Advertisement

Experimental Brain Research

, Volume 202, Issue 1, pp 45–54 | Cite as

Motor and non-motor error and the influence of error magnitude on brain activity

  • Karin Graziella Nadig
  • Lutz Jäncke
  • Roger Lüchinger
  • Kai Lutz
Research Article

Abstract

It has been shown that frontal cortical areas increase their activity during error perception and error processing. However, it is not yet clear whether perception of motor errors is processed in the same frontal areas as perception of errors in cognitive tasks. It is also unclear whether brain activity level is influenced by the magnitude of error. For this purpose, we conducted a study in which subjects were confronted with motor and non-motor errors, and had them perform a sensorimotor transformation task in which they were likely to commit motor errors of different magnitudes (internal errors). In addition to the internally committed motor errors, non-motor errors (external errors) were added to the feedback in some trials. We found that activity in the anterior insula, inferior frontal gyrus (IFG), cerebellum, precuneus, and posterior medial frontal cortex (pMFC) correlated positively with the magnitude of external errors. The middle frontal gyrus (MFG) and the pMFC cortex correlated positively with the magnitude of the total error fed back to subjects (internal plus external). No significant positive correlation between internal error and brain activity could be detected. These results indicate that motor errors have a differential effect on brain activity compared with non-motor errors.

Keywords

Sensorimotor transformation task Error perception fMRI Internal model Posterior medial frontal cortex 

Notes

Acknowledgments

The study was supported by Swiss National Science Foundation (320000-111777). The authors are grateful to Stefan Bode for helpful comments on earlier drafts and to Marcus Cheetham for proofreading this manuscript.

References

  1. Abler B, Walter H, Erk S (2005) Neural correlates of frustration. Neuroreport 16:669–672CrossRefPubMedGoogle Scholar
  2. Annett M (1970) A classification of hand preference by association analysis. Br J Psychol 61:303–321PubMedGoogle Scholar
  3. Baumgartner T, Lutz K, Schmidt CF, Jancke L (2006) The emotional power of music: how music enhances the feeling of affective pictures. Brain Res 1075:151–164CrossRefPubMedGoogle Scholar
  4. Blakemore SJ (2003) Deluding the motor system. Conscious Cogn 12:647–655CrossRefPubMedGoogle Scholar
  5. Blakemore SJ, Sirigu A (2003) Action prediction in the cerebellum and in the parietal lobe. Exp Brain Res 153:239–245CrossRefPubMedGoogle Scholar
  6. Blakemore SJ, Frith CD, Wolpert DM (2001) The cerebellum is involved in predicting the sensory consequences of action. Neuroreport 12:1879–1884CrossRefPubMedGoogle Scholar
  7. Botvinick MM, Braver TS, Barch DM, Carter CS, Cohen JD (2001) Conflict monitoring and cognitive control. Psychol Rev 108:624–652CrossRefPubMedGoogle Scholar
  8. Brazdil M, Mikl M, Marecek R, Krupa P, Rektor I (2007) Effective connectivity in target stimulus processing: a dynamic causal modeling study of visual oddball task. Neuroimage 35:827–835CrossRefPubMedGoogle Scholar
  9. Bubic A, von Cramon DY, Jacobsen T, Schroger E, Schubotz RI (2009) Violation of expectation: neural correlates reflect bases of prediction. J Cogn Neurosci 21:155–168CrossRefPubMedGoogle Scholar
  10. Buchel C, Friston KJ (1998) Dynamic changes in effective connectivity characterized by variable parameter regression and Kalman filtering. Hum Brain Mapp 6:403–408CrossRefPubMedGoogle Scholar
  11. Buchel C, Holmes AP, Rees G, Friston KJ (1998) Characterizing stimulus-response functions using nonlinear regressors in parametric fMRI experiments. Neuroimage 8:140–148CrossRefPubMedGoogle Scholar
  12. Buchel C, Dolan RJ, Armony JL, Friston KJ (1999) Amygdala-hippocampal involvement in human aversive trace conditioning revealed through event-related functional magnetic resonance imaging. J Neurosci 19:10869–10876PubMedGoogle Scholar
  13. Carter CS, Braver TS, Barch DM, Botvinick MM, Noll D, Cohen JD (1998) Anterior cingulate cortex, error detection, and the online monitoring of performance. Science 280:747–749CrossRefPubMedGoogle Scholar
  14. Casey BJ, Thomas KM, Welsh TF, Badgaiyan RD, Eccard CH, Jennings JR, Crone EA (2000) Dissociation of response conflict, attentional selection, and expectancy with functional magnetic resonance imaging. Proc Natl Acad Sci USA 97:8728–8733CrossRefPubMedGoogle Scholar
  15. Chaminade T, Fonlupt P (2003) Changes of effective connectivity between the lateral and medial parts of the prefrontal cortex during a visual task. Eur J Neurosci 18:675–679CrossRefPubMedGoogle Scholar
  16. Chiu PH, Holmes AJ, Pizzagalli DA (2008) Dissociable recruitment of rostral anterior cingulate and inferior frontal cortex in emotional response inhibition. Neuroimage 42:988–997CrossRefPubMedGoogle Scholar
  17. Debener S, Ullsperger M, Siegel M, Fiehler K, von Cramon DY, Engel AK (2005) Trial-by-trial coupling of concurrent electroencephalogram and functional magnetic resonance imaging identifies the dynamics of performance monitoring. J Neurosci 25:11730–11737CrossRefPubMedGoogle Scholar
  18. Fiehler K, Ullsperger M, von Cramon DY (2004) Neural correlates of error detection and error correction: is there a common neuroanatomical substrate? Eur J Neurosci 19:3081–3087CrossRefPubMedGoogle Scholar
  19. Fletcher PC, Anderson JM, Shanks DR, Honey R, Carpenter TA, Donovan T, Papadakis N, Bullmore ET (2001) Responses of human frontal cortex to surprising events are predicted by formal associative learning theory. Nat Neurosci 4:1043–1048CrossRefPubMedGoogle Scholar
  20. Floyer-Lea A, Matthews PM (2004) Changing brain networks for visuomotor control with increased movement automaticity. J Neurophysiol 92:2405–2412CrossRefPubMedGoogle Scholar
  21. Floyer-Lea A, Matthews PM (2005) Distinguishable brain activation networks for short- and long-term motor skill learning. J Neurophysiol 94:512–518CrossRefPubMedGoogle Scholar
  22. Friston KJ, Frith CD, Turner R, Frackowiak RS (1995) Characterizing evoked hemodynamics with fMRI. Neuroimage 2:157–165CrossRefPubMedGoogle Scholar
  23. Hariri AR, Bookheimer SY, Mazziotta JC (2000) Modulating emotional responses: effects of a neocortical network on the limbic system. Neuroreport 11:43–48CrossRefPubMedGoogle Scholar
  24. Holroyd CB, Nieuwenhuis S, Yeung N, Nystrom L, Mars RB, Coles MG, Cohen JD (2004) Dorsal anterior cingulate cortex shows fMRI response to internal and external error signals. Nat Neurosci 7:497–498CrossRefPubMedGoogle Scholar
  25. Huettel SA, McCarthy G (2004) What is odd in the oddball task? Prefrontal cortex is activated by dynamic changes in response strategy. Neuropsychologia 42:379–386CrossRefPubMedGoogle Scholar
  26. Imamizu H, Kawato M (2009) Brain mechanisms for predictive control by switching internal models: implications for higher-order cognitive functions. Psychol Res 73(4):527–544Google Scholar
  27. Imamizu H, Kuroda T, Miyauchi S, Yoshioka T, Kawato M (2003) Modular organization of internal models of tools in the human cerebellum. Proc Natl Acad Sci USA 100:5461–5466CrossRefPubMedGoogle Scholar
  28. Imamizu H, Kuroda T, Yoshioka T, Kawato M (2004) Functional magnetic resonance imaging examination of two modular architectures for switching multiple internal models. J Neurosci 24:1173–1181CrossRefPubMedGoogle Scholar
  29. Imamizu H, Higuchi S, Toda A, Kawato M (2007) Reorganization of brain activity for multiple internal models after short but intensive training. Cortex 43:338–349CrossRefPubMedGoogle Scholar
  30. Jabbi M, Bastiaansen J, Keysers C (2008) A common anterior insula representation of disgust observation, experience and imagination shows divergent functional connectivity pathways. PLoS One 3:e2939CrossRefPubMedGoogle Scholar
  31. Kawato M (1999) Internal models for motor control and trajectory planning. Curr Opin Neurobiol 9:718–727CrossRefPubMedGoogle Scholar
  32. Kawato M, Wolpert D (1998) Internal models for motor control. Novartis Found Symp 218:291–304 discussion 304–307CrossRefPubMedGoogle Scholar
  33. Keisker B, Hepp-Reymond MC, Blickenstorfer A, Meyer M, Kollias SS (2009) Differential force scaling of fine-graded power grip force in the sensorimotor network. Hum Brain Mapp 30(8):2453–2465Google Scholar
  34. Kerns JG, Cohen JD, AWr MacDonald, Cho RY, Stenger VA, Carter CS (2004) Anterior cingulate conflict monitoring and adjustments in control. Science 303:1023–1026CrossRefPubMedGoogle Scholar
  35. Kiehl KA, Liddle PF (2001) An event-related functional magnetic resonance imaging study of an auditory oddball task in schizophrenia. Schizophr Res 48:159–171CrossRefPubMedGoogle Scholar
  36. Knutson B, Cooper JC (2005) Functional magnetic resonance imaging of reward prediction. Curr Opin Neurol 18:411–417CrossRefPubMedGoogle Scholar
  37. Koelsch S, Fritz T, von Cramon DY, Muller K, Friederici AD (2006) Investigating emotion with music: an fMRI study. Hum Brain Mapp 27:239–250CrossRefPubMedGoogle Scholar
  38. Kuchinke L, Jacobs AM, Grubich C, Vo ML, Conrad M, Herrmann M (2005) Incidental effects of emotional valence in single word processing: an fMRI study. Neuroimage 28:1022–1032CrossRefPubMedGoogle Scholar
  39. Lane RD, Reiman EM, Ahern GL, Schwartz GE, Davidson RJ (1997) Neuroanatomical correlates of happiness, sadness, and disgust. Am J Psychiatry 154:926–933PubMedGoogle Scholar
  40. Levesque J, Joanette Y, Mensour B, Beaudoin G, Leroux JM, Bourgouin P, Beauregard M (2003) Neural correlates of sad feelings in healthy girls. Neuroscience 121:545–551CrossRefPubMedGoogle Scholar
  41. Li CS, Yan P, Chao HH, Sinha R, Paliwal P, Constable RT, Zhang S, Lee TW (2008) Error-specific medial cortical and subcortical activity during the stop signal task: a functional magnetic resonance imaging study. Neuroscience 155:1142–1151CrossRefPubMedGoogle Scholar
  42. Luppino G, Matelli M, Camarda R, Rizzolatti G (1993) Corticocortical connections of area F3 (SMA-proper) and area F6 (pre-SMA) in the macaque monkey. J Comp Neurol 338:114–140CrossRefPubMedGoogle Scholar
  43. 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–T163CrossRefPubMedGoogle Scholar
  44. Ochsner KN, Ray RD, Cooper JC, Robertson ER, Chopra S, Gabrieli JD, Gross JJ (2004) For better or for worse: neural systems supporting the cognitive down- and up-regulation of negative emotion. Neuroimage 23:483–499CrossRefPubMedGoogle Scholar
  45. Phan KL, Wager T, Taylor SF, Liberzon I (2002) Functional neuroanatomy of emotion: a meta-analysis of emotion activation studies in PET and fMRI. Neuroimage 16:331–348CrossRefPubMedGoogle Scholar
  46. Phelps EA, O’Connor KJ, Gatenby JC, Gore JC, Grillon C, Davis M (2001) Activation of the left amygdala to a cognitive representation of fear. Nat Neurosci 4:437–441CrossRefPubMedGoogle Scholar
  47. Phillips ML, Drevets WC, Rauch SL, Lane R (2003) Neurobiology of emotion perception. I: The neural basis of normal emotion perception. Biol Psychiatry 54:504–514CrossRefPubMedGoogle Scholar
  48. Picard N, Strick PL (2001) Imaging the premotor areas. Curr Opin Neurobiol 11:663–672CrossRefPubMedGoogle Scholar
  49. Ridderinkhof KR, Ullsperger M, Crone EA, Nieuwenhuis S (2004) The role of the medial frontal cortex in cognitive control. Science 306:443–447CrossRefPubMedGoogle Scholar
  50. Sanfey AG, Rilling JK, Aronson JA, Nystrom LE, Cohen JD (2003) The neural basis of economic decision-making in the Ultimatum Game. Science 300:1755–1758CrossRefPubMedGoogle Scholar
  51. Siegrist J, Menrath I, Stocker T, Klein M, Kellermann T, Shah NJ, Zilles K, Schneider F (2005) Differential brain activation according to chronic social reward frustration. Neuroreport 16:1899–1903CrossRefPubMedGoogle Scholar
  52. Tanji J (1994) The supplementary motor area in the cerebral cortex. Neurosci Res 19:251–268CrossRefPubMedGoogle Scholar
  53. Toni I, Ramnani N, Josephs O, Ashburner J, Passingham RE (2001a) Learning arbitrary visuomotor associations: temporal dynamic of brain activity. Neuroimage 14:1048–1057CrossRefPubMedGoogle Scholar
  54. Toni I, Rushworth MF, Passingham RE (2001b) Neural correlates of visuomotor associations. Spatial rules compared with arbitrary rules. Exp Brain Res 141:359–369CrossRefPubMedGoogle Scholar
  55. Ullsperger M, von Cramon DY (2001) Subprocesses of performance monitoring: a dissociation of error processing and response competition revealed by event-related fMRI and ERPs. Neuroimage 14:1387–1401CrossRefPubMedGoogle Scholar
  56. Ullsperger M, von Cramon DY (2004) Neuroimaging of performance monitoring: error detection and beyond. Cortex 40:593–604CrossRefPubMedGoogle Scholar
  57. Ullsperger M, Volz KG, von Cramon DY (2004) A common neural system signaling the need for behavioral changes. Trends Cogn Sci 8:445–446 author reply 446–447CrossRefPubMedGoogle Scholar
  58. Ullsperger M, Nittono H, von Cramon DY (2007) When goals are missed: dealing with self-generated and externally induced failure. Neuroimage 35:1356–1364CrossRefPubMedGoogle Scholar
  59. van Veen V, Holroyd CB, Cohen JD, Stenger VA, Carter CS (2004) Errors without conflict: implications for performance monitoring theories of anterior cingulate cortex. Brain Cogn 56:267–276CrossRefPubMedGoogle Scholar
  60. Wolpert DM, Kawato M (1998) Multiple paired forward and inverse models for motor control. Neural Netw 11:1317–1329CrossRefPubMedGoogle Scholar
  61. Wolpert DM, Ghahramani Z, Jordan MI (1995) An internal model for sensorimotor integration. Science 269:1880–1882CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Karin Graziella Nadig
    • 1
  • Lutz Jäncke
    • 1
  • Roger Lüchinger
    • 2
  • Kai Lutz
    • 1
  1. 1.Department of NeuropsychologyUniversity of ZurichZurichSwitzerland
  2. 2.Institute for Biomedical Engineering, Swiss Federal Institute of Technology, ETH ZurichZurichSwitzerland

Personalised recommendations