Mathematical Psychology and Psychophysiology promotes an understanding of the mind and its neural substrates by applying interdisciplinary approaches to issues concerning behavior and the brain. The contributions present model from many disciplines that share common, conceptual, functional, or mechanistic substrates and summarize recent models and data from neural networks, mathematical genetics, psychoacoustics, olfactory coding, visual perception, measurement, psychophysics, cognitive development, and other areas. The contributors to Mathematical Psychology and Psychophysiology show the conceptual and mathematical interconnectedness of several approaches to the fundamental scientific problem of understanding mind and brain. The book's interdisciplinary approach permits a deeper understanding of theoretical advances as it formally structures a broad overview of the data.
Mathematical Psychology and Psychophysiology promotes an understanding of the mind and its neural substrates by applying interdisciplinary approaches to issues concerning behavior and the brain. The contributions present model from many disciplines that share common, conceptual, functional, or mechanistic substrates and summarize recent models and data from neural networks, mathematical genetics, psychoacoustics, olfactory coding, visual perception, measurement, psychophysics, cognitive development, and other areas. The contributors to Mathematical Psychology and Psychophysiology show the conceptual and mathematical interconnectedness of several approaches to the fundamental scientific problem of understanding mind and brain. The book's interdisciplinary approach permits a deeper understanding of theoretical advances as it formally structures a broad overview of the data.
This is the last major work of Eugene N. Sokolov, Professor of Psychophysiology at Moscow State University from 1950 to 2008. It summarizes the contributions of a lifetime on the neural mechanism of consciousness. Working at the intersection of psychology, neurophysiology and mathematics, Sokolov early introduced the concept of quantifiable 'difference in neuronal activity' and 'cognitive distance' as corresponding metrics in the physical and mental models of reality. He demonstrated the power of multidimensional vector mathematics to represent the neural computations that mediate between the brain's neural model and the mind's mental model of reality. Sokolov and colleagues showed a mathematical commonality among the neuronal mechanisms that mediate the perception of basic features of visual stimuli including color, brightness, line orientation and motion. This led to a general vector model linking perceptual and memory processes to adaptive motor mechanisms. They extended the model to encompass broader, more complex functions, such as the perception of emotions in facial expressions, semantic differences in verbal stimuli and differential executive control mechanisms. Integrating evidence from human psychophysics, animal neurophysiology and vector mathematics they developed a unified model to characterize quantitatively many complex relations between objective and subjective aspects of reality. Sokolov's studies of neuronal mechanisms of mental phenomena led him to distinguish two categories of neurons: 'consciousness neurons' directly associated with awareness of perceptual, emotional and cognitive events, and neurons that are necessary for, but not directly involved in, conscious processes. The book integrates his findings with major themes shaping twenty-first century understanding of the brain-mind relationship. It relates the findings both to work of other Russian investigators, such as Pavlov, Luria, and Rusinov, and to work of many Western researchers, including von Bekesy, Eccles, Edelman, Ehrenstein, Grossberg, John, Koch and Crick, Ledoux, Llinas, Milner, Penfield, Penrose, Posner, and Schrödinger.
This Oxford Handbook offers a comprehensive and authoritative review of important developments in computational and mathematical psychology. With chapters written by leading scientists across a variety of subdisciplines, it examines the field's influence on related research areas such as cognitive psychology, developmental psychology, clinical psychology, and neuroscience. The Handbook emphasizes examples and applications of the latest research, and will appeal to readers possessing various levels of modeling experience. The Oxford Handbook of Computational and mathematical Psychology covers the key developments in elementary cognitive mechanisms (signal detection, information processing, reinforcement learning), basic cognitive skills (perceptual judgment, categorization, episodic memory), higher-level cognition (Bayesian cognition, decision making, semantic memory, shape perception), modeling tools (Bayesian estimation and other new model comparison methods), and emerging new directions in computation and mathematical psychology (neurocognitive modeling, applications to clinical psychology, quantum cognition). The Handbook would make an ideal graduate-level textbook for courses in computational and mathematical psychology. Readers ranging from advanced undergraduates to experienced faculty members and researchers in virtually any area of psychology--including cognitive science and related social and behavioral sciences such as consumer behavior and communication--will find the text useful.
This volume is the third volume of papers originating from the European Mathematical Psychology Group. Earlier volumes were: E. Degreef & J. van Buggenhaut (Eds.), Trends In Mathematical Psychology, Amsterdam, North-Holland Publ. Cy., 1984, and E.E. Roskam & R. Suck (Eds.), Progress in Mathematical Psychology, Amsterdam: Elsevier Science Publ. As the title indicates, this volume presents work in progress, which was reported in one of the recent annual meetings of the European Mathematical Psychology Group. The Group finds it worthwhile to disseminate this work, using a review process which is somewhat less strict, and a publication lag which is shorter, than would be the case for standard international journals. The editor is happy that the meetings of the European Mathematical Psychology Group are regularly attended by colleagues from overseas. Their contributions also appear in this volume, as was the case in earlier volumes. Despite apparent heterogeneity, the reader will observe that European mathemati cal psychologists have a keen interest in basic issues of mathematical modeling and measurement theory, and that also substantive topics, such as decision making, per ception, and performance are studied in the context of formal modeling. Also, and per haps of more than casual importance for future developments, is the fact that theory, experiment, and data analysis go closely together. It should therefore not surprise that psychometric topics, and topics in scaling are represented in this volume, alongside with topics of a more 'purely' mathematical nature.
The SAGE Library in Social and Personality Psychology Methods provides students and researchers with an understanding of the methods and techniques essential to conducting cutting-edge research. Each volume within the Library explains a specific topic and has been written by an active scholar (or scholars) with expertise in that particular methodological domain. Assuming no prior knowledge of the topic, the volumes are clear and accessible for all readers. In each volume, a topic is introduced, applications are discussed, and readers are led step by step through worked examples. In addition, advice about how to interpret and prepare results for publication are presented. Social Psychophysiology for Social and Personality Psychology provides methodological and technical information to help social psychologists make valid and valuable use of peripheral neurophysiological and endocrine measures of psychological constructs.
