Perspectives on Psychological Science

Addiction models have frequently invoked motivational mechanisms to explain the initiation and maintenance of addictive behaviors. However, in doing so, these models have emphasized the unique characteristics of addictive behaviors and overlooked the commonalities that they share with motivated behaviors in general. As a consequence, addiction research has failed to connect with and take advantage of promising and highly relevant advances in motivation and self-regulation research. The present article is a call for a convergence of the previous approaches to addictive behavior and the new advances in basic motivation and self-regulation. The authors emphasize the commonalities that addictive behaviors may share with motivated behavior in general. In addition, it is suggested that the same psychological principles underlying motivated action in general may apply to understand challenging aspects of the etiology and maintenance of addictive behaviors.

Can interventions meaningfully increase intelligence? If so, how? The Database of Raising Intelligence is a continuously updated compendium of randomized controlled trials that were designed to increase intelligence. In this article, the authors examine nearly every available intervention involving children from birth to kindergarten, using meta-analytic procedures when more than 3 studies tested similar methods and reviewing interventions when too few were available for meta-analysis. This yielded 4 meta-analyses on the effects of dietary supplementation to pregnant mothers and neonates, early educational interventions, interactive reading, and sending a child to preschool. All 4 meta-analyses yielded significant results: Supplementing infants with long-chain polyunsaturated fatty acids, enrolling children in early educational interventions, reading to children in an interactive manner, and sending children to preschool all raise the intelligence of young children.

One of the oldest questions in cognitive science is whether cognitive operations are modular or distributed across domains. We propose that fMRI has made a unique contribution to this question by elucidating the nature of structure–function relations. We focus our discussion on language, which is the classic domain for arguments in favor of domain specificity and a fixed neural architecture. We argue that fMRI has provided evidence for the idea that there is a dynamic functional architecture, rather than a fixed neural architecture, that emerges across the lifespan, pursuant to injury and in response to language experience. We use empirical examples to highlight how fMRI has helped restructure theory by shedding light on how functionally distinct modular components of the grammar can recruit some of the same neural regions, how areas considered to be domain-specific may be recruited in a domain-general fashion, and how language network specialization and left lateralization dynamically emerge in response to experience. fMRI provides a window into neural plasticity and dynamic functional organization not easily afforded by behavior alone.

In the 1980s and 1990s, there was a major theoretical debate in the memory domain regarding the multiple memory systems and processing modes frameworks. The components of processing framework argued for a middle ground: Instead of neatly divided memory systems or processing modes, this framework proposed the existence of numerous processing components that are recruited in different combinations by memory tasks and yield complex patterns of associations and dissociations. Because behavioral evidence was not sufficient to decide among these three frameworks, the debate was largely abandoned. However, functional neuroimaging evidence accumulated during the last two decades resolves the stalemate, because this evidence is more consistent with the components framework than with the other two frameworks. For example, functional neuroimaging evidence shows that brain regions attributed to one memory system can contribute to tasks associated with other memory systems and that brain regions attributed to the same processing mode (perceptual or conceptual) can be dissociated from each other. Functional neuroimaging evidence suggests that memory processes are supported by transient interactions between a few regions called process-specific alliances. These conceptual developments are an example of how functional neuroimaging can contribute to theoretical debates in cognitive psychology.

A central question in the study of the mind is how cognitive functions are shaped by a complex interplay of genetic and experiential processes. Recent evidence from cultural neuroscience indicates that cultural values, practices, and beliefs influence brain function across a variety of cognitive processes from vision to social cognition. This evidence extends to low-level perceptual systems comprised of domain-specific mechanisms, suggesting the importance of ecological and cultural variation in the evolutionary and developmental processes that give rise to the human mind and brain. In this article, we argue that investigating the architecture of the human mind will require understanding how the human mind and brain shape and are shaped by culture–gene coevolutionary processes.

The conception of the aging mind that emerged from behavioral and structural imaging studies portrayed the mind as a victim of passive deterioration and decline with age, with a few domains of preserved function. The advent of functional neuroimaging has demonstrated that the aging brain is an adaptive and plastic structure that responds dynamically to cognitive challenge and structural deterioration—thus, fundamentally changing views of cognitive aging. In addition, a neural theory of the aging mind based on behavioral data—the dedifferentiation view of cognitive aging—was largely confirmed when neuroimaging technology became available to test it. We argue that functional neuroimaging has advanced cognitive aging theories by creating a stronger emphasis on compensatory mechanisms related to brain plasticity and potential reorganization as evidenced by the resurgence of interest and research in cognitive training research designed to improve cognition through enhancement of neural structures or reorganization of functional circuitry.

What mechanisms underlie declines in memory and other cognitive abilities as we age? Before functional neuroimaging, answers to this question relied primarily on behavioral measures despite aging’s obvious roots in biology. Functional imaging now permits a glimpse of the biological underpinnings of cognition, and recent discoveries offer new insights into how brain function differs in older age. Focusing primarily on studies of working memory, I discuss how neuroimaging provides converging evidence to support and clarify mechanistic accounts of cognitive aging, and how imaging can guide the development of cognitive interventions. These methods promise to adjudicate between hypothesized mechanisms of age differences, and they are generating new, testable hypotheses to elucidate cognitive decline, cognitive stability, and plasticity in older age.

Environmental cues often remind us of earlier experiences by triggering the reactivation of memories of events past. Recent evidence suggests that memory reactivation can be observed using functional MRI and that distributed pattern analyses can even provide evidence of reactivation on individual trials. The ability to measure memory reactivation offers unique and powerful leverage on theoretical issues of long-standing interest in cognitive psychology, providing a means to address questions that have proven difficult to answer with behavioral data alone. In this article, we consider three instances. First, reactivation measures can indicate whether memory-based inferences (i.e., generalization) arise through the encoding of integrated cross-event representations or through the flexible expression of separable event memories. Second, online measures of memory reactivation may inform theories of forgetting by providing information about when competing memories are reactivated during competitive retrieval situations. Finally, neural reactivation may provide a window onto the role of replay in memory consolidation. The ability to track memory reactivation, including at the individual trial level, provides unique leverage that is not afforded by behavioral measures and thus promises to shed light on such varied topics as generalization, integration, forgetting, and consolidation.

Research on cognition often leads to debates that are centered on how many processes exist and how they interact to guide behavior. These debates occur across a range of domains and are often difficult to resolve with behavioral data because similar behavioral predictions can be made by models with different core assumptions. Such model mimicry limits researchers’ ability to find differential support for one type of model over the other using behavioral data alone. We argue that functional neuroimaging can help overcome this problem by providing additional dependent measures to constrain model testing. Recent advances in analysis, like multivariate approaches, expand the amount and type of data available for model testing. We illustrate the benefits of this approach by highlighting imaging results that directly speak to the debate over the nature of recollection processes in memory. These results show how functional neuroimaging can advance studies of cognition by providing richer data sets for contrasting cognitive models.

The use of fMRI to inform cognitive theory depends upon the assumption that there is an isomorphic relationship between functional states and brain states. Even if this assumption is accepted, employing fMRI to make cognitive inferences is not straightforward. We discuss these inferential difficulties and describe an example in which fMRI data has had a significant impact on a cognitive theory despite them. The embodied cognition framework states that accessing a conceptual feature engages the same processes that are active when the feature is directly experienced. fMRI studies have consistently found that accessing a feature activates cortical regions slightly anterior to the regions activated when the feature is experienced. We suggest that this neural dissociation between accessing and perceiving a feature is inconsistent with the strong form of embodied cognition theory and that this inconsistency would likely not have been identified without fMRI. We describe how the observation of this forward shift has led to new ways of thinking about perceptual and conceptual representations and the relation between them. Finally, we argue that despite the strong assumptions that are needed to make functional inferences from fMRI, this does not detract from its value as a source of convergent evidence.

The idea of fMRI’s “seductive allure” is supported by two widely cited studies. Upon closer analysis of these studies, and in light of more recent research, we find little empirical support for the claim that brain images are inordinately influential.

Neuroimaging can inform cognitive theories to the extent that particular patterns of brain activity are sensitively and specifically associated with particular types of cognitive processes. We illustrate the utility of neuroimaging data in one specific case: understanding cognitive influences on pain. We first argue that pain self-reports are often inadequate to fully characterize pain experience and the processes that underlie it. Then, we describe how neuroimaging measures have been used to corroborate the effects of psychological manipulations on pain by focusing on placebo treatments and demonstrating effects on the best available correlates of pain experience. In addition, using placebo analgesia as an example, we argue that brain evidence is useful for building psychological theories likely to yield valid and generalizable predictions, because biologically informed theories are grounded in the constraints inherent in the relevant physiological systems. Finally, we suggest that neuroimaging findings will become increasingly useful for constraining psychological inference as brain patterns diagnostic of particular types of mental events are identified and characterized. In our view, the relationships between biological findings and cognitive theory are empirically based and must develop through an iterative process of synthesis across studies, topics, and methods.

Work on functional neuroimaging of cognition falls into two categories. The first aims at localizing specific cognitive subsystems in specific brain regions. In this research, the cognitive subsystems in question need to be defined independently of the neuroimaging data because the interpretation of the data requires such definition; so functional neuroimaging is informed by cognitive theories rather than informing them. The second category uses neuroimaging data to test cognitive theories. As cognitive theories are expressed in cognitive terms, such theories have to be embellished by explicit proposals about relationships between cognition and the brain if they are to become capable of generating predictions about the results of experiments that use functional neuroimaging. Whether functional neuroimaging can succeed in informing a cognitive theory depends critically upon the plausibility of such supplementary proposals. It is also critical to avoid the “consistency fallacy.” When neuroimaging data from an experiment are consistent with predictions from a particular cognitive theory, this cannot be offered as evidence in support of that theory unless it can be shown that there were possible other outcomes of the experiment that are inconsistent with the theory—outcomes that would have falsified predictions from the theory had they been obtained.

In this article, we ask about the contribution of fMRI data to our understanding of theories of cognition and about the contribution of theories of cognition to our understanding of fMRI data. Experiments using fMRI can contribute to our understanding of cognition when they are designed to test the predictions of a particular cognitive theory. Although not all cognitive theories make clear predictions about patterns of activity in the brain fMRI experiments are often well suited to testing the predictions of those that do. However, many fMRI studies that are concerned with cognitive functional neuroanatomy are not designed to test predictions of cognitive theories but are instead designed to investigate the role played by different regions of the brain in cognitive activity. These fMRI studies do not shed light on cognitive theories but instead depend on cognitive theories to interpret the data—an interpretation that is only as valid as the cognitive theory on which it is based. These considerations suggest that the relationship between fMRI and theories of cognition is a two-way street.

How can functional magnetic resonance imaging (fMRI) advance cognitive theory? Some have argued that fMRI can do little beyond localizing brain regions that carry out certain cognitive functions (and may not even be able to do that). However, in this article, we argue that fMRI can inform theories of cognition by helping to answer at least four distinct kinds of questions. Which mental functions are performed in brain regions specialized for just that function (and which are performed in more general-purpose brain machinery)? When fMRI markers of a particular Mental Process X are found, is Mental Process X engaged when people perform Task Y? How distinct are the representations of different stimulus classes? Do specific pairs of tasks engage common or distinct processing mechanisms? Thus, fMRI data can be used to address theoretical debates that have nothing to do with where in the brain a particular process is carried out.