The Winding Path

I intend to get back into writing for this blog again now that I’ve completed my diploma. But before that I’d like to present this piece by one of the intelligent, thoughtful people I befriended during the past year. So here’s Jack White with a few cautions regarding our use and understanding of fMRI research findings.

-Mark
***

Show someone a brain scan and there’s a better chance they will accept accompanying scientific evidence that contains faulty logic and flawed reasoning. A study published in Cognition shows the persuasive value of brain scans that use functional magnetic resonance imaging (fMRI), or at least their ability to switch off critical thought. Interestingly, this effect may not be limited to members of the lay public. Researchers from Yale University showed that neuroscience students were more satisfied with descriptions of psychological phenomena if neuroscientific explanations were included. But the neuroscience did not contribute any real evidence to the findings being reported – it was “scientific-sounding but empirically and conceptually uninformative” information – in other words, bunk.

When used to explain cognitive phenomena, the seductive allure of fMRI and its appeal to scientific legitimacy tend to obscure its very real limitations. Its capacity to observe the neural correlates of mental constructs, such as learning and emotion, is often misrepresented by an overenthusiastic news media. A Stanford study into media coverage on fMRI over a 13-year period found that a significant majority did not explain the capabilities and limitations of the technology. Most coverage was optimistic in tone, rather than balanced or critical, presenting fMRI as a modern cartographer of the mind.

While the popular press has never been associated with ideals of scientific rigour, its treatment of fMRI and cognitive neuroscience is an illuminating example of the interplay between science and public interest. The perception that fMRI can provide hard evidence to soft topics places a premium on stories that can cite neuropsychological measures to back up reported findings. While newspapers and popular magazines are not the right forum for in-depth discussions of specialised areas of scientific knowledge, the superficial nature of reporting on neuroscience can be problematic. Readers may be excused for adopting a philosophy of “neuroessentialism”, what the Stanford study defines as the tendency to equate subjectivity and personal identity with mechanisms of the brain. Headlines that trumpet the latest findings into the psychology of schoolyard bullies or psychopathic prison inmates often outline the fMRI evidence used to justify the researchers’ claims, without delving into the assumptions behind such work or its implications.

Dangers associated with trusting our sources are not limited to the responsible reporting of research findings in the mainstream press. As cognitive neuroscience seeks out correlations between mental phenomena and biological patterns, it’s tempting to overextend the significance of fMRI results. Despite the impression gleaned from reading some journal articles, the efficacy of neuroimaging to investigate higher-order cognitive processes is currently the subject of vigorous debate. On the technical side of things, Nikos Logothetis and Russell Poldrack both provide succinct overviews of what we can and cannot infer from fMRI data. Some pertinent items are summarised as following:

• Indirect measures: Standard fMRI scanning uses the blood-oxygen-level dependent or BOLD method, which measures increases in oxygenated blood flow to areas of brain tissue. Although they are highly correlated, the BOLD signal is an indirect measure of neural activity and the exact relationship between the two is unknown.
• Limited visibility: Neurons are densely packed and can fire hundreds of impulses per second. Current fMRI scanning methods are limited in spatial resolution to volume elements of tissue that, while remaining small in size, contain millions of neurons and tens of millions of interconnections. These limitations can be partially overcome by single electrode research on animals and new statistical methods, but not all research is taking advantage of these methods.
• Ambiguous baselines: Cognitive experiments rely on baseline measures of the participant’s metabolic activity while at rest, which are then subtracted from scans of the BOLD signal taken while the task in question is being performed. The fMRI signal therefore indicates a differential measure of brain metabolism – not raw quantity. It is assumed that the subtraction method isolates the metabolic activity related to the experimental task. This neglects the fact that the brain is metabolically active even at rest. If cognitive functions are distributed across areas of the brain that are active in both conditions, then the subtraction process renders the overall picture incomplete and inaccurate.
• Emergent processes: Rather than mapping onto the brain in a one-to-one fashion, cognitive functions are distributed across the brain and operate interdependently. For example, the process of visual word recognition involves perception, attention, lexical search processes and semantic classification. Each of these functions exhibit patterns of brain activity that are mutually intertwined and impossible to deduce from fMRI signals alone.

Poldrack also outlines the inherent problem of reverse inference that so often typifies fMRI work into cognitive neuroscience. This occurs when neuroimaging evidence is used to infer the workings of specific cognitive functions, such as memory recall or word learning. Not only is this a logical fallacy, Poldrack argues, it reflects the tendency for scientists to adopt a “strongly modular approach to structure-function relationships” in the brain, one that is not borne out by data. He opines that

this facile leap to localizationist conclusions [is derived] from lesion and neuroimaging results. Despite the longstanding appreciation for the importance of functional integration within the neuroimaging literature, the widespread use of functional and effective connectivity analyses has not yet come about. Given that many cognitive processes may be distinguished not by activity in specific regions but by patterns of activity across regions, there is reason for caution regarding many of the inferences that have been driven by highly modular approaches.

While the debate rages on, the nexus between public interest and scientific discourse provides an interesting vantage point to observe attitudes and approaches to fMRI. One can only expect that more knowledge about the limitations involved with its use will instruct rather than deter, given the steady encroachment of neuroscience into applied fields of public policy, law, and economics.

Related links:

• Brain imaging: a decade of coverage in the media - Science Communication
• The role of fMRI in cognitive neuroscience: where do we stand? - Current Opinion in Neurobiology
• Seeing is believing - Cognition
• Seductive allure of neuroscience explanations - Journal of Cognitive Neuroscience
• The fMRI smackdown cometh - Mind Hacks
• Fake method for research impartiality (fMRI) - The Scientist

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Previously I wrote a brief overview of Merlin Donald’s paper which paints a picture of how our culture and our brain co-evolved. I also raised a question of what it might mean for the future. Now I’m going to give you an overview of Donald’s theory which actually details how that co-evolution may have happened. To try to give you a clearer picture I’m drawing on some of what Donald wrote in his book, Origins of the Modern Mind, in which he fully defined his theory.

It’s a theory which drew on the work of people from many fields including neuropsychology, cognitive neuroscience, anthropology, and comparative biology. The crux of the theory is that our cognitive-cultural evolution went through three transitions; each new stage involving a new way of mentally representing reality. It’s important to note that each stage builds on top of the previous, retaining all the advantages so that the last stage also includes all the previous ones.

Episodic Culture

This stage involved the ability to mentally represent complex events, including social ones, but with a very limited capacity to voluntarily express those representations. And while complex events could be understood, they could only be understood in a very situation-specific way. Modern apes are at this stage¹. An example of the limitations of this stage can be found in apes’ use of sign language. Apes can be taught how to sign, but they seem to only be able to use signs in the contexts in which they’re taught. However, humans can learn to apply the same sign in any context in which it could conceivably be relevant (and even when not relevant. Just think of how we’re coming up with new uses for old words all the time).

Mimetic Culture

The first transition brings us to a mimetic form of culture. It happened about 2 million years ago with the emergence of Homo erectus, who were the first of our ancestors to show clear evidence of an advanced, tool-using society. While some who came before do show evidence of tool-use, it wasn’t as systematic and widespread as it was with Homo erectus. Donald argues that our ancestors must have undergone a significant evolutionary adaptation at around that time, citing various sources as evidence including fossil records, cultural relics such as tools, and comparative anatomical evidence. The result of the adaptation was a form of representation which included the ability to model actions. This form of culture gets it name from that modeling ability; mimetic skill, or mimesis, which is the ability to consciously act in a way which conveys a message. Donald suggests that our ancestors still weren’t able to communicate verbally, but they now possessed enough nonverbal ability to allow individuals to share their knowledge of skills, such as tool-making, through various forms of behaviour including gestures, whole-body movement, facial expressions, eye movements, etc.

Mythic Culture

The second adaptation happened less than 400,000 years ago with the emergence of Homo sapiens, our closest ancestors. The adaptation was the ability to speak (and of course understand speech). This stage involved many cultural achievements including clothing, building shelter, transporting heaving objects, a huge variety of tools and weapons, social and religious activities involving elaborate rituals including dancing, masks and costumes. It was the latter achievement from which this form of culture gets its name; our ancestors could now form an understanding of the world which integrated everything that they experienced into a narrative form. They could construct and communicate those stories far more effectively than they could before, not just because of the advantages speech provide, but also because of the improvements to memory and thinking that came along with speech.

Theoretic Culture

The third, and to this point the last (though not necessarily the final) transition was not a biological one. It involved the use of tools to get our representations out of our heads, allowing us to manipulate them in more ways than ever possible before. By moving our ideas outside our heads those concrete representations became part of our cognitive processes. Our “thoughts” now also exist in various forms of written language, but also as every other kind of representation that technology allows, from graphs to photos to video, as well as music and other forms accessible to our other senses. Most importantly, along with this new form or representation came a new form of thinking; theoretical thought. This form of thought allows a much greater scrutiny of reality, and much more accurate representations than were possible at previous stages.

So there you have a brief outline of Donald’s proposed theory. It’s important because it provides a framework for understanding and further examining our current culture and cognition, the various ways in which we view the world, how that differs from culture to culture, and what might change in the future as our culture continues to develop. If you’d like to learn more I highly recommend picking up Origins of the Modern Mind.

Related entries:

• How did our mind and brain evolve?
• How do we process complex social interactions?

One of the big unanswered questions in psychology (it’s also relevant for a few other fields) is how our mind and brain evolved. Merlin Donald has invested a lot of effort into answering that question. Last year he had a paper published which tries to answer it (or at least head towards an answer) through a discussion of the co-evolution of brain and culture. This post and the next two will cover the central ideas of the paper.

Like the chicken and the egg, the evolution of brain and culture are so intertwined that the question of which came first is just as difficult to answer. And maybe just as irrelevant; figuring out which came first is a distraction from figuring out the processes involved. Donald refers to how groups of our distant ancestors gradually became involved in more and more complex interactions. This included relatively simple imitation of tool-making and tool-using through to more cognitively demanding activities such as cooperative hunting and migration. These interactions became an increasingly complex and ever more important part of culture. Without social interaction we don’t develop many of the abilities we tend to take for granted (like language). We’ve now reached a point where exposure to sociocultural influences is absolutely necessary for the full development of an infant into an adult.

Donald compares the interactions between people (and each person’s brain) and culture to a distributed network of computers (e.g., the Internet). Like any computer connected to the Internet a person “connected” to culture is capable of much more than a person alone. The connection between people takes the form of social interaction. It starts with learning the basic social skills necessary to develop a more complex connection. That more complex connection allows us to learn the skills necessary to use the abundant technology which culture allowed us to create.

Literacy also emerged from the co-evolution of brain and culture. Reading and writing depend on spending lots of time learning very specific skills to the point where they’re automatic. Since they require such extensive learning those skills are clearly not innate. After all, no-one can read without being told what the squiggly lines mean. But it’s also clear that the learning process produces physical changes in the brain. This can be seen in people who’ve suffered very specific brain damage and are unable to read, but can still write, while others have the opposite problem.

The skills required to use various forms of technology are also obviously learned, but not so obvious are the changes that learning and continued use has on the development of our brain. It’s possible that habitual, culture-specific skills which people learn from a young age, such as using the Internet, result in physical changes in the brain just as they do for literacy. However more research needs to be done before we can reach any strong conclusions.

There are also some more interesting questions which need to be answered, for example, as children’s use of Internet resources increases, how do their general knowledge skills change? If they’re more reliant on instant access to a variety of information, is there a trade off between broad versus deep knowledge, or specialisation versus generalisation. I.e., being knowledgeable in more fields of knowledge but less knowledgeable of the details of each field, versus knowing more in one field. Do technologies such as advanced search engines change the way people’s brains process information?

Next up, Donald’s theory of the evolution of our culture and mind. After that, his proposal of a hypothetical neural process which is similar to working memory, but which works over a longer time scale, and possibly what gave humans an edge over our primate ancestors.

Related entries:

• How our mind, brain and culture evolved: A proposed theory.
• How do we process complex social interactions?