While clearly not intended to be an accurate model, this item speaks to national concern about 'brain-power' and its importance. It comically sums up the sentiment that 'in tough times, you better get smart' mentally that many of those that frequent university bookstores share. Indeed, in many real-life emergencies, being smart about your actions pays off. So, these ubiquitous brain images, where did they originate from? The simple understanding that brains are furrowed, squishy and (kind of) bean shaped had to have come from somewhere. Neuroimaging has undoubtedly played a role here. Gore-centered websites like 4Chan and Bestgore have also contributed some, if incomplete, specimens. Neuroimaging, like fMRI and CT scanning, has also provided cursorial information on the processes of the brain as well. These processes are interpreted by (and for) the public and translated into images that represent our understanding of the brain as we know it. These conceptions suggest ways we give meaning to neuroscience and how we incorporate it into our everyday lives. Hint; we commission factories in China to manufacture inflatable, canned brains to sell to American university students.
Particularly telling are the images of the brain at work, or in action. Even neuroscience can boast only a tenuous grasp on the many complex mechanisms that transmit signals throughout the brain and the electro-chemical processes we do understand render the 'workings' of brain inconspicuous and uneventful. While I trust one day these mechanisms will be mapped in full, for now the images of the public imagination of the brain working serve to elucidate the way we understand neural process.
One of the most salient conceptual models I have come across is that of the brain as muscle or something to be "worked out" in some physiological way. The media depicts this as a very natural and intuitive analogy, brain as muscle, and supports the idea that you can increase brain power by doing cognitive work. This model provides some explanation for (and validation of), the "use it or lose it" mentality. It rewards what we relate to as hard physical work; this is fairly puritan in retrospect.
Another is the 'brain as machine' conceptual model of the brain at work. Many will recognize the characteristic 'cogs' on the wheels of cognition. Here we see a reverence for industrialism and ingenuity. This suggests a little less standard deviation than the 'muscle-man' model and therefore it's a little more egalitarian. Our understanding of machinery would suggest here that the working brain can be turned off or shut down, can work at varying outputs and requires maintenance. This also supports the "fuel" for the brain concept so many energy drink and supplement companies espouse.
Providing valuable fodder for technology marketing is the 'brain as computer' model. This model is of increasing importance to the general public's interpretation of neuroscience. Generative talk about certain behaviors being "hard-wired" or how we can "re-wire" our brains (like firmware?) gives way to narratives on storage capacity, databases, being 'programmed' to do something. While all conceptual models of the brain at work will also implicitly suggest how we understand the brain not at work, or at some lessened capacity, the computer model forces us to associate the infinite powers of technology with our brain capacities. Intimidating though it seems, I find potential utility in using this illimitable model of understanding and would suggest it is more of a sustainable model then muscle or machinery, as these both have been supplanted by computer technology in more cases than one. Real fruition can, in theory, come from using such conceptual models to understand the brain in all its mystique. The computer model standardizes brain power in some sense, as computers themselves are becoming a near human right. Neuroscience is already deep into integrating dialogue with computer science, building AI systems modeled off the human brain. So-called "cognitive computing" projects like The Blue Brain Project at the Ecole Polytechnique Federale de Lausanne (EPFL) and the DARPA funded SyNAPSE, in association with IBM, are working on full AI 'brains' hosted on supercomputers. These projects, when realized (speculated within the next two decades), will undoubtedly have transformative semantic power and will be a fertile site for anthropological analysis. For now, the human brain remains humblingly complex, but irresistibly interesting and up for myriad interpretations. For now, the brain is only limited through our imagination.