The Evolution of Sex Differences in Throwing

One of the most robust sex differences occurs in throwing. Men can throw (on average) much faster and therefore much farther than women, and this gap even exists at comparable levels of sports such as baseball and softball. The most common explanations are that a) men are, on average, larger and stronger than women, and b) most cultures gender throwing activities as male, leading to earlier acquisition and much more practice. YouTube has plenty of videos of men throwing with their off hand that point to the critical role of learning. 

However, Lombardo & Deaner (2018; L&D) have just published a hypothesis that while these factors are at play, they rest on top of an underlying biological advantage and that 'throwing is a male adaptation'. Specifically, they claim that there has been greater selective evolutionary pressure on men (as compared to women) to develop the strength, skills and anatomy needed to throw for large distances and great accuracy. Men have evolved to be better throwers than women.

This post will briefly review the hypothesis and the evidence, and then come to two conclusions. First, many of the differences they discuss seem quite closely aligned to the cultural sex differences around throwing that we know exist and so may not be biologically innate. Second, and more importantly, there may not even be a throwing-specific sex difference to explain. Right now, the only clear finding is that men throw faster; but they are also (on average) stronger and larger for non-throwing reasons. There is, as yet, no clear evidence that men are better throwers. I will then review some recent data of my own that suggests when the full perception-action task dynamic is analysed in closer detail, trained women show every sign of being equally skilled throwers as trained men.

Affordance Maps and the Geometry of Solution Spaces

I study throwing for two basic reasons. One, it is intrinsically fascinating and I want to know how it works. Second, it's become a rich domain in which to study affordances, and it is really forcing me to engage in great detail with the specifics of what these are.

My approach to affordances is that they are dynamical properties of tasks, which means that in order to study them, I need to be able to characterise my task dynamics in great detail. I developed an analysis (Wilson et al, 2016) to do this, and I also have a hunch this analysis will fit perfectly with the motor abundance analyses like UCM (Wilson, Zhu & Bingham, in press). I have recently discovered that another research group (led by Dagmar Sternad) has been doing this whole package for a few years, which is exciting news. Here I just want to briefly summarise the analysis and what the future might hold for this work.

What Limits the Accuracy of Human Throwing?

Throwing a projectile in order to hit a target requires you to produce one lot of the set of release parameters that result in a hit; release angle, velocity (speed and direction) and height (relative to the target). My paper last year on the affordances of targets quantified these sets using a task dynamical analysis.

There is one additional constraint; these release parameters have to occur during a very short launch window. This window is the part of the hand's trajectory during which the ball must be released in order to intercept the target. It is very easy to release slightly too late (for example) and drill the projectile into the ground.

How large is this launch window? It is surprisingly, terrifyingly small; Calvin (1983) and Chowdhary & Challis (1999) have suggested it is on the order of 1ms. Those papers used a sensitivity analysis on simulated trajectories to show that accuracy is extremely sensitive to timing errors and this millisecond level precision is required to produce an accurate throw.

Smeets, Frens & Brenner (2002) tested this hypothesis with dart throwing. If this intense pressure on timing the launch window determines accuracy, then throwers should organise their behaviour and throw in a way that makes their launch window as tolerant of errors as possible. They replicated the sensitivity analyses on human data to see if people try to give themselves the maximum error tolerance in the launch, or whether they were trying to accommodate errors in other variables.

What they found is that the launch window timing is not the limiting factor. Their throwers (who were not especially expert) did not throw so as to minimise the sensitivity of the launch window timing to errors. Quite the contrary; they lived in a fairly sensitive region of the space, and then didn't make timing errors. They did throw so as to reduce the sensitivity to speed errors, however, and errors in the targeting came from errors in the spatial path of the hand that the system did not adequately compensate for, rather than the timing of the hand's release. (The authors saw some evidence that the position, speed and direction of the hand trajectory were organised into a synergy, which aligns nicely with the motor abundance hypothesis).

I would like to replicate and extend this analysis process using more detailed simulations and data from better throwers. I've become convinced it's a very useful way to think of what is happening during the throw. I also think these results point to some interesting things about throwing. Specifically, while timing and speed must both be produced with great accuracy, the system has developed two distinct solutions to coping with errors. Timing errors are reduced by evolving neural systems that can reliably produce the required precision. Speed errors have been left to an online perception-action control process which adapts the throw to suit local demands. The latter is the more robust solution; so why was timing solved with brain power?

Expectations and the Size-Weight Illusion

The size-weight illusion (SWI) occurs when people are asked to judge the weights of two different sized but identically weighted objects. The smaller object is judged to be heavier. There are a variety of explanations for this illusion (see Buckingham, 2014 for a review). I'm going to be reviewing some papers on it as I develop some experiments connected to my throwing research.

One set of explanations is 'bottom up', i.e. perceptual. Amazeen & Turvey, 1996 suggested that people do not perceive weight but inertia (this is the dynamic touch hypothesis about the inertia tensor) and Zhu & Bingham (2011) have proposed the illusion is not the misperception of weight but the correct perception of throwability (I obviously quite like this one, and have discussed it here). Interestingly Zhu et al (2013) have since shown that the inertia tensor does not explain the throwing related SWI!

The second set of explanations is 'top down'. The basic hypothesis is that the sensorimotor system expects larger things to weigh more than smaller things, within a class of 'things'. This expectation has been learned over time via experience of the real world in which this is basically true. Large mugs weight more than small mugs, even if large mugs weigh less than small anvils.

There are two interesting papers that have looked at the top-down hypothesis.

What Can You Do With Uncontrolled Manifold Analysis?

There is generally more than one way to perform a task (the ‘bliss of motor abundance’) and so it’s possible for a movement to incur a little noise that doesn’t actually affect performance that much.
Uncontrolled manifold analysis (UCM) is a technique for analysing a high-dimensional movement data set with respect to the outcome or outcomes that count as successful behaviour in a task. It measures the variability in the data with respect to the outcome and decomposes it into variability that, if unchecked, would lead to an error and variability that still allows a successful movement.

In the analysis, variability that doesn’t stop successful behaviour lives on a manifold. This is the subspace of the values of the performance variable(s) that lead to success. When variability in one movement variables (e.g. a joint angle, or a force output) is offset by a compensation in one or more other variables that keeps you in that subspace, these variables are in a synergy and this means the variability does not have to be actively controlled. This subspace therefore becomes the uncontrolled manifold. Variability that takes you off the manifold takes you into a region of the parameter space that leads to failure, so it needs to be fixed. This is noise that needs control.

With practice, both kinds of variability tend to decrease. You produce particular versions of the movement more reliably (decreasing manifold variance, or V-UCM) and you get better at staying on the manifold (decreasing variance living in the subspace orthogonal to the UCM, or V-ORT). V-UCM decreases less, however (motor abundance) so the ratio between the two changes. Practice therefore makes you better at the movement, and better at allocating your control of the movement to the problematic variability. This helps address the degrees of freedom control problem.

My current interest is figuring out the details of this and related analyses in order to apply it to throwing. For this post, I will therefore review a paper using UCM on throwing and pull out the things I want to be able to do. All and any advice welcome!

The Affordances of Prehistoric Objects

I have a new paper in press at Scientific Reports (Wilson, Zhu, Barham, Stanistreet & Bingham, 2016; see also the slides from my EWEP14 talk) and I am so excited about it I can hardly cope. This project has been the most pure, good-old-fashioned science fun I've had in years and I'm very proud of the result.

Figure 1. Spheroids

The paper is an affordance analysis of some prehistoric objects (spherical rocks called 'spheroids') that were excavated from a cave in South Africa. There are several theories about what the prehistoric humans used these for, but one is that they were projectiles used for hunting. I created a simulation of projectile motion and set the parameters of the simulation using data from the literature on throwing for maximum distance. We then showed that a majority of our sample spheroids were ideally suited for throwing to inflict useful damage to a medium sized prey animal over fairly long distances. Given that we know humans have been anatomically specialising for throwing for millions of years, and given that we know modern humans can perceive the affordance for throwing to a maximum distance and select objects that best fit this affordance, we argue that these simulations provide evidence that these objects were selected to be used as projectiles.

This slightly out-of-left-field project was the result of some good luck, some careful management and the hard work of all my collaborators as we tied this together. The paper stands as an exemplar and proof-of-concept of how a task-dynamical affordance analysis can tell us about the behaviour of prehistoric humans.

Quantifying the Affordances for Throwing for Distance and Accuracy

I have a new paper in press at JEP:HPP (Wilson, Weightman, Bingham & Zhu, in press; supplemental material). It is the end result of five years work across two jobs, and it has involved kinematic data collection from expert throwers in Leeds and Wyoming, analysis of that data, then interpretation of that data in the context of detailed simulations we ran in order to identify the affordance property of the target structuring behaviour. This is my first paper on affordances, my first about my current favourite topic of throwing, and probably the heftiest empirical piece I have ever done, so getting it published in my journal of choice is pretty exciting!

I'm going to just lay out the basic framework of the paper here. I will leave the (very many) details to the paper. The paper consists of two experiments, a series of simulations, and a discussion of affordances as dispositional properties of tasks best described at the level of task dynamics. This last bit feeds into the argument in the (mostly philosophical) literature on the nature of affordances; bad news, people who think they are relations - they aren't, and I've got two experiments that back that up!

Help with a lay summary of my throwing research

I am applying for a research fellowship and part of the application is a 2500 character lay summary; see below. I would love all and any feedback from you about how well it scans for you.

I have also put a public copy of this and the scientific abstract on Google Drive that can take comments, if you are so inclined:
Lay summary
Scientific abstract

The remit of the section is
Provide a lay summary of your proposed project. This should be understandable by an A-level science student. Explain why you have chosen to work in this subject area and what it is about your proposed research that you find particularly exciting, interesting or important. Also explain the potential impact or wider benefits to society of your research. 

EDIT AFTER FEEDBACK:
Imagine you are standing on the rocky shore of a lake with a friend, who challenges you to a competition: who will be first to hit that floating branch with a rock? You and your friend hunt for suitable rocks to throw, hefting them in your hand until you find some that feel just right. You then take turns throwing those rocks to try and hit the branch, getting closer on each throw until finally one of you scores a direct hit.

The simplicity of this commonplace game is deceptive. Throwing is actually so difficult that humans are the only species who have specialised in it. We have hands that can grasp objects; bodies that help make the precisely timed throwing action possible; and the ability to perceive which objects are most suitable for throwing. Evolutionary biologists believe that throwing provided our relatively small and weak ancestors with the ability to hunt large animals such as mammoths. But throwing still plays a large role in modern life, even if it is more likely to show up these days in the sports arena than on the plains of North America.

Thanks to sports science, we know a lot about what throwing looks like when it happens. What we don’t know is how a skilled thrower produces that throw in the first place. What makes an object ideal for throwing, and how do we perceive this when we heft that object? How do we perceive where our target is? And, most importantly, how do we use this information to select a throw that will move this object in just the right way so as to hit that target? This project is all about answering those questions. We will measure expert and novice throwers aiming to hit distant targets and track their movements with high speed cameras. We will then analyse this data using cutting edge techniques to identify how people produce the throws they do.

I find throwing fascinating because there are so many unanswered questions from many different disciplines. Psychologists want to know how we perceive the environment and produce the throw; neuroscientists want to know how our brain works to support this behaviour; evolutionary biologists want to know how all these skills came together in our species and how this might have supported the evolution of language. My colleagues and I have the tools we need to actually answer these questions, and we believe that the answers will be of interest to many people, including scientists but also coaches and athletes interested in improving their techniques and accelerating their learning.

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ORIGINAL
Imagine you are standing on the rocky shore of a lake with a friend, who challenges you to a competition: who will be first to hit that floating branch with a rock? You and your friend hunt for suitable rocks to throw, hefting them in your hand until you find some that feel just right. Then you take turns throwing those rocks to try and hit the branch, getting closer on each throw until finally one of you scores a direct hit.

This game might seem an odd thing to want to study scientifically – it all seems so straight forward. But this simplicity is deceptive. Throwing to hit a target like this is actually a surprisingly difficult action that requires you to produce a precisely timed movement that suits the task at hand (how far is the target? How big?). Throwing is in fact so difficult that humans are the only species who have specialised in it. We have hands that can grasp objects, bodies that help make the precisely timed throw possible, and the ability to perceive which objects are most suitable for throwing. Evolutionary biologists believe that throwing provided our relatively small and weak ancestors with the ability to hunt large animals such as mammoths. But even today, throwing still plays a large role in modern life, even if it’s more likely to show up in the sports arena than on the plains of North America.

Thanks to research in sports, we know a lot about what throwing looks like when it happens. What we don’t know is how a skilled thrower produces that throw in the first place. What makes an object ideal for throwing, and how do we perceive this when we heft that object? How do we perceive where our target is? And, most importantly, how do we use this information to select a throw that will move this object in just the right way so as to hit that target? This project is all about answering those questions, using modern motion-capture and data analysis techniques.

I find throwing fascinating because there are so many unanswered questions from so many different disciplines (e.g. psychology, neuroscience, evolutionary biology). But even better, my colleagues and I have the tools we need to actually answer these questions! We believe that the answers will be of interest to many people, including scientists but also coaches and athletes interested in improving their techniques and accelerating their learning. It’s rare to find a research question with such wide appeal, and this makes it a very exciting topic for me to work on as a scientist.
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Learning the affordances for maximum distance throwing

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?

Is hefting to perceive the affordance for throwing a smart perceptual mechanism?

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). 

Hefting for a Maximum Distance Throw

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.

The Task Dynamics of Throwing to a Maximum Distance

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 :)

Task Dynamics And The Information They Create

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. 

How do we perceive which objects afford throwing the farthest?

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.

Shared neural resources for throwing and language: a whacky idea for an experiment

For some time now, there has been an hypothesis floating around in evolutionary biology that the human capacity for language emerged, in part, from the development of our ability to throw long distances with high speed and accuracy. There are a few reasons to think this, mostly correlational, inferential kinds of reasons, but they are accumulating.

We were chatting one day about how to test this hypothesis a bit more directly, and we came up with a whacky experiment. We'd like advice from neuroscientists with experience in brain stimulation techniques about whether this sort of thing is feasible. We'd also like to brainstorm the logic of this experiment and see if we can come up with a practical design that stands a chance of finding something. We then need collaborators; I can handle the throwing side (analysis, measurement, etc) but we don't know anything about TMS and would need an expert on board.

There are many other reasons why this might fail, though - I still need to do a detailed lit review on the throwing/language references I have. Our main problem is that we don't know the kind of obvious difficulties in doing TMS in this kind of context. We'd like to assemble a) an experiment and b) a research team to do the experiment if we can get it to make sense, and if it works we will submit the hell out of this to Nature :)

Did language emerge from the neural systems supporting aimed throwing?

Aimed throwing is surprisingly uncommon in the animal kingdom. Humans do it par excellence, and otherwise it only shows up occasionally, even in our closest relatives. Chimpanzees will throw things (often faeces) but unlike humans don't throw things when hunting or trying to get food; when non-human animals throw things, it's usually part of a social encounter.

Throwing is a fascinating task for many reasons; I hope to blog some about the perception-action aspects of this task in the future as I prepare a couple of papers on the topic with my colleagues Qin Zhu and Geoff Bingham (who have previously done some excellent work on throwing to a maximum distance and the size-weight illusion; various papers available here). There are many fascinating questions about the perception of the affordances of throwing and distances to targets which we're starting to tackle empirically.

Biomechanically, throwing an object accurately over any distance requires the precise transmission of force from the large trunk muscles along a kinetic chain formed by the segments of the arm. The large trunk muscles generate forces the arm cannot, and this force is then transmitted by the motion of the arm; each segment weighs progressively less and so the force accelerates each one faster than the last. The end result is a hand moving at high speed. This requires careful timing; if the motion of the segments aren't coordinated carefully you will waste energy moving the limbs in ways that aren't helping the throw.

There has been some speculation for a while now that the neural mechanisms that help support this fine tuned coordination and control for throwing might also be just the kind of resources that could support the development of spoken language. Speech is a complex action that requires exquisite control over the coordination and timing of numerous elements, just like throwing. One hypothesis is that our ancestors began to develop the ability to throw long distances (this being favoured by natural selection processes because it enabled us to hunt and kill huge prey with much less physical risk to ourselves; e.g. Calvin, 1983). Evolution selected for neural resources that supported this activity, and this then opened the door to the possibility of complex spoken language. So do we speak the way we do because we throw the way we do?

Perceiving long distances in action scaled units

I have so many things I need to write up just now, but it's been a struggle finding the time. I hope to post on Chemero's last chapter, task-specific devices, calibration and some new coordination data soon. In the meantime, I thought I'd take advantage of the fact that I'm reading some new articles on an interesting topic, and I wanted to organise some thoughts and see if anyone had any comments!

Perception is action-scaled

Traditional theories of perception claim that we perceive the world in generic terms, and must transform that perception into a task relevant variable after picking the information up. The ecological suggestion is that the act of perception itself is directly scaled in action-relevant units, and that this perception will therefore be task-specific. In order to directly perceive action relevant properties (i.e. affordances) perception must be smart (think of the analogy of the polar planimeter).

We are capable of perceiving the distance of things in the world; but we don't perceive them as being '6m away'. Instead, the system is interested in how to reach for an object, so you need to calibrate your perception of distance in terms of, say, arm length units. Calibration is the process of placing a measurement on a scale, and the ecological approach has been interested in action relevant scales such as arm lengths (for reaching; Mon-Williams & Bingham, 2007) and leg lengths (for stair climbing; e.g. Warren, 1984). One of Chemero's points is relevant here; body scale is probably only a proxy measure for ability to perform the action and the real action scale the system is using (the effectivity) will be more complicated. But body scale is mostly where the field is at right now.

The Size-Weight Illusion is Functional, and It's About Throwing

My colleagues, Geoff Bingham and Qin Zhu, have recently published some fascinating data which has emerged from their work on the uniquely human skill, long-distance throwing. This is a novel and rich perception-action task which Bingham and Zhu (and recently, me) have been investigating for some time, with many interesting results. I'll get onto blogging about this project once I've caught up with the coordination studies and have had some time to get my head around the data I'm helping generate.

I wanted to blog about this new paper, though, because it's an exciting result which deserves all the attention it gets. The result is about the size-weight illusion, one of the most robust illusions around. As I've talked about before, illusions are a concern to ecological psychologists only in that they suggest the task has been incorrectly characterised. This paper presents data that suggests the size-weight illusion is actually functional, and that it reflects the readiness of the human perception-action system to throw objects long distances.

This paper has seen some activity in the popular press already (e.g. here and here): Geoff's hoping for the NYT Science section too! 

UPDATE: Geoff being interview on NPR