The scientific study of consciousness features a vast array of conflicting theories, but cross-disciplinary exchange between researchers from different camps is not always prevalent. This book seeks to address these complexities by providing a thorough introduction to the field while remaining accessible to those new to the topic. By exploring empirical methods, surveying a variety of competing theories, and outlining challenges for current approaches, it equips readers with the tools to evaluate existing theories. It also showcases contributions from the originators and leading proponents of today's most influential theories, providing unparalleled depth and clarity into diverse theoretical perspectives. Offering a thorough overview of scientific consciousness studies, this book presents new perspectives on a topic that has long puzzled scientists and philosophers alike.
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A deep dive into consciousness science, covering empirical methods, competing theories, and overcoming contemporary challenges.
Part I. The Science of Consciousness: History, Methods, and
Characteristics:
1. Introduction; 1.1. A historical perspective on
consciousness; 1.2. Philosophical perspectives on consciousness; 1.3. What
this book has to offer; 1.4. How to read this book;
2. Experimental
approaches to consciousness: 2.1 Experimental approaches to states of
consciousness; 2.2 Experimental approaches to contents of consciousness; 2.3
Problems, pitfalls, and methodological considerations;
3. Characteristics of
consciousness: 3.1 Where in the brain?: The neural correlates of
consciousness (NCC); 3.2 When do contents 'reach' consciousness?: The
temporal aspects of consciousness; 3.3 Access versus phenomenal
consciousness: is there 'overflow'?; 3.4 Is consciousness discrete or
graded?; 3.5 Is consciousness unified?; 3.6 Attention and neglect; 3.7
Phylogenetic and ontogenetic emergence of consciousness: Evolution, animals,
mirrors, and babies; 3.8 The role of consciousness; 3.9 The quest for
generalisability; Part II. Portrayals and Evaluations of Empirical ToCs:
4.
What is a theory of consciousness?: 4.1. The self-organizing
metarepresentational account (SOMA) Axel Cleeremans; 4.2. Challenge I: the
non-conscious alternative;
5. Process theories: 5.1. Predictive processing
theory and consciousness (PPT) Anil Seth; 5.2. The global neuronal workspace
theory of consciousness (GNWT) Claire Sergent and Daphné Rimsky-Robert; 5.3.
Higher order theories (HOTs) and the perceptual reality monitoring theory
(PRM) Matthias Michel; 5.4. Challenge II: underconstraining consciousness:
the small network argument;
6. Causal structure theories: 6.1. Recurrent
processing theory (RPT) Victor A. F. Lamme; 6.2. Integrated information
theory (IIT) William Marshall; 6.3 Challenge III: the unfolding argument;
7.
Biological theories: 7.1. Dendritic integration theory (DIT) Jaan Aru, Talis
Bachmann, Mototaka Suzuki and Matthew E. Larkum; 7.2. The 'felt uncertainty'
theory of consciousness (FUT) Mark Solms; 7.3. Challenge IV: the other
systems argument;
8. Quantum theories: 8.1. The orchestrated objective
reduction theory of consciousness (Orch-OR) Stuart Hameroff; 8.2. Challenges
for quantum theories of consciousness;
9. Illusionism: 9.1. The attention
schema theory (AST) Michael S. A. Graziano; 9.2. The sensorimotor theory of
phenomenal consciousness (SMT) J. Kevin O'Regan; 9.3. Challenges for
illusionist theories; Part III. The Science of Consciousness:
10. The science
of consciousness: an opinionated perspective: 10.1 Scientific theories of
consciousness; 10.2 At the core of current ToCs; 10.3 How to escape the core
problems of today's ToCs?; 10.4 Summary; Appendix; References.
Michael H. Herzog is a professor for Psychophysics at the Brain Mind Institute of the Swiss Federal Technology Institute of Lausanne. He previously studied Mathematics, Biology, and Philosophy at the Universities of Erlangen, Tübingen, and the Massachusetts Institute of Technology. Michael is co-author of the Open Access book Understanding Statistics and Experimental Design (2019). Aaron Schurger is Assistant Professor of Computational Cognitive Neuroscience at Chapman University. He studied computer science at Indiana University, Bloomington and completed his Ph.D. in Psychology and Neuroscience at Princeton University. Throughout his career, Aaron has conducted research on conscious versus non-conscious neural information processing, with a focus on the psychophysics of near-threshold sensory perception. Adrien Doerig is a professor in Cognitive Computational Neuroscience at Freie Universität Berlin. He studied neuroscience and physics at the Swiss Federal Technology Institute of Lausanne, where he completed his Ph.D. Adrien's research focuses on applying artificial neural network models to deepen our understanding human cognition, and using psychophysics, computational modelling, and philosophical approaches to study consciousness scientifically.
