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euroscience is everywhere. As more research is being done into the patterns and


processes of the brain, we are seeing more articles, blogs and suggestions about how this research can be transferred in all sorts of contexts – including learning and development. It seems that every week we are presented with a new piece of fMRI (functional magnetic resonance im- aging)1


psychology. It is worth looking, therefore, at what impact including neuroscientific information has on our understanding of psychology. Weisberg et al3


looked into why research that offers us another


pretty picture of the brain. Tese pictures (and the associated data) are then used to explain all sorts of psychological (and other) phenomena, often with exaggerated claims. Such research has the potential to shape our views on all sorts of things, with even some US legal scholars suggesting that neuroimaging technology could be used in both jury selection and as a better-quality replacement for the existing polygraph lie detector.2 Much of the research is at


best poorly understood – and at worst wildly misinterpreted. Tis can lead to the creation of “neuromyths” – scientific-sounding explanations that do not reflect the reality of understanding in the field. According to Lia Commissar, a project manager at the Wellcome Trust, “[neuromyths] seem to persist because they are easy to understand, fit everyday observation, are heavily promoted or are easy to implement. However, unfortunately they often have little or no evidence supporting the impact they will have on learning”. Our own industry is far from


immune to this – so where does the truth lie? We will explore below some of the key issues that neuroscience research faces, and the implication for learning and development.


The incredible (and popular) appeal of neuroscientific explanations


Researchers have noted that psycho- logical explanations seem to generate more public interest (and appear much more credible) when they are accompanied by scientific information – and in particular neuroscientific information. Perhaps oddly (since they are clearly concerned with similar questions), the public seems much less interested in run of the mill cognitive


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people find cognitive neuroscience particularly alluring – and in particu- lar why neuroscientific explanations are found to be so persuasive. Most articles and information in the popular press tends to focus on neuroscience’s ability to explain behaviour – something that we as development professionals have been looking to do for years. Understanding why neuroscience seems to have such a significant impact on why people find explanations so persuasive and convincing could help us to i) structure our own programmes and interventions accordingly and ii) be aware of any potential challenges from delegates who may have read the “next big thing” in the science


accurate) explanations were rated much more positively than bad explanations (which were generally circular restatements of the problem). Likewise, explanations with neuroscientific information were rated as much more satisfactory than those without. Combining these effects means that adding pointless neuroscience made people rate bad explanations as good. In the words of the study, “adding irrelevant neuro- science information thus somehow impairs people’s baseline ability to make judgments about explanations”.


It gets worse with pictures McCabe and Castel4


further


explored a similar problem when they studied the effect of including brain images in articles describing neuroscience. In particular, they were looking to see whether simply adding a picture of the brain would increase readers’ perceptions of the credibility of neuroscience data. Subjects were given identical


We need to beware of uncritically accepting the latest claims – particularly when they are accompanied by neuro-babble


section of the Sunday paper. Te Weisberg experiments looked at whether the addition of spurious neuroscientific information changed people’s judgments of explanations for psychological effects that otherwise did not differ in content or logic. Te studies employed a 2x2 design – explanation type (good vs bad) and neuroscience (with vs without). Tis provided a baseline measurement of participants’ abilities to distinguish good vs bad explanations as well as any influence on this ability by the additional presence of neuroscientific information. Study subjects were given a one-paragraph description of a well explored psychological effect together with an explanation for that effect which they were asked to rate based on how effective they considered the explanation to be. Te results of the experiments were clear. Good (scientifically


explanations of fictional brain studies summarising cognitive neuroscience research that included no image, a bar graph depicting the results, or a brain image and asked to rate the explanations for the quality of their scientific reasoning. Tose explana- tions that included a brain image were rated as significantly more persuasive than either other condition – even though both the bar graph and the research without imagery presented identical information. Tis effect was replicated with other visual representations of the data (a complex topographical map) and with a real-world article taken from a major publication. In other words, including a picture of the brain makes any explanation sound more persuasive! McCabe and Castel’s data sup-


ports the idea that “there is, indeed, something special about the brain images with respect to influencing judgments of scientific credibility”. Combined with the Weisberg study, researchers believe that these sorts of explanations appeal to our reductionist approach to understanding the mind as an extension of the brain – it’s easier to believe that “this specific bit of the brain does this particular thing” than to understand the complex and 


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