In order to interpret or anticipate what others intend to do, we are able to extrapolate their intentions by “reading” their movements (or their minds) (Sebanz, Bekkering, & Knoblich, 2006). Not only is this a very important ability of social interaction in everyday life, but also a crucial competence for athletes in interactive sports, like table tennis or fencing. To prevail in sport competitions, athletes need to know in advance what their opponents are intending on doing. With this knowledge, they can prepare in a sufficient amount of time for an appropriate (re)action. Therefore, it is not surprising that humans are very sensitive to biological motion. Neurophysiological studies show that biological motion selectively activates specific areas/domains in the human brain (e.g. areas in the inferior frontal gyrus and the superior temporal sulcus) (Giese & Poggio, 2003). A variety of behavioural studies showed that humans can extract a great amount of information of another person’s actions even though information is limited. For example, we can identify gender (Kozlowski & Cutting, 1977; Pollick, Kay, Heim, & Stringer, 2005) and mood of a walking person (Dittrich, Troscianko, Lea, & Morgan, 1996). Further, we can identify and categorise the action a model is performing (Johansson, 1973), and – this especially is interesting for this study – we can judge the weight a person is lifting (Bingham, 1993; Grierson, Ohson, & Lyons, 2013; Runeson & Frykholm, 1981; Shim, Hecht, Lee, Yook, & Kim, 2009) by observing those actions in point-light (or stick diagram) displays. These performances are based on the analysis of salient point lights fixed to the main joints of a human model. That is, the kinematic profiles of these moving points provide sufficient information for the observer to dissect the action (Blake & Shiffrar, 2007; Viviani, Figliozzi, & Lacquaniti, 2011b).
In weight estimation tasks, a person is displayed lifting objects of different weights and participants are asked to judge the weight. It is not possible to identify the weight from the object (because they all look alike, e.g. different heavy boxes with the same dimensions) but by observing the body movement of the lifter. Participants are usually very successful in accomplishing those tasks even though the lifter is just depicted as point light figure or the lifted object is not displayed (Bingham, 1993; Grierson et al., 2013; Runeson & Frykholm, 1981; Shim et al., 2009). It is an open debate whether good estimation performances of observed lifting actions are based on visual or motor experiences. This study aims to provide new insights by using stimuli that look plausible in normal and time-reversed video play back (lifting and lowering an object). The alteration of the video play back direction makes it possible to change the goal of an action (e.g. from lifting to placing an object) while its average kinematic profile is preserved.
There are two main hypotheses discussed to explain good identification performances of observed biological motion: the motor simulation hypothesis (MSH, e.g. Gallese, Fadiga, Fogassi, & Rizzolatti, 1996; Gallese & Goldman, 1998; sometimes referred to as the direct matching hypothesis, Rizzolatti, Fogassi, & Gallese, 2001) and the visual analysis hypothesis (VAH, e.g. Johansson, 1973; Rizzolatti et al., 2001). The MSH assumes that our own motor system contributes to the understanding of another person’s actions. That is, we simulate the observed actions of others through our own motor system. By doing so, we can identify the goals or inner states of observed persons, which help us to anticipate their future actions (Gallese & Goldman, 1998). At the neurological level this ability is based on the mirror neuron system that was first found in macaque monkeys (di Pellegrino, Fadiga, Fogassi, Gallese, & Rizzolatti, 1992; Rizzolatti, Fadiga, Gallese, & Fogassi, 1996a; Gallese et al., 1996) and was soon afterwards also found in the human brain (Fadiga, Fogassi, Pavesi, & Rizzolatti, 1995; Rizzolatti et al., 1996b). “MNs [mirror neurons] respond both when a particular action is performed by the recorded monkey and when the same action performed by another individual is observed” (Gallese & Goldman, 1998, p. 495). The MSH postulates that an externally triggered action plan is activated in the observer – not for its execution – but for putting oneself in the observed person’s situation. The activation creates analogous mental occurrences in the observer as in the observed person, which allows ‘mind-reading’ of the person’s goals and intentions (Gallese & Goldman, 1998).
Two variations of the MSH have been postulated: a strong version (Gallese, Keysers, & Rizzolatti, 2004; Rizzolatti et al., 2001) and a weak version (Fogassi et al., 2005). The weak version of the MSH assumes that the goal of the observed action is mainly represented by motor simulation in the observer whereas the kinematic details of that action are less important. This assumption is consistent with the finding that the mirror neuron system of the monkey codes the same act (in this case grasping) differently depending on the goal of the action (Fogassi et al., 2005). Thereby, other factors like grasp intensity or movement kinematics were ruled out to be responsible for the different activation patterns. The strong version suggests that all parts of the action plan of observed actions (for example, the exerted force and the movement kinematics) are simulated by the motor system of the observer based on the mirror neuron system. This assumption refers to the observation that the human mirror neuron system, in contrast to that of monkeys, is also active when objectless movements of an actor are observed (Gallese et al., 2004).
The visual analysis hypothesis assumes that every element which forms an action are analysed purely based on visual information without involving the observer’s motor system (Giese & Poggio, 2003; Rizzolatti et al., 2001). Giese and Poggio (2003) proposed a neurophysiological model with two pathways: one for form processing (related to features like orientation, body shapes, etc.) and one for motion processing. This model assumes that biological motion is recognized by a set of learned patterns. “These patterns are encoded as sequences of ‘snapshots’ of body shapes by neurons in the form pathway, and by sequences of complex optic flow patterns in the motion pathway” (Giese & Poggio, 2003, p. 181). Thereby, the form pathway is located in the ventral processing stream and the motion pathway is located in the dorsal processing stream referring to the two visual pathways hypothesis by Goodale and Milner (1992).
Several studies tested the contributions of the aforementioned hypotheses to explain weight judgement performances by humans observing an actor lifting different weights (Auvray, Hoellinger, Hanneton, & Roby-Brami, 2011; Hamilton, Joyce, Flanagan, Frith, & Wolpert, 2007; Maguinness, Setti, Roudaia, & Kenny, 2013). Auvray et al. (2011) tested all three explanations with several experiments. They found evidence favouring the weak version of the MSH. Their main argument against the strong version of the MSH was based on the findings in Experiment 2. Here, five different kinematic parameters were identified that varied consistently with the lifting action (action execution) with different weights. However, observer’s weight judgements were mainly based on one parameter - in particular acceleration - although this parameter “explained a relatively small part of the variance of the information related to weight during action execution” (Auvray et al., 2011, p. 1100). Furthermore, showing the observer more details of the executed action (only the hand and the lifted object, each represented as one moving point vs. a stick diagram of the whole grasping arm) did not increase weight judgement performance (Experiment 1). The strongest evidence against the visual analysis hypothesis results from Experiment 3, where subjects were confronted with their own lifting movements and those of others. Even though subjects failed to recognise their own actions above chance level, they relied on different kinematic parameters when judging their own lifting movements compared to the movements of others.
Hamilton et al. (2007) also found evidence against the strong version of the MSH. In line with Auvray et al. (2011), they investigated lifting actions with displays showing just the arm of a model grasping a small box. They also found a difference between kinematic parameters that correlated with weight and the kinematic information used for weight judgements. Subjects did not use grasp information for their judgements even though grasp duration was a good predictor of weight.
In contrast, there are several neurophysiological studies that have found evidence in favour of the strong version of the MSH (Alaerts, Senot, Swinnen, Craighero, Wenderoth, & Fadiga, 2010; Aziz-Zadeh, Maeda, Zaidel, Mazziotta, & Iacoboni, 2002; Borroni & Baldissera, 2008; Montagna, Cerri, Borroni, & Baldissera, 2005; Strafella & Paus, 2000). By using transcranial magnetic stimulation (TMS), these studies showed activity in the primary motor cortex elicited by different parameters of an observed action. The authors detected that this activity is effector specific (Aziz-Zadeh et al., 2002), muscle specific (Strafella & Paus, 2000), and synchronized to the temporal characteristics of the observed action (Montagna et al., 2005). Furthermore, Alaerts et al., (2010) showed that corticospinal excitability while observing a model grasping and lifting an object was not only modulated by the identity of the involved muscles, but also by the exerted force of the observed action. Results revealed higher corticospinal activity in the observer when the model lifted a heavy weight as compared to a light weight.
In summary, it remains unclear to what extent the motor system of an observer is involved in weight judgement tasks. The depicted behavioural studies found evidence in favour of the weaker version of the MSH, whereas the findings of the neurophysiological studies correspond to the assumptions of the strong version of the MSH more. Therefore, this study aimed at testing the weak version of the MSH. Hence, the action goal serves as a crucial hint in the interpretation of other’s actions. Therefore, the experimental manipulation was to alter the action goal of lifting and lowering actions. We implemented this by showing lifting and lowering actions normal and in a time-reversed order of sequence. Using this procedure, to lift an object changes to placing an object while the average kinematic profiles of the actions remain the same (Lestou, Pollick, & Kourtzi, 2008). Based on the weak version of the MSH, we hypothesize that weight judgements will differ between the video play back directions even though the average movement kinematics remain constant.