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What Can Neuroscience Learn from Contemplative Practices?
A recent wave of brain research has advanced our understanding of the neural mechanisms of conscious states, contents and functions. A host of questions remain to be explored, as shown by lively debates between models of higher vs. lower-order aspects of consciousness, as well as global vs. local models. (Baars 2007; Block, 2009; Dennett and Cohen, 2011; Lau and Rosenthal, 2011). Over some twenty-five centuries the contemplative traditions have also developed explicit descriptions and taxonomies of the mind, to interpret experiences that are often reported in contemplative practices (Radhakrishnan & Moore, 1967; Rinbochay & Naper, 1981). These traditional descriptions sometimes converge on c...
Non-Ordinary Mental Expressions
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Comparative Neuropsychology and Brain Imaging
This volume is a special commemorative publication in honor of Professor Dr. Ulrike Halsband, from the University of Freiburg in Germany, on the occasion of her 60th birthday, and includes chapters specially written for the volume, with recent views, reviews and results on such fields as functioneuroanatomytomy, neuropsychology, education, animal behavior, altered states of consciousness, hypnosis and the history of psychology in Germany. The contributors are internationally well-known scholars from academic and clinical institutions abroad in Europe. --
Parapsychology and Religion
Everton Maraldi explores how research on alleged anomalous processes informs the study of religious/spiritual experiences and examines the theoretical and methodological possibilities and challenges of an interdisciplinary dialogue between parapsychology and psychology of religion.
Learning Machine Translation
How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.
Large-scale Kernel Machines
Solutions for learning from large scale datasets, including kernel learning algorithms that scale linearly with the volume of the data and experiments carried out on realistically large datasets. Pervasive and networked computers have dramatically reduced the cost of collecting and distributing large datasets. In this context, machine learning algorithms that scale poorly could simply become irrelevant. We need learning algorithms that scale linearly with the volume of the data while maintaining enough statistical efficiency to outperform algorithms that simply process a random subset of the data. This volume offers researchers and engineers practical solutions for learning from large scale ...
Music and Moral Management in the Nineteenth-Century English Lunatic Asylum
This book traces the role played by music within asylums, the participation of staff and patients in musical activity, and the links drawn between music, health, and wellbeing. In the first part of the book, the author draws on a wide range of sources to investigate the debates around moral management, entertainment, and music for patients, as well as the wider context of music and mental health. In the second part, a series of case studies bring to life the characters and contexts involved in asylum music, selected from a range of public and private institutions. From asylum bands to chapel choirs, smoking concerts to orchestras, the rich variety of musical activity presents new perspectives on music in everyday life. Aspects such as employment practices, musicians’ networks and the purchase and maintenance of musical instruments illuminate the ‘business’ of music as part of moral management. As a source of entertainment and occupation, a means of solace and self-control, and as a device for social gatherings and contact with the outside world, the place of music in the asylum offers valuable insight into its uses and meanings in nineteenth-century England.
Toward Brain-computer Interfacing
This volume presents a timely overview of the latest BCI research, with contributions from many of the important research groups in the field.
Predicting Structured Data
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.
Pattern Recognition
This book constitutes the refereed proceedings of the 28th Symposium of the German Association for Pattern Recognition, DAGM 2006. The book presents 32 revised full papers and 44 revised poster papers together with 5 invited papers. Topical sections include image filtering, restoration and segmentation, shape analysis and representation, recognition, categorization and detection, computer vision and image retrieval, machine learning and statistical data analysis, biomedical data analysis, and more.
