Fundamentals of functional neuroimaging

INTRODUCTION Functional neuroimaging techniques have become a central research tool for psychologists, cognitive scientists, and neuroscientists. The use of neuroimaging data from functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies is central to the fields of cognitive neuroscience, affective neuroscience, social cognitive neuroscience, neuroeconomics, and related disciplines. fMRI and PET data are being combined with data on human performance, psychophysiology, genetics, and computational models of performance and neural function in increasingly sophisticated ways. The result is enhanced models of human brain function in relation to thought, emotion, and behavior, which can be used to both understand the mind and guide applied research on performance enhancement, clinical assessment, and treatment. The best such models are informed by the rich histories of cognitive psychology and psychophysiology, and - due largely to the integration of neuroimaging data - are increasingly grounded in brain physiology. This grounding permits stronger and more specific connections with the neurosciences and biomedical sciences, allowing behavioral scientists to leverage a vast and growing literature on brain systems developed in these fields. All neuroscience methods have limitations, and neuroimaging is no exception. The current trend is toward increasingly multidisciplinary approaches that use multiple methodologies to overcome some of the limitations of each method used in isolation. For example, currently available techniques allow electroencephalography (EEG) and fMRI data to be collected simultaneously (Goldman, Stern, Engel Jr., & Cohen, 2000), which provides improved temporal precision, among other benefits. Neuroimaging data are also being combined with transcranial magnetic stimulation (TMS), combining the ability of neuroimaging to observe brain activity with the ability of TMS to manipulate brain function and examine causal effects (Bohning et al., 1997). The rapid pace of development and interdisciplinary nature of the neurobehavioral sciences presents an enormous challenge to researchers. Moving this kind of science forward requires a collaborative team with expertise in psychology, neuroanatomy, neurophysiology, physics, biomedical engineering, statistics, signal processing, and other disciplines. Having a successful team requires that individuals push beyond the boundaries of their disciplines and develop expertise in multiple areas, so that there is enough overlap that the team can work well together.