As I highlighted in my blog about fMRI lie detection, there is much hype surrounding the use of neuro imaging techniques. In an article on Adolescent Maturity and Decision Making linked in my previous post, there is a great discussion of such hype and why we should be cautious about being overly swayed by one technique:
Neuroimaging has captured the public interest, arguably because the resulting images are popularly seen as “hard” evidence whereas behavioral science data are seen as subjective. For example, in one study, subjects were asked to evaluate the credibility of a manufactured news story describing neuroimaging research findings. One version of the story included the text, another included an fMRI image, and a third summarized the fMRI results in a chart accompanying the text. Subjects who saw the brain image rated the story as more compelling than did subjects in other conditions . More strikingly, simply referring verbally to neuroimaging data, even if logically irrelevant, increases an explanation’s persuasiveness .
Despite being popularly viewed as revealing the “objective truth,” neuroimaging techniques involve an element of subjectivity. Investigators make choices about thickness of brain slices, level of clarity and detail, techniques for filtering signal from noise, and choice of the individuals to be sampled . Furthermore, the cognitive or behavioral implications of a given brain image or pattern of activation are not necessarily straightforward. Researchers generally take pains to highlight the correlative nature of the relationship; however, such statements are often misinterpreted as causal . Establishing a causal relationship is more complicated than it might, at first, seem. For example, there is rarely a one-to-one correspondence between a particular brain region and its discrete function; a given brain region can be involved in many cognitive processes, and many types of cognitive processes may be subserved by a particular brain structure .
Some neuroscientists lament that the technology has been used too liberally to draw conclusions where there is little empirical basis for interpreting the results. For example, a 2007 New York Times Op-Ed piece reported the results of a study in which fMRI was used to view the brains of 20 undecided voters while they watched videos of presidential candidates; they had previously rated the candidates on a scale of 1 to 10 from “very unfavorable” to “very favorable” . The results of the brain scans were interpreted as reflecting the inner thoughts of the participants. For instance, “[w]hen viewing images of [Senator Clinton], these voters exhibited significant activity in the anterior cingulate cortex, an emotional center of the brain that is aroused when a person feels compelled to act in two different ways but must choose one. It looked as if they were battling unacknowledged impulses to like [Senator] Clinton” . The editorial drew a swift response from several neuroscientists who believed that, in addition to subverting the standard peer review process before presenting data to the public, the investigators did not address the issue of reverse inference . In neuroimaging terms, reverse inference is using neuroimaging data to infer specific mental states, motivations, or cognitive processes. Because a given brain region may be activated by many different processes, careful study design and analysis are imperative to making valid inferences [36,37]. In symbolic logic terminology, reverse inference errors are related to the “fallacy of affirming the consequent” (e.g., “All dogs are mammals. Fred is a mammal. Therefore, Fred is a dog.”).
In sum, neuroimaging modalities involve an element of subjectivity, just as behavioral science modalities do. A concern is that high-profile media exposures may leave the mistaken impression that fMRI, in particular, is an infallible mind-reading technique that can be used to establish guilt or innocence, infer “true intentions,” detect lies, or establish competency to drive, vote, or consent to marriage.