Abstract
In this paper, we examine the role of degrees of freedom and their degeneracy in learning in the brain–computer interface paradigm. Though the traditional notion of degrees of freedom in motor learning gave emphasis to muscle and joint activity, the broader concept of dimensions of behavior is relevant to brain–computer interface learning where there is no muscle activity. The role of degeneracy in the dimensions of brain activity is proposed to enhance learning through robustness to stability loss and adaptability in the search for new stable states. Principles for the application of augmented information for learning to coordinate and control the degenerate degrees of freedom in the brain–computer interface are outlined.
Similar content being viewed by others
References
Adams JA (1971) A closed-loop theory of motor learning. J Motor Behav 3:111–150
Basar E (ed) (1990) Chaos in brain function. Springer, Berlin Heidelberg New York
Beek PJ, Turvey MT, Schmidt RC (1992) Autonomous and nonautonomous dynamics of coordinated rhythmic movement. Ecol Psychol 4:65–96
Bernstein N (1967) The co-ordination and regulation of movements. Pergamon, London
Bilodeau EA, Bilodeau IM (1961) Motor skills learning. Ann R Psychol 12:243–280
Birbaumer N, Ghanayim N, Hinterberger T, Iversen I, Kotchoubey B, Kübler A, Perelmouter J, Taub E, Flor H (1999) A spelling device for the paralysed. Nature 398:297–298
Birbaumer N, Kübler A, Ghanayim N, Hinterberger T, Perelmouter J, Kaiser J, Iversen I, Kotchoubey B, Neumann N, Flor H (2000) The thought translation device (TTD) for completely paralyzed patients. IEEE Rehabil Eng 8:190–193
Birbaumer N, Hinterberer T, Kübler A, Neumann N (2003) The thought-translation device (TTD): neurobehavioral mechanisms and clinical outcome. IEEE Neurol Sci 11:120–123
Chen H-H, Liu Y-T, Mayer-Kress G, Newell KM (2005) Learning the pedalo locomotion task. J Motor Behav (in press)
Eckhardt RB (2000) Human paleobiology. Cambridge University Press, Cambridge
Edelman GM, Gally J (2001) Degeneracy and complexity in biological systems. Proc Natl Acad Sci USA 98:13763–13768
Eubank SG, Farmer JD (1997) Probability, random processes, and the statistical description of dynamics. In: Lam L (ed) Introduction to nonlinear physics. Springer, Berlin Heidelberg New York, pp 106–178
Fernández P, Solé RV (2004) The role of computation in complex regulatory networks. In: Koonin E, Wolf Y, Karev G (eds) Scale-free networks and genome biology. Landes Bioscience, Georgetown
Fowler CA, Turvey MT (1978) Skill acquisition: an event approach with special reference to searching for the optimum of a function of several variables. In: Stelmach GE (ed) Information processing in motor control and learning. Academic, New York, pp 1–40
Freeman WJ (2003) The wave packet: an action potential for the 21st century. J Integr Neurosci 2:3–30
Freeman WJ, Gaal G, Jorsten R (2003) A neurobiological theory of meaning in perception. Part III: multiple cortical areas synchronize without loss of local autonomy. Int J Bifurcation Chaos 13:2845–2856
Friston KJ, Price CJ (2003) Degeneracy and redundancy in cognitive anatomy. Trends Cog Sci 7:151–152
Greene PH (1969) Seeking mathematical models for skilled actions. In: Bootzin D, Muffley HC (eds) Biomechanics. Proceedings of the first Rock Island arsenal biomechanics symposium. Plenum, New York
Haken H (1996) Principles of brain functioning: a synergetic approach to brain activity, behavior and cognition. Springer, Berlin Heidelberg New York
Jeannerod M (1997) The cognitive neuroscience of action. Blackwell, Oxford
Jen E (ed) (2002) Robust design: a repertoire of biological, ecological, and engineering case studies. Oxford University Press, Oxford
Jordan MI (1990) Motor learning and the degrees of freedom problem. In: Jeannerod M (ed) Attention and performance XIII. Lawrence Erlbaum, Hillsdale, pp 796–836
Kay BA (1988) The dimensionality of movement trajectories and the degrees of freedom problem: a tutorial. Hum Move 7:343–364
Latash ML (1996) The Bernstein problem: how does the central nervous system make its choices? In: Latash ML, Turvey MT (eds) Dexterity and its development. Lawrence Erlbaum, Mahwah, pp 277–304
Lipsitz LA, Goldberger AL (1992) Loss of ‘complexity’ and aging: potential applications of fractals and chaos theory to senescence. JAMA 267:1806–1809
Liu YT, Mayer-Kress G, Newell KM (2004a) Beyond curve fitting to inferences about learning. J Motor Behav 36:233–238
Mayer-Kress G (1994) Localized measures for non-stationary time-series of physiological data. Integrative Physiol Behav Sci 29:205–210
McFarland DJ, Wolpaw JR (2003) EEG-based communication and control: speed-accuracy relationships. Appl Psychophysiol Biofeedback 28:217–231
Neuper C, Muller GR, Kübler A, Birbaumer N, Pfurtscheller G (2003) Clinical application of an EEG-based brain-computer interface: a case study in a patient with severe motor impairment. Clin Neurol 114:399–409
Newell KM (1976) Knowledge of results and motor learning. In: Keogh J, Hutton RS (eds) Exercise and sport sciences reviews, vol 4. Journal Publishing, Santa Barbara
Newell KM (1991) Motor skill acquisition. In: Rosenzweig MR, Porter LW (eds) Annual review of psychology, vol 42. Annual Reviews, Palo Alto, pp 213–237
Newell KM (1996a) Change in movement and skill: learning, retention, and transfer. In: Latash M, Turvey M (eds) Dexterity and its development. Lawrence Erlbaum, Mahwah, NJ, pp 393–432
Newell KM (1996b) The dynamics of stereotypic behaviors. In: Sprague RL, Newell KM (eds) Stereotypies: brain–behavior relationships. American Psychological Association, Washington
Newell KM, McDonald PV (1994) Learning to coordinate redundant biomechanical degrees of freedom. In: Swinnen S, Heuer H, Massion J, Casaer P (eds) Interlimb coordination: neural, dynamical and cognitive constraints. Academic, New York, pp 515–536
Newell KM, McGinnis PM (1985) Kinematic information feedback for skilled performance. Hum Learn 4:39–56
Newell KM, Vaillancourt D (2001) Dimensional change in motor learning. Hum Move 4-5:695–716
Newell KM, Valvano J (1998) Therapeutic intervention as a constraint in learning and relearning movement skills. Sci J Occup Ther 5:51–57
Newell KM, Morris LR, Scully DM (1985) Augmented information and the acquisition of skill in physical activity. In: Terjung RL (ed) Exercise and sport sciences reviews, vol 13. Collamore, Lexington, pp 235–261
Newell KM, van Emmerik REA, McDonald PV (1989a) On simple movements and complex theories (and vice-versa). Behav Brain 12:229–230
Newell KM, Kugler PN, van Emmerik REA, McDonald PV (1989b) Search strategies and the acquisition of coordination. In: Wallace SA (ed) Perspectives on coordination. North Holland, Amsterdam, pp 86–122
Newell KM, Liu YT, Mayer-Kress G (2001) Time scales in motor learning and development. Psychol Rev 108:57–82
Newell KM, Liu Y-T, Mayer-Kress G (2003) A dynamical systems interpretation of epigenetic landscapes for infant motor development. Infant Behav 26:449–472
Rodriguez E, George N, Lachaux JP, Martinerie J, Renault B, Varela FJ (1999) Perception’s shadow: long-distance synchronization of human brain activity. Nature 397:430–433
Ryle G (1949) The concept of mind. The University of Chicago Press, Chicago
Saltzman EL (1979) Levels of sensorimotor representation. J Math Psychol 20:91–163
Schaal S, Sternad D, Osu R, Kawato M (2004) Rhythmic arm movement is not discrete. Nat Neurosci 7:1136–1143
Scholz JP, Schöner G (1999) The uncontrolled manifold concept: identifying control variables for a functional task. Exp Brain Res 126:289–306
Snoddy GS (1926) Learning and stability. J Appl Psychol 10:1–36
Sporns O, Edelman GM (1993) Solving Bernstein’s problem: a proposal for the development of coordinated movement by selection. Child Dev 64:960–981
Thorndike EL (1913) Educational psychology, vol. 2. Columbia University, New York
Tononi G, Sporns O, Edelman GM (1999) Measures of degeneracy and redundancy in biological networks. Proc Natl Acad Sci USA 96:3257–3262
Turvey MT, Shaw RE (1999) Ecological foundations of cognition: degrees of freedom and conserved quantities in animal-environment systems. J Conscious Stud 6:111–123
Turvey MT, Shaw RE, Mace W (1978) Issues in a theory of action: degrees of freedom, coordinative structures, and coalitions. In: Requin J (ed) Attention and performance VII. Lawrence Erlbaum, Hillsdale, pp 557–598
Walker MP, Brakefield T, Hobson TA, Stickgold R (2003) Dissociable stages of human memory consolidation and reconsolidation. Nature 425:616–620
Wolpaw JR, McFarland DJ (2004) Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proc Natl Acad Sci USA 101:17849–17854
Wolpaw JR, Birbaumer N, Heetderks WJ, McFarland DJ, Peckham PH, Schalk G, Donchin E, Quatrano LA, Robinson CJ, Vaughan TM (2000) Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng 8:164–173
Zatsiorsky VM (1998) Kinematics of human motion. Human Kinetics, Champaign
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Irene Ruspantini and Niels Birbaumer
Rights and permissions
About this article
Cite this article
Newell, K.M., Liu, YT. & Mayer-Kress, G. Learning in the brain–computer interface: insights about degrees of freedom and degeneracy from a landscape model of motor learning. Cogn Process 6, 37–47 (2005). https://doi.org/10.1007/s10339-004-0047-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10339-004-0047-6