Support vector machines are being used increasingly in affective science as a data-driven classification method and feature reduction technique. Whereas traditional statistical methods typically compare group averages on selected variables, SVMs use a predictive algorithm to learn multivariate patterns that optimally discriminate between groups. In this review, we provide a framework for understanding the methods of SVM-based analyses and summarize the findings of seminal studies that use SVMs for classification or data reduction in the behavioral and neural study of emotion (...) and affective disorders. We conclude by discussing promising directions and potential applications of SVMs in future research in affective science. (shrink)

Classifying different meditation techniques is essential for the progress of meditation research, as this will enable discerning which effects are associated with which techniques, in addition to supporting the development of increasingly effective and efficient meditation-based training programs and clinical interventions. However, both the task of defining meditation itself, as well as defining specific techniques, faces many fundamental challenges. Here we describe problems involved in this endeavor and suggest an integrated model for defining meditation. For classifying different meditation techniques, we (...) draw on classical, contemporary, and holistic systems of classification. We analyze different techniques and propose that all meditation techniques are based on a specific set of activities, that is: focusing, releasing, imagining, and moving in relation to an object of meditation, including fields of experience. Meditative activities can be combined and unified in the activities of observing, producing, and being aware. All meditative activities are unified in awareness of awareness. Defining specific meditation techniques may be done by specifying which activities and objects are involved. The advantage of our approach is that it can potentially account for the inner workings of all current systems of classification and hence it lays the foundation for formulating an overarching system of meditation that can guide future research and practice. (shrink)