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Although science has made considerable progress in discovering the neural basis of cognition, how consciousness arises remains elusive. In this book, Pennartz analyzes which aspects of conscious experience can be peeled away to access its core: the relationship between brain processes and the qualitative nature of consciousness. Pennartz traces the problem back to its historical foundations and connects early ideas to contemporary computational neuroscience. What can we learn from neural network models, and where do they fall short in bridging the gap between neurons and conscious experiences? How can neural models of cognition help us define requirements for conscious processing in the brain? These questions underlie Pennartz’s examination of the brain’s anatomy and neurophysiology. This analysis is not limited to visual perception but broadened to include other sensory modalities and their integration. Formulating a representational theory, Pennartz outlines properties that complex neural structures must express to process information consciously. This theoretical framework is constructed using empirical findings from neuroscience and from theoretical arguments such as the ‘Cuneiform Room’ and the ‘Wall Street Banker’. Positing that qualitative experience is a multimodal and multilevel phenomenon at its roots, Pennartz places this body of theory in the wider context of mind-brain philosophy.

Our intuition tells us that we, our conscious selves, cause our own voluntary acts. Yet scientists have long questioned this; Thomas Huxley, for example, in 1874 compared mental events to a steam whistle that contributes nothing to the work of a locomotive. New experimental evidence (most notably, work by Benjamin Libet and Daniel Wegner) has brought the causal status of human behavior back to the forefront of intellectual discussion. This multidisciplinary collection advances the debate, approaching the question from a variety of perspectives. The contributors begin by examining recent research in neuroscience which suggests that consciousness does not cause behavior, offering the outline of an empirically based model which shows how the brain causes behavior and where consciousness might fit in. Other contributors address the philosophical presuppositions that may have informed the empirical studies, raising questions about what can be legitimately concluded about the existence of free will from Libet’s and Wegner’s experimental results. Others examine the effect recent psychological and neuroscientific research could have on legal, social, and moral judgments of responsibility and blame—in situations including a Clockwork Orange-like scenario of behavior correction.

Humans are awesome. Our brains are gigantic, seven times larger than they should be for the size of our bodies, use 25% of all the energy the body requires each day, and became enormous in hardly any time in evolution, leaving our cousins, the great apes, behind. So the human brain is special, right? Wrong: according to the evidence uncovered by the author, humans have developed cognitive abilities that outstrip those of all other animals because we have a brain built in the image of other primate brains that managed to gather the largest number of neurons in the cerebral cortex due to a technological innovation that allowed a larger caloric intake in less time: cooking.

This book offers a range of perspectives on a simple problem: How does the brain choose efficiently and adaptively among options to ensure coherent, goal-directed behavior? The contributors, from fields as varied as anatomy, psychology, learning theory, neuroimaging, neurophysiology, behavioral economics, and computational modeling, present an overview of key approaches in the study of cognitive control and decision making. The book presents a survey of cutting-edge research on the topic. The chapters consider such topics as the anatomical and physiological basis of control, examining core components of the control system, including contributions of the cerebral cortex, the ways in which subcortical brain regions underpin the control functions of the cortex, and neurotransmitter systems; variations in control seen in the development from adolescence to adulthood, in healthy adults, and in patient populations; recent developments in computational approaches, including reinforcement learning; and overarching trends in the current literature, including neuroeconomics, social decision making, and model-based approaches to data from neuroimaging and electrophysiology.

For many psychiatric disorders, neurobiological findings do not help to diagnose a specific disease or to predict its outcome. This book suggests to take a new look at mental disorders by using computational models to better understand human decision making. It shows how such models can be applied to basic learning mechanisms that cut across established nosological boundaries of mental disorders. Such a computational and dimensional approach focuses on the malleability of human behavior and its biological underpinnings. The book argues that this computational and dimensional approach can help to promote and focus neurobiological research, however, it does not replace an anthropological understanding of clinical questions including the definition of mental disorders and ethical considerations. This is illustrated by describing the new understanding of mental disorders with respect to clinical and neuro-computational aspects of psychosis, affective and addictive disorders.