Experimental Brain Research

, Volume 173, Issue 4, pp 742–750

Visual angle is the critical variable mediating gain-related effects in manual control

  • David E. Vaillancourt
  • Pamela S. Haibach
  • Karl M. Newell
Research Article


Theoretically visual gain has been identified as a control variable in models of isometric force. However, visual gain is typically confounded with visual angle and distance, and the relative contribution of visual gain, distance, and angle to the control of force remains unclear. This study manipulated visual gain, distance, and angle in three experiments to examine the visual information properties used to regulate the control of a constant level of isometric force. Young adults performed a flexion motion of the index finger of the dominant hand in 20 s trials under a range of parameter values of the three visual variables. The findings demonstrate that the amount and structure of the force fluctuations were organized around the variable of visual angle, rather than gain or distance. Furthermore, the amount and structure of the force fluctuations changed considerably up to 1°, with little change higher than a 1° visual angle. Visual angle is the critical informational variable for the visuomotor system during the control of isometric force.


  1. Beuter A, Haverkamp H, Glass L, Carriere L (1995) Effect of manipulating visual feedback parameters on eye and finger movements. Int J Neurosci 83:281–294PubMedCrossRefGoogle Scholar
  2. Caminiti R, Ferraina S, Johnson PB (1996) The sources of visual information to the primate frontal lobe: a novel role for the superior parietal lobule. Cereb Cortex 6:319–328PubMedGoogle Scholar
  3. Ebner TJ, Fu Q (1997) What features of visually guided arm movements are encoded in the simple spike discharge of cerebellar Purkinje cells? Prog Brain Res 114:431–447PubMedGoogle Scholar
  4. Elble RJ, Koller WC (1990) Tremor. The John Hopkins University Press, BaltimoreGoogle Scholar
  5. Ellermann JM, Siegal JD, Strupp JP, Ebner TJ, Ugurbil K (1998) Activation of visuomotor systems during visually guided movements: a functional MRI study. J Magn Reson 131:272–285CrossRefPubMedGoogle Scholar
  6. Gibbs CB (1962) Controller designs, interactions of controlling limbs, time-lags, and gains in positional and velocity systems. Ergonomics 17:385–402Google Scholar
  7. Gogel WC, Eby DW (1997) Measures of perceived linear size, sagittal motion, and visual angle from optical expansions and contractions. Percept Psychophys 59:783–806PubMedGoogle Scholar
  8. Hess RA (1973) Nonadjectival rating scales in human response experiments. Hum Factors 15:275–280Google Scholar
  9. Jagacinski RJ, Flach JM (2003) Control theory for humans: quantitative approaches to modeling performance. Lawrence Erlbaum Associates, MahwahGoogle Scholar
  10. Jagacinski RJ, Monk DL (1985) Fitts’ Law in two dimensions with hand and head movements. J Mot Behav 17:77–95PubMedGoogle Scholar
  11. Jeannerod M, Arbib MA, Rizzolatti G, Sakata H (1995) Grasping objects: the cortical mechanisms of visuomotor transformation. Trends Neurosci 18:314–320CrossRefPubMedGoogle Scholar
  12. Jones KE, Hamilton AF, Wolpert DM (2002) Sources of signal-dependent noise during isometric force production. J Neurophysiol 88:1533–1544PubMedGoogle Scholar
  13. Keppel G (1991) Design and analysis: a researcher’s handbook. Prentice Hall, Upper Saddle RiverGoogle Scholar
  14. Laidlaw DH, Bilodeau M, Enoka RM (2000) Steadiness is reduced and motor unit discharge is more variable in old adults. Muscle Nerve 23:600–612CrossRefPubMedGoogle Scholar
  15. Levin CA, Haber RN (1993) Visual angle as a determinant of perceived interobject distance. Percept Psychophys 54:250–259PubMedGoogle Scholar
  16. Milner AD, Goodale MA (1993) Visual pathways to perception and action. Prog Brain Res 95:317–337PubMedCrossRefGoogle Scholar
  17. Mushiake H, Strick PL (1995) Pallidal neuron activity during sequential arm movemetns. J Neurophysiol 74:2754–2758PubMedGoogle Scholar
  18. Newell KM, McDonald PV (1994) Information, coordination modes and control in a prehensile force task. Hum Mov Sci 13:375–391CrossRefGoogle Scholar
  19. Newell KM, Slifkin AB (1998) The nature of movement variability. In: Piek J (ed) Motor control and human skill: a multidisciplinary perspective. Human Kinetics, Champaign, pp 143–160Google Scholar
  20. Pincus SM (1991) Approximate entropy as a measure of system complexity. Proc Natl Acad Sci USA 88:2297–2301PubMedCrossRefGoogle Scholar
  21. Rosenbluth D, Allman JM (2002) The effect of gaze angle and fixation distance on the responses of neurons in V1, V2, and V4. Neuron 33:143–149CrossRefPubMedGoogle Scholar
  22. Rougier P, Farenc I, Berger L (2004) Modifying the gain of the visual feedback affects undisturbed upright stance control. Clin Biomech (Bristol, Avon) 19:858–867CrossRefGoogle Scholar
  23. Schaab JA, Radwin RG, Vanderheiden GC, Hansen PK (1996) A comparison of two control-display gain measures for head-controlled computer input devices. Hum Factors 38:390–403PubMedGoogle Scholar
  24. Slifkin AB, Newell KM (1999) Noise, information transmission, and force variability. J Exp Psychol Hum Percept Perform 25:837–851CrossRefPubMedGoogle Scholar
  25. Slifkin AB, Vaillancourt DE, Newell KM (2000) Intermittency in the control of continuous force production. J Neurophysiol 84:1708–1718PubMedGoogle Scholar
  26. Stein JF, Glickstein M (1992) Role of the cerebellum in visual guidance of movement. Physiol Rev 72:967–1017PubMedGoogle Scholar
  27. Stephens JA, Taylor A (1974) The effect of visual feedback on physiological muscle tremor. Electroencephalogr Clin Neurophysiol 36:457–464CrossRefPubMedGoogle Scholar
  28. Vaillancourt DE, Newell KM (2000) Amplitude changes in the 8–12, 20–25, and 40 Hz oscillations in finger tremor. Clin Neurophysiol 111:1792–1801CrossRefPubMedGoogle Scholar
  29. Vaillancourt DE, Newell KM (2003) Aging and the time and frequency structure of force output variability. J Appl Physiol 94:903–912PubMedGoogle Scholar
  30. Vaillancourt DE, Larsson L, Newell KM (2002) Time-dependent structure in the discharge rate of human motor units. Clin Neurophysiol 113:1325–1338CrossRefPubMedGoogle Scholar
  31. Vaillancourt DE, Thulborn KR, Corcos DM (2003) Neural basis for the processes that underlie visually guided and internally guided force control in humans. J Neurophysiol 90:3330–3340PubMedCrossRefGoogle Scholar
  32. Vaillancourt DE, Mayka MA, Corcos DM (2006) Intermittent visuomotor processing in the human cerebellum, parietal cortex, and premotor cortex. J Neurophysiol 95:922–931CrossRefPubMedGoogle Scholar
  33. Wickens CD (1984) Engineering psychology and human performance. Merrill, ColumbusGoogle Scholar
  34. Wolpert DM, Miall RC, Winter JL, Stein JF (1992) Evidence for an error deadzone in compensatory tracking. J Motor Behav 24:299–308CrossRefGoogle Scholar
  35. Wyman D, Steinman RM (1973) Small step tracking: implications for the oculomotor “dead zone”. Vision Res 13:2165–2172CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • David E. Vaillancourt
    • 1
  • Pamela S. Haibach
    • 2
  • Karl M. Newell
    • 2
  1. 1.Departments of Movement Sciences (M/C 994), Bioengineering, and NeurologyUniversity of Illinois at ChicagoChicagoUSA
  2. 2.Department of KinesiologyThe Pennsylvania State UniversityUniversity ParkUSA

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