Chapter 2 - Why fMRI? Neuroimaging and the movement toward multidisciplinary science

Neuroimaging and the `common language’ of the brain

Human neuroimaging, especially fMRI and PET, is a growing new field now with thousands of publications per year. Why all the excitement? One of the goals of neuroimaging is a movement towards multidisciplinary science. This is one thing we’re particularly excited about. For many years, people in different fields have been studying diverse aspects of the mind, the brain, and the body. Psychologists study the mind and behavior while neuroscientists study the brain. Medical and clinical researchers study the treatment and prevention of illness including those of the mind and the brain, which we increasingly understand to be interconnected with other body systems. Clinical trials study health related interventions and biologists study living systems. The fields of statistics, engineering, and computer science have each emerged as leading disciplines in the study of complex computational and biological processes with different traditions of techniques and approaches.

These fields form rich but largely separate traditions. This is in some sense inevitable as a field grows and matures with a strongly shared history of knowledge and increasingly specialized techniques among its practitioners. This canalization and deepening of roots is complemented by new growth of fields that evolve at the intersections among established fields before developing their own research traditions. Psychophysiologists study the mind as related to peripheral physiology. Neuroimmunologists study the brain as related to the immune system. Psychoneuroimmunologists study intersections of the mind, brain, and immune functions. Each of these disciplines provides a crucial but incomplete window into the most exciting frontier in contemporary science: the study of the mind and the brain - the study of us.

There is an old story about a group of blind people who each feel an elephant and try to understand together what they are observing. One person feels something long, rubbery, and flexible. Another perceives a smooth, firm surface and a third identifies a flat, delicate membrane. The study of the mind and the brain is a really, really big elephant. Its study spans several dimensions of analysis. One is a dimension of scale ranging from molecules to cells to systems. Another is a dimension of time from the opening and closing of ion channels in nanoseconds to the long-term relationships between brain and mind over a human lifetime or perhaps over the lifespan of a culture or a species. A third is a dimension of abstractness from concrete physiology to our capacities for abstract thought and emotion: for love, hope, cruelty, and empathy. Each discipline brings something unique to the table, but each specializes in a different ``piece of the elephant’’. To understand the whole image, we need to study these pieces deeply and rigorously, and then put them together into a picture of the integrated function of the human brain, mind, body, and environment.

The potential for such integration is one of the most exciting things about fMRI as a technique. Not only does the technology for collecting fMRI data draw on knowledge and techniques from at least a half dozen disciplines but fMRI can also be used to study just about anything related to the brain and the mind. This includes everything from abstract thought to cognitive performance, to mental illness and psychopathology, to brain regulation of inflammation in the body. For a practitioner to integrate the information and techniques required to do these studies well draws on knowledge from dozens of other disciplines.

fMRI and other types of neuroimaging also provide a way for practitioners of different disciplines to come together and speak in the ``common language’’ of the brain. For example, consider a neuroscientist studying the molecular basis of learning, a pharmacologist interested in antipsychotic drugs, a psychiatrist examining depression, and a social psychologist investigating the nature of altruistic behavior. What do all these researchers have in common and what could they possibly converse about relating to each of their core scientific interests? Why, the dopamine system, of course! It is very likely each of these researchers has been studying brain processes related to the mesolimbic dopamine system, which connects the midbrain, ventral striatum, and prefrontal cortex. The researchers each might have results related to brain activity in the ventral striatum that could help inform the others’ ideas about what the system is doing in relation to their outcomes of interest.

Neuroimaging research can even help establish bridges between researchers in the same field who didn’t realize their ideas were grounded in similar neurophysiological processes. For example, some social psychologists study motivation and appetite, others the effects of psychological distance, still others emotion regulation, and another group stereotyping and prejudice. All these areas contain a proliferation of theories, many of which include specific names and concepts (e.g., ``construal level theory’’). How do the mechanisms underlying these theories relate? Do some rely on the same core processes and systems and, if so, what are they and how are they related? Once again, the ventral striatum and medial prefrontal cortex likely play prominent roles in all these areas of social psychological inquiry. Grounding theories in models of brain function can help establish premises in measurable processes. These theories can then be shared across researchers and fields to facilitate building a cumulative science of social cognition and behavior.

Multiple roles, multiple fields: An example

LetÕs look at some of the unique roles different disciplines play in an fMRI study by using an example of a basic fMRI study on how antidepressants work. Yes, we still don’t really know much about how antidepressants, opioids, or any of the other systemic drugs (which we have been administering for decades or longer) work. This is in large part because these drugs affect neurons and glia all over the brain and we don’t know much about the effects on the various systems that support thought, emotion, and decision-making. We don’t even have a good consensus on which brain systems sustain those processes and which implement basic functions like attention, learning, and emotion. We do know a lot, but - to continue with our example - if we find that an antidepressant affects the prefrontal cortex, it is difficult to say what that means regarding the course of a personÕs mental health or their life.

So, back to our study - we won’t try to solve the whole mystery at once. Rather, this study will simply seek to establish which brain regions change with antidepressant treatment in order to test whether the drugs do indeed alter the function of the prefrontal cortex and other brain regions. The psychologist uses expertise in experimental design to construct a task which can isolate particular mental processes related to depression. The psychologist and statistician both have expertise in ascertaining that the design is efficient and well powered, and that it will produce valid causal inferences about the effects of the drug on the brain. A pharmacologist has information about the cellular and molecular mechanisms of the drug’s action and the kinetics of its absorption into brain tissue; the pharmacologist possibly also has data about its effects on brain vasculature and blood gas levels that may produce artifacts. A psychiatrist knows how drug dose and time course relate to expected clinical efficacy. A neuroscientist may have unique knowledge about how the drug penetrates into the brain and about the effects on neurons, glia, and/or various neural systems. The right training uniquely positions an MR physicist or biomedical engineer to ensure that we can obtain high-quality functional and structural images, and ideally minimize artifacts in the brain areas about which we care the most. The physicist or biomedical engineer may also have crucial information about how vascular and physiological drug effects might impact the fMRI signal independent of neural function. A computer scientist can manage and process the potentially huge volume of data acquired during the experiment, likely by borrowing signal processing techniques from mathematics and electrical engineering. During data analysis, the statistician again plays a critical role in examining the data and the assumptions underlying the statistical tests, ultimately giving us a (hopefully valid!) picture of which brain areas the drug affects. A neuroanatomist can help localize the effects that emerge. The neuroscientist’s purview, together with the psychologist and psychiatrist, is interpreting the results and their meaning.

That provides an overview of the different roles and contributions of various fields in an fMRI study. This description does not imply we need a team of 12 experts to do the study Ñ in fact, that would be highly impractical. For the best science, we need collaboration of experts in multiple disciplines and individuals with proficiency in diverse aspects of design, analysis, and interpretation. A scientist using fMRI might come from any one of these disciplines, but likely has some capability in nearly all of them. While it’s probably impossible to truly be an expert in each of these areas, a good scientist will know something about all of them, have some idea about what she or he doesnÕt know, and recognize when and how to ask for advice from colleagues.

A confluence is the running together of rivers into a greater river. This is what the collaboration of disciplines is like: many great rivers running together with their ideas and techniques intermingling and combining. This process is very good for both science and society far beyond the immediate applications of fMRI. This confluence can help those who learn and practice collaboration become educated in a rich set of scientifically grounded ideas. It can lead to new ways of thinking about the mind, health, and disease.

Challenges and motivation for multidisciplinary science

All this sounds great, right? The catch is that it’s actually not easy for people from different disciplines to work together because they must learn and talk about unfamiliar concepts and be willing to not be the expert. Collaboration requires scientists from different disciplines to care about ideas and problems outside the scope of their defined interests and perhaps to publish in journals unfamiliar to or not prestigious in their particular field (very few journals are prestigious across all fields). It also requires time spent educating other team members about basic concepts which are not groundbreaking within one’s own discipline but which may be crucial and perhaps innovative in the context of interdisciplinary science.

For example, many MRI physicists are rewarded for innovating new methods to acquire data, not for explaining the basics of tried-and-true clinical study methods like our example above or for spending time tweaking those methods to minimize the artifacts in the brain structures which impact neuroscientists. Those who are willing to talk to the rest of us should be treated like gold, as should statisticians and others with specialized knowledge to contribute.

So how do we get people to talk to one another and work together? One answer lies in individual scientists developing multiple types of expertise, so that the gulf between the psychologist and the physicist, or the pharmacologist and the statistician, is not so great that they have nothing to say to one another. ``Bridge’’ scientists are the glue that holds the team together. A little knowledge goes a long way in that respect, just like knowing a few words of someone else’s language can produce a dramatically different social interaction than sharing no words. Offering a route to develop expertise is one of the reasons we wanted to write this book.

Another answer is the movement towards multidisciplinary science, which is a challenging but laudable goal. Multidisciplinary refers to the idea that the study makes novel contributions to multiple disciplines. Take our example of the antidepressant fMRI study. If it is the study of a relatively novel drug with still unexplored mechanisms of action in the brain, it will be of interest to pharmacology. If it links two strong changes in thought and emotion, it may be of interest to psychologists and clinicians. If it involves novel innovations in data acquisition, it may be of interest in the field of MR physics. And if it involves novel computational methods to analyze brain networks, it might be of interest to the fields of computer science, informatics, and related disciplines. Not only is this difficult to pull off but also most studies should probably not try to be novel in so many different ways. However, the potential for innovation in multiple disciplines is one of the things that draw scientists from different areas together to contribute their expertise, creativity, and ideas.