Everyone is familiar with the speed-accuracy trade-off (SAT). To make good choices, we need to balance the conflicting demands of fast and accurate decision making. After all, hasty decisions often lead to poor choices, but accurate decisions may be useless if they take too long. This notion is intuitive because it reflects a fundamental aspect of cognition: not only do we deliberate over the evidence for decisions, but we can control that deliberative process. This control raises many questions for the study of choice behaviour and executive function. For example, how do we figure out the appropriate balance between speed and accuracy on a given task? How do we impose that balance on our decisions, and what is its neural basis? Researchers have addressed these and related questions for decades, using a variety of methods and offering answers at different levels of abstraction. Given this diverse methodology, our aim is to provide a unified view of the SAT. Extensive analysis of choice behaviour suggests that we make decisions by accumulating evidence until some criterion is reached. Thus, adjusting the criterion controls how long we accumulate evidence and therefore the speed and accuracy of decisions. This simple framework provides the platform for our unified view. In the pages that follow, leading experts in decision neuroscience consider the history of SAT research, strategies for determining the optimal balance between speed and accuracy, conditions under which this seemingly ubiquitous phenomenon breaks down, and the neural mechanisms that may implement the computations of our unifying framework.

An examination of the link between the vigor with which we move and the value that the brain assigns to the goal of the movement. Why do we reflexively run toward people we love, but only walk toward others? In Vigor, Reza Shadmehr and Alaa Ahmed examine the link between how the brain assigns value to things and how it controls our movements. They find that brain regions thought to be principally involved in decision making also affect movement vigor--and that brain regions thought to be principally responsible for movement also bias patterns of decision making.

Goal-Directed Decision Making: Computations and Neural Circuits examines the role of goal-directed choice. It begins with an examination of the computations performed by associated circuits, but then moves on to in-depth examinations on how goal-directed learning interacts with other forms of choice and response selection. This is the only book that embraces the multidisciplinary nature of this area of decision-making, integrating our knowledge of goal-directed decision-making from basic, computational, clinical, and ethology research into a single resource that is invaluable for neuroscientists, psychologists and computer scientists alike. The book presents discussions on the broader field of decision-making and how it has expanded to incorporate ideas related to flexible behaviors, such as cognitive control, economic choice, and Bayesian inference, as well as the influences that motivation, context and cues have on behavior and decision-making. - Details the neural circuits functionally involved in goal-directed decision-making and the computations these circuits perform - Discusses changes in goal-directed decision-making spurred by development and disorders, and within real-world applications, including social contexts and addiction - Synthesizes neuroscience, psychology and computer science research to offer a unique perspective on the central and emerging issues in goal-directed decision-making

This is the most comprehensive and up-to-date account of the control of vertebrate head movements and its biomechanical and neural basis. It covers the entire spectrum of research on head-neck movements, ranging from the global description and analysis of a particular behavior to its underlying mechanisms at the level of neurotransmitter release and membrane biophysics.

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. - The first complete volume on MATLAB focusing on neuroscience and psychology applications - Problem-based approach with many examples from neuroscience and cognitive psychology using real data - Illustrated in full color throughout - Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Gregory Bateson was a philosopher, anthropologist, photographer, naturalist, and poet, as well as the husband and collaborator of Margaret Mead. This classic anthology of his major work includes a new Foreword by his daughter, Mary Katherine Bateson. 5 line drawings.