Opinion
Internal Models and Body Schema in Tool Use Martina Rieger1,2 1
Department of Psychology, Goethe University, Frankfurt am Main, Germany, University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
2
Performing actions with tools requires additional processes in comparison to performing actions without tools. The question how existing models of action control can be extended or modified to incorporate tool use is however still open to debate. According to the model of action control depicted in Figure 1A (adapted and modified from Blakemore, Wolpert, & Frith, 2002) intended action effects (e.g., wanting to switch on the light) or anticipated action effects (e.g., the expectation that a light will appear when pressing the light switch), as well as perceived action effects (e.g., the perception of a piano sound by a pianist) or affordances (e.g., seeing a graspable object) activate inverse (motor) models. Inverse motor models compute the motor commands which usually lead to the intended/anticipated/perceived action effects or match the affordance of perceived objects. The motor command is then sent to the effectors. Some modulation/inhibition of motor commands also occurs, because otherwise one would constantly react to environmental stimuli which activate action tendencies. Inhibition of the motor commands also enables the prediction of action outcomes during action planning. An efference copy of the motor command is used by forward motor models to predict the consequences of the action on the body and on the environment (predicted effects). Predicted and intended/anticipated action effects are compared, and if necessary discrepancies (errors) can be corrected before a movement is (fully) executed. During and after action execution, actual (observed) effects become available; they are compared to predicted as well as intended/anticipated effects. It should be noted that internal models do not function as single units. Rather, during an action the outputs from multiple internal models are blended depending on their appropriateness for the current context. Therefore, a large number of different actions can be generated with a limited number of internal models. Motor learning usually consists of an optimization and more adaptive selection of already existing internal models (Wolpert & Kawato, 1998). This adaptive selection results in successively lower discrepancies between the different types of effects after repeated action execution. In tool use people develop internal models of the tool transformation (e.g., Imamizu, Higuchi, Toda, & Kawato, 2007; Imamizu, Kuroda, Miyauchi, Yoshioka, & Kawato, Zeitschrift fu¨r Psychologie 2012; Vol. 220(1):50–52 DOI: 10.1027/2151-2604/a000091
2003; Su¨lzenbru¨ck, 2012). Internal tool models are thought to be ‘‘cognitive’’ models, distinct from motor models which are responsible for basic sensorimotor transformations, because activation in the cerebellum related to internal tool models occurs in areas distinct from areas that are responsible for motor functions (Imamizu et al., 2003). Internal tool models probably contain not only information about the tool mechanism itself. Tool mechanisms per se are not always represented during action planning with tools. Rather, the abstract mapping between body movements and effective tool parts is represented (Massen, in press). This indicates that internal tool models may include some representation of the body movement, albeit not the basic sensorimotor transformation. How can internal tool models be incorporated into the outlined model of action control? It is unlikely that inverse tool models and inverse motor models are activated in parallel, as the motor system needs to know about the behavior of a tool before motor commands can be selected. Thus, one may assume that they are activated in serial order. A strict serial order of inverse tool models and inverse motor models is however unlikely as well, because, if given a chance, tool users may modify tool transformations in order to optimally achieve task goals or to perform biomechanically comfortable movements (Herbort, 2012). For example, a hammer can be grasped at different positions depending on whether one wants to perform a spatially accurate or a powerful movement with it. Thus, information from inverse motor models must be available to inverse tool models. This indicates that inverse tool models and inverse motor models must be able to reciprocally communicate with each other. A possible scenario of how tool models and motor models may work together is outlined in Figure 1B. Inverse tool models are activated first. The inverse tool models inform the inverse motor models, and both types of inverse models reciprocally inform each other before finally the motor command is specified. Predictive processes through forward models occur in a similar way: the efference copy of the motor command informs forward motor models, which in turn inform forward tool models, both types of forward models reciprocally inform each other and compute predicted effects The acquisition of new tool transformations is similar to the acquisition of new movements: Early in the acquisition of a new tool transformation internal models Ó 2012 Hogrefe Publishing
Opinion
Figure 1. Action models: (A) Model of action control adapted and modified from Blakemore et al. (2002). (B) Modified action model including internal tool models. (C) Modified action model in which a tool-specific body schema informs internal motor models. for similar known tools are activated and their output is blended in order to cope with the novel tool. After acquisition, only the specific internal models required by the new tool are activated (Imamizu et al., 2007). There is also another way how internal motor models may be informed about the tool transformations. Very simple tools, for example sticks, which basically consist of an extension of the hand, seem to be incorporated into the body schema, Ó 2012 Hogrefe Publishing
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at least after active tool use for a certain amount of time (e.g., Maravita & Iriki, 2004). In actions without tools, information about the body (schema) must be available to internal models: in order to specify motor commands and to predict movement effects, biomechanical constraints of the body (e.g., how the joints can move), physical extensions of the body (e.g., how long the arm is), and physical fitness (e.g., whether a jump of a certain distance is feasible) have to be taken into account. Simple tools could be incorporated into the body schema by adjusting its parameters, for example when using a stick, the parameter ‘‘hand length’’ could be adjusted. Internal models may then be informed by the toolspecific body schema during the computation of motor commands and predicted effects (see Figure 1C). The idea is appealing, because it conforms to folk psychological ideas about how experts, for example musicians, perform actions with tools (e.g., ‘‘being one with the instrument’’). One may assume that with extended learning, tool-specific body schemas may develop even for very complex tools. However, so far no evidence for the existence of tool-specific body schemas for complex tools exists. Indeed, even levers, which are only slightly more complex than sticks as they introduce only one additional joint, are not represented as simple extensions of effectors (Massen, 2012). Furthermore, even the idea that simple tools can be incorporated into the body schema has been questioned: rather than an extension of the body those tools may induce a multisensory shift of spatial attention to the side of space where the tip of the tool is actively held (Holmes, Sanabria, Calvert, & Spence, 2007). From a theoretical viewpoint, one may even wonder whether a body schema, which is independent of internal motor models, actually exists or whether it is implicitly represented in them. In conclusion, the question how existing models of action control can be extended or modified in order to incorporate tool use has so far not been satisfactorily answered. Two possible scenarios of how tool transformations can be integrated into a model of action control have been outlined: (a) internal tool models operate in addition to internal motor models, requiring additional computational steps, or (b) parameters of the body schema are adjusted in a toolspecific way, making additional computational steps unnecessary. The following questions remain open: (1) What information is represented in internal tool models? (2) How and in which order do internal tool models and internal motor models inform each other? (3) Can tools really become part of the body schema?
References Blakemore, S.-J., Wolpert, D. M., & Frith, C. D. (2002). Abnormalities in the awareness of action. Trends in Cognitive Sciences, 6, 237–242. Herbort, O. (2012). Task-dependent selection of a tool-transformation. Zeitschrift fu¨r Psychologie, 220. Holmes, N. P., Sanabria, S., Calvert, G. A., & Spence, C. (2007). Tool-use: Capturing multisensory spatial attention or extending multisensory peripersonal space? Cortex, 43, 469–489.
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Imamizu, H., Higuchi, S., Toda, A., & Kawato, M. (2007). Reorganization of brain activity for multiple internal models after short but intensive training. Cortex, 43, 338–349. Imamizu, H., Kuroda, T., Miyauchi, S., Yoshioka, T., & Kawato, M. (2003). Modular organisation of internal models of tools in the human cerebellum. Proceedings of the National Academy of Sciences, 100, 461–466. Maravita, A., & Iriki, A. (2004). Tools for the body (schema). Trends in Cognitive Sciences, 8, 79–86. Massen, C. (2012). Cognitive representations of tool-use interactions. Manuscript submitted for publication. Massen, C. (in press). Planung und kognitive Repra¨sentation von Handlungen mit Werkzeugen [Planning and cognitive representation of tool use actions]. Psychologische Rundschau. Su¨lzenbru¨ck, S. (2012). The impact of continuous and terminal visual feedback on the mastery of visuo-motor transformations. Zeitschrift fu¨r Psychologie, 220. Wolpert, D. M., & Kawato, M. (1998). Multiple paired forward and inverse models for motor control. Neural Networks, 11, 1217–1329.
Martina Rieger M2 – Department for Medical Sciences and Management Institute for Psychology UMIT – University for Health Sciences, Medical Informatics and Technology Eduard Wallno¨fer Zentrum 1 6060 Hall in Tirol Austria Tel. +43 50 8648-3905 E-mail
[email protected]
The Opinion section of this journal aims to encourage further inquiry and debate. The opinions expressed in the contributions to this section are those of the authors and not necessarily those of the journal, the editors, or the publisher.
Zeitschrift fu¨r Psychologie 2012; Vol. 220(1):50–52
Ó 2012 Hogrefe Publishing
