Moment-to-moment fluctuations in fMRI amplitude and interregion coupling are predictive of inhibitory performance



We investigated how moment-to-moment fluctuations in fMRI amplitude and interregional coupling are linked to behavioral performance during a stop signal task. To quantify the relationship between single-trial amplitude and behavior on a trial-by-trial basis, we modeled the probability of successful inhibition as a function of response amplitude via logistic regression analysis. At the group level, significant logistic slopes were observed in, among other regions, the inferior frontal gyrus (IFG), caudate, and putamen, all bilaterally. Furthermore, we investigated how trial-by-trial fluctuations in responses in attentional regions covaried with fluctuations in inhibition-related regions. The coupling between several frontoparietal attentional regions and the right IFG increased during successful versus unsuccessful performance, suggesting that efficacious network interactions are important in determining behavioral outcome during the stop signal task. In particular, the link between responses in the right IFG and behavior were moderated by moment-to-moment fluctuations in evoked responses in the left intraparietal sulcus. A supplemental figure for this article may be downloaded from http://

Supplementary material (49 kb)
Supplementary material, approximately 340 KB.


  1. Aron, A. R., Durston, S., Eagle, D. W., Logan, G. D., Stinear, C. M., & Stuphorn, V. (2007). Converging evidence for a frontobasal-ganglia network for inhibitory control of action and cognition. Journal of Neuroscience, 27, 11860–11864.PubMedCrossRefGoogle Scholar
  2. Aron, A. R., Fletcher, P. C., Bullmore, E. T., Sahakian, B. J., & Robbins, T. W. (2003). Stop-signal inhibition disrupted by damage to right inferior frontal gyrus in humans. Nature Neuroscience, 6, 115–116.PubMedCrossRefGoogle Scholar
  3. Aron, A. R., & Poldrack, R. A. (2006). Cortical and subcortical contributions to stop signal response inhibition: Role of the subthalamic nucleus. Journal of Neuroscience, 26, 2424–2433.PubMedCrossRefGoogle Scholar
  4. Boehler, C. N., Münte, T. F., Krebs, R. M., Heinze, H.-J., Schoenfeld, M. A., & Hopf, J.-M. (2009). Sensory MEG responses predict successful and failed inhibition in a stop-signal task. Cerebral Cortex, 19, 134–145.PubMedCrossRefGoogle Scholar
  5. Booth, J. R., Burman, D. D., Meyer, J. R., Lei, Z., Trommer, B. L., Davenport, N. D., et al. (2005). Larger deficits in brain networks for response inhibition than for visual selective attention in attention deficit hyperactivity disorder (ADHD). Journal of Child Psychology & Psychiatry, 46, 94–111.CrossRefGoogle Scholar
  6. Boucher, L., Palmeri, T. J., Logan, G. D., & Schall, J. D. (2007). Inhibitory control in mind and brain: An interactive race model of countermanding saccades. Psychological Review, 114, 376–397.PubMedCrossRefGoogle Scholar
  7. Brass, M., Derrfuss, J., Forstmann, B., & von Cramon, D. Y. (2005). The role of the inferior frontal junction area in cognitive control. Trends in Cognitive Sciences, 9, 314–316.PubMedCrossRefGoogle Scholar
  8. Brass, M., Wenke, D., Spengler, S., & Waszak, F. (2009). Neural correlates of overcoming interference from instructed and implemented stimulus-response associations. Journal of Neuroscience, 29, 1766–1772.PubMedCrossRefGoogle Scholar
  9. Britten, K. H., Newsome, W. T., Shadlen, M. N., Celebrini, S., & Movshon, J. A. (1996). A relationship between behavioral choice and the visual responses of neurons in macaque MT. Visual Neuroscience, 13, 87–100.PubMedCrossRefGoogle Scholar
  10. Brown, J. W., & Braver, T. S. (2005). Learned predictions of error likelihood in the anterior cingulate cortex. Science, 307, 1118–1121.PubMedCrossRefGoogle Scholar
  11. Casey, B. J., Trainor, R. J., Orendi, J. L., Schubert, A. B., Nystrom, L. E., Giedd, J. N., et al. (1997). A developmental functional MRI study of prefrontal activation during performance of a go-no-go task. Journal of Cognitive Neuroscience, 9, 835–847.CrossRefGoogle Scholar
  12. Chamberlain, S. R., Hampshire, A., Müller, U., Rubia, K., Del Campo, N., Craig, K., et al. (2009). Atomoxetine modulates right inferior frontal activation during inhibitory control: A pharmacological functional magnetic resonance imaging study. Biological Psychiatry, 65, 550–555.PubMedCrossRefGoogle Scholar
  13. Chambers, C. D., Bellgrove, M. A., Gould, I. C., English, T., Garavan, H., McNaught, E., et al. (2007). Dissociable mechanisms of cognitive control in prefrontal and premotor cortex. Journal of Neurophysiology, 98, 3638–3647.PubMedCrossRefGoogle Scholar
  14. Chambers, C. D., Bellgrove, M. A., Stokes, M. G., Henderson, T. R., Garavan, H., Robertson, I. H., et al. (2006). Executive “brake failure” following deactivation of human frontal lobe. Journal of Cognitive Neuroscience, 18, 444–455.PubMedGoogle Scholar
  15. Chambers, C. D., Garavan, H., & Bellgrove, M. A. (2009). Insights into the neural basis of response inhibition from cognitive and clinical neuroscience. Neuroscience & Biobehavioral Reviews, 33, 631–646.CrossRefGoogle Scholar
  16. Chen, C.-Y., Muggleton, N. G., Tzeng, O. J. L., Hung, D. L., & Juan, C.-H. (2009). Control of prepotent responses by the superior medial frontal cortex. NeuroImage, 44, 537–545.PubMedCrossRefGoogle Scholar
  17. Chikazoe, J., Jimura, K., Asari, T., Yamashita, K., Morimoto, H., Hirose, S., et al. (2009). Functional dissociation in right inferior frontal cortex during performance of go/no-go task. Cerebral Cortex, 19, 146–152.PubMedCrossRefGoogle Scholar
  18. Cohen, M. S. (1997). Parametric analysis of fMRI data using linear systems methods. NeuroImage, 6, 93–103.PubMedCrossRefGoogle Scholar
  19. Colzato, L. S., van den Wildenberg, W. P., & Hommel, B. (2007). Impaired inhibitory control in recreational cocaine users. PLoS ONE, 2, e1143.CrossRefGoogle Scholar
  20. Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215.PubMedCrossRefGoogle Scholar
  21. Cox, R. W. (1996). AFNI: Software for the analysis and visualization of functional magnetic resonance neuroimages. Computers & Biomedical Research, 29, 162–173.CrossRefGoogle Scholar
  22. Dehaene, S., Posner, M. I., & Tucker, D. M. (1994). Localization of a neural system for error detection and compensation. Psychological Science, 5, 303–305.CrossRefGoogle Scholar
  23. Duann, J.-R., Ide, J. S., Luo, X., & Li, C.-S. R. (2009). Functional connectivity delineates distinct roles of the inferior frontal cortex and presupplementary motor area in stop signal inhibition. Journal of Neuroscience, 29, 10171–10179.PubMedCrossRefGoogle Scholar
  24. Eagle, D. M., Baunez, C., Hutcheson, D. M., Lehmann, O., Shah, A. P., & Robbins, T. W. (2008). Stop-signal reaction-time task performance: Role of prefrontal cortex and subthalamic nucleus. Cerebral Cortex, 18, 178–188.PubMedCrossRefGoogle Scholar
  25. Eagle, D. M., & Robbins, T. W. (2003). Inhibitory control in rats performing a stop-signal reaction-time task: Effects of lesions of the medial striatum and d-amphetamine. Behavioral Neuroscience, 117, 1302–1317.PubMedCrossRefGoogle Scholar
  26. Eimer, M. (1993). Effects of attention and stimulus probability on ERPs in a Go/Nogo task. Biological Psychology, 35, 123–138.PubMedCrossRefGoogle Scholar
  27. Floden, D., & Stuss, D. T. (2006). Inhibitory control is slowed in patients with right superior medial frontal damage. Journal of Cognitive Neuroscience, 18, 1843–1849.PubMedCrossRefGoogle Scholar
  28. Forstmann, B. U., Jahfari, S., Scholte, H. S., Wolfensteller, U., van den Wildenberg, W. P. M., & Ridderinkhof, K. R. (2008). Function and structure of the right inferior frontal cortex predict individual differences in response inhibition: A model-based approach. Journal of Neuroscience, 28, 9790–9796.PubMedCrossRefGoogle Scholar
  29. Garavan, H., Ross, T. J., Kaufman, J., & Stein, E. A. (2003). A midline dissociation between error-processing and response-conflict monitoring. NeuroImage, 20, 1132–1139.PubMedCrossRefGoogle Scholar
  30. Garavan, H., Ross, T. J., Murphy, K., Roche, R. A. P., & Stein, E. A. (2002). Dissociable executive functions in the dynamic control of behavior: Inhibition, error detection, and correction. NeuroImage, 17, 1820–1829.PubMedCrossRefGoogle Scholar
  31. Garavan, H., Ross, T. J., & Stein, E. A. (1999). Right hemispheric dominance of inhibitory control: An event-related functional MRI study. Proceedings of the National Academy of Sciences, 96, 8301–8306.CrossRefGoogle Scholar
  32. Gehring, W., Goss, B., Coles, M., Meyer, D., & Donchin, E. (1993). A neural system for error detection and compensation. Psychological Science, 4, 385–390.CrossRefGoogle Scholar
  33. Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. Cambridge: Cambridge University Press.Google Scholar
  34. Genovese, C. R., Lazar, N. A., & Nichols, T. (2002). Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage, 15, 870–878.PubMedCrossRefGoogle Scholar
  35. Hester, R., Fassbender, C., & Garavan, H. (2004). Individual differences in error processing: A review and reanalysis of three eventrelated fMRI studies using the GO/NOGO task. Cerebral Cortex, 14, 986–994.PubMedCrossRefGoogle Scholar
  36. Hester, R., Madeley, J., Murphy, K., & Mattingley, J. B. (2009). Learning from errors: Error-related neural activity predicts improvements in future inhibitory control performance. Journal of Neuroscience, 29, 7158–7165.PubMedCrossRefGoogle Scholar
  37. Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). New York: Wiley.CrossRefGoogle Scholar
  38. Kalaska, J. F., & Crammond, D. J. (1995). Deciding not to GO: Neuronal correlates of response selection in a GO/NOGO task in primate premotor and parietal cortex. Cerebral Cortex, 5, 410–428.PubMedCrossRefGoogle Scholar
  39. Kastner, S., & Ungerleider, L. G. (2001). The neural basis of biased competition in human visual cortex. Neuropsychologia, 39, 1263–1276.PubMedCrossRefGoogle Scholar
  40. Kriegeskorte, N., Simmons, W. K., Bellgowan, P. S., & Baker, C. I. (2009). Circular analysis in systems neuroscience: The dangers of double dipping. Nature Neuroscience, 12, 535–540.PubMedCrossRefGoogle Scholar
  41. Leber, A. B., Turk-Browne, N. B., & Chun, M. M. (2008). Neural predictors of moment-to-moment fluctuations in cognitive flexibility. Proceedings of the National Academy of Sciences, 105, 13592–13597.CrossRefGoogle Scholar
  42. Leung, H.-C., & Cai, W. (2007). Common and differential ventrolateral prefrontal activity during inhibition of hand and eye movements. Journal of Neuroscience, 27, 9893–9900.PubMedCrossRefGoogle Scholar
  43. Li, C.-S. R., Huang, C., Constable, R. T., & Sinha, R. (2006). Imaging response inhibition in a stop-signal task: Neural correlates independent of signal monitoring and post-response processing. Journal of Neuroscience, 26, 186–192.PubMedCrossRefGoogle Scholar
  44. Li, C.-S. R., Yan, P., Chao, H. H., Sinha, R., Paliwal, P., Constable, R. T., et al. (2008). Error-specific medial cortical and subcortical activity during the stop signal task: A functional magnetic resonance imaging study. Neuroscience, 155, 1142–1151.PubMedCrossRefGoogle Scholar
  45. Li, C.-S. R., Yan, P., Sinha, R., & Lee, T.-W. (2008). Subcortical processes of motor response inhibition during a stop signal task. NeuroImage, 41, 1352–1363.PubMedCrossRefGoogle Scholar
  46. Liddle, P. F., Kiehl, K. A., & Smith, A. M. (2001). Event-related fMRI study of response inhibition. Human Brain Mapping, 12, 100–109.PubMedCrossRefGoogle Scholar
  47. Lim, S. L., Padmala, S., & Pessoa, L. (2009). Segregating the significant from the mundane on a moment-to-moment basis via direct and indirect amygdala contributions. Proceedings of the National Academy of Sciences, 106, 16841–16846.CrossRefGoogle Scholar
  48. Loftus, G. R., & Masson, M. E. (1994). Using confidence intervals in within-subject designs. Psychonomic Bulletin & Review, 1, 476–490.CrossRefGoogle Scholar
  49. Logan, G. D. (1994). On the ability to inhibit thought and action: A user’s guide to the stop signal paradigm. In D. Dagenbach & T. H. Carr (Eds.), Inhibitory processes in attention, memory, and language (pp. 189–239). San Diego: Academic Press.Google Scholar
  50. Logan, G. D., & Cowan, W. B. (1984). On the ability to inhibit thought and action: A theory of an act of control. Psychological Review, 91, 295–327.CrossRefGoogle Scholar
  51. Logan, G. D., Schachar, R. J., & Tannock, R. (1997). Impulsivity and inhibitory control. Psychological Science, 8, 60–64.CrossRefGoogle Scholar
  52. Maddock, R. J. (1999). The retrosplenial cortex and emotion: New insights from functional neuroimaging of the human brain. Trends in Neurosciences, 22, 310–316.PubMedCrossRefGoogle Scholar
  53. Magno, E., Foxe, J. J., Molholm, S., Robertson, I. H., & Garavan, H. (2006). The anterior cingulate and error avoidance. Journal of Neuroscience, 26, 4769–4773.PubMedCrossRefGoogle Scholar
  54. Menon, V., Adleman, N. E., White, C. D., Glover, G. H., & Reiss, A. L. (2001). Error-related brain activation during a go/nogo response inhibition task. Human Brain Mapping, 12, 131–143.PubMedCrossRefGoogle Scholar
  55. Nachev, P., Wydell, H., O’Neill, K., Husain, M., & Kennard, C. (2007). The role of the pre-supplementary motor area in the control of action. NeuroImage, 36(Suppl. 2), T155-T163.PubMedCrossRefGoogle Scholar
  56. Padmala, S., & Pessoa, L. (2008). Affective learning enhances visual detection and responses in primary visual cortex. Journal of Neuroscience, 28, 6202–6210.PubMedCrossRefGoogle Scholar
  57. Padmala, S., & Pessoa, L. (2010). Interactions between cognition and motivation during response inhibition. Neuropsychologia, 48, 558–565.PubMedCrossRefGoogle Scholar
  58. Pessoa, L., Gutierrez, E., Bandettini, P. B., & Ungerleider, L. G. (2002). Neural correlates of visual working memory: fMRI amplitude predicts task performance. Neuron, 35, 975–987.PubMedCrossRefGoogle Scholar
  59. Pessoa, L., & Padmala, S. (2005). Quantitative prediction of perceptual decisions during near-threshold fear detection. Proceedings of the National Academy of Sciences, 102, 5612–5617.CrossRefGoogle Scholar
  60. Pessoa, L., & Ungerleider, L. G. (2004). Top-down mechanisms for working memory and attentional processes. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences (3rd ed., pp. 919–930). Cambridge, MA: MIT Press.Google Scholar
  61. Picton, T. W., Stuss, D. T., Alexander, M. P., Shallice, T., Binns, M. A., & Gillingham, S. (2007). Effects of focal frontal lesions on response inhibition. Cerebral Cortex, 17, 826–838.PubMedCrossRefGoogle Scholar
  62. Preuschoff, K., Quartz, S. R., & Bossaerts, P. (2008). Human insula activation reflects risk prediction errors as well as risk. Journal of Neuroscience, 28, 2745–2752.PubMedCrossRefGoogle Scholar
  63. Purushothaman, G., & Bradley, D. C. (2005). Neural population code for fine perceptual decisions in area MT. Nature Neuroscience, 8, 99–106.PubMedCrossRefGoogle Scholar
  64. Ramautar, J. R., Slagter, H. A., Kok, A., & Ridderinkhof, K. R. (2006). Probability effects in the stop-signal paradigm: The insula and the significance of failed inhibition. Brain Research, 1105, 143–154.PubMedCrossRefGoogle Scholar
  65. Ratcliffe, S. J., & Shults, J. (2008). GEEQBOX: A MATLAB toolbox for generalized estimating equations and quasi-least squares. Journal of Statistical Software, 25, 1–14.Google Scholar
  66. Ray, N. J., Jenkinson, N., Brittain, J., Holland, P., Joint, C., Nandi, D., et al. (2009). The role of the subthalamic nucleus in response inhibition: Evidence from deep brain stimulation for Parkinson’s disease. Neuropsychologia, 47, 2828–2834.PubMedCrossRefGoogle Scholar
  67. Ress, D., Backus, B. T., & Heeger, D. J. (2000). Activity in primary visual cortex predicts performance in a visual detection task. Nature Neuroscience, 3, 940–945.PubMedCrossRefGoogle Scholar
  68. Rubia, K., Smith, A. B., Brammer, M. J., & Taylor, E. (2003). Right inferior prefrontal cortex mediates response inhibition while mesial prefrontal cortex is responsible for error detection. NeuroImage, 20, 351–358.PubMedCrossRefGoogle Scholar
  69. Rubia, K., Smith, A. B., Taylor, E., & Brammer, M. (2007). Linear age-correlated functional development of right inferior fronto-striato-cerebellar networks during response inhibition and anterior cingulate during error-related processes. Human Brain Mapping, 28, 1163–1177.PubMedCrossRefGoogle Scholar
  70. Swick, D., Ashley, V., & Turken, A. U. (2008). Left inferior frontal gyrus is critical for response inhibition. BMC Neuroscience, 9, 102.PubMedCrossRefGoogle Scholar
  71. Sylvester, C. M., Shulman, G. L., Jack, A. I., & Corbetta, M. (2007). Asymmetry of anticipatory activity in visual cortex predicts the locus of attention and perception. Journal of Neuroscience, 27, 14424–14433.PubMedCrossRefGoogle Scholar
  72. Talairach, J., & Tournoux, P. (1988). A co-planar stereotaxic atlas of the human brain. New York: Thieme.Google Scholar
  73. van den Wildenberg, W. P., van Boxtel, G. J., van der Molen, M. W., Bosch, D. A., Speelman, J. D., & Brunia, C. H. (2006). Stimulation of the subthalamic region facilitates the selection and inhibition of motor responses in Parkinson’s disease. Journal of Cognitive Neuroscience, 18, 626–636.PubMedCrossRefGoogle Scholar
  74. Verbruggen, F., & Logan, G. D. (2008). Response inhibition in the stop-signal paradigm. Trends in Cognitive Sciences, 12, 418–424.PubMedCrossRefGoogle Scholar
  75. Vink, M., Kahn, R. S., Raemaekers, M., van den Heuvel, M., Boersma, M., & Ramsey, N. F. (2005). Function of striatum beyond inhibition and execution of motor responses. Human Brain Mapping, 25, 336–344.PubMedCrossRefGoogle Scholar
  76. Williams, B., Ponesse, J., Schachar, R., Logan, G., & Tannock, R. (1999). Development of inhibitory control across the life span. Developmental Psychology, 35, 205–213.PubMedCrossRefGoogle Scholar
  77. Xue, G., Aron, A. R., & Poldrack, R. A. (2008). Common neural substrates for inhibition of spoken and manual responses. Cerebral Cortex, 18, 1923–1932.PubMedCrossRefGoogle Scholar
  78. Zeger, S. L., & Liang, K. Y. (1986). Longitudinal data analysis for discrete and continuous outcomes. Biometrics, 42, 121–130.PubMedCrossRefGoogle Scholar
  79. Zhou, D., Thompson, W. K., & Siegle, G. (2009). MATLAB toolbox for functional connectivity. NeuroImage, 47, 1590–1607.PubMedCrossRefGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2010

Authors and Affiliations

  1. 1.Department of Psychological and Brain SciencesIndiana UniversityBloomington

Personalised recommendations