In contrast, the perception-action approach considers perception and action to be interconnected; perception plays a role in action and action plays a role in perception (A. D. Wilson, 2010). This ecological approach is heavily influenced by Gibson’s (1979) ontological perspective that premised rich information is available in all environmental stimuli (independent of the perceiver) and, without requiring complex cognitive involvement, this meaningful information can guide action. Gibson’s theory is therefore one of direct perception; a bottom-up, data-driven process.
Central to the perception-action approach is the idea that objects, events or places present opportunities for the perceiving individual to take action (Hirose, 2002). Gibson (1979) described these opportunities as affordances which individuals perceive relatively automatically if they are tuned-in to them (like a radio that is tuned-in to receive a signal; a process Gibson called resonance). For example, a ball affords kicking; a flat-surface affords walking; a tree affords climbing and an apple affords eating. However, an object will commonly have multiple affordances. For example, a chair might be sat on, stepped on or hurled through a window; a stick might be used as a lever or swung as a weapon. Although affordances are invariant properties of the environment, they are always considered in relation to the individual and are limited by capabilities (Gibson, 1979). For example, a rock affords being thrown, but not if the individual perceives he or she is not strong enough to throw it.
The ability to throw objects over long distances is unique to humans; in fact, it is suggested this ability conferred such a significant advantage to hunting and fighting that it enabled us to survive the last Ice Age (Zhu & Bingham, 2011). It is likely, therefore, the ability to throw objects over very long (>25m) distances evolved through the process of natural selection. As well as physical ability, being able to throw objects over long distances requires the ability to perceive the affordance of “throwability” (Zhu, 2008).
Can people accurately perceive this affordance to maximise long-distance throwing?
To answer this question, a perception-action approach is required and this guides the methodology of empirical investigation.
From a dynamical systems perspective, Bernshteĭn (1967) explained that the Human Action System (HAS; the one capable of throwing) has a large number of redundant degrees of freedom (anything that is free to vary). These need to be controlled in order to take effective action; otherwise every task would have multiple solutions and action would be indecisive. According to Bingham (1988), the HAS overcomes this problem by forming synergies and constraining itself to the task dynamics; picking one solution to overcome the task. Therefore, the solutions of the HAS are extremely task-specific; they are known as Task Specific Devices (TSDs). To investigate the HAS, the researcher must constrain enquiry to that which fits the task-dynamics; focussing on one TSD at a time. Therefore, there is similarity between the approach of the researcher and the approach of the HAS.
According to A. D. Wilson and Golonka (2013), the first step in an investigation into a specific perception-action task is to conduct a task-analysis in order to define, from a first-person-perspective, “the specific task that a perceiving-acting cognitive agent is faced with” (p. 1). The goal of the task is throwing to a maximum distance. The variables that determine distance in the dynamics of projectile-motion are the size and weight of the object, the release angle/velocity and the air density, drag and gravity (Parker, 1977; Zhu, Dapena, & Bingham, 2009). Some can be controlled (the size/weight of the object and the release angle/velocity) and thus represent the resources available to solve the task (specifying these resources is step two in the methodology). However, the size and weight of the object give rise to the affordance of throwability; these variables are perceived rather than controlled per se. The other dynamics cannot be controlled.
The third step is the assembly of resources in order to solve the problem. This means hypothesising that the TSD solves the problem of maximum throwability by choosing an object of optimum size/weight and selecting a maximum release velocity and optimum release angle (Bingham, Schmidt, & Rosenblum, 1989). The final step is to test the hypothesised TSD by assessing if people assemble and use the resources as described in step three.
Therefore, the first question is whether people can perceive the affordance of throwability. Bingham et al. (1989) created objects of different sizes and weights. Within each category of size, participants were asked to heft the objects and select the weight they believed could be thrown furthest. The results showed that, within each size, participants were able to throw their preferred choice the furthest thus demonstrating they had perceived the affordance accurately. Although only three people participated in the throwing task, the results were replicated reliably by Zhu and Bingham (2008).
Bingham et al. (1989) discovered the size-weight ratio for participants’ preferred objects reflected the size-weight illusion (that a larger-sized object needs to be heavier to be perceived as equal weight). Therefore, in contrast to standard cognitive science that often uses illusions as evidence of perceptual flaws, this provided evidence that the “misperception” was functional. The pertinent question is how are people able to perceive the affordance? The researchers also examined the kinematics (information about motion) of hefting and found that, when grasped, larger objects produced greater changes in tendon-length and corresponding changes in stiffness. They reported that “hefting with preferred objects produced an invariant phase between the wrist and elbow” (p. 507) which maintained the optimum timing and flow of energy for launching a projectile at maximum release velocity. They hypothesised that participants were able to detect the affordance via hefting due to changes in the stiffness of the wrist; the dynamics of hefting and throwing are therefore similar which allows hefting to provide information about how size and weight affects throwing. This hypothesised mechanism is a type of a smart perceptual mechanism as proposed by Runeson (1977). However, this particular one has been disconfirmed because the hypothesis requires that both size and weight affect the dynamics of throwing; Zhu and Bingham (2008) found that only weight does.
Zhu et al. (2009) conducted an experiment with unskilled throwers. Before training, participants were unable to perceive the affordance of throwability. The experiment was designed to test if participants could learn to perceive affordance by learning to throw and, if so, whether the ability is conferred via a smart perceptual mechanism or via functional-learning. The functional-learning hypothesis is that people perceive size, weight and distance-thrown separately and, by testing an extensive number of different size and weight combinations they build up enough knowledge to be able to extrapolate the function that relates the variables (Zhu et al.). This is also the essence of the schema theory of motor learning (Schmidt, 1975). The participants were assigned to one of four groups and trained for one month. Participants in the first three groups were trained using objects of constant size, constant weight and constant density respectively. The fourth group were also trained using objects with constant density but their vision was obscured so they could not see the distance achieved. The results showed that all groups improved their throwing ability equally by improving the consistency of the release angle and increasing the release velocity. The first three groups also acquired the ability to accurately perceive the affordance in untested size/weight combinations. This firmly supports the smart theory as, due to experimental design, the participants did not receive enough variation to enable functional-learning. The fourth group did not acquire the ability to perceive the affordance until after they were given visual feedback which demonstrates the essential role of feedback in calibrating the system.
It is clear that humans have evolved to be able to perceive affordances. Although it appears that a smart-mechanism exists that perceives the affordance of throwability, it is not known what the variable is that the mechanism detects. However, it appears to relate to perceived heaviness.
It is argued that standard cognitive psychology lacks the tools to be able to investigate perception-action systems; future research should continue from an ecological perception-action approach that adheres to the guidelines proposed by A. D. Wilson and Golonka (2013).
References
Bernshteĭn, N. A. (1967). The co-ordination and regulation of movements: Pergamon Press.
Bingham, G. P. (1988). Task-specific devices and the perceptual bottleneck. Human Movement Science, 7(2), 225-264.
Bingham, G. P., Schmidt, R., & Rosenblum, L. D. (1989). Hefting for a maximum distance throw: A smart perceptual mechanism. Journal of Experimental Psychology: Human Perception and Performance, 15(3), 507.
Gibson, J. J. (1979). The ecological approach to visual perception: Houghton Mifflin.
Hirose, N. (2002). An ecological approach to embodiment and cognition. Cognitive Systems Research, 3(3), 289-299. doi: http://dx.doi.org/10.1016/S1389-0417(02)00044-X
Parker, G. (1977). Projectile motion with air resistance quadratic in the speed. Am. J. Phys, 45(7), 606-610.
Runeson, S. (1977). On the possibility of “smart” perceptual mechanisms. Scandinavian Journal of Psychology, 18(1), 172-179.
Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological review, 82(4), 225.
Wilson, A. D. (2010). A perception-action approach to rhythmic movement coordination.
Wilson, A. D., & Golonka, S. (2013). Embodied Cognition is Not What You Think It Is. Frontiers in Psychology, 4. doi: 10.3389/fpsyg.2013.00058
Wilson, R. A., & Keil, F. C. (2001). The MIT Encyclopedia of the Cognitive Sciences Retrieved from http://books.google.co.uk/books?id=-wt1aZrGXLYC
Zhu, Q. (2008). Learning Affordances for Maximum Distance Throws in the Context of Learning to Throw. Indiana Indiana University.
Zhu, Q., & Bingham, G. P. (2008). Is hefting to perceive the affordance for throwing a smart perceptual mechanism? Journal of Experimental Psychology: Human Perception and Performance, 34(4), 929-943. doi: 10.1037/0096-1523.34.4.929
Zhu, Q., & Bingham, G. P. (2011). Human readiness to throw: the size–weight illusion is not an illusion when picking the best objects to throw. Evolution and Human Behavior, 32(4), 288-293.
Zhu, Q., Dapena, J., & Bingham, G. P. (2009). Learning to throw to maximum distances: Do changes in release angle and speed reflect affordances for throwing? Human Movement Science, 28(6), 708-725. doi: http://dx.doi.org/10.1016/j.humov.2009.07.005