There and up again: On the uses and misuses of neuroimaging in psychology

Abstract

The aim of this article is to discuss the conditions under which functional neuroimaging can contribute to the study of higher-cognition. We begin by presenting two case studies-on moral and economic decision-making-which will help us identify and examine one of the main ways in which neuroimaging can help advance the study of higher cognition. We agree with critics that fMRI studies seldom 'refine' or 'confirm' particular psychological hypotheses, or even provide details of the neural implementation of cognitive functions. However, we suggest that neuroimaging can support psychology in a different way, namely, by selecting among competing hypotheses of the cognitive mechanisms underlying some mental function. One of the main ways in which neurimaging can be used for hypothesis selection is via reverse inferences, which we here examine in detail. Despite frequent claims to the contrary, we argue that successful reverse inferences do not assume any strong or objectionable form of reductionism or functional locationism. Moreover, our discussion illustrates that reverse inferences can be successful at early stages of psychological theorizing, when models of the cognitive mechanisms are only partially developed.

Brain Imaging, Forward Inference, and Theories of Reasoning

“…A companion article to Henson ( 2006 ), by Poldrack ( 2006 ), described “reverse inference,” by which the presence of a particular cognitive process is inferred from a pattern of brain activity [see Del Pinal and Nathan ( 2013 ), for a critical review]. Poldrack noted that a researcher’s confidence in a reverse inference can be explained in terms of Bayes’s Theorem, with the conditional probability that the cognitive process is engaged when a particular brain region is activated depending, in part, on the prior likelihood that cognitive process appears in the experimental context.…”

Mining the Brain for a New Taxonomy of the Mind

“…There are at least two different kinds of inferences that one might be interested in supporting, here. The first, known as reverse inference, is the ability to conclude that a particular mental operation is occurring given the observation of brain activity, whether in a single region or across the brain (Poldrack ; Del Pinal and Nathan ; Hutzler ; Machery, ; see also Norman et al ) . The second, known as forward inference, is the complement: the ability to predict which brain region(s) will be engaged by a particular psychological process (Henson ; Mitchell et al ).…”

The Future of Cognitive Neuroscience? Reverse Inference in Focus

“…Although there are various methodological worries concerning LRI (for an overview, see Del Pinal & Nathan, ), here we focus on what is, arguably, the most pressing and influential one: the lack of selectivity objection .…”

“…According to these approaches, the apparent persuasiveness of the selectivity objection is due to a subtle misconstrual of the way in which Bayes's theorem should be applied in reverse inference. The basic observation, proposed independently by Hutzler () and Del Pinal and Nathan (), is that the evidence used in reverse inferences should explicitly incorporate the task under consideration. In what follows, we shall focus on our variant (for a discussion of the differences and comparative (dis)advantages of each view, see Del Pinal & Nathan, ).…”

“…The basic observation, proposed independently by Hutzler () and Del Pinal and Nathan (), is that the evidence used in reverse inferences should explicitly incorporate the task under consideration. In what follows, we shall focus on our variant (for a discussion of the differences and comparative (dis)advantages of each view, see Del Pinal & Nathan, ). Simply put, the suggestion is to take as the basic units of evidence not simply instances of neural activation in certain locations but rather ordered pairs of neural activation and kinds of tasks, <n i ,Z j > : …”