The Wrong Box Score
Besides being a great read about Shane Battier and success in professional basketball, The No-Stats All-Star article by Michael Lewis in last Sunday’s New York Times Magazine carries a larger lesson about how our understanding of the world is shifting. One of its main points is that we are becoming increasingly statistics driven, with sports at the leading edge of this transformation. We can spend lots of money on stars, like the New York Yankees, or we look more closely at what actually leads to success and how we can achieve that with less money. Shane Battier epitomizes this change because his individual stats are rather mediocre, his physical skills rather normal for an NBA player. But he makes his team win.
The key question becomes, how does he do this? That is where Michael Lewis mixes qualitative research (interviews) and ethnographic insight (coming from Battier’s own experience) with an examination of new ways of measuring everything that might count about a basketball game. It’s a powerful mix.
For me it illustrates two important points about how we can develop better measures, ones that are closer to what actually determine outcomes and that don’t fall into so easily into measuring our own beliefs about the world. And yes, by “our own” I mean the researchers who come up with the measures. Here’s a relevant section describing Daryl Morey, the man behind the Houston Rockets new approach to figuring out what works:
What [Morey] will say, however, is that the big challenge on any basketball court is to measure the right things. The five players on any basketball team are far more than the sum of their parts; the Rockets devote a lot of energy to untangling subtle interactions among the team’s elements. To get at this they need something that basketball hasn’t historically supplied: meaningful statistics. For most of its history basketball has measured not so much what is important as what is easy to measure — points, rebounds, assists, steals, blocked shots — and these measurements have warped perceptions of the game. (“Someone created the box score,” Morey says, “and he should be shot.”) How many points a player scores, for example, is no true indication of how much he has helped his team.
Here is how it makes a difference. Battier doesn’t get great traditional stats – points scored, shots blocked, and so forth. But he does things that, on aggregate, make a bigger difference.
Dear readers. Dr. Charles Whitehead wrote a long and thoughtful response to my earlier post on the Flynn Effect, but I worried that comments may not get read as often (or carefully) as the main posts, so I’m taking the liberty of giving Dr. Whitehead his own post. For more about Charles Whitehead’s work and his online activities, see Charles Whitehead: Social Mirrors here at Neuroanthropology.
From an anthropological point of view cognitive scientists are being less than rational when they treat intelligence scales as though they are measuring something fundamental and innate in human beings. No doubt innate abilities are used by people when they tackle IQ tests, but it is unlikely that such abilities evolved under selection pressure for this kind of problem solving.
Intelligence scales are culturally embedded artifacts designed to meet the idiosyncratic needs of postindustrial western societies, and reflect the equally idiosyncratic assumptions found in the west – such as our habit of referring to someone as “brainy” when we mean “intelligent”, and the widely held assumption that brains got bigger during human evolution because of selection pressure for “intelligence” (and/or language: e.g. Deacon 1992). The idea that human intelligence is the ultimate pinnacle of biological evolution may be little more than colonialist propaganda, suggesting that “scientific” societies are the ultimate pinnacle of cultural evolution – and hence morally entitled to dominate others who formerly managed perfectly well without the blessings of “modernity”.
Sir Francis Galton devised the first intelligence test in the late 19th century and this was followed by the scale developed by Alfred Binet and Théophile Simon between 1905 and 1911 (Atkinson et al., 1993: 457-8). As early as 1884 Galton examined more than 9,000 visitors to the London exhibition and found to his chagrin that eminent British scientists could not be distinguished from ordinary citizens on the basis of head size (ibid: 458). From that point on the kind of assumptions made by Galton have continued to pervade scientific thinking with little or no empirical encouragement.
Two hot topics for more than a decade:
Mental Health and Global Warming.
Two issues connected in the most profound of ways… Continue reading
Shihui Han and Georg Northoff have just published Culture-Sensitive Neural Substrates of Human Cognition: A Transcultural Neuroimaging Approach. This article will prove foundational for “cultural neuroscience,” a term Han & Northoff use near the end of the article. I highly recommend that everyone read the full version (pdf), but will outline and comment on it here.
In this Perspectives piece in Nature Neuroscience Reviews, Han and Northoff review the evidence on how culture influences neural mechanisms, highlight the need to integrate social neuroscience and cultural cognition research, argue for transcultural neuroimaging as an effective method for cultural neuroscience, and lay out implications for the future of this emerging field.
But if you don’t take my word for it, here’s their abstract:
Our brains and minds are shaped by our experiences, which mainly occur in the context of the culture in which we develop and live. Although psychologists have provided abundant evidence for diversity of human cognition and behaviour across cultures, the question of whether the neural correlates of human cognition are also culture-dependent is often not considered by neuroscientists. However, recent transcultural neuroimaging studies have demonstrated that one’s cultural background can influence the neural activity that underlies both high- and low-level cognitive functions. The findings provide a novel approach by which to distinguish culture-sensitive from culture-invariant neural mechanisms of human cognition.
Cultural Effects on Cognition
Han and Northoff systematically cover research on “cultural effects on cognition,” including perceptual processing, attentional modulation, language and music, and number representation and mental calculation. Their Figure 1, presented below, summarizes research on culture and attention, highlighting context-dependent differences in attention between Americans and East Asians.
Maximilian Forte over at Open Anthropology recently covered an interview with Maurice Bloch that appeared in Eurozine. In his summary, Forte highlights certain parts of the interview in a way which struck me as quite relevant to neuroanthropology. Interestingly, Forte had a similarly positive reaction to Bloch’s statements, even though his Open Anthropology project is focused on a different sort of public engagement and synthetic approach than what we do here.
Here’s why, captured in one of the more striking lines from Bloch: “I would consider that all human beings are anthropologists: all are concerned with the general theoretical questions about the nature of human beings, about explanations of diversity and similarity. Of course I’m not worried about the continuation of this form of anthropology.”
What about anthropology in its present, institutional form? There, things are not so clear. Bloch makes this provocative statement, “anthropologists have not been addressing those questions that are burning questions for human beings. Other people have done it and have not made use of what anthropologists have learned… I think we should engage with the general questions that people are ask, rather than spending our time navel gazing.”
On the applied side, particularly with regards to development and anthropology, Bloch tells us that the anthropologists’ “role is one of caution. Because we have learned that easy answers don’t work. So we anthropologists will always have a negative role [in public debates] and I think that’s right.” In contrast, however, the development and conservation experts who come in with big money, big ideologies and big power do not necessarily want to hear the “it’s complicated” anthropology message.
Wen Li, James D. Howard, Todd B. Parrish, and Jay A. Gottfried have a fascinating article in the most recent edition of Science, ‘Aversive Learning Enhances Perceptual and Cortical Discrimination of Indiscriminable Odor Cues.’ The researchers trained subjects to discern between the aroma of chemicals that initially were indistinguishable using electric shocks (!) coupled with one of the two aromas. The research is a great example of perceptual learning, a form of neural enculturation that I think is absolutely essential to understanding cultural difference but little appreciated in anthropology.
Subjects in the experiment were given a test of their ability to discern between very closely related chemicals: ‘On each trial, subjects smelled sets of three bottles (two containing one odorant, the third containing its chiral opposite) and selected the odd stimulus.’ Before the training, subjects selected the odd odor out 33% of the time — no better than random. After the repeated association of one chemical with shocks, subjects’ ability to discriminate the smells improved markedly, showing that negative reinforcement training could ‘enhance perceptual discriminability between initially indistinguishable odors.’ Moreover, the neural representation of the smells changed, as found with fMRI.
From their abstract:
We combined multivariate functional magnetic resonance imaging with olfactory psychophysics to show that initially indistinguishable odor enantiomers (mirror-image molecules) become discriminable after aversive conditioning, paralleling the spatial divergence of ensemble activity patterns in primary olfactory (piriform) cortex. Our findings indicate that aversive learning induces piriform plasticity with corresponding gains in odor enantiomer discrimination, underscoring the capacity of fear conditioning to update perceptual representation of predictive cues, over and above its well-recognized role in the acquisition of conditioned responses. That completely indiscriminable sensations can be transformed into discriminable percepts further accentuates the potency of associative learning to enhance sensory cue perception and support adaptive behavior.
At the end of my last post, or the one before that, I had a late-night ‘inspiration’ that must have sounded a bit like an outburst about how our brains are not like computers. There’s lots of good reasons for making that assertion, whether or not it’s an outburst. But one of the key issues is concern about ‘embodiment’ in cognitive science and the discussion of embodied cognition. Daniel, in his comments, put a link to the posting by Chris Chatham, 10 Important Differences Between Brains and Computers, which is excellent. There’s also an interesting discussion of this going on at Dr. Ginger Campbell’s blog on her Brain Science Podcasts, both of which (discussion and podcasts) I strongly recommend. See the first two topics on the list you can find here on ‘Artificial Intelligence.’
For the anthropologists in our audience, however, the term ‘embodied cognition’ is a bit unfortunate, not because it’s not a great term, but because an earlier intellectual movement in anthropology already snagged the adjective ‘embodied’ and then didn’t push the issue far enough to actually deal with physiological and biological dimensions of being embodied. That is, in anthropology, the term ‘embodiment’ has not been allowed to really stretch its wings, and has instead been more narrowly constrained to dealing with phenomenological, interactional, and theoretical issues deriving primarily from feminism, Foucauldian post-structuralism, and Bourdieu-ian sociology. All of these streams are important, but they do not yet engage with the sort of material that cognitive scientists mean when they use the term ‘embodied.’ The danger is that anthropologists will see the term, ‘embodied cognition,’ and it will not seem quite as disruptive to anthropology-as-usual as it should be.
Chatham’s posting makes this key issue clearer in his tenth reason that brains are not like computers: brains have bodies:
This is not as trivial as it might seem: it turns out that the brain takes surprising advantage of the fact that it has a body at its disposal. For example, despite your intuitive feeling that you could close your eyes and know the locations of objects around you, a series of experiments in the field of change blindness has shown that our visual memories are actually quite sparse. In this case, the brain is “offloading” its memory requirements to the environment in which it exists: why bother remembering the location of objects when a quick glance will suffice? A surprising set of experiments by Jeremy Wolfe has shown that even after being asked hundreds of times which simple geometrical shapes are displayed on a computer screen, human subjects continue to answer those questions by gaze rather than rote memory. A wide variety of evidence from other domains suggests that we are only beginning to understand the importance of embodiment in information processing.