Over the past decade, an explosion of empirical research in a variety of fields has allowed us to understand human moral sensibility as a sophisticated integration of cognitive, emotional, and motivational mechanisms shaped through evolution, development, and culture. Evolutionary biologists have shown that moral cognition evolved to aid cooperation; developmental psychologists have demonstrated that the elements that underpin morality are in place much earlier than we thought; and social neuroscientists have begun to map brain circuits implicated in moral decision making. This volume offers an overview of current research on the moral brain, examining the topic from disciplinary perspectives that range from anthropology and neurophilosophy to justice and law.
The contributors address the evolution of morality, considering precursors of human morality in other species as well as uniquely human adaptations. They examine motivations for morality, exploring the roles of passion, extreme sacrifice, and cooperation. They go on to consider the development of morality, from infancy to adolescence; findings on neurobiological mechanisms of moral cognition; psychopathic immorality; and the implications for justice and law of a more biological understanding of morality. These new findings may challenge our intuitions about society and justice, but they may also lead to more a humane and flexible legal system.
Scott Atran, Abigail A. Baird, Nicolas Baumard, Sarah Brosnan, Jason M. Cowell, Molly J. Crockett, Ricardo de Oliveira-Souza, Andrew W. Delton, Mark R. Dadds, Jean Decety, Jeremy Ginges, Andrea L. Glenn, Joshua D. Greene, J. Kiley Hamlin, David J. Hawes, Jillian Jordan, Max M. Krasnow, Ayelet Lahat, Jorge Moll, Caroline Moul, Thomas Nadelhoffer, Alexander Peysakhovich, Laurent Prétôt, Jesse Prinz, David G. Rand, Rheanna J. Remmel, Emma Roellke, Regina A. Rini, Joshua Rottman, Mark Sheskin, Thalia Wheatley, Liane Young, Roland Zahn
The computer analogy of the mind has been as widely adopted in contemporary cognitive neuroscience as was the analogy of the brain as a collection of organs in phrenology. Just as the phrenologist would insist that each organ must have its particular function, so contemporary cognitive neuroscience is committed to the notion that each brain region must have its fundamental computation. In After Phrenology, Michael Anderson argues that to achieve a fully post-phrenological science of the brain, we need to reassess this commitment and devise an alternate, neuroscientifically grounded taxonomy of mental function.
Anderson contends that the cognitive roles played by each region of the brain are highly various, reflecting different neural partnerships established under different circumstances. He proposes quantifying the functional properties of neural assemblies in terms of their dispositional tendencies rather than their computational or information-processing operations. Exploring larger-scale issues, and drawing on evidence from embodied cognition, Anderson develops a picture of thinking rooted in the exploitation and extension of our early-evolving capacity for iterated interaction with the world. He argues that the multidimensional approach to the brain he describes offers a much better fit for these findings, and a more promising road toward a unified science of minded organisms.
For many years, researchers have studied visual recognition with objects—single, clean, clear, and isolated objects, presented to subjects at the center of the screen. In our real environment, however, objects do not appear so neatly. Our visual world is a stimulating scenery mess; fragments, colors, occlusions, motions, eye movements, context, and distraction all affect perception. In this volume, pioneering researchers address the visual cognition of scenes from neuroimaging, psychology, modeling, electrophysiology, and computer vision perspectives.
Building on past research—and accepting the challenge of applying what we have learned from the study of object recognition to the visual cognition of scenes—these leading scholars consider issues of spatial vision, context, rapid perception, emotion, attention, memory, and the neural mechanisms underlying scene representation. Taken together, their contributions offer a snapshot of our current knowledge of how we understand scenes and the visual world around us.
Elissa M. Aminoff, Moshe Bar, Margaret Bradley, Daniel I. Brooks, Marvin M. Chun, Ritendra Datta, Russell A. Epstein, Michèle Fabre-Thorpe, Elena Fedorovskaya, Jack L. Gallant, Helene Intraub, Dhiraj Joshi, Kestutis Kveraga, Peter J. Lang, Jia Li Xin Lu, Jiebo Luo, Quang-Tuan Luong, George L. Malcolm, Shahin Nasr, Soojin Park, Mary C. Potter, Reza Rajimehr, Dean Sabatinelli, Philippe G. Schyns, David L. Sheinberg, Heida Maria Sigurdardottir, Dustin Stansbury, Simon Thorpe, Roger Tootell, James Z. Wang
Each edition of this classic reference has proved to be a benchmark in the developing field of cognitive neuroscience. The fifth edition of The Cognitive Neurosciences continues to chart new directions in the study of the biological underpinnings of complex cognitio—the relationship between the structural and physiological mechanisms of the nervous system and the psychological reality of the mind. It offers entirely new material, reflecting recent advances in the field.
Many of the developments in cognitive neuroscience have been shaped by the introduction of novel tools and methodologies, and a new section is devoted to methods that promise to guide the field into the future—from sophisticated models of causality in brain function to the application of network theory to massive data sets. Another new section treats neuroscience and society, considering some of the moral and political quandaries posed by current neuroscientific methods.
Other sections describe, among other things, new research that draws on developmental imaging to study the changing structure and function of the brain over the lifespan; progress in establishing increasingly precise models of memory; research that confirms the study of emotion and social cognition as a core area in cognitive neuroscience; and new findings that cast doubt on the so-called neural correlates of consciousness.
This book offers a concise and accessible introduction to the emerging field of artificial cognitive systems. Cognition, both natural and artificial, is about anticipating the need for action and developing the capacity to predict the outcome of those actions. Drawing on artificial intelligence, developmental psychology, and cognitive neuroscience, the field of artificial cognitive systems has as its ultimate goal the creation of computer-based systems that can interact with humans and serve society in a variety of ways. This primer brings together recent work in cognitive science and cognitive robotics to offer readers a solid grounding on key issues.
The book first develops a working definition of cognitive systems—broad enough to encompass multiple views of the subject and deep enough to help in the formulation of theories and models. It surveys the cognitivist, emergent, and hybrid paradigms of cognitive science and discusses cognitive architectures derived from them. It then turns to the key issues, with chapters devoted to autonomy, embodiment, learning and development, memory and prospection, knowledge and representation, and social cognition. Ideas are introduced in an intuitive, natural order, with an emphasis on the relationships among ideas and building to an overview of the field. The main text is straightforward and succinct; sidenotes drill deeper on specific topics and provide contextual links to further reading.
Our ordinary, everyday thinking requires an astonishing range of cognitive activities, yet our cognition seems to take place seamlessly. We move between cognitive processes with ease, and different types of cognition seem to share information readily. In this book, David Danks proposes a novel cognitive architecture that can partially explain two aspects of human cognition: its relatively integrated nature and our effortless ability to focus on the relevant factors in any particular situation. Danks argues that both of these features of cognition are naturally explained if many of our cognitive representations are understood to be structured like graphical models.
The computational framework of graphical models is widely used in machine learning, but Danks is the first to offer a book-length account of its use to analyze multiple areas of cognition. Danks demonstrates the usefulness of this approach by reinterpreting a variety of cognitive theories in terms of graphical models. He shows how we can understand much of our cognition—in particular causal learning, cognition involving concepts, and decision making—through the lens of graphical models, thus clarifying a range of data from experiments and introspection. Moreover, Danks demonstrates the important role that cognitive representations play in a unified understanding of cognition, arguing that much of our cognition can be explained in terms of different cognitive processes operating on a shared collection of cognitive representations. Danks’s account is mathematically accessible, focusing on the qualitative aspects of graphical models and separating the formal mathematical details in the text.
Cognitive neuroscience explores the relationship between our minds and our brains, most recently by drawing on brain imaging techniques to align neural mechanisms with psychological processes. In Mind and Brain, William Uttal offers a critical review of cognitive neuroscience, examining both its history and modern developments in the field. He pays particular attention to the role of brain imaging--especially functional magnetic resonance imaging (fMRI)--in studying the mind-brain relationship. He argues that, despite the explosive growth of this new mode of research, there has been more hyperbole than critical analysis of what experimental outcomes really mean. With Mind and Brain, Uttal attempts a synoptic synthesis of this substantial body of scientific literature.
Uttal considers psychological and behavioral concerns that can help guide the neuroscientific discussion; work done before the advent of imaging systems; and what brain imaging has brought to recent research. Cognitive neuroscience, Uttal argues, is truly both cognitive and neuroscientific. Both approaches are necessary and neither is sufficient to make sense of the greatest scientific issue of all: how the brain makes the mind.
In The Measure of Madness, Philip Gerrans offers a novel explanation of delusion. Over the last two decades, philosophers and cognitive scientists have investigated explanations of delusion that interweave philosophical questions about the nature of belief and rationality with findings from cognitive science and neurobiology. Gerrans argues that once we fully describe the computational and neural mechanisms that produce delusion and the way in which conscious experience and thought depend on them, the concept of delusional belief retains only a heuristic role in the explanation of delusion.
Gerrans proposes that delusions are narrative models that accommodate anomalous experiences. He argues that delusions represent the operation of the Default Mode Network (DMN)—the cognitive system that provides the raw material for humans’ inbuilt tendency to provide a subjectively compelling narrative context for anomalous or highly salient experiences—without the “supervision” of higher cognitive processes present in the nondelusional mind. This explanation illuminates the relationship among delusions, dreams, imaginative states, and irrational beliefs that have perplexed philosophers and psychologists for over a century.
Going beyond the purely conceptual and the phenomenological, Gerrans brings together findings from different disciplines to trace the flow of information through the cognitive system, and applies these to case studies of typical schizophrenic delusions: misidentification, alien control, and thought insertion. Drawing on the interventionist model of causal explanation in philosophy of science and the predictive coding approach to the mind influential in computational neuroscience, Gerrans provides a model for integrative theorizing about the mind.
The event-related potential (ERP) technique, in which neural responses to specific events are extracted from the EEG, provides a powerful noninvasive tool for exploring the human brain. This volume describes practical methods for ERP research along with the underlying theoretical rationale. It offers researchers and students an essential guide to designing, conducting, and analyzing ERP experiments. This second edition has been completely updated, with additional material, new chapters, and more accessible explanations. Freely available supplementary material, including several online-only chapters, offer expanded or advanced treatment of selected topics.
The first half of the book presents essential background information, describing the origins of ERPs, the nature of ERP components, and the design of ERP experiments. The second half of the book offers a detailed treatment of the main steps involved in conducting ERP experiments, covering such topics as recording the EEG, filtering the EEG and ERP waveforms, and quantifying amplitudes and latencies. Throughout, the emphasis is on rigorous experimental design and relatively simple analyses. New material in the second edition includes entire chapters devoted to components, artifacts, measuring amplitudes and latencies, and statistical analysis; updated coverage of recording technologies; concrete examples of experimental design; and many more figures. Online chapters cover such topics as overlap, localization, writing and reviewing ERP papers, and setting up and running an ERP lab.
In the last decade, the synergistic interaction of neurosurgeons, engineers, and neuroscientists, combined with new technologies, has enabled scientists to study the awake, behaving human brain directly. These developments allow cognitive processes to be characterized at unprecedented resolution: single neuron activity. Direct observation of the human brain has already led to major insights into such aspects of brain function as perception, language, sleep, learning, memory, action, imagery, volition, and consciousness. In this volume, experts document the successes, challenges, and opportunity in an emerging field.
The book presents methodological tutorials, with chapters on such topics as the surgical implantation of electrodes and data analysis techniques; describes novel insights into cognitive functions including memory, decision making, and visual imagery; and discusses insights into diseases such as epilepsy and movement disorders gained from examining single neuron activity. Finally, contributors consider future challenges, questions that are ripe for investigation, and exciting avenues for translational efforts.
Contributors Ralph Adolphs, William S. Anderson, Arjun K. Bansal, Eric J. Behnke, Moran Cerf, Jonathan O. Dostrovsky, Emad N. Eskandar, Tony A. Fields, Itzhak Fried, Hagar Gelbard-Sagiv, C. Rory Goodwin, Clement Hamani, Chris Heller, Mojgan Hodaie, Matthew Howard III, William D. Hutchison, Matias Ison, Hiroto Kawasaki, Christof Koch, Rüdiger Köhling, Gabriel Kreiman, Michel Le Van Quyen, Frederick A. Lenz, Andres M. Lozano, Adam N. Mamelak, Clarissa Martinez-Rubio, Florian Mormann, Yuval Nir, George Ojemann, Shaun R. Patel, Sanjay Patra, Linda Philpott, Rodrigo Quian Quiroga, Ian Ross, Ueli Rutishauser, Andreas Schulze-Bonhage, Erin M. Schuman, Demetrio Sierra-Mercado, Richard J. Staba, Nanthia Suthana, William Sutherling, Travis S. Tierney, Giulio Tononi, Oana Tudusciuc, Charles L. Wilson