At the time of these publications Kety and Schmidt were considered vascular physiologists more than brain scientists. Nevertheless the ability to measure CBF, a proven correlate of brain metabolism, opened up the remarkable possibility of studying brain function in humans. The development of FMRI in the s, generally credited to Seiji Ogawa and Ken Kwong, is the latest in long line of innovations, including positron emission tomography PET and near infrared spectroscopy NIRS , which use blood flow and oxygen metabolism to infer brain activity.
As a brain imaging technique FMRI has several significant advantages:. The attractions of FMRI have made it a popular tool for imaging normal brain function — especially for psychologists. Over the last decade it has provided new insight to the investigation of how memories are formed, language, pain, learning and emotion to name but a few areas of research. FMRI is also being applied in clinical and commercial settings.
The cylindrical tube of an MRI scanner houses a very powerful electro-magnet. The magnetic field inside the scanner affects the magnetic nuclei of atoms.
Normally atomic nuclei are randomly oriented but under the influence of a magnetic field the nuclei become aligned with the direction of the field.
The stronger the field the greater the degree of alignment. When pointing in the same direction, the tiny magnetic signals from individual nuclei add up coherently resulting in a signal that is large enough to measure. The key to MRI is that the signal from hydrogen nuclei varies in strength depending on the surroundings.
This provides a means of discriminating between grey matter, white matter and cerebral spinal fluid in structural images of the brain. All such techniques are designed to scan the raw MRI data into the computer more rapidly than with the standard procedure. Once the image is acquired, other data processing techniques can speed things up to achieve real-time imaging.
One novel procedure is simply to ignore the redundant information in the original data. Since some of the data in effect cancels out other data, one has only to process a part of the data to approach real-time imaging. All these fast procedures hold promise of replacing invasive cerebral and cardiac angiography with noninvasive MRI techniques.
Once it becomes possible to capture a single image in a few tens of milliseconds, it also becomes possible to improve the signal-to-noise ratio by averaging signals over repeated trials. The trick in this procedure Event Related fMRI is to carry out that averaging out of order, rather than in the order of the sequential trials.
Such a strategy, first developed in , allows randomly mixed trials to be selectively averaged. Now that equipment has been reduced in size to a manageable level, it has become possible to implement intraoperative MRI iMRI surgery. Rather than depending on stereotaxic atlases, which give a series of average three-dimensional coordinates for the brain, or on images taken prior to surgery, surgeons are now able to examine internal structures during the course of the operation and guide their actions based on immediately available data.
The development of small MRI magnets that can image the brain and then be moved out of the way has been pioneered by Odin Medical Technologies in Israel. Their PoleStar N equipment has so far mainly been applied to brain tumor surgery. However, as the technology improves even further it may become much more widely used in many other types of surgery.
The extensive literature on standard and functional MRI techniques is bursting with other dazzling ideas for future applications. Another trend in MRI is the search for techniques that accurately distinguish between different kinds of materials, not just concentrations of water or blood. One strategy of exceptional promise is MRI spectroscopy, by which MRI signals are picked up simultaneously from different chemicals.
Success would permit qualitative as well as quantitative study of the brain in living subjects. Imagine being able to track out the distribution or, better yet, dynamically changing distributions of transmitter substances in the living brain. This discussion only scratches the surface of possibilities.
At the rate things are going, a decade or two from now these speculations may have become realities, and even more ambitious speculations will be before us.
Expect wonderful things to happen in two closely related areas. Research on the brain leading to fundamental understanding of how this wonderful organ works will continue to be forthcoming, as will new developments in curing illnesses now considered incurable. MRI and other imaging machines are wondrous, but they can be used as readily to confuse and mystify as to enlighten and clarify. But, like all other natural scientists, psychologists have felt the urge to seek the underlying brain mechanisms that account for that observed behavior.
Sometimes this has led to widely, but uncritically, accepted nonsense. Among the most egregious abuses are devices such as the polygraph, which purportedly evaluates the truth or falsity of an uttered statement. Its inventor died in jail for this deception. With the introduction of the new imaging devices, particularly fMRI systems, it seemed that the long-sought goal of a valid noninvasive method for correlating brain and cognitive activity was at hand.
The application of this technique, however, is based on certain highly questionable assumptions. The key conceptual problem faced by those who would correlate cognitive processes with brain activity is their implicit assumption that the mind comprises separable modules that can be isolated and examined independently of each other and, thus, separately localized.
This premise assumes that the hypothetical cognitive processes produced by the brain interact linearly one can simply add or subtract one from another, as opposed to their being complex multiplicative functions of each other and that they maintain their same properties when used in different tasks.
For example, it assumes that a component of a reaction-time process such as the time it takes to select a response remains the same regardless of how many stimuli are simultaneously presented.
This latter criterion is one of the most fragile of the assumptions underlying the current stampede of work seeking the locations in the brain of what I believe are more likely to be the result of highly interconnected neural mechanisms, none of which operate in complete isolation from other cerebral regions.
Robert G. In short, mental or cognitive activity is more likely to represent an indivisible entity that cannot be broken up in modules. The history of cognitive processes and faculties is replete with a vocabulary of items that were once popular and then disappeared. Unfortunately, this process of trying to turn operationally defined processes into actual concrete entities continues to this day.
The important point about this holist-modularist controversy is that if it turns out that cognition is not divisible into modules in any meaningful way, then the great project of localizing these nonexistent modules in particular regions of the brain becomes unrealizable in principle, as well as in practice.
This brings us to some related problematical technical issues. The two pictures are subtracted from each other on a pixel-by-pixel basis, and the locus of any residual difference is proposed as the localized site of the cognitive process. In other words, it begs the question. Since then, fMRI has contributed to some of the most incredible discoveries of our time. Overall, fMRI has allowed researchers to paint a more complete picture of the brain and its interconnected parts.
In the clinical setting, doctors use fMRI scans to evaluate potential risks for patients before brain surgery. In , researchers at the University of Berlin discovered that reading suspenseful stories like E.
As scientists continue to explore the effect of the humanities on the human experience using fMRI technology, they continue to find hidden ways the arts influence us on the neurological level and quite literally stimulate our brains. The solution is not to limit our recordings, but to improve our analysis approaches to the multivariate problem that is the brain e. There are many ways to analyse an fMRI dataset, so which do you choose? Especially when many of the available options make sense and can be easily justified, but different choices generate slightly different results.
This dilemma will be familiar to anyone who has ever analysed fMRI. A recent paper identified 6, slightly different paths through the analysis pipeline, resulting in 34, different sets of results.
By fully exploiting this wiggle room, it should be possible to generate almost any kind of result you would like see here for further consideration. Although this flexibility is not strictly a limit in fMRI and certainly not unique to fMRI , it is definitely something to keep in mind when interpreting what you read in the fMRI literature.
Otherwise there is a danger that you will only see what you want to see i. It is often pointed out the fMRI can only provide correlational evidence.
The same can be said for any other measurement technique. Simply because a certain brain area lights up with a specific mental function, we cannot be sure that the observed activity actually caused the mental event see here. Only an interference approach can provide such causal evidence. Although this is strictly correct, this does not necessarily imply the causal methods are better.
Neural recordings can provide enormously rich insights into how brain activity unfolds during normal behaviour. In contrast, causal methods allow you to test how the system behaves without a specific area. Because there is likely to be redundancy in the brain multiple brain areas capable of performing the same function , interference approaches are susceptible to missing important contributions.
Moreover, perturbing the neural system is likely to have knock-on effects that are difficult to control for, thereby complicating positive effects. These issues probably deserve a dedicated post in the future. But the point for now is simply to note that one approach is not obviously superior to the other.
It depends on the nature of the question. A final point worth raising is the spectre of reverse inference making. In an influential review paper , Russ Poldrak outlines the problem:. Perusal of the discussion sections of a few fMRI articles will quickly reveal, however, an epidemic of reasoning taking the following form:. Reverse inferences are not a valid from of deductive reasoning, because there might be other cognitive functions that activate the brain area.
Nevertheless, the general form of reasoning can provide useful information, especially when the function of the particular brain area is relatively specific and particularly well-understood.
Using accumulated knowledge to interpret new findings is necessary for theory building. However, in the asbence of a strict one-to-one mapping between structure and function, reverse inference is best approached from a Bayesian perspective rather than a logical inference.
Summary : fMRI is one of the most popular methods in cognitive neuroscience, and certainly the most headline grabbing. To appreciate these limits, it is important understand some of the basic principles of fMRI. We also need to consider fMRI as part of a broader landscape of available techniques, each with their unique strengths and weakness figure 6.
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