CONEUR-776; NO. OF PAGES 2 Please cite this article in press as: Miller EK, Phelps EA, Preface: Current Opinion in Neurobiology — Cognitive Neuroscience 2010Curr Opin Neurobiol (2010), doi:10.1016/j.conb.2010.03.008 Available online at www.sciencedirect.com Preface: Current Opinion in Neurobiology — Cognitive Neuroscience 2010 Editorial overview Earl K Miller and Elizabeth A Phelps Current Opinion in Neurobiology 2010, 20:1–2 0959-4388/$ – see front matter # 2010 Elsevier Ltd. All rights reserved. DOI 10.1016/j.conb.2010.03.008 Earl K Miller The Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA URL: http://www.ekmiller.org/ Earl K. Miller is the Picower Professor of Neuroscience and Associate Director of MIT’s Picower Institute for Learning and Memory. His work focuses on the neural basis of cognition. Dr. Miller is a Fellow of the American Association for the Advancement of Science and a recipient of the National Academy of Science’s Troland Research Award and the Society for Neuroscience Young Investigator Award. Elizabeth A Phelps Department of Psychology, and Center for Neural Science New York University, New York, NY, USA Elizabeth A Phelps received her PhD from Princeton University and is the silver professor of Psychology and Neural Science at New York University. Her research examines how the human brain processes emotion, particularly as it relates to learning, memory, and decision- making. Dr Phelps is a fellow of the American Association for the Advancement of Science, served as the president of the Society for Neuroeconomics and is the current editor of the APA Journal Emotion. Much of our understanding of the brain is modular. Investigation has necessarily focused on its individual parts’ regions at different levels of analysis (e.g. individual neurons and brain areas), in part because that understanding the parts is a prerequisite to understanding the whole, and in part because of historical limitations inherent in our tools of investigation. But recent years have seen a rise in approaches designed to gain a more integrative understanding of the brain as interacting networks of neurons, areas, and systems. Functional neuroimaging has allowed big pictures of activity throughout the human brain. This permits direct comparisons of patterns of activation across many brain areas simultaneously and, by examining coherent fluctuations in blow flood, identifies putative large- scale, brain-wide, networks (e.g. [1]). There has also been the rise of large- scale multiple-electrode neurophysiology, the implantation of up to 100 or more electrodes, often in multiple brain structures. This allows comparisons of neuron populations in different brain areas that are not confounded by extraneous factors (differences in level of experience, ongoing behavior, etc.) as well as measurements of the relative timing of activity between neurons that give insight into network properties [2]. This growth in integrative approaches is technically and conceptually driven. Many inves- tigators are employing the classic techniques of systems neuroscience (e.g. single-electrodes, microstimulation, and pharmacology) to compare and contrast brain areas and test how they interact. In short, neuroscience is increasingly building on our knowledge about the brain’s parts to begin to put them together. Our goal with this special issue was to highlight integrative approaches to brain function. To this end, we focused on the most integrative of brain functions, cognitive control. Cognitive, or executive, control is the ability to coordinate thought and action by directing them toward goals, often far- removed goals. Thus, by definition, cognitive control involves coordination of multiple brain mechanisms across multiple brain areas and systems. We chose investigators who are addressing how cognitive control results from networks of interacting neurons, areas, and systems. One area of increasing interest is neural oscillations, coordinated rhythmic activity of large numbers of neurons. There is mounting evidence for its role in cognition, as reviewed in several papers in this issue. Duzel et al. discuss the role of gamma and theta rhythms in encoding, consolidation, and retrieval of memories. Jutras and Buffalo also highlight memory formation and outline how gamma and theta rhythms and their interactions in the medial temporal lobe support the processes underlying learning at the cellular level. Engel and Fries focus on beta-band (13–30 Hz) oscillations. www.sciencedirect.com Current Opinion in Neurobiology 2010, 20:1–2