Beyond Brain Mapping: Using Neural Measures to Predict Real-World Outcomes

Abstract

One goal of social science in general, and of psychology in particular, is to understand and predict human behavior. Psychologists have traditionally used self-report measures and performance on laboratory tasks to achieve this end. However, these measures are limited in their ability to predict behavior in certain contexts. We argue that current neuroscientific knowledge has reached a point where it can complement other existing psychological measures in predicting behavior and other important outcomes. This brain-as-predictor approach integrates traditional neuroimaging methods with measures of behavioral outcomes that extend beyond the immediate experimental session. Previously, most neuroimaging experiments focused on understanding basic psychological processes that could be directly observed in the laboratory. However, recent experiments have demonstrated that brain measures can predict outcomes (e.g., purchasing decisions, clinical outcomes) over longer timescales in ways that go beyond what was previously possible with self-report data alone. This approach can be used to reveal the connections between neural activity in laboratory contexts and longer-term, ecologically valid outcomes. We describe this approach and discuss its potential theoretical implications. We also review recent examples of studies that have used this approach, discuss methodological considerations, and provide specific guidelines for using it in future research.

Keywords: brain-as-predictor; brain-behavior relationship; ecological validity; neuroscience; prediction.

Fig. 1

The brain-as-predictor approach. Traditionally, psychologists have been interested in mapping the relationship between psychological processes (e.g., cognitions, emotions) and real-world outcomes (e.g., health behaviors, discrimination). In contrast, neuroscientists have traditionally used neuroimaging tools to map the relationship between psychological process and brain mechanisms. The brain-as-predictor approach integrates these methods by using brain systems that previously have been linked to specific psychological processes to predict meaningful outcomes beyond the confines of the laboratory. This approach offers new ways to explain previously unaccounted variance in behavioral outcomes and to test whether hypothesized psychological processes (via their neural associates) are predictive of those outcomes. Bidirectional arrows emphasize that each construct is likely to affect the others and that the brain-as-predictor approach complements existing methods for studying the other relationships shown. Note that arrows in this figure indicate conceptual relationships between independent and dependent variables rather than causality; manipulation of brain function (e.g., using transcranial magnetic stimulation or in clinical lesion studies) is necessary in order to establish causal relationships between brain measures and behavior.