Advertisement

Neural effects of short-term training on working memory

  • Martin Buschkuehl
  • Luis Hernandez-Garcia
  • Susanne M. Jaeggi
  • Jessica A. Bernard
  • John Jonides
Article

Abstract

Working memory training has been the focus of intense research interest. Despite accumulating behavioral work, knowledge about the neural mechanisms underlying training effects is scarce. Here, we show that 7 days of training on an n-back task led to substantial performance improvements in the trained task; furthermore, the experimental group showed cross-modal transfer, as compared with an active control group. In addition, there were two neural effects that emerged as a function of training: first, increased perfusion during task performance in selected regions, reflecting a neural response to cope with high task demand; second, increased blood flow at rest in regions where training effects were apparent. We also found that perfusion at rest was correlated with task proficiency, probably reflecting an improved neural readiness to perform. Our findings are discussed within the context of the available neuroimaging literature on n-back training.

Keywords

ASL n-back Cognitive training Longitudinal fMRI Transfer 

Supplementary material

13415_2013_244_MOESM1_ESM.pdf (687 kb)
ESM 1 (PDF 687 kb)

References

  1. Aguirre, G. K., Detre, J. A., & Alsop, D. C. (2002). Experimental design and the relative sensitivity of BOLD and perfusion fMRI. NeuroImage, 15(3), 488–500. doi: 10.1006/nimg.2001.0990 PubMedCrossRefGoogle Scholar
  2. Anguera, J. A., Bernard, J. A., Jaeggi, S. M., Buschkuehl, M., Benson, B. L., Jennett, S., … Seidler, R. D. (2012). The effects of working memory resource depletion and training on sensorimotor adaptation. Behavioural Brain Research, 228(1), 107–115. doi: 10.1016/j.bbr.2011.11.040
  3. Bäckman, L., Nyberg, L., Soveri, A., Johansson, J., Andersson, M., Dahlin, E., … Rinne, J. O. (2011). Effects of working-memory training on striatal dopamine release. Science, 333(6043), 718. doi: 10.1126/science.1204978
  4. Behzadi, Y., Restom, K., Liau, J., & Liu, T. T. (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage, 37(1), 90–101. doi: 10.1016/j.neuroimage.2007.04.042 PubMedCentralPubMedCrossRefGoogle Scholar
  5. Bernard, J. A., Jaeggi, S. M., Buschkuehl, M., Hernandez-Garcia, L., & Jonides, J. (2014). Working Memory Training Gains Mitigate TMS-Induced Working Memory Performance Disruption. Manuscript in preparation.Google Scholar
  6. Buschkuehl, M., Jaeggi, S. M., & Jonides, J. (2012). Neuronal effects following working memory training. Developmental Cognitive Neuroscience, 2. Supplement, 1, S167–S179. doi: 10.1016/j.dcn.2011.10.001 Google Scholar
  7. Cavanna, A. E., & Trimble, M. R. (2006). The precuneus: a review of its functional anatomy and behavioural correlates. Brain, 129(3), 564–583. doi: 10.1093/brain/awl004 PubMedCrossRefGoogle Scholar
  8. Chein, J. M., & Morrison, A. B. (2010). Expanding the mind’s workspace: training and transfer effects with a complex working memory span task. Psychonomic Bulletin & Review, 17(2), 193–199. doi: 10.3758/PBR.17.2.193 CrossRefGoogle Scholar
  9. Chein, J. M., & Schneider, W. (2005). Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning. Brain Research. Cognitive Brain Research, 25(3), 607–623. doi: 10.1016/j.cogbrainres.2005.08.013 PubMedCrossRefGoogle Scholar
  10. Colom, R., Román, F. J., Abad, F. J., Shih, P. C., Privado, J., Froufe, M., … Jaeggi, S. M. (2013). Adaptive n-back training does not improve fluid intelligence at the construct level: Gains on individual tests suggest that training may enhance visuospatial processing. Intelligence, 41(5), 712–727. doi: 10.1016/j.intell.2013.09.002
  11. Cox, R. W. (1996). AFNI: Software for Analysis and Visualization of Functional Magnetic Resonance Neuroimages. Computers and Biomedical Research, 29(3), 162–173. doi: 10.1006/cbmr.1996.0014 PubMedCrossRefGoogle Scholar
  12. Dahlin, E., Neely, A. S., Larsson, A., Bäckman, L., & Nyberg, L. (2008). Transfer of learning after updating training mediated by the striatum. Science, 320(5882), 1510–1512.PubMedCrossRefGoogle Scholar
  13. Dai, W., Garcia, D., de Bazelaire, C., & Alsop, D. C. (2008). Continuous flow-driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields. Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine, 60(6), 1488–1497. doi: 10.1002/mrm.21790 CrossRefGoogle Scholar
  14. Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19, 450–466.CrossRefGoogle Scholar
  15. de Fockert, J. W., Rees, G., Frith, C. D., & Lavie, N. (2001). The role of working memory in visual selective attention. Science, 291(5509), 1803–1806. doi: 10.1126/science.1056496 PubMedCrossRefGoogle Scholar
  16. Detre, J. A., Leigh, J. S., Williams, D. S., & Koretsky, A. P. (1992). Perfusion imaging. Magnetic Resonance in Medicine, 23(1), 37–45.PubMedCrossRefGoogle Scholar
  17. Hempel, A., Giesel, F. L., Garcia Caraballo, N. M., Amann, M., Meyer, H., Wüstenberg, T., … Schröder, J. (2004). Plasticity of cortical activation related to working memory during training. The American Journal of Psychiatry, 161(4), 745–747.Google Scholar
  18. Hernandez-Garcia, L., & Buschkuehl, M. (2012). Advances in Longitudinal MRI Diagnostic Tests. Expert Opinion on Medical Diagnostics, 6(4), 1–11. doi: 10.1517/17530059.2012.686995 CrossRefGoogle Scholar
  19. Hernandez-Garcia, L., Jahanian, H., & Rowe, D. B. (2010). Quantitative analysis of arterial spin labeling FMRI data using a general linear model. Magnetic Resonance Imaging, 28(7), 919–927. doi: 10.1016/j.mri.2010.03.035 PubMedCentralPubMedCrossRefGoogle Scholar
  20. Hernandez-Garcia, L., Lewis, D. P., Moffat, B., & Branch, C. A. (2007). Magnetization transfer effects on the efficiency of flow-driven adiabatic fast passage inversion of arterial blood. NMR in Biomedicine, 20(8), 733–742. doi: 10.1002/nbm.1137 PubMedCentralPubMedCrossRefGoogle Scholar
  21. Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Perrig, W. J. (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences of the United States of America, 105(19), 6829–6833. doi: 10.1073/pnas.0801268105 PubMedCentralPubMedCrossRefGoogle Scholar
  22. Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Shah, P. (2011). Short- and long-term benefits of cognitive training. Proceedings of the National Academy of Sciences of the United States of America, 108(25), 10081–10086. doi: 10.1073/pnas.1103228108 PubMedCentralPubMedCrossRefGoogle Scholar
  23. Jaeggi, S. M., Buschkuehl, M., Perrig, W. J., & Meier, B. (2010). The concurrent validity of the N-back task as a working memory measure. Memory, 18(4), 394–412. doi: 10.1080/09658211003702171 PubMedCrossRefGoogle Scholar
  24. Jaeggi, S. M., Buschkuehl, M., Shah, P., & Jonides, J. (2013). The role of individual differences in cognitive training and transfer. Memory & Cognition. doi: 10.3758/s13421-013-0364-z Google Scholar
  25. Jaeggi, S. M., Studer-Luethi, B., Buschkuehl, M., Su, Y.-F., Jonides, J., & Perrig, W. J. (2010). The relationship between n-back performance and matrix reasoning – implications for training and transfer. Intelligence, 38(6), 625–635. doi: 10.1016/j.intell.2010.09.001 CrossRefGoogle Scholar
  26. Jahanian, H., Noll, D. C., & Hernandez-Garcia, L. (2011). B0 field inhomogeneity considerations in pseudo-continuous arterial spin labeling (pCASL): effects on tagging efficiency and correction strategy. NMR in Biomedicine, 24(10), 1202–1209. doi: 10.1002/nbm.1675 PubMedCrossRefGoogle Scholar
  27. Jaušovec, N., & Jaušovec, K. (2012). Working memory training: improving intelligence–changing brain activity. Brain and Cognition, 79(2), 96–106. doi: 10.1016/j.bandc.2012.02.007 PubMedCrossRefGoogle Scholar
  28. Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage, 17(2), 825–841.PubMedCrossRefGoogle Scholar
  29. Jolles, D. D., Grol, M. J., Van Buchem, M. A., Rombouts, S. A. R. B., & Crone, E. A. (2010). Practice effects in the brain: Changes in cerebral activation after working memory practice depend on task demands. NeuroImage, 52(2), 658–668. doi: 10.1016/j.neuroimage.2010.04.028 PubMedCrossRefGoogle Scholar
  30. Jonides, J. (2004). How does practice makes perfect? Nature Neuroscience, 7(1), 10–11. doi: 10.1038/nn0104-10 PubMedCrossRefGoogle Scholar
  31. Jonides, J., Lewis, R. L., Nee, D. E., Lustig, C., Berman, M. G., & Moore, K. S. (2008). The mind and brain of short-term memory. Annual Review of Psychology, 59, 193–224. doi: 10.1146/annurev.psych.59.103006.093615 PubMedPubMedCentralCrossRefGoogle Scholar
  32. Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. The Behavioral and Brain Sciences, 30(2), 135–154. doi: 10.1017/S0140525X07001185. discussion 154–187.PubMedCrossRefGoogle Scholar
  33. Kelly, C., Foxe, J. J., & Garavan, H. (2006). Patterns of normal human brain plasticity after practice and their implications for neurorehabilitation. Archives of Physical Medicine and Rehabilitation, 87(12 Suppl 2), S20–29. doi: 10.1016/j.apmr.2006.08.333 PubMedCrossRefGoogle Scholar
  34. Kundu, B., Sutterer, D. W., Emrich, S. M., & Postle, B. R. (2013). Strengthened effective connectivity underlies transfer of working memory training to tests of short-term memory and attention. The Journal of Neuroscience, 33(20), 8705–8715. doi: 10.1523/JNEUROSCI.5565-12.2013 PubMedCentralPubMedCrossRefGoogle Scholar
  35. Lamm, C., Windischberger, C., Leodolter, U., Moser, E., & Bauer, H. (2001). Evidence for premotor cortex activity during dynamic visuospatial imagery from single-trial functional magnetic resonance imaging and event-related slow cortical potentials. NeuroImage, 14(2), 268–283. doi: 10.1006/nimg.2001.0850 PubMedCrossRefGoogle Scholar
  36. Marvel, C. L., & Desmond, J. E. (2010). The contributions of cerebro-cerebellar circuitry to executive verbal working memory. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 46(7), 880–895. doi: 10.1016/j.cortex.2009.08.017 PubMedCentralPubMedCrossRefGoogle Scholar
  37. McNab, F., Varrone, A., Farde, L., Jucaite, A., Bystritsky, P., Forssberg, H., & Klingberg, T. (2009). Changes in cortical dopamine D1 receptor binding associated with cognitive training. Science, 323(5915), 800–802. doi: 10.1126/science.1166102 PubMedCrossRefGoogle Scholar
  38. Mozolic, J. L., Hayasaka, S., & Laurienti, P. J. (2010). A cognitive training intervention increases resting cerebral blood flow in healthy older adults. Frontiers in Human Neuroscience, 4, 1–10. doi: 10.3389/neuro.09.016.2010 CrossRefGoogle Scholar
  39. Nichols, T., Brett, M., Andersson, J., Wager, T., & Poline, J.-B. (2005). Valid conjunction inference with the minimum statistic. NeuroImage, 25(3), 653–660. doi: 10.1016/j.neuroimage.2004.12.005 PubMedCrossRefGoogle Scholar
  40. Olesen, P. J., Westerberg, H., & Klingberg, T. (2004). Increased prefrontal and parietal activity after training of working memory. Nature Neuroscience, 7(1), 75–79. doi: 10.1038/nn1165 PubMedCrossRefGoogle Scholar
  41. Owen, A. M., McMillan, K. M., Laird, A. R., & Bullmore, E. (2005). N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25(1), 46–59. doi: 10.1002/hbm.20131 PubMedCrossRefGoogle Scholar
  42. Owens, M., Koster, E. H. W., & Derakshan, N. (2013). Improving attention control in dysphoria through cognitive training: transfer effects on working memory capacity and filtering efficiency. Psychophysiology, 50(3), 297–307. doi: 10.1111/psyp.12010 PubMedCrossRefGoogle Scholar
  43. Perfetti, B., Saggino, A., Ferretti, A., Caulo, M., Romani, G. L., & Onofrj, M. (2009). Differential patterns of cortical activation as a function of fluid reasoning complexity. Human Brain Mapping, 30(2), 497–510. doi: 10.1002/hbm.20519 PubMedCrossRefGoogle Scholar
  44. Persson, J., Larsson, A., & Reuter-Lorenz, P. A. (2013). Imaging fatigue of interference control reveals the neural basis of executive resource depletion. Journal of Cognitive Neuroscience, 25(3), 338–351. doi: 10.1162/jocn_a_00321 PubMedCrossRefGoogle Scholar
  45. Pickering, S. J. (2006). Working memory and education. Academic Press.Google Scholar
  46. Posner, M. I., & Snyder, C. R. R. (1975). Attention and cognitive control. In Information processing and cognition: The Loyola symposium (pp. 55–85). Hillsdale, NJ: Erlbaum.Google Scholar
  47. Premji, A., Rai, N., & Nelson, A. (2011). Area 5 Influences Excitability within the Primary Motor Cortex in Humans. PLoS ONE, 6(5), e20023. doi: 10.1371/journal.pone.0020023 PubMedCentralPubMedCrossRefGoogle Scholar
  48. Reuter-Lorenz, P. A., & Cappell, K. A. (2008). Neurocognitive Aging and the Compensation Hypothesis. Current Directions in Psychological Science, 17(3), 177–182. doi: 10.1111/j.1467-8721.2008.00570.x CrossRefGoogle Scholar
  49. Rudebeck, S. R., Bor, D., Ormond, A., O’Reilly, J. X., & Lee, A. C. H. (2012). A potential spatial working memory training task to improve both episodic memory and fluid intelligence. PloS One, 7(11), e50431. doi: 10.1371/journal.pone.0050431 PubMedCentralPubMedCrossRefGoogle Scholar
  50. Rypma, B., Berger, J. S., Prabhakaran, V., Bly, B. M., Kimberg, D. Y., Biswal, B. B., & D’Esposito, M. (2006). Neural correlates of cognitive efficiency. NeuroImage, 33(3), 969–979. doi: 10.1016/j.neuroimage.2006.05.065 PubMedCrossRefGoogle Scholar
  51. Schneiders, J. A., Opitz, B., Krick, C. M., & Mecklinger, A. (2011). Separating Intra-Modal and Across-Modal Training Effects in Visual Working Memory: An fMRI Investigation. Cerebral Cortex. doi: 10.1093/cercor/bhr037 PubMedGoogle Scholar
  52. Schneiders, J. A., Opitz, B., Tang, H., Deng, Y., Xie, C., Li, H., & Mecklinger, A. (2012). The impact of auditory working memory training on the fronto-parietal working memory network. Frontiers in Human Neuroscience, 6, 173. doi: 10.3389/fnhum.2012.00173 PubMedCentralPubMedCrossRefGoogle Scholar
  53. Schweizer, S., Grahn, J., Hampshire, A., Mobbs, D., & Dalgleish, T. (2013). Training the emotional brain: improving affective control through emotional working memory training. The Journal of Neuroscience, 33(12), 5301–5311. doi: 10.1523/JNEUROSCI.2593-12.2013 PubMedCrossRefGoogle Scholar
  54. Schweizer, S., Hampshire, A., & Dalgleish, T. (2011). Extending brain-training to the affective domain: increasing cognitive and affective executive control through emotional working memory training. PloS One, 6(9), e24372. doi: 10.1371/journal.pone.0024372 PubMedCentralPubMedCrossRefGoogle Scholar
  55. Smith, E. E., & Jonides, J. (1997). Working memory: a view from neuroimaging. Cognitive Psychology, 33(1), 5–42. doi: 10.1006/cogp.1997.0658 PubMedCrossRefGoogle Scholar
  56. Stephenson, C. L., & Halpern, D. F. (2013). Improved Matrix Reasoning is Limited to Improving Working Memory Capacity Using Intensive N-back Tasks with a Visuospatial Component. Intelligence, 41, 341–357. doi: 10.1016/j.intell.2013.05.006 CrossRefGoogle Scholar
  57. Takeuchi, H., Sekiguchi, A., Taki, Y., Yokoyama, S., Yomogida, Y., Komuro, N., … Kawashima, R. (2010). Training of Working Memory Impacts Structural Connectivity. The Journal of Neuroscience, 30(9), 3297–3303. doi: 10.1523/JNEUROSCI.4611-09.2010 Google Scholar
  58. Takeuchi, H., Taki, Y., Nouchi, R., Hashizume, H., Sekiguchi, A., Kotozaki, Y., … Kawashima, R. (2012). Effects of working memory training on functional connectivity and cerebral blood flow during rest. Cortex. doi: 10.1016/j.cortex.2012.09.007
  59. Takeuchi, H., Taki, Y., Sassa, Y., Hashizume, H., Sekiguchi, A., Fukushima, A., & Kawashima, R. (2011). Working Memory Training Using Mental Calculation Impacts Regional Gray Matter of the Frontal and Parietal Regions. PLoS ONE, 6(8), e23175. doi: 10.1371/journal.pone.0023175 PubMedCentralPubMedCrossRefGoogle Scholar
  60. Tjandra, T., Brooks, J. C. W., Figueiredo, P., Wise, R., Matthews, P. M., & Tracey, I. (2005). Quantitative assessment of the reproducibility of functional activation measured with BOLD and MR perfusion imaging: implications for clinical trial design. NeuroImage, 27(2), 393–401. doi: 10.1016/j.neuroimage.2005.04.021 PubMedCrossRefGoogle Scholar
  61. Wager, T. D., & Smith, E. E. (2003). Neuroimaging studies of working memory: a meta-analysis. Cogn Affect Behav Neurosci, 3(4), 255–74.PubMedCrossRefGoogle Scholar
  62. Wang, J., Aguirre, G. K., Kimberg, D. Y., & Detre, J. A. (2003a). Empirical analyses of null-hypothesis perfusion FMRI data at 1.5 and 4 T. NeuroImage, 19(4), 1449–1462.PubMedCrossRefGoogle Scholar
  63. Wang, J., Aguirre, G. K., Kimberg, D. Y., Roc, A. C., Li, L., & Detre, J. A. (2003b). Arterial spin labeling perfusion fMRI with very low task frequency. Magnetic Resonance in Medicine, 49(5), 796–802. doi: 10.1002/mrm.10437 PubMedCrossRefGoogle Scholar
  64. Westerberg, H., Jacobaeus, H., Hirvikoski, T., Clevberger, P., Östensson, M.-L., Bartfai, A., & Klingberg, T. (2007). Computerized working memory training after stroke – A pilot study. Brain Injury, 21(1), 21–29. doi: 10.1080/02699050601148726 PubMedCrossRefGoogle Scholar
  65. Williams, D. S., Detre, J. A., Leigh, J. S., & Koretsky, A. P. (1992). Magnetic resonance imaging of perfusion using spin inversion of arterial water. Proceedings of the National Academy of Sciences, 89(1), 212.CrossRefGoogle Scholar
  66. Yoo, S.-S., Paralkar, G., & Panych, L. P. (2004). Neural substrates associated with the concurrent performance of dual working memory tasks. The International Journal of Neuroscience, 114(6), 613–631. doi: 10.1080/00207450490430561 PubMedCrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2014

Authors and Affiliations

  • Martin Buschkuehl
    • 1
    • 6
  • Luis Hernandez-Garcia
    • 2
  • Susanne M. Jaeggi
    • 3
  • Jessica A. Bernard
    • 4
    • 5
  • John Jonides
    • 4
  1. 1.MIND Research InstituteIrvineUSA
  2. 2.Functional MRI LaboratoryUniversity of MichiganAnn ArborUSA
  3. 3.School of EducationUniversity of CaliforniaIrvineUSA
  4. 4.Department of PsychologyUniversity of MichiganAnn ArborUSA
  5. 5.Department of Psychology and NeuroscienceUniversity of Colorado BoulderBoulderUSA
  6. 6.MIND Research InstituteIrvineUSA

Personalised recommendations