Abstract
When reflecting on the nature of skilled action, it is easy to fall into familiar dichotomies such that one construes the flexibility and intelligence of skill at the level of intentional states while characterizing the automatic motor processes that constitute motor skill execution as learned but fixed, invariant, bottom-up, brute-causal responses. In this essay, I will argue that this picture of skilled, automatic, motor processes is overly simplistic. Specifically, I will argue that an adequate account of the learned motor routines that constitute embodied skills cannot be given in a purely bottom-up, brute-causal fashion. Rather, motor control is intelligent all the way down. To establish this, I will first review two recent accounts of skill, Stanley and Krakauer (Front Hum Neurosci, 2013. doi:10.3389/fnhum.2013.0050) and Papineau (R Inst Philos Suppl 73:175–196, 2013), which characterize the automatic motor control responsible for the fine-grained movements constitutive of motor skill as brute, low-level phenomena. I will then isolate five key features that should apply to skilled motor control, if these accounts are correct. Together, the accounts posit that motor control is: (1) ballistic, (2) invariant, (3) independent of general action trajectories, (4) Insensitive to semantic content, and (5) independent of personal-level intentions. In the final section of this paper, I will appeal to optimal control theory for empirical evidence to challenge the commitment to skilled action as qualified by the above features.
Similar content being viewed by others
Notes
In the course of this paper, when I use the word “skill” I will be referring exclusively to skilled bodily actions. I will not take a stance on whether any subpersonal processes, whether perceptual or motor, are properly classified as skills and though I think that a theory of bodily skill will have various interesting implications for our understanding of cognitive skill, I will remain silent on those implications here.
For a notable exception, see Levy (forthcoming) where he forwards a hybrid account where intelligence characterizes both personal-level intentional states and motor representations.
Such an account is also gestured at by Wu (2013).
For Stanley, knowing how is equivalent to having a skill.
See Fridland (2013) for a discussion of problems associated with individuating propositions either in a coarse or fine-grained way.
It is possible to cash out propositions in a more fine-grained fashion such that every variation in movement execution is mirrored by an improvement in propositional knowledge. This is the view forwarded by Pavese (2013). However, on the S&K view, the fine-grained, kinematic details of motor skill execution are not cashed out in terms of propositional knowledge but rather in terms of motor acuity.
See Fridland (2014) for an illustration of the importance of fine-grained motor control in giving an adequate account of skill.
When I use “fine-grained”, I have in mind both the parameters and time-scale of movement. As such, fine-grained movements are evident in both the millimeter and microsecond adjustments that are characteristic of skilled action.
S&K write that “motor skills have an acuity component that is directly analogous to perceptual acuity” (p. 16).
As S&K write, “Shmuelof et al. have recently coined the term “motor acuity” to describe the practice related reductions in movement variability and increases in movement smoothness….Such adaptions are not the acquisition of something that is characteristically manifest in intentional action, i.e., they are not the acquisition of skills” (p. 15).
It seems safe to assume that for Papineau, “conscious” does not just mean “phenomenal” or “experienced” but something more like “an intentional, personal-level states that one is a aware of being in”.
For a response to the claim that these considerations entail that skilled bodily actions are mostly non-conscious, see Shepherd (2015).
For a similar account of intentions organizing action in a top-down manner, by setting the parameters which prime or trigger automatic action execution, see Wu (2013). Wu writes, “We thus act intentionally. In playing the piano, the automaticity aimed for is that the specific notes played need not be represented in one’s intention. “Parameter specification” is automatic because no top-down modulation at the level of intention is required to specify the specific notes played, the ordering of fingering and so forth. Certainly, in learning that passage, one can act with a changing set of demonstrative intentions, say to play that note with these fingers, and this is attentionally demanding. One has to attentively focus on relevant notes or relevant keys. But once the piece is mastered, setting those parameters is automatic” (p. 18–19).
Adaptation learning can be understood as follows: “In these paradigms, subjects experience a perturbation of their hand during reaching or pointing movements: lateral displacement by prisms, rotation of movement direction, or lateral forces applied by a robot arm. Specifically, these paradigms have focused on adaptation, a form of learning characterized by gradual improvement in performance in response to altered conditions.” (Krakauer and Mazzoni 2011, p. 1).
“Learning tasks of this type do not generally have a built-in limit of performance: there is no systematic error to reduce to zero, and final performance is different from baseline” (Shmuelof et al. 2012, p. 579).
As Mandelbaum writes in describing ballisticity, “The proper input is not necessarily processed every time the input reaches the module, but once the processing starts, one cannot stunt it at will, either through top-down effort or via other roughly psychological means” (forthcoming, pp. 6–7).
Though, as Helen De Cruz has pointed out to me in personal communication, this evidence does not support the stronger claim that skilled agents are able to intervene upon or inhibit their actions more quickly than novices. It only supports the claim that skilled actions are not ballistic. Further research is needed to support the, to my mind, plausible prediction that with expertise, inhibitory control over skilled action increases.
As Haith and Krakauer (2013a) write, “far from viewing redundancy as a problem, redundancy should actually be regarded as a positive thing. It makes it easier to find solutions to a given task and allows goals to be achieved more flexibly and robustly. Redundancy, therefore, makes life easier for the motor system to develop adequate means of control and in general enables superior control strategies” (p. 9).
For similar claims cashed out in an account of the relationship between intentions and actions, see Shepherd (2014).
As Haith and Krakauer point out, “there is no need to wait for a large perturbation to prompt an adjustment of one’s movement. Even small deviations from expected trajectories should prompt a flexible change in motor commands” (2013a, p. 15).
Recall that, as we saw above, overcoming perturbations in adaptation paradigms is attributable to model-based representations (i.e., internal forward models) and not to open-loop, model-free processes.
For more on this, see Haith and Krakauer (2013b).
For a preliminary account of how personal-level intentions and the motor representations involved in skilled motor routines might be related see Butterfill and Sinigaglia (2014). For a response to their view, see Mylopoulos and Pacherie (forthcoming).
For arguments as to why these states should be thought of as representing information in different codes, see Butterfill and Sinigaglia (2014), Mylouplous and Pacherie (forthcoming), and Levy (forthcoming).
See Mylopoulos and Pacherie (forthcoming) for convincing reasons why the Butterfill and Sinigaglia (2014) demonstrative solution to the interface problem is left wanting. However, the considerations above also put pressure on Mylopoulos and Pacherie (forthcoming) who have not quite given us a way to understand dynamic interfacing.
References
Bartlett, R., Wheat, J., & Robins, M. (2007). Is movement variability important for sports biomechanists? Sports Biomechanics, 6, 224–243.
Beilock, S. (2007). Understanding skilled performance: Memory, attention, and ‘choking under pressure’. In T. Morris, P. Terry, & S. Gordon (Eds.), Sport & exercise psychology: International perspectives (pp. 153–166). Morgantown, WV: Fitness Information Technology.
Beilock, S. (2010). Choke. New York: Free Press.
Beilock, S., & Carr, T. (2001). On the fragility of skilled performance: What governs choking under pressure? Journal of Experimental Psychology, 130, 701–725.
Beilock, S., Carr, T., MacMahon, C., & Starkes, J. (2002). When paying attention becomes counterproductive: Impact of divided versus skill-focused attention on novice and experienced performance of sensorimotor skills. Journal of Experimental Psychology, 8, 6–16.
Bernstein, N. I. (1967). The coordination and regulation of movements. Oxford: Pergamon.
Butterfill, S. A., & Sinigaglia, C. (2014). Intention and motor representation in purposive action. Philosophy and Phenomenological Research, 88(1), 119–145.
Cohen, J. R., & Poldrack, R. A. (2008). Automaticity in motor sequence learning does not impair response inhibition. Psychonomic Bulletin & Review, 15, 105–115.
Cole, K. J., & Abbs, J. H. (1986). Coordination of three-joint digit movements for rapid finger-thumb grasp. Journal of Neurophysiology, 55, 1407–1423.
Deidrichsen, J. (2007). Optimal task-dependent changes of bimanual feedback control and adaptation. Current Biology, 17, 1675–1679.
Domkin, D., Laczko, J., Jaric, S., Johansson, H., & Latash, M. L. (2002). Structure of joint variability in bimanual pointing tasks. Experimental Brain Research, 143, 11–23.
Fridland, E. (2013). Problems with intellectualism. Philosophical Studies, 165(3), 879–891.
Fridland, E. (2014). They’ve lost control: Reflections on skill. Synthese, 91(12), 2729–2750.
Haith, A., & Krakauer, J. (2013a). Theoretical models of motor control and motor learning. In A. Gollhofer, W. Taube, & J. B. Nielsen (Eds.), Routledge handbook of motor control and motor learning (pp. 1–28). USA: Routledge.
Haith, A., & Krakauer, J. W. (2013b). Model-based and model-free mechanisms of human motor learning. In Progress in motor control (pp. 1–21). New York: Springer.
Korenberg, A. T., & Ghahramani, Z. (2002). A Bayesian view of motor adaptation. Current Psychology, 21(4–5), 537–564.
Krakauer, J., & Mazzoni, P. (2011). Human sensorimotor learning: adaptation, skill, and beyond. Current Opinion in Neurobiology, 21, 1–9.
Levy, N. (2015). Embodied savoir-faire: Knowledge-how requires motor representations. Synthese. doi:10.1007/s11229-015-0956-1.
Liu, D., & Todorov, E. (2007). Evidence for the flexible sensorimotor strategies predicted by optimal feedback control. The Journal of Neuroscience, 27(35), 9354–9368.
Logan, G. D. (1979). On the use of concurrent memory load to measure attention and automaticity. Journal of Experimental Psychology: Human Perception and Performance, 5, 189–207.
Logan, G. D. (1982). On the ability to inhibit complex movements: A top-signal study of typewriting. Journal of Experimental Psychology: Human Perception and Performance, 8, 778–792.
Logan, G. D. (1983). Time, information, and the various spans in typewriting. In W. E. Cooper (Ed.), Cognitive aspects of skilled typewriting (pp. 197–224). New York: Springer.
Logan, G. (1985). Skill and automaticity: Relations, implications, and future directions. Canadian Journal of Psychology, 39(2), 367–386.
Mandelbaum, E. (2014). The automatic and the ballistic: Modularity beyond perceptual processes. Philosophical Psychology, 28(8), 1147–1156.
Milner, D., & Goodale, M. A. (2006). The visual brain in action. Oxford: Oxford University Press.
Milner, D., & Goodale, M. A. (2010). Cortical visual systems for perception and action. In N. Gangopadhay, M. Madary, & F. Spicer (Eds.), Perception, action, and consciousness (pp. 71–94). Oxford: Oxford University Press.
Mylopoulos, M. & Pacherie, E. (2016). Intentions and motor representations: The interface challenge. Review of Philosophy and Psychology. doi:10.1007/s13164-016-0311-6.
Nagengast, A. J., Braun, D. A., & Wolpert, D. M. (2009). Optimal control predicts human performance on objects with internal degrees of freedom. PLoS Computational Biology, 5(6), e1000419. doi:10.1371/journal.pcbi.1000419.
Papineau, D. (2013). In the zone. Royal Institute of Philosophy Supplement, 73, 175–196.
Pavese, C. (2013). The unity and scope of knowledge. Dissertation, Rutgers University.
Posner, M. I., & Snyder, C. R. R. (1975). Attention and cognitive control. In R. L. Solso (Ed.), Information processing and cognition: The Loyola symposium (pp. 153–175). NJ: Erlbaum.
Scholz, J. P., & Schoner, G. (1999). The uncontrolled manifold concept: identifying control variables for a functional task. Experimental Brain Research, 126, 289–306.
Scholz, J. P., Schoner, G., & Latash, M. L. (2000). Identifying the control structure of multijoint coordination during pistol shooting. Experimental Brain Research, 135, 382–404.
Shepherd, J. (2014). The contours of control. Philosophical Studies, 170(3), 395–411.
Shepherd, J. (2015). Conscious control over action. Mind and Language, 30(3), 320–344.
Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. Psychological Review, 84(2), 127–190.
Shmuelof, L., Krakauer, J. W., & Mazzoni, P. (2012). How is a motor skill learned? Change and invariance at the levels of task success and trajectory control. Journal of Neurophysiology, 108(2), 578–594.
Stanley, J. (2011a). Knowing (how). Noûs, 45(2), 207–238.
Stanley, J. (2011b). Know how. Oxford: Oxford University Press.
Stanley, J., & Krakauer, J. (2013). Motor skill depends on knowledge of facts. Frontiers of Human Neuroscience,. doi:10.3389/fnhum.2013.0050.
Stanley, J., & Williamson, T. (2001). Knowing how. Journal of Philosophy, 98, 411–444.
Todorov, E. (2004). Optimality principles in sensorimotor control. Nature Neuroscience, 7(9), 907–915.
Todorov, E., & Jordan, M. I. (2002). Optimal feedback control as a theory of motor coordination. Nature Neuroscience, 5(11), 1226–1235.
Wu, W. (2013). Mental action and the threat of automaticity. In Andy Clark, Julian Kiverstein, & Tillman Vierkant (Eds.), Decomposing the will (pp. 244–261). Oxford: Oxford University Press.
Yarrow, K., Brown, P., & Krakauer, J. W. (2009). Inside the brain of an elite athlete: the neural processes that support high achievement in sports. Nature Reviews Neuroscience, 10, 585–596.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fridland, E. Skill and motor control: intelligence all the way down. Philos Stud 174, 1539–1560 (2017). https://doi.org/10.1007/s11098-016-0771-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11098-016-0771-7