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Andrew D Wilson & Sabrina Golonka are two psychologists who are interested in developing a more coherent, naturalised approach to the scientific study of human behaviour. Andrew studies the perceptual control of action, with a special interest in learning. Sabrina studies similarity and categorisation. We're both interested in exploring non-representational theories in psychology, including dynamical systems and ecological psychology.
Andrew Wilson
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- February 28, 2013
- 09:11 AM
- 183 views
The affordances of objects and pictures of those objects
by Andrew Wilson in Notes from Two Scientific Psychologists
People interested in how perception and action affect cognition have begun talking about affordances. This should be great news; the ecological approach suggests that affordances are the properties of the world that we perceive that enable us to control our actions, so if you are interested in how action can ground, say, memory or language, then discussing affordances should enable real progress. The term 'affordance', however, is a technical term, and it refers to very particular properties of an organism's environment. There are methods for experimentally identifying exactly how these properties are composed, and there are methods for testing our perception of them. If you aren't using these methods, and if you aren't using the term correctly, then you aren't studying affordances.A recent example of this kind of work is Pecher et al (2013). They were interested to see whether object affordances play a role in working memory for those objects. They ran two experiments which used pictures of objects with varying affordances for manipulability, and found that in each case memory for these objects was not affected by an interfering motor task, suggesting affordances are not used to structure working memory. There is a key problem here, and that is that pictures of objects do not afford the same things as the objects themselves. Interact with a coffee cup, and a picture of a coffee cup; they provide very different opportunities for interaction. You cannot drink out of a picture of a coffee cup; you cannot hold it by the handle because it has no handle! (See Snow et al, 2011 for a demonstration of this in an fMRI context). The fact that these things afford different things is not intrinsically a problem; the affordances of these things and the different information these different affordances produce is, after all, how we can perceive that they are different things. It is a problem, however, if you are trying to study how the affordances of coffee cups might affect your memory for coffee cups by using pictures of coffee cups. You aren't studying the affordances of coffee cups, and you shouldn't actually get to say that you are studying the affordances of coffee cups. Studying affordances is hard. They are odd things; they are properties of the world (e.g. the spatial extent of an object) as measured by the action capabilities of the organism (e.g. hand span) during the performance of a particular task (e.g. prehension). This means that you can only identify their exact composition by running experiments involving the objects, an organism and a task. An outstanding example of how to do this is Mon-Williams & Bingham (2011). They had people reaching and grasping objects that varied in size along various dimensions. They then systematically investigated the effects of these size variations on the spatial structure of the prehension movement (structure such as the maximum grip aperture). They identified that the relevant action capability was the opposition axis. Imagine a line between your thumb and forefinger. This line has a length and an orientation. People are navigating their hands by setting those two parameters, and they alter how they grasp objects as the relationship between the opposition axis and the maximum object extent changes. The MOE is the longest possible distance across the object. If you tilt your hand as you reach for an object, you can increase the effective width your hand has to span. This, not width, is what the perception-action system is measuring with respect to the opposition axis. This set up holds for a certain range of prehension tasks (one handed grasping of objects within a size range that can be spanned by the thumb and forefinger). This holds, therefore, for grasping something like a coffee cup, and the MOE measured with respect to the opposition axis is the affordance for this object to a person. This will therefore not hold for a picture of a coffee cup. Pictures are thin, almost 2D objects and do not fall within the relevant range. So using pictures of cups to study the affordances of cups will simply not work. So what do pictures of objects tell us about what those objects afford? This is a very complex question with no answer as yet, because no one to my knowledge has looked. Gibson (1979) struggled with this question; he acknowledged that there is something important here, took an initial swing at an analysis and left it there. If anyone knows of anyone who has picked this problem up properly, I would love to know. It's an important question and would help provide an ecological way into accounting for what's going on in, say, the sentence-picture verification task. We discuss this briefly in our recent Frontier paper - there is as yet no account of what information a picture of an object might contain about that object's affordances and no one relying on picture of objects has ever done the necessary work. It would be exciting to see, because it would impact many lines of research (I'm looking at you too, fMRI). SummaryPictures of objects do not afford the same things as the objects themselves. Two things that are not the same thing are, it turns out, not the same thing, and if you want to study affordances it's time to front up to this indisputable fact of the matter. Mon-Williams, M. & Bingham, G.P. (2011). Discovering affordances that determine the spatial structure of reach-to-grasp movements. Experimental Brain Research, 211(1), 145-160. Pecher, D., de Klerk, R., Klever, L., Post, S., van Reenen, J., & Vonk, M. (2013). The role of affordances for working memory for objects Journal of Cognitive Psychology, 25 (1), 107-118 DOI: 10.1080/204... 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Pecher, D., de Klerk, R., Klever, L., Post, S., van Reenen, J., & Vonk, M. (2013) The role of affordances for working memory for objects. Journal of Cognitive Psychology, 25(1), 107-118. DOI: 10.1080/20445911.2012.750324
- February 12, 2013
- 05:11 AM
- 49 views
'Embodied Cognition Is Not What You Think It Is' - the paper!
by Andrew Wilson in Notes from Two Scientific Psychologists
Whoops, we did it again - a paper based on the blog! This time we are in press at Frontiers in Psychology, in a Research Topic on embodied cognition, with a paper we somehow got away with calling 'Embodied Cognition is Not What You Think It Is'. This paper draws from a lot of posts on the blog on embodied cognition, perception-action and language. We have used this opportunity to tackle some key issues head on, and we like this paper a lot :) We cover all the important issues and we set up what we think is the way forwards for embodied cognitive science. In addition, it sets up the ground work that we want to build on with our own Research Topic on Radical Embodied Cognitive Neuroscience. We've laid out what we think is the task facing the brain; this is what the brain is engaging with, and so this is what we think neuroscience needs to work with in order to understand what the brain is doing.It's the kind of paper that will either land with a splash or vanish without trace. We want it to make some serious waves, and we're hoping that we can encourage people to publish free Commentaries on it at Frontiers, to challenge us or pick up our challenges, and, most fun for all, to come work with us to take all this forwards! We want this to be the basis of an empirical research programme and we want you all to work with us on it :) At the very least, feel free to pepper us with questions; this paper is the start of something for us, not the end and we're interested in the response to this paper to frame the next step.The paper We begin the paper by introducing our argument that embodied cognition is unavoidably a more radical hypothesis than a lot of people think. As soon as you allow things other than the brain to be central players in cognition, it changes the game entirely, and cognitive science will have to change to match. Embodied cognition explanations will replace traditional cognitive ones. We lay out what we think are the four key questions truly embodied cognition research must tackle:What is the task to be solved?What are the resources that the organism has access to in order to solve the task?How can these resources be assembled so as to solve the task? Does the organism, in fact, use these resources?We then review research in the robotics and animal literature (based in part on some of the great examples in Barrett, 2011) that establishes that truly embodied solutions are viable alternatives to traditional cognitive explanations. After that we look at the outfielder problem and the dynamical system's model of the A-not-B error (Thelen et al, 2001) as examples of research that follows this research programme with great success. We finish this section with a contrast; we look at research we don't think is really about embodiment (specifically, Eerland et al, 2011 and Miles et al, 2010) and describe why we think this. It's exciting to have this critique published, as a counterpoint to the papers themselves.We initially ended the paper there, but the reviewers pushed us to take this analysis further to make the paper more than just a review. So we went 'balls out' (to quote Reviewer 3 :) and included Sabrina's work on a non-representational account of language. We talk about linguistic information and its parallels to perceptual information, and take our first swing at the key question, how does linguistic information get it's meaning? We round this out with a critique of two 'embodied' attempts to understand language comprehension, the action-sentence compatibility effect (e.g. Glenberg & Kaschak, 2002) and the sentence-picture verification task (e.g. Stanfield & Zwann, 2001).We wrap up with a shoutout to Clever Hans and Oskar Pfungst which Sabrina is inordinately proud of :) Thanks to Frontiers for helping us out with costs, and thanks to our reviewers who gave us a fair ride and pushed us into adding the language section; it really makes this paper kick a lot of ass. Thanks also to the editors, Dermot Lynott, Louise Connell & Judith Holler for hosting the topic and accepting our feisty abstract. And thanks to all our readers on the blog who have asked us annoying questions and guided us in interesting directions as we attempt to pull all these threads together. Now go download the open access paper , tweet about it, tell everyone you know - at the very least our alt metrics will look exciting! Wilson, A., & Golonka, S. (2013). Embodied Cognition is Not What you Think it is Frontiers in Psychology, 4 DOI: 10.3389/fpsyg.2013.00058... Read more »
Wilson, A., & Golonka, S. (2013) Embodied Cognition is Not What you Think it is. Frontiers in Psychology. DOI: 10.3389/fpsyg.2013.00058
- February 8, 2013
- 06:26 AM
- 174 views
Learning the affordances for maximum distance throwing
by Andrew Wilson in Notes from Two Scientific Psychologists
Over the last couple of posts, I have reviewed data that shows people can perceive which object they can, in fact, throw the farthest ahead of time by hefting the object. Both the size and the weight of the object affect people's judgements and the distance thrown; however, only weight affects the dynamics of throwing (release angle and velocity are unaffected by changes in size). This rules out the smart perceptual mechanism proposed by Bingham et al (1989), which proposed that both size and weight changes affect hefting and throwing the same way. So how are people perceiving this affordance? What does the affordance space look like? Zhu & Bingham (2010) investigated two options; smart mechanism and function learning.First, they took advantage of the fact that their previous work (Zhu & Bingham, 2008) had measured the shape of the affordance property to be learned. Figure 1 is from that paper, and shows how distance travelled varies as you vary size and weight (for actual throws; this needs some simulation work too). This function is the affordance and is what people need to learn if they want to be able to perceive the affordance for any given size/weight combination. Figure 1. Distance thrown as a function of the ball's size and weight (Zhu & Bingham, 2008) There are two basic ways to come to 'know' the shape of this function. First. there might a smart mechanism at work (just not the one Bingham et al suggested). If there is a single variable whose value specifies the distance thrown for any given combination of size and weight, and if this variable is created by both hefting and throwing, a smart mechanism could latch onto this variable during learning. The second option is function learning, a more common cognitive approach. in which people perceive size, weight and distance thrown (i.e. knowledge of results) separately and learn the function that relates them together. The idea is that each time you throw, you are sampling from this function. You get a size, a weight, and a distance for that size-weight combination. Over time you experience a variety of sizes and weights and resulting distances, and you extrapolate the function that relates them (like regression analysis; it's curve fitting to data). Then, when you're given a novel size-weight combination, you look up this function and generate an estimate for the distance it will travel, allowing you to pick the object that will go the farthest. (If you're familiar with the motor control literature, this is how Richard Schmidt proposes we form schemas and generalised motor programmes). Figure 1, however, tells us that in this case, the function to be learned is actually quite complicated. Size and weight make independent contributions to distance thrown, so you would need an extensive sample across a wide variety in order to learn the function. A smart mechanism, however, would only need to sample the space in a manner that produced enough variation in distance to be detected and guide the process of differentiating the relevant information variable. The two accounts therefore make different predictions about the consequences of training with limited sets of objects, and Zhu & Bingham (2010) therefore tested the two ideas by training people with different object sets.The ExperimentEveryone (4 groups of 8 novice throwers; all except one happened to be female, but this has more to do with the fact that girls don't get encouraged to throw a lot) were asked to do the hefting task and select the objects they thought they could throw the farthest. They then threw all the objects. They were then trained in one of four experimental conditions: Constant size (7.62cm diameter)Constant weight (69g)Constant density (size and weight varied to preserve a density of 0.3g/cm3)Constant density with vision of the throw obscured during training (no knowledge of results)Training was extensive and took place over a month; they were then retested on their throwing and affordance perception using all the balls. The predictions were Function learning: each group would only be able to accurately judge throwability to a maximum distance within their training set. So the Constant Size group would have learned the function relating that size with variations in weight to distance, and so would only be able to generalise within that size range because the function changes for different sizes. Similar for the Constant Weight and Density groups.Smart mechanism: each group would have experienced enough variation in resulting distance to be able to attune to the relevant information variable that specifies the affordance property mapped in Figure 1. They would therefore be able to perceive the affordance accurately throughout the space (e.g. the Constant Size group would be able to do it even for objects of different sizes).If visual information about distance travelled is required to learn the affordance, the final group will not improve at the hefting task even if their throwing improves.The results were straightforward:Prior to training, all participants were poor at judging throwability to a maximum distance via hefting. They were also poor at throwing ( on average they could muster no more than 9.6m, compared to the typical 29m seen in Zhu & Bingham, 2008). During training, all four groups improved their distances to about the same extent. There was variation in the overall averages, but different groups threw balls of different average weights which affects distance. When Zhu & Bingham compared performance on the ball weights the four groups threw in common, performance was statistically identical.After training, all three groups that had visual feedback about their thrown distances during training could perceive the affordance for novel objects via hefting. Their judgments became more reliable and mapped more closely to the balls they actually threw the farthest in post-test. The Constant Density group with No Vision remained unable to reliably judge throwability to a maximum distance, despite equivalent improvements in throwing ability. They only began to improve at the very end, when they repeated the hefting task after having thrown all the balls with vision, but they remained more variable than the other Constant De... Read more »
Zhu, Q., & Bingham, G. (2010) Learning to perceive the affordance for long-distance throwing: Smart mechanism or function learning?. Journal of Experimental Psychology: Human Perception and Performance, 36(4), 862-875. DOI: 10.1037/a0018738
- January 24, 2013
- 05:30 AM
- 110 views
Is hefting to perceive the affordance for throwing a smart perceptual mechanism?
by Andrew Wilson in Notes from Two Scientific Psychologists
In the last post, I reviewed Geoff's first paper looking at whether people can perceive the affordance for throwing an object to a maximum distance and a first swing at identifying the information specifying the affordance. People can perceive the affordance. Bingham et al then identified an invariant relation between the timing of the motions of the wrist and elbow when people hefted the balls they chose as optimal for throwing, and showed that this kinematic pattern specified a peak in the function which determined how much kinetic energy was transferred to the ball. They suggested that this relation in the joint movements served as information for the dynamic property which led to a maximum distance throw, and that this is how hefting was able to provide information about throwing. They suggested that this was a smart perceptual mechanism for perceiving the affordance property. That was where things stood until Zhu & Bingham (2008) ran an extensive replication and extension of the original study, to test the specific smart perceptual mechanism proposed by Bingham et al (1989). Experiment 1: Replicating Bingham et al, 1989This experiment had ten people first heft then throw objects to a maximum distance. There were 6 object sizes covering the full range of graspable objects (1-6in). Within each size there were 8 weights. The exact weights differed (see Zhu & Bingham, 2008, Table 1) because of limitations in the materials used; but within each size each weight increase was 1.55 times the previous weight. This constant geometric progression preserved the relational structure of the weight distribution within each size. Participants hefted weights in increasing order within each size and ranked their top three choices for throwing to a maximum distance. The weighted average of the selected weights provides an estimate of the actual preferred weight for that size, overcoming the fact that there were only a finite number of actual options, samples from a continuous relation. In a separate session, all the participants threw all of the objects as far as they could three times in a random order. Participants all threw with varying ability and picked different weights within each size, mostly explained by variations in the size of the participant. However, they all showed the same pattern as Bingham et al 1989; they picked heavier weights for larger sizes, and threw their preferred objects the farthest. To compare people, Zhu and Bingham rescaled the selected weights as a function of the preferred weight (to get everyone on the same scale) and plotted the distance thrown (Figure 1)Figure 1. The distance thrown as a function of ball size and weight (scaled by preferred weight))For each size, follow the line along the rescaled weight dimension. There is a peak distance for each combination, and that peak is projected down onto the floor of the plot. 0 on the rescaled weight axis corresponds to the preferred object and the line is arranged around the preferred object weight. As in the previous study, people can heft objects and perceive the affordance for throwing to a maximum distance. Experiment 2: What if you heft with something other than your hand?Bingham et al 1989 suggested that people choose heavier weights as size increases to offset the size-induced increased in stiffness about the wrist, which would in turn preserve the timing between the elbow and wrist movement that optimised the flow of kinetic energy along the arm to the projectile. This, they suggested, was the smart perceptual mechanism people were employing to perceive a throwing affordance via hefting. If this is the case, then hefting without involving the wrist would interfere with this perception, even though both size and weight were being perceived. Two groups of participants therefore hefted the balls with either their elbow or their feet. They could see the size and feel the weight; but could they perceive the affordance? The answer is not really; their judgements were much more variable and they systematically selected objects that were too heavyFigure 2. Left: Mean selected weights using the hand (diamonds), elbow (squares) and foot (triangles). Right: Standard deviations of these judgmentsExperiment 3: Hefting with your foot to throw with your footThe smart perceptual mechanism being investigated suggests that people can use hefting-by-hand to perceive throwing affordances because the dynamics (specifically, the optimal way to transmit force) of the two tasks overlap. This isn't the case for the elbow or the foot; but can people select objects they can throw with their foot the farthest if they heft with their feet? The answer is no, not really. People's judgments were fairly random, and people did not typically throw their preferred objects the farthest. This presumably would get better with practice, but in general Experiments 2 & 3 together suggest that the perception of the throwing affordance relies on the overlap between hefting with the hand and throwing with the hand, because that's how we typically interact with the dynamics of projectile motion.Experiment 4: Do size and weight both matter for achieving maximum distance?The specific smart perceptual mechanism proposed by Bingham et al (1989) is that both size and weight affect the dynamics of both hefting and throwing in the same way. Weight is known to affect the dynamics of throwing; as weight increases, release velocities come down. What about size?4 participants threw objects of 4 sizes, 8 weights within each size. The authors measured the release angle produced (which was, on average, a quite low 24°; the optimal angle for maximum distance given air resistance is about 36°). Zhu & Bingham then used these angles and the thrown distances for these objects from Experiment 1 in a simulation of projectile motion to estimate the release velocities (this reflects limited access to the necessary equipment, I think; our more recent work measures these release parameters directly from the high speed video footage). Once the weights reached .05kg, the release velocities decreased with increasing weight. However, neither release angle nor release velocity showed any consistent effect of size, suggesting that only weight affects the dynamics of throwing. Size has it's effect via the dynamics of projectile motion; as size (specifically, the cross sectional area)... Read more »
Zhu, Q., & Bingham, G. (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
Bingham, G., Schmidt, R., & Rosenblum, L. (1989) Hefting for a maximum distance throw: A smart perceptual mechanism. Journal of Experimental Psychology: Human Perception and Performance, 15(3), 507-528. DOI: 10.1037//0096-1523.15.3.507
- January 21, 2013
- 04:46 AM
- 73 views
Hefting for a Maximum Distance Throw
by Andrew Wilson in Notes from Two Scientific Psychologists
From the task dynamic analysis of throwing for maximum distance, we've identified the fact that for a given release angle and maximum release velocity, there is an object whose size and weight optimises the distance it will travel when thrown. Can people perceive this combination ahead of time? More specifically, can people identify the object which affords throwing to a maximum distance, and if so, how?Bingham, Schmidt & Rosenblum (1989) is the first paper investigating this question. It is a bear of a paper; I've stripped a lot of the methodological detail out in my summary so I can focus on the bigger picture. That bigger picture is this; Bingham et al first check whether people can identify objects that afford throwing to a maximum distance by hefting them ahead of time (they can). They then investigate the kinematics of hefting to identify an invariant relation in the timing of the wrist and elbow velocities and relate that invariant to the dynamics of throwing (specifically how it maximises the transfer of kinetic energy from the torso muscles to the projectile). They propose that using this invariant reflects a smart perceptual solution (Runeson, 1977) to the problem of selecting objects to throw to a maximum distance - future work (Zhu & Bingham, 2008) will actually show that this specific smart mechanism doesn't hold up, although the replacement is smart too. Perceiving object affordances for throwing Bingham et al created a set of objects varying in size and weight and asked people to heft those objects to identify, within each size, the weight they thought they could throw the farthest. You've probably done this yourself at some point; standing on a rocky shore, holding rocks until you find that one that feels just right. People found the task very natural, and chose their objects with confidence. The main result; as size increased, people preferred heavier objects. (This, by the way, looks a little like the pattern you see in the size-weight illusion, and the connection between that 'illusion' and throwing seems to not be an accident; Zhu & Bingham, 2011). Figure 1. The weight of preferred objects as a function of object sizeThey then had some of those people throw all the objects, and they measured the actual distance each object travelled. Smaller objects went further, and on average people threw the objects they preferred the farthest. They had indeed perceived the affordance for maximum distance throwing via hefting. Figure 2. Distance thrown as a function of size (I = smallest, IV = largest) and preferenceSo the initial answer to the question is 'yes'. People can choose the optimal objects ahead of time, and both their judgments and their performance depend on both the size and weight of the object (as we would expect from the task analysis). Bingham et al then explored a potential mechanism by which hefting was providing information relevant to throwing.The kinematics of hefting The data above showed that people were perceiving a relation between size and weight that was related to throwing. Specifically, they were perceiving the maximum of the size-weight-distance function. Weight (or more precisely, mass) is a dynamic property. We perceive dynamic properties via their kinematics, the motions they produce; this is the perceptual bottleneck. So people aren't detecting weight, per se, but some kinematic consequence of the size and weight of the ball during hefting that is specific to the dynamics of throwing.Maximising distance means maximising release velocity, and this means maximising the kinetic energy delivered to the projectile. Throwers generate force in their large torso muscles, but then have to transfer that energy to the projectile as efficiently and as quickly as possible. The system adopts two smart solutions. Efficiency comes from careful timing of the motions of the limbs so that the force generated by the muscles is used to accelerate lighter and lighter limbs with minimal loss, producing faster and faster movements. Speed comes from storing energy in tendons and then releasing that energy with a fast snap at the wrist (this is what tendons are for). Hefting and throwing both exhibit these kinematic properties, at least from the elbow down, and this overlap is the best place to go looking to see how hefting an object can produce information about that object's affordances for throwing. Experiments 3 and 4 therefore investigated what changing the size and weight of objects did to these wrist and elbow kinematics, looked for invariant features of these kinematics when hefting preferred objects and related that invariant to the dynamics of throwing. As object size increased, the preferred weight increased (Figure 1). Experiment 3 established that increasing object size increased the stiffness about the wrist joint by altering the amount of tendon available for prestretching and energy storage. Bouncing an object in your hand can be modeled as a harmonic mass-spring oscillator, and increases in stiffness increase the preferred frequency of such oscillators. In other words, if you just increase the object size you'll end up wanting to bounce faster and faster - you will perturb the timing of the wrist motion, which will interfere with the task of preserving the timing between the wrist and other limb segments that transfers energy efficiently. If you also increase the mass appropriately, however, you can preserve the timing over changes in object size. Perhaps hefting an optimum object produces a specific oscillation timing? If so, this invariant kinematic pattern might therefore specify throwability to a maximum distance.Experiment 4 therefore looked at how changes in object size and weight affected the timing of flexion and extension in the wrist and elbow. Changing object size altered the timing in the wrist; changing object mass altered the timing in the elbow. To preserve an invariant pattern of timing between the wrist and elbow, size and weight therefore needed to change in particular ways in relation to one another. Size and weight do vary in particular ways for preferred objects, and hefting these produced an invariant timing between the wrist and elbow. This invariant pattern is therefore a candidate to be information about the throwing affordances of the object which is available during hefting. So what dynamic property is it specifying? The goal of controlling the timing between the limb segments is to efficiently transfer energy from t... Read more »
Bingham, G., Schmidt, R., & Rosenblum, L. (1989) Hefting for a maximum distance throw: A smart perceptual mechanism. Journal of Experimental Psychology: Human Perception and Performance, 15(3), 507-528. DOI: 10.1037//0096-1523.15.3.507
- January 14, 2013
- 04:27 AM
- 114 views
Do our fingers wrinkle in the wet to improve our grip?
by Andrew Wilson in Notes from Two Scientific Psychologists
If you sit in the bath for more than 10 minutes or so, you'll notice that your fingers get wrinkled like a prune. People thought for a while that this was a local response to the wet conditions, but it turns out the wrinkling is an active, neurally controlled process. In 1936 two scientists observed a boy who had suffered some temporary damage to the median nerve; he lost feeling in his thumb, index and middle finger and, surprisingly, those fingers didn't wrinkle in the wet. There's a great post on this case and some more recent work here.Things that are under active control are usually functional; that is, they're usually doing something useful. In 2011, Mark Changizi and colleagues published a speculative piece in which they suggested that our fingers do not wrinkle randomly. Instead, they noted that the form of the wrinkles match efficient drainage networks, and suggested that perhaps the wrinkles act like rain tread to help water drain away from our fingertips when we grip things. Fingers form a 'convex promontory', like a hill. Drainage networks on hills have raised sections branching down from the highest point. These raised sections are connected to each other, and separate out troughs along the hill. Changizi et al qualitatively examined pictures of 28 wrinkled fingers and showed that this basic layout is characteristic of our wrinkly fingers too. Figure 1 (adapted from Changizi et al, 2011). On the left is a satellite photo of a natural drainage network in CA and a schematic of the drainage 'tree'; black lines are the connected raised sections. On the right is an example set of wrinkled fingertips and the comparable schematicIf this is the case, wrinkled fingers should improve our precision grip in wet conditions. Kareklas, Nettle & Smulders (2013) tested this hypothesis with a simple behavioural study. They had people pass small objects from one hand to another to move them from one box to another, and measured the total time it took to do the task. People's hands were either wrinkled or not, and the objects were either dry or in water. Figure 1. Results of Kareklas et al, 2013. Black bars are unwrinkled fingers, red bars are wrinkledAs you can see from Figure 1, finger wrinkling had no effect on the time to handle all the dry objects. For wet objects, wrinkled fingers led to a significant improvement. Wrinkled fingers aid precision gripping. (Changizi mentioned to me that he's run a similar design and found similar results; nothing published yet). Some thoughts This makes good sense and these early data are certainly positive. There's a lot still to do, though, to confirm this evolutionary hypothesis. I think a careful analysis of the form of the wrinkles and what happens to the water as the fingers compress on a wet object will answer a lot of the following questions.The authors of both papers highlight several unanswered questions that demand answers: Who else in the animal kingdom wrinkles when wet? Changizi has a picture of a wrinkly macaque but neither paper knows about any of our other relatives, or any other animals. If animals that don't grip show wrinkles, there may be more to it.Why aren't we wrinkly all the time? The authors suggest that a) there was no benefit of wrinkles with dry objects and b) there may be some costs to wrinkling - perhaps decreased sensitivity and risk of damage.What about toes? They also wrinkle, presumably for similar reasons. It remains to be seen what the functional consequences of these wrinkles are.What is the mechanism? Are the wrinkles draining water away? Are they changing some property of the skin, such as the friction coefficient? Some other things occurred to me as I read this. There must be a way to quantify the form of these drainage networks, so that you can compare them to see exactly how close to these optimal tree structures wrinkly fingertips are. You can see the basic pattern is there in Changizi's paper, but you have to squint a little. It also occurred to me that the drainage networks on hills are shaped by the flow of water over long periods of time; their characteristic form is the result of extensive wear and tear. Our fingertips are actively forming our wrinkles, so while the outcome might be similar the process is very different and this may account for why the wrinkles aren't such straight forward examples of these drainage systems. It's a fascinating hypothesis about a mundane part of our lives, and I hope someone can take this research forwards in more detail. Edit: Ed Yong, science journalist extraordinaire, got Mark Changizi into a Twitter discussion with evolutionary biologist T Ryan Gregory about a) whether these data can support an evolutionary hypothesis and b) what it would take to do so. It's a good read (they handle each other respectfully but don't pull their punches) and they end up where I am; this is intriguing but a long way from actually convincing, and there are many obvious things to do next that must get done. Onwards!Edit 2: T Ryan Gregory has posted a detailed analysis of why this sort of adaptationist thinking annoys him. As I say in his comments, I think he's right (the evidence so far is entirely incomplete and Mark does himself no favours in the way he talks as if he's already solved the problem) but I'd hate to throw out a perfectly sensible hypothesis without doing the tests he suggests. References... Read more »
Changizi, M., Weber, R., Kotecha, R., & Palazzo, J. (2011) Are Wet-Induced Wrinkled Fingers Primate Rain Treads?. Brain, Behavior and Evolution, 77(4), 286-290. DOI: 10.1159/000328223
Kareklas, K., Nettle, D., & Smulders, T. (2013) Water-induced finger wrinkles improve handling of wet objects. Biology Letters, 9(2), 20120999-20120999. DOI: 10.1098/rsbl.2012.0999
- January 3, 2013
- 05:41 AM
- 144 views
Using coordination to study learning across the lifespan
by Andrew Wilson in Notes from Two Scientific Psychologists
What happens to our ability to learn new movement skills as we age? There is surprisingly little research on this topic; a relatively recent review (Voelcker-Rehage, 2008) found only 25 articles about learning in old age, and no systematic programme of work. The answer to this question matters a lot; rehabilitation after events such as a stroke pretty much always entail (re)learning movement skills, and if our ability to learn gets worse with age, rehabilitation faces an uphill struggle. I have been studying coordinated rhythmic movement for some time now, and now we have a good handle on the task dynamic my colleagues at Indiana and I have begun using it to study the process of learning more generally. We decided to use it to look at learning in old age, to see what we could see. This project grew out of a grant I had from Remedi when I was a post-doc in Aberdeen. I wanted to use coordination to look at learning post-stroke. One of the problems with studying this is finding useful novel tasks to learn - you need to give the stroke patients something they've never done before so you can be sure that any improvement is about learning, and not simply recovery of function. My thought at the time was that I could use any changes at 180° to assess recovery and changes at 90° to assess learning. We tested a huge number of patients and age matched controls, but the project didn't pan out because neither group (all aged around 65) couldn't learn to move at 90°. The question remained, what was going on? We now have the first of three papers on this question out in press. Coats, Snapp-Childs, Wilson & Bingham (2012) trained 3 groups of people (people in their 20s, 70s and 80s) to produce a unimanual coordinated rhythmic movement at 90°. We used my coordination feedback method and had people move one joystick to control a dot on a screen to move at 0°, 90° and 180° relative to a computer controlled dot. We then trained each group to move at 90°, and we quantified both improvement (the difference between Baseline and Post Training) and learning rate (our paper is the first to look at the latter in older adults). We assessed coordination stability using the proportion of time on target, which is the average proportion of the trial spent at the target relative phase, +/- an error bandwidth of 20°. We introduced this measure to replace the more commonly used absolute error and standard deviation of relative phase measures. These numbers have a problem, namely that you cannot interpret one without the other. When people try to do, say, 90°, they often produce very stable behaviour because they are actually failing to do what you asked and have slipped into the easier 0°. If you look at the variability data, it looks like people are doing quite well. The proportion measure is a valid measure of how well people are doing what you asked them to do, and we've shown that it successfully resolves the kind of trouble the other variability measures can get you into (Snapp-Childs, Wilson & Bingham, 2011). We therefore asked three questions 1. Can older adults learn to move at 90°?The answer is 'a little'. We did see some improvement, but much less than the younger adult group.Figure 1. Performance at 90° for the three groups before and after training 2. How did the learning rates compare?We fit the proportion time on task data from each session with exponential functions. The fits were all very good, confirming that people improve quickly to begin with and then improve steadily and more slowly over the rest of training. We computed the slope of the exponential function at Baseline to quantify the learning rate. The two older groups were the same and about half the rate of the younger adults.Figure 2. Learning rate data for the three groups 3. Maybe the older adults just can't use joysticksOne problem you run into using lab tasks with older adults is that they are often not familiar with joysticks, PCs, etc. We examined the 0° and 180° data to see how the older adult performance compared at these baseline conditions. Figure 3 tells us two interesting things; first, there was no difference between the groups at 0°, suggesting they could do the basic task. Second, there was a difference between the young and older adults at 180°; the older adults were worse. This is our first clue as to why older adults are performing worse.Figure 3. 0° and 180° performance for the three groupsWhat have we learned?The advantage of this task is that we have a detailed understanding of the mechanisms that produce the various observed effects (formalised in Geoff's model; see our recent Avant paper for an overview). This theoretically motivated and empirically supported ... Read more »
Coats, R. O., Snapp-Childs, W., Wilson, A. D., & Bingham, G. P. (2012) Perceptuo-motor learning rate declines by half from 20s to 70/80s. Experimental Brain Research. DOI: 10.1007/s00221-012-3349-4
- December 6, 2012
- 05:12 AM
- 150 views
The Task Dynamics of Throwing to a Maximum Distance
by Andrew Wilson in Notes from Two Scientific Psychologists
In my last post I went over the formal concept of task dynamics as a way of analysing a task to identify the affordances in that task. This post will examine the task dynamics of projectile motion and relate these to throwing to a maximum distance.This version of the task has been studied in detail over the last few years. There is another version of the task, namely throwing to hit a target (same dynamic, different parameters, therefore same task) and we will get to that later; we're working now on data from this task.Part of my goal here is to lay out the research programme you should be following, if you want to study anything to do with perception and action. If you are interested in movement, and you aren't doing this kind of analysis as part of your work, then, I will suggest, you are doing it wrong. As we will see in future posts, this level of detail isn't just playing with numbers; a formal understanding of the underlying dynamics governing the task we are studying is utterly crucial if we want to be able to understand what people are doing, rather than simply describe their behaviour. Also it's fun :) Throwing to a maximum distance, from the point of view of physics Throwing is an example of projectile motion. The dynamics of projectile motion describe how an object moves through space after being given an initial push and then being left alone, other than the effects of gravity - no additional propulsion. That initial push can be anything (being thrown, being shot out of a gun or cannon, being hit by a baseball bat), and the resulting motion looks like this: Figure 1. The dynamics of projectile motionThe distance travelled by the projectile depends on the object size and weight, the release height, angle and velocity, drag, air density, and gravity. For a given object, maximising distance entails selecting and executing a release angle of around 36° (assuming typical air resistance values) and maximising your release velocity. A person will have a maximum release velocity that they can generate. Given this release velocity and angle, the only remaining way to affect the distance is to identify and use an object whose size and weight combination produces the maximum distance for those release parameters. For a given size, as weight increases, distance will first increase, reach a peak and and then decrease. The location of this peak will reflect the relationship between the force imparted by the release velocity and the mass to be accelerated (think about (or better, try) throwing a ping pong ball vs a golf ball, for example).For a given weight, as size increases, distance will first increase, reach a peak and and then decrease. The location of this peak will reflect the trade-off between the force imparted by the release velocity and the cross-section of the object, which creates air resistance. There is therefore a function that relates size, weight and distance in the world. Each combination of size and weight will produce a different peak distance in this function, and all combinations produce a surface with it's own peak This function maps the affordance property 'throwable to a maximum distance'.Throwing to a maximum distance, from the point of view of the organism Embodied perception-action research must always remember that it has to also analyse the task from the first person perspective of the organism (Barrett, 2011). As far as the organism is concerned, the task dynamic variables listed above can be sorted in the following way:Things to be perceived: object size, object weight Things to be controlled: release height, release velocity, release angle Things outside your control: drag, air density, gravityPerception: The perceptual question is whether people are sensitive to the size/weight/distance function; can they perceive the affordance? Specifically, given objects which vary in size and weight, can people select the one they can, in fact, throw the farthest? The answer is yes (Bingham, Schmidt & Rosenblum, 1989; Zhu & Bingham, 2008) although poor throwers require practice to be able to do so.Learning is critical.The next perceptual question is how do they perceive this affordance - what is the information? The answer is 'we don't know yet', but recent work has ruled out the inertia tensor as the dynamic property generating that information (Zhu, Shockley, Riley, Tolston & Bingham, 2012). I'll go into these papers in the next few posts. The perceptual questions in this task are therefore about perception of object affordances and how they relate to distance. People are therefore perceiving properties of the object (size and weight) measured with respect to the task demands (maximising the distance of a projectile motion throw). This can be expressed in terms of the perceptual equivalent of the real world function mapping size and weight to distance. We will therefore measure the perceptual function using action measures (see below) and relate it to the known world function.Action: Implementing a given throw requires implementing the dynamics of throwing, and coupling those dynamics to the dynamics of projectile motion. You couple two dynamical systems together by having the output of one feed into the other (and sometimes vice versa). Throwing is a one way coupling, and it is achieved by having the dynamics of throwing produce three values (release angle, release velocity and release height) which can be used as parameters on the relevant variables making up the dynamics of projectile motion. All three of these can be measured, and are action measures of the perception of the object affordances. Such measures are the 'gold standard' when measuring perception-for-action (Bingham & Pagano, 1998).To maximise distance, the release angle should be approximately 36° and the release velocity should be as high as possible. Release height varies between people but we're finding it remains fairly constant, and it doesn't currently look as if people are actively controlling it. It is therefore a frozen degree of freedom (c.f. Bernstein, 1967). People typically produce suitable angles quite quickly, and are able to do so more reliably with training. With practice, people improve distance by increasing release velocity, and (if they are allowed to see the distance the ball travels) these action improvements come hand in ha... Read more »
Runeson, S. (1977) On the possibility of "smart" perceptual mechanisms. Scandinavian Journal of Psychology, 18(1), 172-179. DOI: 10.1111/j.1467-9450.1977.tb00274.x
- November 30, 2012
- 09:18 AM
- 85 views
Task Dynamics And The Information They Create
by Andrew Wilson in Notes from Two Scientific Psychologists
Over the next weeks I want to turn my attention to a detailed account of the process by which you go about studying affordances (formalised as task dynamics) and the perception of affordances (via the kinematic consequences of those task dynamics) using throwing for maximum distances and for accuracy as the task. This post will introduce the basic research programme. Future posts will work through papers from my colleagues Qin Zhu & Geoff Bingham in order (I've done a couple already), as well as work from the animal literature because I want to find ways to use the analyses we're developing to answer questions about throwing and weight perception there. These posts will do a few things. First, it's important to be as clear as possible about what affordances are, how we might possibly perceive them and how we can do the relevant science within the ecological approach to answer those two questions. Sabrina is developing ways to apply these methodological principles to the study of language, and we have both been working on the issue of information and how it comes to have meaning for us. Being clear about how this all unfolds in the perception-action literature is vital, because this is the foundation for what comes next. Second, I'm working on some throwing data right now and I need to work through the key papers in detail anyway. Third, I'm going to be developing an undergraduate perception-action class for 2014, and this will help me develop course material by laying out the form of the analysis and getting feedback on how well it's coming across. One of my goals is to look at all my collated and edited notes and realise I've accidentally written a text book :)I'm going to talk about throwing because it's utterly fascinating. It's a complex task but it's one centred around a core dynamic (that of projectile motion) that physics has a pretty good handle on. This is letting us run detailed simulations of the task to identify the affordance structure of the task and see how throwers are operating with respect to those. Throwing entails perception of object and target affordances and the coordination of multiple body segments into precisely timed actions controlled by that perception. It also connects to all kinds of things in our evolutionary history (including, possibly, the origins of spoken language in the form we know) and our psychology (including the size-weight illusion and issues of the psychologist's fallacy). It's close to being that grail of psychology, something only humans do (other animals throw but rarely if ever for the kinds of distances and accuracy we can manage with ease). And most of all, it is endlessly interesting. The deeper I get into this, the cooler it gets. Task specific, smart solutions The ecological approach to perception and action studies tasks one at a time. Why? Because it proposes that the perception-action system solves things one at a time as well. We produce functional behaviour by temporarily assembling ourselves into smart solutions to the problems we face (Runeson, 1977). Smart solutions differ from general purpose rote solutions the way heuristics differ from algorithms; they take advantage of things which are locally true and use those as reliable shortcuts to solve particular problems, instead of trying to come up with a longer, more complex solution that can be successfully applied to multiple situations. Why do we think perception-action systems are smart? Two reasons: first, for tasks you do often that contain reliable shortcuts, smart solutions are faster, more efficient and more stable than rote solutions. These are good things. Second, it is often the only way to solve a given problem. Human bodies have a large number of redundant degrees of freedom (Bernstein, 1967), which means that we can in principle solve a given task in many different ways. The only way to reliably pick one solution is to allow yourself to be constrained by the task dynamics, because otherwise there are too many possible ways to move and we would be frozen by indecision. So you identify the task and then pick a solution. This problem also applies to the analysis of human movement - in order for a scientist to understand why we moved the way we did, we have to constrain our possible explanations to those that fit in the task dynamic or else we will never find the answer (Bingham, 1988).An example: I can, in principle, reach for my coffee in a straight line, or in a wide curve, or with my arm going behind my back. However, I typically don't, and the solution I adopt in typical cases (reaching in a straight line) is the stable one offered by the dynamics of the task at hand (things like where the objects are, etc). If those dynamics change (say an obstacle is placed in front of me) my redundant degrees of freedom provide the flexibility to produce a new solution - but this solution will again reflect the dynamics of the new task, the one which now includes an obstacle. Each solution is constrained by the dynamic properties of the part of the world I'm interacting with; these properties are the affordances of the task and so this is what it means to say actions are controlled by the perception of affordances. (By the by, Rosenbaum investigates this kind of thing in the context of his 'end-state-comfort' effect, which states that people typically plan their actions so that they end their movements in a comfortable posture. What he actually means is that their movements unfold so as to conform to the perceived underlying task dynamics, but his analysis has never taken that final, critical step into dynamics that we will here. I just realised this as I was writing and it's useful.)Task DynamicsThese facts of the matter mean that we have to be able to distinguish one task from another, and by we I mean both me the perceiving-acting organism and me the scientist studying perceiving-acting organisms. You can only do this at the level of task dynamics (Bingham, 1995) and this is why dynamical systems theory got such a foothold in this kind of work.Dynamical systems theory is a set of mathematical tools for describing how a system is put together and how that system changes state over time. The latter is dictated by the former, and therefore measuring those changes over time (the dynamics of the system) & how that dynamic responds to perturbations provides information about how the system is put together; both it's composition (what elements make up the system) and it's organisation (how those elements are arranged; I talked about this previously in the context of developing the perception-action model of coordinated rhythmic movement). Dynamics provides all the elements required to describe both the form of the change over time (the kinematics) and the forces which caused that particular motion (the kinetics). Kinematic variables include time, position and all the temporal derivatives of position (velocity, acceleration, jerk, etc). Kinetic variables are all of these as well as mass. A given dynamical... Read more »
Runeson, S. (1977) On the possibility of "smart" perceptual mechanisms. Scandinavian Journal of Psychology, 18(1), 172-179. DOI: 10.1111/j.1467-9450.1977.tb00274.x
Bingham, G. (1988) Task-specific devices and the perceptual bottleneck. Human Movement Science, 7(2-4), 225-264. DOI: 10.1016/0167-9457(88)90013-9
Jacobs, D., Runeson, S., & Michaels, C. (2001) Learning to visually perceive the relative mass of colliding balls in globally and locally constrained task ecologies. Journal of Experimental Psychology: Human Perception and Performance, 27(5), 1019-1038. DOI: 10.1037//0096-1523.27.5.1019
- November 15, 2012
- 05:36 AM
- 204 views
Psychological Science...meet me at camera 3
by Andrew Wilson in Notes from Two Scientific Psychologists
Psychological Science, I think we need to talk. I was reading this farewell from your outgoing editor, and it would all be nice enough if I hadn't also just read your latest offering to the altar of 'embodied' cognition. Frankly, it made me wonder whether you actually read all the things you publish.Robert Kail, the outgoing editor, had this to say about the ideal Psychological Science paper:...the ideal Psychological Science manuscript is difficult to define, but easily recognized — the topic is fundamental to the field, the design is elegant, and the findings are breathtaking.There are a few problems here; 'breathtaking' results have the tendency to be wrong, for example, and while I'll all for elegant design, sometimes, to make a breath taking claim, you need to run those 4 control conditions. But my main problem is less with these criteria and more with the papers that apparently meet them.I've talked a lot about 'embodied' cognition research here, work I think doesn't deserve the name and is typically full of flaws anyway. My two main examples have been how thinking about the future or the past makes you sway forward or backwards and how leaning to the left makes the Eiffel Tower seem smaller. Both of these (quite flawed) papers appeared to great fanfare in Psychological Science. In fact, quite a lot of this work appears in Psych Science, to the point where I nearly made that feature the first thing to check on an embodied cognition paper to know it's not the real deal. So I don't have a lot of confidence in the process of selection at Psych Science to begin with.This week it got even worse. Kille et al (2012) published a study where they had people sitting on wobbly chairs. They then asked people to rate the stability of some celebrity relationships, and to rate how important they felt several qualities were to a relationship, including several related to stability. People in the wobbly chair condition rated celebrity relationships as less stable than people in the non-wobbly chair condition (effect size (partial eta squared) of .15). They also preferred stability related traits in relationships more (effect size of .1). In both cases, the mean difference was about half a point on a 9 point scale. The authors argue that 'embodiment motivates mate selection preferences'.When I look to Kail's criteria, I wonder how these papers get published:Embodied cognition is a fundamental topic, but these papers aren't taking it seriously.The design was elegant, in that they showed a simple pattern of results. But there was no serious discussion of why these results should have happened. There was instead a brief note at the end that saidIndeed, we suspect that one reason cognition may become embodied is to ensure that one's needs - which may arise from physical states - are met through goal pursuit.Following this logic through, they are claiming that we have evolved to try and resolve temporary postural instability by selecting more stable mates. This makes so little sense when you spell it out, but it sounds so exciting the way they said it. I guess that's why they said it their way rather than mine.Are the findings breathtaking? Well, I did get a little breathless after reading this but not in that way Kail was intending, I don't think (unless he meant from simultaneously laughing and banging my head against the table for 20 straight minutes). But to be serious, these results are meaningless because, like all this research, there is no clear effort to establish the mechanism by which the postural manipulation and the judgement data are connected to one another. Why would a minor and easily corrected postural instability affect the important task of mate selection (or even the judgement task they are using as a proxy for mate selection)? With no clear task analysis of how this extended, embodied cognitive system is formed and why, we cannot interpret these results. Finally, this is just more 'small effect size' research, which I've previously argued is not as clever as people think it is. There's a perception in psychology that squeezing out a significant result means you ran a clever experiment and managed to defeat the complexity that is human cognition. It's actually a hint that you have asked the wrong question, I think, and I think this because when you manage to ask the right question, you go from tiny effects to unambiguous results. Small effect sizes are not compulsory for psychology; if we get better at asking our questions, we will get clearer answers.So how did this get published in Psych Science? It's a good question, and one I don't actually know the answer to. If I had to guess, I'd say it's because it's yet another sexy little result in 'embodied' cognition, and sexy sells. But sexy is hurting our discipline - these tiny, astonishing effects aren't being replicated, are probably wrong, and are, to my mind, fairly average science anyway.What about all the other papers Psych Science publishes?I pick on the 'embodied' stuff because I know what to look for. There are good papers in Psych Science. Karen Adolph, my favourite developmental psychologist, recently published some great work about the emergence of walking in infants in this journal, and I'm sure some of the other papers not in my field are good too. But my first reaction to seeing the paper wasn't 'hey Karen, great job', it was 'oh Karen, why did you waste that awesome paper on Psych Science?'. Based on interactions on Twitter I'm not the only person who has come to view what is supposed to be our flagship journal with pity and contempt, even when what it publishes is good.I'm going to guess that isn't what Kail wanted for the journal, and not what the incoming editor Eric Eich wants either. But until the journal stops publishing all this poorly conceived 'sexy' work, I will never wish Psych Science as a home for any of my papers.ReferencesAdolph, K. E., Cole, W. G., Komati, M., Garciaguirre, J. S., Badaly, D., Lingeman, J. M., Chan, G. L. Y, & Sotsky, R. B. (2012). How do you learn to walk? Thousands of steps and dozens of falls per day. Psychological Science, 23(11), 1387-1394. DownloadKille, D., Forest, A., & Wood, J. (2012). Tall, Dark, and Stable: Embodiment Motivates Mate Selection Preferences Psychological Science DOI: 10.1177/0956797612457392... Read more »
Kille, D., Forest, A., & Wood, J. (2012) Tall, Dark, and Stable: Embodiment Motivates Mate Selection Preferences. Psychological Science. DOI: 10.1177/0956797612457392
- November 9, 2012
- 09:19 AM
- 179 views
How do we perceive which objects afford throwing the farthest?
by Andrew Wilson in Notes from Two Scientific Psychologists
Previous work has established that people with throwing experience can perceive the affordance of 'throwability'. If you let these people heft objects with a range of sizes and weights, they will confidently select the one they think they can throw the farthest, and they tend to be correct. It's a very natural task, one you have probably done yourself on a beach or lakeside looking for stones to throw into the water. This is only the first, and relatively easy step in any ecological task analysis. Once you've identified an affordance property and established that people are sensitive to it, you need to identify the information supporting this perception. For throwing, this has not been done, and while the paper I'm reviewing here doesn't solve the problem, it does rule out a highly likely contender for the source of the information that has implications for a lot of other research. Previous research (Zhu & Bingham, 2011) had identified that the objects people select to throw all feel equally heavy, regardless of size. This suggests that people are using the felt heaviness of the objects to judge throwability. 'Felt heaviness' is a function of both size and weight, and produces the size-weight illusion where larger objects must be heavier to feel equally heavy. Zhu & Bingham (2011) gave people balls of different size and weight and, for each size, had people judge which weight they could throw the farthest. They then used one of these objects as the comparison object, and asked people to find which larger ball felt equally heavy from the other size sets. People chose the ball within each set that they had also judged to be maximally throwable. Across sizes, balls that afford maximum distance throwing feel like they are equally heavy; the size weight illusion is not an illusion, it's about throwing.So how do we perceive heaviness? It's not simply weight, size matters; so the question really is, what property of the object are we perceiving when we judge heaviness? The best suggestion in the literature comes from research on dynamic touch, which suggests that the proprioceptive perception of heaviness is not about the object property 'weight', it's about the object property rotational inertia. There is a wealth of evidence that judgments of heaviness vary with this property, which is the resistance the object offers to being moved in a rotational movement (say, flexing your arm at your elbow; see Amazeen & Turvey, 1996). So we now have a couple of pieces; can we tie them together? People seem to be using felt heaviness to judge which objects they prefer to throw. Felt heaviness seems to be about the rotational inertia of the object. Zhu, Shockley, Riley, Tolston & Bingham (2012) therefore tested the hypothesis that the key property of the object driving the perception of the affordance for throwing is rotational inertia. The authors had competent throwers hold balls in their hands that varied in size, weight and rotational inertia. The latter is manipulated by varying the way the mass of the ball is distributed; shifting more of the mass off centre away from the axis of rotation increases the rotational inertia (i.e. makes it harder to rotate). People then hefted the objects by moving their wrists up and down while holding the ball. After hefting a range of weights and inertias within a given size, people judged which object they thought afforded throwing to a maximum distance. Then, people went through the size sets again. This time, they looked for a ball that felt equally heavy to a comparison object, which, unknown to them, happened to be the ball for that size they had previously judged to be maximally throwable. The question was this: what objects did they pick, and what properties did these objects all have in common - size, weight, or inertia? Figure 1. Judgments sorted by object size and weightZhu et al looked at the data two ways. The first (Figure 1) was to sort the data by size and weight. There are three basic results. First, people chose the same objects for both the heaviness and throwability task, replicating the previous result. Second, people chose a heavier object for the larger size. Third, which objects people picked in either task were not affected by changes in rotational inertia (contradicting Amazeen & Turvey, 1996 and the work following on from that paper). Figure 2. Judgments sorted by size and rotational inertiaFigure 2 shows the rotational inertias of the selected objects. Remember, these objects were judged as equally heavy and all affording throws to a maximum distance. However, the rotational inertias varied, and varied differently for the differently sized objects.The overall pattern of results is that 1) perceived heaviness is the basis of the judgments of throwability but 2) rotational inertia is not the basis of perceived heaviness or throwability. Without knowing the property being perceived, we can't (yet) begin to identify the information about that property. The hunt continues! Failure to replicate Amazeen & Turvey (1996) The fact that rotational inertia is not the property underpinning perception of throwability is surprising, but that's how things go. What's more interesting is that rotational inertia, for the first time, was not the property underpinning perception of heaviness. Why did this otherwise robust result not replicate here? The main difference is in the objects used. Previous work typically has people wielding long, weighted rods over varying inertia. The resulting inertias (and variation in inertias) are quite large. In contrast, hefting these spheres, all graspable in a hand, produces a small range of smaller inertias. Geoff has suggested to me that the most likely explanation is that the inertias of these spheres is below threshold (although no one has ever done any psychophysics on dynamic touch to establish what the thresholds for rotational inertia are). The consequence of this result is that because of this threshold issue, rotational inertia can't be the property people are perceiving in this task, and, contrary to previous claims, it can't be the property that explains all perception of heaviness. Summary People can heft objects and perceive the affordance property throwability. Until ... Read more »
Zhu, Q., Shockley, K., Riley, M., Tolston, M., & Bingham, G. (2012) Felt heaviness is used to perceive the affordance for throwing but rotational inertia does not affect either. Experimental Brain Research. DOI: 10.1007/s00221-012-3301-7
- October 24, 2012
- 09:10 AM
- 241 views
Giving children with movement problems a leg up with robots
by Andrew Wilson in Notes from Two Scientific Psychologists
Developmental coordination disorder (DCD) is a surprisingly common problem; it's thought that 6-8% of school aged children are diagnosable. DCD is a motor disorder, where children have great difficulty in producing skilled actions, especially anything requiring fine motor control. Handwriting, tying your shoelaces, sports of any kind are all huge problems for these children. One key question about DCD is why does it occur. Part of the problem in answering this is that it is a behavioural diagnosis; you get diagnosed if you have severe motor impairments that aren't a known side effect of something else. Regardless, there are two basic ways in which children might end up with such problems; crudely, they might have difficulties in producing movements, or they might have difficulty learning movements. My colleague and author on this paper, Mark Mon-Williams, uses the analogy that children with DCD may be bad drivers of perfectly working cars or good drivers of malfunctioning cars. It's obviously a little messier than that, but this is the essential idea, and the answer has implications for the kind of interventions you'll try and design.When I post-doc'd with Mark, I did research with children with DCD and was peripherally involved in the pilot testing of the robots used in this paper. I made a prediction at the time: I bet that children with DCD are bad drivers and don't have a learning problem. I based this on two observations. First, occupational therapists do succeed in helping these children learn skills the children want to learn, such as riding a bike. It's hard, it takes time, but it's doable. Second, in our experiments I saw that the children were moving poorly, but always in a manner that made perfect sense if you assumed they were producing movements that matched their skill level. One study asked children to reach and grasp and turn a dowelling, and the task was set up that you could sometimes choose to make an initially difficult reach in order to end up with a comfortable end posture after the turn. The children with DCD almost always chose to do the first movement as easily as possible, and just suck up the costs later on (van Swieten et al, 2010). They weren't planning ahead for the turn part, as skilled reachers do; they were just coping with having to make a reach first. This always struck me as evidence that children with DCD were learning just fine; but what they were learning, without help, was to make the best of their not very good action systems. The question is - can we help them to do better? Therapy works but it's time consuming and costly and there aren't enough hours in the day, let alone occupational therapists in the health service. One increasingly common solution is robots; have them provide assistance and let the therapist run a room with 20 of them at a time. The pilot work I mentioned had tested a robotic system and a game to practice fine motor control of the hand, and we'd shown that the idea was sound and that the kids were motivated to stick with it. The remaining question - what do you get the children to do? Snapp-Childs, Mon-Williams & Bingham (2012) had 8 children with DCD (aged 7-8) play a simple video game using a Phantom Omni force feedback robot. The game had the children use the stylus to control a fish on the screen, and move it around a three-dimensional track in a race with a computer controlled fish. The track, via the robot, exerted a 'magnetic pull' on the children's hand; if you started to move off the track, the robot would pull you back onto it. This magnetic effect helps keep you on the path, and, importantly, the strength of the pull can be varied systematically to provide more or less assistance.Figure 1. (A) Example of display and target path. (B) The Phantom together with the display.They then varied the amount of magnetic pull until they found a level of assistance at which the children with DCD were performing just as well as the typically developing controls. At Baseline, they measured performance across a range of assistance levels from this comparable level to very little assistance. The two measures were how long it took to complete the path and the normalised path length (where anything greater than 1 suggests time spent off the target path). Predictably, the children with DCD got worse faster than the controls (white symbols in Figure 2).Training started at the level of assistance where performance was equal across the groups, and the children worked their way up through three levels of task difficulty (speed of the competitor fish, length of the path, and level of magnetic attraction). The difficulty was increased when the child had won 2 races in a row, and training took place in up to 5 sessions, each separated by a week. They then repeated the Baseline assessment at Post-Training (filled symbols in Figure 2). Figure 2. Duration (a) and normalised path length (b) data. Level 1 of 'attraction' is the most assistance, 8 the leastThe results were straight-forward. The children with DCD started out getting hit hard as the magnetic help went away. Over time, they learned to successfully produce fast and accurate tracings of the tracks without that assistance. Why does this work? To learn a new motor skill, you have to first be able to produce something that's in the ballpark. Only then can you start to fine tune the movement, making it more efficient and stable. Even newborn babies don't start as blank slates; they come equipped with a repertoire of spontaneous movements that serve as a foot in the door of this problem. Children with DCD seem to have problems with this initial step; they produce unstable and therefore highly variable movements to begin with, and there's not enough 'signal' in amongst the 'noise' for a learning process to hone in on. The robot helps them through this initial Catch-22, by helping them produce stable and repeatable movements. What's important is that the children with DCD can then capitalise on this help and learn enough to not need the help all the time. This suggests that children with DCD do not have a learning problem.An important part of this study was the ability to carefully step the task difficulty up by reducing the amount of assistance over time. This meant that the children were continually asked to actively pick up more and more of the responsibility and not simply come to depend on the robot. In addition, the task required the children to always actively produce their own movements; the robot never simply dragged them around the track. The active production of movements is an important part of creating an action a learning system can tune in to (Bingham, 1988 + a wide literature on active vs passive training, including an upcoming follow-up from this research group). SummaryI like this work; I get a kick out of having been right in my prediction and this is basically the study I wanted to run sometime. My only beef is that Geoff... Read more »
Snapp-Childs, W., Mon-Williams, M., & Bingham, G. (2012) A Sensorimotor Approach to the Training of Manual Actions in Children With Developmental Coordination Disorder. Journal of Child Neurology. DOI: 10.1177/0883073812461945
- October 16, 2012
- 07:12 AM
- 267 views
Why does linguisitic information mean what it does?
by Andrew Wilson in Notes from Two Scientific Psychologists
Sabrina has been working on a series of posts on an ecological analysis of language (here, here and here, plus more on the way). Her focus has been on the nature of the information for language, and the similarities and differences this information has with the information for perception. We're working some of this analysis into a paper, and writing that got me thinking about this in a little more detail.Our main move on language is to reject the assumption that language is a qualitatively different kind of task than perception & action. The goal is to find ways to talk about these behaviours using the same basic analysis tools. Part of that is to draw the analogy to how perceptual information gets its meaning and use that to describe how linguistic information gets its meaning. What I want to do here is just map this analogy out a little, because I ended up in an interesting place and I want feedback from people who know more than us on this about whether this is just plain crazy. In particular, if you know anything about the relationship between neural dynamics and the dynamics of speech, we think this is going to be relevant!How perceptual information gets its meaningWhen we talk about meaning, we're asking how an organism can come to learn what an information variable is information about. Perceptual information is about the underlying dynamics of the event that created the information.What I mean by this is that events in the world can be distinguished and identified only in terms of the dynamics. A dynamical description is one that describes how something changes over time, and includes reference to the underlying forces that caused that change. A fly ball is baseball looks and acts the way it does because it is an example of the projectile motion dynamic. The dynamical equation describing projectile motion events includes terms for the size and mass of the object, the initial speed and angle, gravity, drag and air resistance, and you can use this description to plot out exactly how the position of the ball changes over time.A dynamical event such as a fly ball creates information by interacting with, say, light; but this information is only kinematic, not dynamic. A kinematic description of an event is one that describes how something changes over time, but without reference to the underlying forces. In practical terms, this means that you can use variables like time, position, velocity and the other temporal derivatives of position but you can use variables that include mass or force. The visual perceptual information for a dynamical event is therefore a pattern in the optic array that can be described in terms of things changing over time.It turns out that it is possible for a kinematic pattern to specify a dynamic property. What this means is that the dynamical event creates one and only one kinematic pattern as it unfolds over time. If this is the case, detecting the kinematic pattern is equivalent to perceiving the dynamic event, and this is the mechanism for direct perception of the world.Information is all we have access to, and you never get to peek behind the curtain to check what the dynamics are up to. So in order to learn what a given kinematic pattern means, you have to use that pattern to control some action. If that pattern lets you, say, intercept a fly ball, then that pattern comes to mean the catchable-ness of the ball (the affordance). In other words, perceptual information comes to mean the dynamics of the event that created the kinematic pattern.How linguistic information gets its meaning (the analogy)Linguistic information is also created by a dynamic event, but a much more complicated one. Take speech (but the idea works just as well for writing and gesture). The information that is created is kinematic patterns in the acoustic array. These patterns are caused by the underlying dynamics of articulation (how the lips, tongue and vocal cords change over time). However, and this is a big however, linguistic information does not come to mean the dynamics of articulation. When you detect a pattern in the acoustic array, you don't perceive that your conversation partner's throat is up to - you perceive the meaning of the word that was produced.Remember, the goal is to apply the analysis of how perceptual information gets its meaning to how linguistic information gets its meaning; but we've run into a mismatch. My solution is to remember that the dynamical system producing speech is actually much more than just the articulators. A critical player in speech is the brain, and one of the main reasons the articulators move the way they do is that this is what happens when you couple the neural dynamics of language to an articulation system.The crazy notion that emerges from this analysis is that linguistic information comes to mean the dynamics of the broader system, the dynamical system formed by the coupling of language related neural dynamics to an articulation system. This means the analogy holds (the kinematic information is about an underlying dynamical event in the world).Initial problemsFor perception, events such as projectile motion have the dynamics they do because of physic (see Turvey, Shaw Reed and Mace, 1981 for the details of this analysis). The dynamics of projectile motion is simply how you describe how an object changes it's state over time when it has been fired off with an initial speed and angle and then left to do it's thing. This is not true for language. Why do the neural dynamics have the form they do? One crude answer from applying the analogy is that they are like this because that's how you describe what an extensively trained nervous system changes it's state over time when it's producing that sentence rather than another. Obviously this isn't all that satisfactory, but it's all I have just now. So this analogy only gets us so far; but it does push the ecological analysis quite a long way into the problem, which I like.The coupling between neural and articulation dynamicsThere is apparently a bit of a literature on this (thanks Tom Hartley and Jon Brock for links). The debate in the literature right now seems to be about whether syllables can be described as oscillators. If they can be, then you can start to talk about things like coupling and entrainment between syllable production and the underlying neural oscillations you can measure in speech production. This recent paper in Frontiers in Language Sciences by Fred Cummins is skeptical but only because he thinks the syllable is the wrong place to look, I think; importantly it has links to all the key papers on this topic.We'll get into that literature at some point, but at this point I'm still trying to come to grips with this analysis and whether this literature f... Read more »
Cummins, F. (2012) Oscillators and Syllables: A Cautionary Note. Frontiers in Psychology. DOI: 10.3389/fpsyg.2012.00364
Turvey, M. T., Shaw, R. E., Reed, E. S., . (1981) Ecological laws of perceiving and acting: In reply to Fodor and Pylyshyn (1981). Cognition, 9(3), 237-304. DOI: 10.1016/0010-0277(81)90002-0
- October 5, 2012
- 06:13 AM
- 245 views
A Way Forward on Specification
by Andrew Wilson in Notes from Two Scientific Psychologists
It's been a while since we've blogged; it's been a crazy summer and we've been insanely busy, but things are settling back down. We have a lot planned for the blog, there's much work to be done on a variety of topics in perception, action, embodied cognition and language. First I want to get back on track with my specification project, so that maybe this can start to move forward.*****************************I've been reviewing work that has been undermining the concept of specification in perception. Specification is the idea that the information we detect and use to control our behaviour maps 1:1 with some action-relevant property in the world, and the idea that this is even possible is one of Gibson's key contributions to psychology. Rob Withagen, along with Tony Chemero (hence W&C) have reason to believe that specification is actually too high a bar, and that individual variation in perceptual ability makes it likely that different people will use different, often non-specifying information to solve the same task. This variation is highly likely to be present, because that's kind of how evolution works, and they cite various studies (in collision judgements and dynamic touch) that seem to empirically confirm that this variation exists and the fact that it doesn't go away with fairly extensive practice. Ecological psychologists insist on specification for a reason: the idea of direct perception seems to require it. Direct perception is Gibson's hypothesis that we perceive the world directly in terms of our ability to act on it, without needing internal mental gymnastics to figure out what is going on. Turvey, Shaw, Reed and Mace (1981) proposed that, in order for this to work, perceptual information had to be generated by lawful processes that produced one and only one information variable per property of the world, and that perception required the organism to detect that one variable. Anything less, and it's not clear how the organism can count on having detected the right property in the world without some internal states tracking probabilities and correlations. Withagen and Chemero think that a) evolution demands a less strict policy for perception to work, b) that there is individual variation, that c) this all shows that specification, while possible, is not required for perception (no 1:1 between world and optics or between the optics and perceiver) but that d) perception can still be direct, just on a continuum - the organism has varying degrees of successful contact with properties in the world, rather than the all-or-none contact implied by the Turvey et al analysis. In one respect, they are throwing out the baby and the bathwater but claiming this still lets them have their cake and eat it too. It's exciting if true, but while I think the fact of individual variation needs to be addressed, I'm not yet convinced by the data or the theory and I think there's more to do. Here are some initial thoughts in that direction.These thoughts are designed to lead to real science, and if you want in, let us know. Sabrina and I are very interested in the basic question of how information gets it's meaning - Sabrina's language analyses, for example, depend critically on being able to find a way to have ecological style information in a domain where specification can't possibly work. I've been chatting to Tony and Rob about this work and I'm keen to collaborate: but Sabrina and I are interested in developing broad collaborations to go after this stuff from as many angles as possible, including neuroscientifically. The goal here is to develop and propose grants and experiments - we'll worry about access to equipment later, let's first figure out what we need.We also want this to bring ecological researchers together, not be yet another schism. Rob suggested in an email that I simply put all this in a paper and we could argue back and forth in the literature. I may yet write that paper, just for the record, but I think we can cut through the "talking past each other" bit much faster here on this blog. I would much rather just crack on with a research programme that involves multiple labs all pulling in the same direction for a change. Some reflections on the evidence so farMy first thought is that the evolutionary story is intriguing, but not that convincing. I found the paper (Withagen & Chemero, 2009) to be full of speculation and vague generalised claims about when picking up information would be hard. I think the biological emphasis is a good idea, but exactly none of this can be resolved one way or the other without data. This data has to come from specific, well characterised tasks; there are no 'in general' solutions here. A task could easily involve numerous 'non-specifying variables' but none of them might be stable enough to challenge the specifying variable for attention, for example. You can only do this in particular, one task at a time (Bingham, 1988).In addition, while the idea of individual variation in perceptual capabilities is probably correct, it's important to remember that the back end of the perceptual learning system is the brain. We ecological types tend to ignore the brain, but Sabrina and I are working on getting it back in the game, on our terms. The central nervous system is, I think, our fast response system - the part of us that operates on a millisecond time scale and can support the kind of flexibility our slow-to-change bodies require to survive. This kind of high dimensional system offers all kinds of potential to bypass the two problems W&C think we face: individual variation is only a problem if the different systems can't perform the same function. But there is plenty of evidence for extreme degeneracy in nervous systems - many different 'wirings' can produce the same function (the humble lobster gut can produce one particular critical rhythm with any of 450,000 different nervous systems; Prinz, Bucher & Marder, 2001)sub-optimal solutions (local minima in a task solution space) are most easily avoided by high-dimensional systems, ones with room to manoeuvre. This is a standard trick in neural network programming - adding functionality (dimensions) to the network's capabilities creates ways out of minima, because those minima might only exist to trap behaviour in the lower dimensional network.Whatever the science is that tackles this question, it will have to include neuroscience. Hell, maybe one of the reasons to have a nervous system this flexible is so that perception via specification can work!There is, of course, data to support the evolutionary analysis - work on individual variation in collision judgements and dynamic touch, which Withagen and Chemero cite heavily. My second thought is the same as the first: the empirical case is intriguing, but not that convincing, and, in the case of the dynamic touch work, entirely off topic.... Read more »
Prinz, A., Bucher, D., & Marder, E. (2004) Similar network activity from disparate circuit parameters. Nature Neuroscience, 7(12), 1345-1352. DOI: 10.1038/nn1352
- August 17, 2012
- 05:38 AM
- 169 views
The Small Effect Size Effect - Why Do We Put Up With Small Effects?
by Andrew Wilson in Notes from Two Scientific Psychologists
Small effects sometimes matter - but psychology can do betterOne of the things that bugs me about 'embodied' cognition research is that the effects, while statistically significant, tend to be small. What this means is that the groups were indeed different in the direction the authors claim, but only slightly, and that the authors had enough people showing the effect to make it come out on average. The problem with small effect sizes is that they mean all you've done is nudge the system. The embodied nervous system is exquisitely sensitive to variations in the flow of information it is interacting with, and it's not clear to me that merely nudging such a system is all that great an achievement. What's really impressive is when you properly break it - If you can alter the information in a task and simply make it so that the task becomes impossible for an organism, then you have found something that the system considers really important. The reverse is also true, of course - if you find the right way to present the information the system needs, then performance should become trivially easy. Psychology has become enthralled by statistical significance (to the point that we're possibly gaming the system in order to cross this magical marker). If your effect comes with a p value of less than .05, it is interesting, regardless of how small the effect is in terms of function. This is a problem, and we don't have to put up with it. If you ask a question about the right thing, you should get an unambiguous answer. If your answer is ambiguous, you may not be asking about the right thing. I want to remind readers of a couple of examples of nuisance small effects I've covered here before, then talk a little about some work which either broke or fixed the right thing, to highlight that we don't actually have to suffer from the tyranny of the small effect effect. Small effects in 'embodied' cognitionRegular readers will know we have a low opinion of most of the research that calls itself 'embodied cognition'. My two main examples of this work are 'moving through time' (Miles et al, 2010) and 'leaning to the left' (Eerland et al, 2011). Not only are they good examples of what my field spotter's guide is designed to find, they also suffer from the small effect effect. Miles et al (2010): The authors measured postural sway while people thought about either the future or the past. People's sway was slightly more forwards in the future condition, and slightly more back in the past condition. Miles et al interpreted this as the effect of metaphors about time, which are grounded in things like forward and back motion. The problem is that the significant effect on sway peaked at approximately 2mm in each direction. In terms of posture, this is meaningless. Eerland et al (2011): The authors made people lean either left or right, and then had them estimate the magnitude of a wide range of things that people would not know the actual size for, but would know the ball park size (such as the Eiffel Tower). Leaning to the left reduced estimates of size by a z score of about .08 relative to being upright. Leaning to the right had no effect. The authors interpreted this as showing how access to the mental representation of magnitude (thought to be like a number line) can be primed by posture - a state of the body affects access to a mental state. The main problem here is not only the tiny overall effect and lack of effect to the right, but the fact that out of 39 items only 25 show a difference in the right direction between left and right items, and only 9 show the right overall ordering of left leaning < upright < right leaning. This is the rule, not the exception, in 'embodied' cognition, and is a hint that they aren't really tapping anything interesting. The small effect effect vs. GibsonOne other great example of this problem that I've covered before comes from Gehringer & Engel (1986). They set out to test an ecological analysis of the Ames Room which suggests that people will come to resolve the ambiguous nature of the room if they are allowed to explore. They allowed people progressively more opportunity to move around, and had them judge the relative size of two discs, one in each corner. In the worst case, people erred by about 21mm (out of a possible 30mm error); in the best case (lots of exploration) the error was reduced to 2.6mm, which was of course statistically different from zero error. Gibson, they concluded, was wrong, and direct perception should be thrown out. Of course, a 2.6mm error in a size matching judgement task is actually not a bad effort at all, and Sverker Runeson (1988) proceeded to tear this paper a new one with the kind of keen analysis that makes him my favourite perceptual psychophysicist. The point here is that the authors pointed to their statistical significance and tried to conclude that Gibson's entire theory was flawed, when they had actually almost entirely eradicated the Ames room illusion by letting people move around. Way to miss the real story, chaps.Small ape effects I reviewed a paper here recently about tool use in chimps, and how they are (contrary to what is apparently a heated argument in the literature) able to use weight to distinguish between objects. One of the interesting things about this paper is that the group level effect was often small, and (in Expt 2) not seen in any individual ape! My interest in this work is that I think it would benefit from a proper analysis of the affordances chimps perceive, rather than assumptions about the role of weight. I think that if you did this, you should end up with huge, unambiguous effects like the ones I'm about to describe for context.What it looks like when you break the right thingFor a given visually guided action, the perception-action approach suggests that there is an invariant feature of the optic array which a) specifies the property of the world required to make the action function correctly and b) has to be present for the action to work. In coordinated rhythmic movement, that information is the relative direction of motion, which specifies relative phase. After training at 90°, people use something else, and Geoff Bingham & I wanted to know what it was. It could only be one of three things: relative speed, relative frequency, or relative position, so we designed displays that preserved relative phase (the property in the world) but broke one (and only one) of each of these potential information variables at a time. Relative to unperturbed performance, all the perturbatio... Read more »
Eerland, A., Guadalupe, T., & Zwaan, R. (2011) Leaning to the Left Makes the Eiffel Tower Seem Smaller: Posture-Modulated Estimation. Psychological Science, 22(12), 1511-1514. DOI: 10.1177/0956797611420731
Gehringer, W., & Engel, E. (1986) Effect of ecological viewing conditions on the Ames' distorted room illusion. Journal of Experimental Psychology: Human Perception and Performance, 12(2), 181-185. DOI: 10.1037//0096-1523.12.2.181
Lee YL, & Bingham GP. (2010) Large perspective changes yield perception of metric shape that allows accurate feedforward reaches-to-grasp and it persists after the optic flow has stopped!. Experimental brain research, 204(4), 559-73. PMID: 20563715
Miles, L., Nind, L., Macrae, C. (2010) Moving Through Time. Psychological Science, 21(2), 222-223. DOI: 10.1177/0956797609359333
Runeson, S. (1988) The distorted room illusion, equivalent configurations, and the specificity of static optic arrays. Journal of Experimental Psychology: Human Perception and Performance, 14(2), 295-304. DOI: 10.1037//0096-1523.14.2.295
Wilson, A. D., & Bingham, G. P. (2008) Identifying the information for the visual perception of relative phase. Perception , 70(3), 465-476. DOI: 10.3758/PP.70.3.465
- July 20, 2012
- 08:58 AM
- 367 views
Cracking the Tough Nut of Chimp Tool Use
by Andrew Wilson in Notes from Two Scientific Psychologists
A paper just out in PLoSOne reports that chimpanzees, given some experience and enough of a weight difference, prefer to use heavier hammer stones when cracking hard nuts. This is apparently quite exciting: this is the first study to isolate weight as a property relevant to the task of cracking open a nut. This caught my attention because weight is not actually the only key property that determines nut cracking success. A heavy hammer is great, but it will eventually become too heavy to lift, and for a given size stone there may very well be an optimum weight (similar to how people choose very specific combinations of size and weight when asked to throw objects to a maximum distance; Zhu & Bingham, 2011). In the current experiment, when the only difference between the objects was weight, the chimpanzees often went to the heaviest stone because it took the fewest strikes and least time to crack the nut. But is this just an artefact of the current experiment? And if so, can an ecological approach find ways to find out just how chimps choose their tools?The experimentThere were three experiments, all with the same 6 chimpanzees. One key feature to remember, therefore, is that over the course of the study the chimps all had a lot of practice at this task - this is very interesting and reflected in the data.Experiment 1 used roughly cube shaped hammer stones (6cm x 8cm x 6cm) that weighed 300g, 600g or 1200g. The weight was evenly distributed throughout the objects. The chimps were asked to choose a stone and crack a nut, and were allowed to switch stones if they wanted to. Two of the chimps exhibited a preference for a hammer; Loi preferred the heavy one and Zamba preferred the light one. There was no preference on average, however. All the hammers could successfully crack a nut: when used, however, the heaviest hammer took fewer strikes and less time than the others to crack the nut. There was very little switching around between hammers, however. The cuboid was awkward to hold (hint one that weight is not the only key factor). To crack a nut the chimps had to align a flat side with the anvil stone and could therefore misalign the hammer, wasting a strike. In the next two experiments the hammer stones were replaced with 7cm spheres of the same, evenly distributed weights.Experiment 2 showed an overall group preference for the heaviest object, although no individual chimp showed this preference significantly. Experiment 3 increased the weight range (to 200g, 800g and 1400g) and found a stronger preference for the heaviest hammer; 4 of the 6 chimps showed the effect and would often switch away from the lighter hammers if they picked one up first.Over time, with practice and a wide range of weights, 4 of the chimps learned to use weight to identify the most efficient hammer stone from the set available. What to do next?There are many things to try next, if you are prepared to think about this task ecologically and measure some more interesting things. AffordancesFirst, weight was clearly not the only relevant property. In Experiment 1, the number of strikes and time to crack the nut did not decrease as a linear function of weight - the middle weight was problematic.Number of hits and time to crack the nut as a function of hammer weightChanging to the spherical object cleaned this up - so clearly size and shape matter. Part of makes a good hammer stone is how graspable it is by the chimps. So the first thing to do is to vary the maximum object extent (Mon-Williams & Bingham, 2011) and to do so relative to hand span. You could also add handles, etc. You can also vary size and weight independently within a shape - do chimps learn preferences for specific combinations, as humans do in throwing? What about other properties of the hammer stone? Is it rigid and strong enough? (There's evidence of apes using different stones for different nuts in the wild, for example). All of this manipulates the affordances of the hammer, specifically how moveable it is (Shockley, Carello & Turvey, 2004) and how easy it is to wield as a hammer. Exactly which properties of the hammer the chimps are tuning into is an empirical question, and the current study has limited their search space artificially. By letting them explore a set of hammers with a controlled but wide set of potential properties, we could identify what the chimps are actually perceiving.Information Once we know what they are perceiving, we can ask how are they perceiving it - this means studying information. This, unfortunately, is complicated in haptic perception. Research has demonstrated that when we wield objects, the dynamic property we perceive is not mass or size per se, but the resistance of the object to being moved - it's inertia. The description of the objects inertia in 3D space is called the inertia tensor and the perception of object properties via this tensor is called dynamic touch (Turvey, 1996).The problem is that, while we're pretty sure the inertia tensor is the dynamic property being perceived, we do not know how this is specified in the kinematics (motion) of the haptic system (I mentioned this problem when discussing Withagen's work on non-specifying variables). It's a real obstacle; however, there are still plenty of experiments you can run to show that it is, indeed, the inertia that is the key affordance property, and not the weight. For example, the weight in the hammers in the current study was evenly distributed throughout the objects. This means that the inertia tensor is symmetric (the object resists being moved equally in all directions; think about a tennis ball). To see if behaviour follows the inertia tensor and not simply mass, you need to decouple these properties by changing the distribution of mass throughout the object (think about a tennis racquet). You then let the chimps interact with the objects and see what happens (well, it's a little more complicated than that but this is the basic idea).There are also ways to present visual information about inertia; by setting the object in motion, there is visual information that reflects the underlying dynamic of the mass distribution, for example. Again, non-trivial to do with apes, but the principles are there to be adapted.... Read more »
Schrauf, C, Call, J, Fuwa, K, & Hirata, S. (2012) Do Chimpanzees Use Weight to Select Hammer Tools?. PLoSOne, 7(7). DOI: 10.1371/journal.pone.0041044
- July 6, 2012
- 10:08 AM
- 319 views
Evolution vs.Specification (Specification V)
by Andrew Wilson in Notes from Two Scientific Psychologists
One of Gibson's key contributions was to reveal that it was possible for the optic array to specify a meaningful property of the world. Gibson insisted that specification existed between the world and optics (each property produced one unambiguous pattern, and thus the mapping is 1:1). Specification, said Gibson, meant direct perception was possible, because picking up that one variable meant perceiving the one property that caused it. Turvey, Shaw, Reed & Mace (1981) formalised this idea by describing how ecological laws governed which properties of the world could be specified and identifying that these laws allowed affordances into this set. Turvey et al (hence TSM, because Reed changed his mind later on) then insisted that, in order for perception to be direct, specification also had to exist between the optics and the perceiver; an organism should only use one variable per property, and thus the mapping from world to perceiver is 1:1:1. This is a very high bar, and was put in place to defend ecological psychology from the Establishment attack (Fodor & Pylyshyn, 1981).Withagen & Chemero (2009) think that the 1:1:1 account is incompatible with evolutionary thinking, and they aren't hot on the 1:1 account either. Specifically, they think that any given species will show individual variation in it's members ability to use information, and that in many cases species will end up using sub-optimal solutions (two important elements of evolutionary thinking). The1:1:1 bar, they say, is implausibly high and a naturalised theory of perception (one that is compatible with evolution) will instead predict the common use of non-specifying information. They also claim that this does not stop perception from being direct, so long as you allow 'directness' to live along a continuum.I think there are some important issues here, but I think this paper's presentation is problematic. It contains no analysis of any particular information or task, and instead is full of sentences such as 'it seems more plausible to us that' and 'it is possible that'. This comes off as the kind of woolly evolutionary thinking psychology is rightly scolded for. Gibson and TSM spent a lot of time trying to make us pay less attention to what might be and more to what is.My concerns are mostly along these lines, and once I get them off my chest I want to turn in future posts to some ideas for a research programme to pursue this all in more detail.Problem for TSM #1: Individual variation in information useEvolution implies variability within populations. For perception, W&C claim that this implies that different members of a population will probably use different information variables to solve the same task. W&C note that the TSM account insists that all members use the same information: the specifying information. These ideas are incompatible, evolution is bigger, therefore TSM lose; ...given the myriad functions of perception and their different degrees of importance to the survival and reproduction of the animal, it is quite improbable that there is minimal variation in what information is exploited...Withagen & Chemero, 2009, p. 373.They then go on to cite the various studies that demonstrate individual variation. This, for me, is where I discover this paper has thrown the baby out with the bath water. W&C want to ground ecological psychology in biology, not physics (as TSM do in the 'laws' paper). But they've missed what TSM gained for the field; a method for actually answering this question for specific tasks. One of their key points was that not just any old property ended up structuring light, only properties that can be directly involved in the process of ecological optics (so 'shoeness' no, 'walk-on-ability' yes). Not all information is equal, either: some is available for extended periods of time, some only briefly. The amount of individual variation will therefore actually depend mostly on what information is available. The first place to go looking for the causes of variation, therefore, is in the ecological optics analysis of the invariants created by a given event, and this is where TSM shine. In addition, while individual variation is interesting, you can only interpret it in the context of an ecological optics analysis.This means that the TSM research programme of identifying the local physical environment/event and the properties of that environment/event that are being projected into light is still worth pursuing. It also means considering the spatial and temporal stability of the resulting invariants as well as their relationship to the property in question in order to predict and understand individual variation and actual information use.Take collisions: not everyone finds the variable that specifies the mass ratio, relative velocity change. First, mass ratio is an odd property to want to know about and is not clearly related to the control of action. Second, relative velocity change is really only available around the time of the collision. Exit speed and scatter angle,however, are available for extended periods after the collision (and sometimes correlate to the odd property mass ratio, making the whole thing quite complicated from the first person perspective of the organism). The fact that organisms can fail to find the short lived specifying invariant in the collision task is interesting, but a key part of the explanation is still likely to be in the dynamics of the information itself (and, perhaps, variation in thresholds on the part of the organism). So there is a lot of work left to do here before these experiments live up to their hype from W&C.(One side note here, though: I do think individual variation will show up in interesting places. Conditions such as schizophrenia, autism, developmental coordination disorder, and others are very commonly associated with perceptual deficits or difficulties. Perhaps this is the place to go looking for variation and for seeing what the consequences of genuinely poor perceptual performance is? Perhaps the effects are unlikely to be subtle?)Problem for TSM #2: Sub-optimal solutionsW&C talk about the fact the biological systems do not always evolve the optimal solution to a task. Evolution is full of hacks and weird features that reflect the fact that it is a process that can only build on what it has available at the time. A given species cannot simply acquire a required feature unless the potential for that feature is within the range of the variability in the population. Given that this is such a ubiquitous feature of biology, W&C suggest we should also expect to see it in perception.This may be partly true, but I think there is a key difference here. Humans will not suddenly acquire wings because of the limited variation in our body plans doesn't allow it. Our anatomy is too stable. Of course, this stability is not true throughout the body; our central nervous systems, for example, are extraordinarily flexible and only hold their 'shape' while the information flowing through them remains the same. Change the information, change the shape (the way tools are swiftly integrated into the brain's information about the body). One thing our brains therefore provide us with is the ability to very swiftly alter the capabilities of the 'back end' of all perceptual systems; this, in fact, is what most researchers think of when they talking about perceptual learning. So, in perception, we might actually have access to the kind of flexibility we need to dodge the evolutionary trap of the ... Read more »
Turvey, M. T., Shaw, R. E., Reed, E. S., . (1981) Ecological laws of perceiving and acting: In reply to Fodor and Pylyshyn (1981). Cognition, 9(3), 237-304. DOI: 10.1016/0010-0277(81)90002-0
Withagen, R., & Chemero, A. (2009) Naturalizing Perception: Developing the Gibsonian Approach to Perception along Evolutionary Lines. Theory , 19(3), 363-389. DOI: 10.1177/0959354309104159
Withagen, R., & van der Kamp, J. (2010) Towards a new ecological conception of perceptual information: Lessons from a developmental systems perspective. Human Movement Science, 29(1), 149-163. DOI: 10.1016/j.humov.2009.09.003
- June 23, 2012
- 09:08 AM
- 232 views
Individual Variation in the Use of Perceptual Information (Specification IV)
by Andrew Wilson in Notes from Two Scientific Psychologists
If it is the case that perception requires the use of specifying variables, then there should be no individual variation in what information variables people use. However, as we've already seen, such variation exists: the dynamics of a collision event produces multiple kinematic patterns in the optic array, and people judging the mass ratio of colliding balls use all of these, only one of which actually specifies which ball is heavier. Even with training, people do not always find the specifying variable. This is an example of how the mapping between a property in the world (mass ratio) and the optic array can be one-to-many, with consequences for perception. Figure 1 on this post shows us that there is another mapping to investigate, namely the one from a perceptual array to the organism. Can this mapping also be one-to-many? Withagen & van Wermeskerken (2009) suggest that it can, and that again training does not necessarily help.Dynamic touch and the perception of lengthVarious papers had identified individual variation in which information variable people used at any given moment in time (e.g. Jacobs et al, 2000, 2001) but most studies use small n's and average over participants. Withagen & van Wermeskerken (2009) trained 25 people to judge the length of rods they were wielding and examined the individual learning trajectories to get a sense of just how varied individuals are.The task was length perception by dynamic touch (Turvey, 1996); you present someone with a rod and ask them to hold one end and move the other around, without looking. Experiments using this task suggest we perceive properties such as length via the inertia tensor, which describes the rod's resistance to motion in each dimension. Withagen & van Wermeskerken (2009) had participants wield unseen rods and estimate the maximum reachable distance by winding a surface on a rail out the judged distance. As per Jacobs et al (2000, 2001) the data were expressed as correlations between judged length and the length predicted by each of three candidate variables based in the inertia tensor. The invariant was the ratio M/m, where M is the 1st moment and m is the 0th moment of mass distribution. The two non-specifying variables were the first and third moments (I1 and I3) of the inertia tensor separately. Participants were tested 7 times (Baseline, then after each training set) using rods where I1 and I3 were poorly correlated with length while the ratio always specified the length. People were trained, however, on sets of rods where the non-specifying variables had moderate correlations to the length. The test set enabled the authors to disentangle use of the three variables, while the training sets simulate the fact that, in the world, there are often several competing variables with moderate correlations (or so the authors claim).The results showed wide variation; 5 participants eventually settled on the invariant, 10 started using a non-specifying variable and never switched, and the remaining 10 responded to the feedback but never settled. Participants therefore varied in whether, when and how they responded to the feedback. Withagen & van Wermeskerken (2009) claim that this is evidence that individuals vary in their ability to learn information, as well as in which information they end up using (as might be expected from an evolutionary point of view, if learning capacity is a trait with variation acted on by natural selection; Withagen & Chemero, 2009 and the next post in this series).Comments on the task; it's not ideal. The 'information' variables they test are all dynamic quantities, i.e. they all involve mass. While the inertia tensor does seem to be the dynamic world variable being perceived in these tasks, rather than length per se, there is as yet no kinematic specification of this dynamic entity. Perception trades in kinematic variables, not dynamic ones; this is the perceptual bottleneck. The actual information has not yet been identified, and Withagen & van Wermeskerken are therefore confusing the world with information about the world. Behaviour varies with respect to the information for a property, not the property itself and performance must therefore be evaluated against the information (e.g. coordinated rhythmic movement is organised with respect to relative direction of motion, not relative phase). Without knowing what the information for the inertia tensor is, we cannot yet interpret people's behaviour with respect to it. Part of the variation in learning may simply be an artifact of their training; people only got feedback when judging rods where I1 and I3 had fairly good correlations to actual length. People may only have made small or rare errors, not enough to drive a search for better information. People are very sensitive to the scope of their learning context (Jacobs et al, 2001 and the previous post).Small errors in judged distance might also not be noticed because the feedback required participants to watch where they moved the curtain and see how that matched where they had moved the surface to. The rods were 30-121cm long, making this a non-trivial judgment in and of itself.These problems aside, Withagen & van Wermeskerken did show wide variation in performance; people were clearly not simply doing the same thing (perceiving the specifying variable) using identical perceptual systems. However, given the problems, this paper is very weak evidence about the use of non-specifying information which works against the author's slightly grandiose claims to the contrary. The empirical case supporting the perception of non-specifying variables remains interesting but far from convincing.ReferencesTurvey, M. T. (1996). Dynamic touch. American Psychologist, 51(11), 1134-1152. DownloadWithagen, R., & van Wermeskerken, M. (2009). Individual differences in learning to perceive length by dynamic touch: Evidence for variation in perceptual learning capacities Perception & Psychophysics, 71 (1), 64-75 DOI: 10.3758/APP.71.1.64... Read more »
Withagen, R., & van Wermeskerken, M. (2009) Individual differences in learning to perceive length by dynamic touch: Evidence for variation in perceptual learning capacities. Perception , 71(1), 64-75. DOI: 10.3758/APP.71.1.64
- June 15, 2012
- 08:55 AM
- 344 views
Non-Specifying Variables in the Perception of Collisions (Specification III)
by Andrew Wilson in Notes from Two Scientific Psychologists
Part of Withagen's critique of specification and whether it's necessary to underpin direct perception is a brief review of some empirical literature that shows people using non-specifying variables. I want to spend a few posts reviewing these, because all good potentially sensible ideas need data to confirm whether they're right or not.First up, the perception of relative mass after a collision. Events in the world are dynamic, that is, they involve motion caused by a pattern of underlying forces. Perceptual systems want access to the underlying dynamics of events, because this is the level at which the event is defined (Wilson & Bingham, 2001). However, perceptual systems can only detect kinematics, that is, motion - this is the perceptual bottleneck (Bingham, 1988 and this note on dynamics and kinematics). We can only perceive the underlying dynamics of an event, according to the ecological approach, if we can detect motion that is specific to that dynamic. Runeson coined the phrase kinematic specification of dynamics (Runeson & Frykholm, 1983) and investigated whether there were such kinematic patterns and whether we can detect them. Working with Claire Michaels and David Jacobs, he has also investigated the use of non-specifying variables.Runeson uses judgments of relative mass as an exemplar task. He simulates a collision between two moving balls of varying mass; their behaviour after the collision reflects which one is heavier. There are several kinematic variables available after the collision, including exit speed and scatter angle (the angle between the ball's original and new trajectory). These do not specify relative mass, and how they correlate with it depends on details of the collision. They often feature in cognitive models of judgements in this task, acting as cues refined by heuristics (eg Gilden & Proffitt, 1989).Runeson & Vedeler (1993; Runeson, 1995) identified a kinematic variable that specifies the mass ratio: the relative amount of velocity change. They then demonstrated that participants used this invariant rather than any of the cue-heuristic approaches. One issue with this study was the fact that all the observers had at least one experiment's worth of experience with the task, and Jacobs, Michaels & Runeson (2000) therefore investigated whether there was any perceptual learning in the task that might be causing different labs to find different information being used.8 naive observers performed baseline and post-training judgements of mass ratio, with extensive training in between (288 trials split over 4 blocks and two days). Participants improved with training (their judgements became more accurate and less variable); the question was then, what had changed to support this learning?Jacobs et al correlated the judgements people generated for each collision with the answers each of 5 possible variables would predict; the invariant 'relative amount of velocity change', (INV), exit speed difference (ESD), scatter angle difference (SAD), exit speed and angle differences combined (ESA) and a heuristic model from Gilden & Proffitt (1989; HM). They looked at these correlations in each block of trials (1=baseline, 2-5 = training, 6 = post training), and the results are in Figure 1.Figure 1. Correlations between judgments and various sources of information about the mass ratio, for each observer across all sessions (Figure 5 from Jacobs et al, 2000)The first thing to note are the individual differences; each observer starts out most likely relying of different information (e.g. Observers 2 & 4 both begin using exit speed). Most of the other observers, are using either the invariant or the linear combination of exit speed and angle (ESA); part of the problem here is that these variables are themselves highly correlated (r=.93) and thus it's not possible to disentangle them from these data (but see below). The second thing to note is that with practice, most of the observers were producing judgements with high correlations to the specifying invariant. Finally, the heuristic model rarely outperformed the other variables. We therefore have evidence of different people using different variables to judge the same event, and most of these variables did not specify the dynamic property being judged. With training, however, people tended to switch and begin to rely on the invariant (or a non-specifying variable that happened, for these collisions, to correlate highly with the invariant). De-correlating the candidate variables Jacobs, Runeson & Michaels (2001) ran a follow up study to cope with the problem that ESA and the invariant were highly (.93) correlated. There simply may not have been enough instability in performance controlled by ESA to drive further exploration of the space for better information, so Jacobs et al created some.Experiment 1 tested baseline performance using the collisions from Jacobs et al (2000), then trained people with collisions from one of two sets. The global constraint set were collisions where the correlations corresponded to the set of all possible collisions, and the local constraint set were collisions from a limited set where all the variables specified the mass ratio. Participants in the global constraint group replicated Jacobs et al, and all changed variable use to either the invariant or ESA (which correlated at .89 here). Participants in the local constraint group never changed variable - whatever they began using, they stuck with. They therefore ended up using different (but in their experience, equally effective) information variables and didn't find the actual invariant.Experiment 2 then trained people on sets of collisions in which the non-specifying information variables either did not vary over collisions between balls of different masses (no variation) or had no correlation to the actual mass ratios (zero correlation). A random condition randomised the precollision velocities and the various non-specifying kinematic variables had intermediate correlations with the actual mass ratio. In the no variation group, most observers came to find the invariant during training, but interestingly often switched back to, say, exit speed in the post-test when there was useful variation and correlation for this variable again. They therefore haven't come to rely on the invariant, although they had come to detect it. The zero correlation training group stopped using non-specifying variables during training where they were not informative about mass ratio but didn't always succeed in finding the invariant; if not, their performance simply remained poor throughout. As in Experiment 1 and Jacobs et al, the random group often didn't find the invariant because the non-specifying variables correlated fairly well with mass ratio.Finally, Experiment 3a trained people in a zero correlation condition where only one alternative (either exit speed or scatter angle) had zero correlation with mass ratio. This meant each collision set had the invariant and one other fairly good (.75) information source. The speed zero correlation group all stopped using exit speed and mostly found the invariant; the angle zero correlation group weren't using scat... Read more »
Jacobs, D., Michaels, C., & Runeson, S. (2000) Learning to perceive the relative mass of colliding balls: The effects of ratio scaling and feedback. Perception , 62(7), 1332-1340. DOI: 10.3758/BF03212135
Jacobs, D., Runeson, S., & Michaels, C. (2001) Learning to visually perceive the relative mass of colliding balls in globally and locally constrained task ecologies. Journal of Experimental Psychology: Human Perception and Performance, 27(5), 1019-1038. DOI: 10.1037//0096-1523.27.5.1019
- June 10, 2012
- 05:36 AM
- 327 views
How Information Gets Its Meaning (Specification II)
by Andrew Wilson in Notes from Two Scientific Psychologists
Gibson proposed that specification was required in order for perceptual information to have meaning that was tied to the world in a manner an organism could use. The concept of specification has been placed back under the microscope by recent theoretical and empirical work. Here I want to briefly summarise the theoretical argument put forth by Withagen & van der Kamp (2010), who worry that specification places too strong a constraint on what a perceiving-acting organism might find informative. They suggest that (visual) perception can still be direct with non-specifying patterns, if you stop thinking information is in the relation between the environment and the optic array but rather, in the relation between the optic array and the organism. They propose this because recent empirical work suggests that organisms can happily get around using non-specifying variables; they want to keep directness, however and they don't think Chemero's solution to the problem does the trick. I'll review the studies they cite over the next few posts; first, let's lay out the solutions they propose.Again, I want to emphasise that this is very much a work in progress for me. I'm using these posts to come to grips with the arguments, and I don't yet endorse any of these various critiques. My goal is simply to have a clear understanding of what everyone says, so that we can evaluate those claims later on when I review some data. How information gets its meaning I: Gibson (well, Turvey, Shaw & Mace, anyway)For Gibson and those who followed shortly after, most prominently Turvey, Shaw, Reed & Mace, (1981), specification was critical for a theory of direct perception to succeed. The idea is this: there are properties of the environment to which organisms need to be sensitive. These properties interact with energy such as light and created patterns in structured arrays of energy which can be detected by an organism. The pattern then provides information about the properties if and only if the property caused the pattern by a lawful process that guarantees the two are uniquely related to each other. Specification guarantees that pattern is informative, because of the Shaw's symmetry principle:We can represent the symmetry principle as follows. Let E = ‘‘The environment is the way it is,’’ I = ‘‘The information is the way it is,’’ and P = ‘‘Perception is the way it is.’’ Also, let ‘‘>’’ stand for the logical relation of adjunction, a nontransitive conjunction that we can read as ‘‘specifies.’’ Then, the symmetry principle is[(E > I) & (I > P)] & [(P > I) & (I > E)].In English, this says: ‘‘That the environment is the way it is specifies that information is the way it is and that information is the way it is specifies that perception is the way it is, and that perception is the way it is specifies that the information is the way it is and that information is the way it is specifies that the environment is the way it is.’’ We can simplify this to say that the environment specifies the information, which specifies perception, and perception specifies the information, which specifies the environment. This principle is symmetrical in that the environment, information, and perception determine one another. This, on the Turvey-Shaw-Mace view, is what it is for perception to be direct.Chemero, 2009, p. 111The environmental property is projected as a pattern into light according to the laws of ecological optics. By virtue of this lawful basis, picking up the pattern simply is perceiving the environment because the symmetry principle underwrites a legitimate path back to the environment. This principle is critical, Turvey et al argue, because only it can establish a direct path along which information about things in the world can flow to the organism. The whole system depends on specification, however, so losing specification means losing this path.How information gets its meaning II: Chemero & situation semanticsI've reviewed Chemero's suggestion here; he takes the situation semantics of Barwise & Perry and uses that to underpin the relationship between the world, the pattern and the organism, instead of the lawful basis of the symmetry principle. This removes the need for specification and thus the symmetry principle, and I suggested in my post that this really is a problem. Withagen & van der Kamp (2010) think so to and summarise it very effectively:Arguing that variables that correlate with an environmental property can also carry information about it, Chemero cannot explain the object of perception solely in terms of the variable that is detected....After all, a pattern in the array can correlate with and thus carry information about many environmental properties. For example, because of constraints (i.e., the laws of mechanics) the above-mentioned variable M correlates with the length, the weight, and perhaps even with the color of rods. So what determines that a participant perceives the length of the rod and not its color when detecting this variable?Withagen & van der Kemp, 2010, pg, 7, emphasis addedThis is the cost Chemero incurs by abandoning symmetry; the mapping between pattern and environment is no longer 1:1. He needs another process to constrain the meaning of the pattern to one rather than another property of the world, and if this is internal then we're back with representational, indirect theories of perception. Withagen & van der Kamp still want directness but don't want specification. They attempt to solve this problem by appeal to Oyama's relational theory of information from developmental systems biology (Oyama, 1985, 2000). How information gets its meaning III: Withagen, van der Kamp and developmental systems theory Developmental systems theory is the idea (Oyama, 1985, 2000) that the form of an organism is the result of a developmental process in which multiple factors participate, rather than being specified by, for example, the genome (another classic in the literature is D'Arcy Wentworth Thompson's 1917 book On Growth and Form). In this context, Oyama defines (genetic) information relationally. That is, patterns in a genome (genes) cannot be described as containing information until they take part in a developmental process. Only then can what that a gene means (it's informational content) be revealed, and that meaning will vary with the process in which it takes part. The analogy for Gibsonian information is to stop calling the pattern in the optic array information, and instead simply think of it as just a structure. It should only be thought of as containing information when it takes part in a specific process and is placed in a particular relation (i.e. when it is perceived by a particular organism engaged in a particular task). The informational content, i.e what the pattern means, is then defined by the specifics of the relation. The details of the act of perception constrains the meaning of the pattern, making it information.On this view of information, a given pattern in an array can mean different things to different organisms, or to the same organism at different times. The empirical work I'll review next claims to show that this sort of thing can occur. What an organism perceives at any given time, on this account, is a function of the relation between the pattern detected and that current exploratory behaviour: this, Withagen & van der Kamp claim, is enough to reduce the mapping between pattern and environment back to 1:1. ComparisonEveryone into direct perception agrees that properties of the world interact with energy arrays to create... Read more »
Turvey, M. T., Shaw, R. E., Reed, E. S., . (1981) Ecological laws of perceiving and acting: In reply to Fodor and Pylyshyn (1981). Cognition, 9(3), 237-304. DOI: 10.1016/0010-0277(81)90002-0
Withagen, R., & van der Kamp, J. (2010) Towards a new ecological conception of perceptual information: Lessons from a developmental systems perspective. Human Movement Science, 29(1), 149-163. DOI: 10.1016/j.humov.2009.09.003
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