakata, Active versus latent representations: A neural network model of perseveration, dissociation, and decalage. Developmental Psychobiology, 2002. 40(3): p. 255-265.

    Article  PubMed  Google Scholar 

  36. Davidson, M.C., et al., Development of cognitive control and executive functions from 4 to 13 years: evidence from manipulations of memory, inhibition, and task switching. Neuropsychologia, 2006. 44(11): p. 2037-78.

    Article  PubMed Central  PubMed  Google Scholar 

  37. Diamond, A., The early development of executive functions, in Lifespan cognition: mechanisms of change, E. Bialystok and F.I.M. Craik, Editors. 2006, Oxford University Press: Oxford; New York. p. 70-95.

    Chapter  Google Scholar 

  38. Raj, V. and M.A. Bell, Cognitive processes supporting episodic memory formation in childhood: The role of source memory, binding, and executive functioning. Developmental Review, 2010. 30: p. 384-402.

    Article  Google Scholar 

  39. Hayne, H. and K. Imuta, Episodic memory in 3- and 4-year-old children. Developmental Psychobiology, 2011. 53(3): p. 317-322.

    Article  PubMed  Google Scholar 

  40. Blackwell, K.A., N.J. Cepeda, and Y. Munakata, When simple things are meaningful: working memory strength predicts children’s cognitive flexibility. J Exp Child Psychol, 2009. 103(2): p. 241-9.

    Article  PubMed Central  PubMed  Google Scholar 

  41. Johnson, M.H. and Y. Munakata, Processes of change in brain and cognitive development. Trends Cogn Sci, 2005. 9(3): p. 152-8.

    Article  PubMed  Google Scholar 

  42. Munakata, Y., B.J. Casey, and A. Diamond, Developmental cognitive neuroscience: progress and potential. Trends Cogn Sci, 2004. 8(3): p. 122-8.

    Article  PubMed  Google Scholar 

  43. Munakata, Y., et al., A unified framework for inhibitory control. Trends Cogn Sci, 2011. 15(10): p. 453-9.

    Article  PubMed Central  PubMed  Google Scholar 

  44. Bachevalier, J., L. Malkova, and M. Beauregard, Multiple memory systems: a neuropsychological and developmental perspective, in Attention, memory, and executive function, G.R. Lyon and N.A. Krasnegor, Editors. 1996, P.H. Brookes Pub. Co.: Baltimore. p. 185-198.

    Google Scholar 

  45. Munakata, Y., H.R. Snyder, and C.H. Chatham, Developing Cognitive Control: Three Key Transitions. Curr Dir Psychol Sci, 2012. 21(2): p. 71-77.

    Article  PubMed Central  PubMed  Google Scholar 

  46. Chu-Shore, C.J., et al., Network analysis: applications for the developing brain. J Child Neurol, 2011. 26(4): p. 488-500.

    Article  PubMed Central  PubMed  Google Scholar 

  47. Supekar, K., M. Musen, and V. Menon, Development of large-scale functional brain networks in children. PLoS Biol, 2009. 7(7): p. e1000157.

    Article  PubMed Central  PubMed  Google Scholar 

  48. Fair, D.A., et al., Development of distinct control networks through segregation and integration. Proc Natl Acad Sci U S A, 2007. 104(33): p. 13507-12.

    Article  PubMed Central  PubMed  Google Scholar 

  49. Bressler, S.L. and V. Menon, Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn Sci, 2010. 14(6): p. 277-90.

    Article  PubMed  Google Scholar 

  50. Wechsler, D., Wechsler Intelligence Scale for Children (4th ed.). 2003, San Antonio, TX: The Psychological Corporation.

    Google Scholar 

  51. Wechsler, D., Wechsler Adult Intelligence Scale-IV. 2008, San Antonio, TX: The Psychological Corporation.

    Google Scholar 

  52. Wechsler, D., WISC-IV integrated technical and interpretive manual. 2005, San Antonio, TX: Psychological Corporation.

    Google Scholar 

  53. Hassin, R.R., et al., Implicit working memory. Conscious Cogn, 2009. 18(3): p. 665-78.

    Article  PubMed Central  PubMed  Google Scholar 

  54. Glascher, J., et al., Lesion mapping of cognitive abilities linked to intelligence. Neuron, 2009. 61(5): p. 681-91.

    Article  PubMed Central  PubMed  Google Scholar 

  55. Meyers, J.E. and M.L. Rohling, CT and MRI correlations with neuropsychological tests. Appl Neuropsychol, 2009. 16(4): p. 237-53.

    Article  PubMed  Google Scholar 

  56. Simon, T.J. and S.M. Rivera, Neuroanatomical approaches to the study of mathematical ability and disability, in Why is math so hard for some children?: the nature and origins of mathematical learning difficulties and disabilities, D.B. Berch and M.I.M.M. Mazzocco, Editors. 2007, Paul H. Brookes Pub. Co.: Baltimore, Md. p. xxviii, 457 p.

    Google Scholar 

  57. Piazza, M., et al., Developmental trajectory of number acuity reveals a severe impairment in developmental dyscalculia. Cognition, 2010. 116(1): p. 33-41.

    Article  PubMed  Google Scholar 

  58. Luculano, T., et al., Brain organization underlying superior mathematical abilities in children with autism. Biol Psychiatry, 2013.

    Google Scholar 

  59. Kent, P., The evolution of the wechsler memory scale: a selective review. Appl Neuropsychol Adult, 2013.

    Google Scholar 

  60. Gabrieli, J.D., Cognitive neuroscience of human memory. Annu Rev Psychol, 1998. 49: p. 87-115.

    Article  PubMed  Google Scholar 

  61. Poldrack, R.A., et al., The neural correlates of motor skill automaticity. J Neurosci, 2005. 25(22): p. 5356-64.

    Article  PubMed  Google Scholar 

  62. Cisek, P. and J.F. Kalaska, Neural mechanisms for interacting with a world full of action choices. Annu Rev Neurosci, 2010. 33: p. 269-98.

    Article  PubMed  Google Scholar 

  63. Friston, K.J., et al., The timing of the cognitive cycle. PLoS ONE, 2011. 6(4): p. e14803.

    Article  Google Scholar 

  64. Houk, J.C., et al., Action selection and refinement in subcortical loops through basal ganglia and cerebellum. Philos Trans R Soc Lond B Biol Sci, 2007. 362(1485): p. 1573-83.

    Article  PubMed Central  PubMed  Google Scholar 

  65. Houk, J.C. and S.P. Wise, Distributed modular architectures linking basal ganglia, cerebellum, and cerebral cortex: their role in planning and controlling action. Cereb Cortex, 1995. 5(2): p. 95-110.

    Article  PubMed  Google Scholar 

  66. Hikosaka, O. and M. Isoda, Switching from automatic to controlled behavior: cortico-basal ganglia mechanisms. Trends Cogn Sci, 2010. 14(4): p. 154-61.

    Article  PubMed Central  PubMed  Google Scholar 

  67. Koziol, L.F. and J.T. Lutz, From movement to thought: the development of executive function. Appl Neuropsychol Child, 2013. 2(2): p. 104-15.

    Article  PubMed  Google Scholar 

  68. Koziol, L.F., D.E. Budding, and D. Chidekel, From movement to thought: executive function, embodied cognition, and the cerebellum. Cerebellum, 2012. 11(2): p. 505-25.

    Article  PubMed  Google Scholar 

  69. Heilman, K.M. and L.G. Rothi, Apraxia in Clinical neuropsychology, K.M. Heilman and E. Valenstein, Editors. 2003, Oxford University Press: Oxford; New York. p. 215-235.

    Google Scholar 

  70. Strauss, E., et al., A compendium of neuropsychological tests: administration, norms, and commentary. 3rd ed. 2006, Oxford; New York: Oxford University Press. xvii, 1216 p.

    Google Scholar 

  71. Galea, J.M., et al., Dissociating the roles of the cerebellum and motor cortex during adaptive learning: the motor cortex retains what the cerebellum learns. Cereb Cortex, 2011. 21(8): p. 1761-70.

    Article  PubMed Central  PubMed  Google Scholar 

  72. Bargh, J.A., The automaticity of everyday life, in The automaticity of everyday life: Advances in social cognition, R. Wyer and J.A. Bargh, Editors. 1997, Lawrence Erlbaum Associates: Mahwah, N.J. p. 1-61.

    Google Scholar 

  73. Bargh, J.A. and T.L. Chartrand, The unbearable automaticity of being. American Psychologist, 1999. 54(7): p. 462-479.

    Article  Google Scholar 

  74. Pezzulo, G., Grounding procedural and declarative knowledge in sensorimotor anticipation. Mind & Language, 2011. 26(1): p. 78-114.

    Article  Google Scholar 

  75. Pezzulo, G. and H. Dindo, What should I do next? Using shared representations to solve interaction problems. Exp Brain Res, 2011. 211(3-4): p. 613-30.

    Article  PubMed  Google Scholar 

  76. Pezzulo, G. and F. Rigoli, The value of foresight: how prospection affects decision-making. Front Neurosci, 2011. 5: p. 79.

    Article  PubMed Central  PubMed  Google Scholar 

  77. Ashby, F.G. and W.T. Maddox, Human category learning 2.0. Ann N Y Acad Sci, 2011. 1224: p. 147-61.

    Article  PubMed Central  PubMed  Google Scholar 

  78. Habeck, C., et al., An event-related fMRI study of the neural networks underlying the encoding, maintenance, and retrieval phase in a delayed-match-to-sample task. Brain Res Cogn Brain Res, 2005. 23(2-3): p. 207-20.

    Article  PubMed  Google Scholar 

  79. Veltman, D.J., S.A. Rombouts, and R.J. Dolan, Maintenance versus manipulation in verbal working memory revisited: an fMRI study. Neuroimage, 2003. 18(2): p. 247-56.

    Article  PubMed  Google Scholar 

  80. McNab, F. and T. Klingberg, Prefrontal cortex and basal ganglia control access to working memory. Nat Neurosci, 2008. 11(1): p. 103-7.

    Article  PubMed  Google Scholar 

  81. Awh, E. and E.K. Vogel, The bouncer in the brain. Nat Neurosci, 2008. 11(1): p. 5-6.

    Article  PubMed  Google Scholar 

  82. Chang, C., S. Crottaz-Herbette, and V. Menon, Temporal dynamics of basal ganglia response and connectivity during verbal working memory. Neuroimage, 2007. 34(3): p. 1253-69.

    Article  PubMed  Google Scholar 

  83. Blais, C., et al., Rethinking the role of automaticity in cognitive control. Q J Exp Psychol (Hove), 2010. 65(2): p. 268-76.

    Article  Google Scholar 

  84. Eitam, B., R.R. Hassin, and Y. Schul, Nonconscious goal pursuit in novel environments: the case of implicit learning. Psychol Sci, 2008. 19(3): p. 261-7.

    Article  PubMed  Google Scholar 

  85. Eitam, B., Y. Schul, and R.R. Hassin, Goal relevance and artificial grammar learning. Q J Exp Psychol (Hove), 2009. 62(2): p. 228-38.

    Article  Google Scholar 

  86. Cole, M.W., et al., Multi-task connectivity reveals flexible hubs for adaptive task control. Nat Neurosci, 2013.

    Google Scholar 

  87. Bruya, B., Effortless attention: a new perspective in the cognitive science of attention and action. 2010, Cambridge, Mass.: The MIT Press. viii, 449 p.

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Koziol, L.F. (2014). The Application of Large Scale Brain Systems to Practical “EF” Behavior: Revisiting the Introductory Examples. In: The Myth of Executive Functioning. SpringerBriefs in Neuroscience(). Springer, Cham. https://doi.org/10.1007/978-3-319-04477-4_7

Download citation

Publish with us

Policies and ethics