The field of neurofeedback training has proceeded largely without validation. In this article the authors review studies directed at validating sensory motor rhythm, beta and alpha-theta protocols for improving attention, memory, and music performance in healthy participants. Importantly, benefits were demonstrable with cognitive and neurophysiologic measures that were predicted on the basis of...

We study unsupervised learning by developing introspective generative modeling (IGM) that attains a generator using progressively learned deep convolutional neural networks. The generator is itself a discriminator, capable of introspection: being able to self-evaluate the difference between its generated samples and the given training data. When followed by repeated discriminative learning, des...

Historical and empirical data have linked artistic creativity to depression and other affective disorders. This study examined how vulnerability to experiencing negative affect, measured with biological products, and intense negative emotions influenced artistic creativity. The authors assessed participants' baseline levels of an adrenal steroid (dehydroepiandrosterone-sulfate, or DHEAS), previ...

In the 1890s, one of Charcot's most important protégés, Dr. Paul Richer (1849-1933), drew and sculpted a series of representations of the main types of nerve pathology. That series included drawings of pleomorphic hysterical crises and sculptures depicting patients suffering from labio-glosso-laryngeal paralysis and myopathy, as well as Parkinson's disease. Richer was a resident at La Salpêtriè...

Image analogies is a framework for processing images by example. Image analogies uses training data A and A′ in order to learn a filter that can be applied to an unfiltered target image B to produce an analogous image B′. This means that B′ relates to B the same way A′ relates to A. The framework is general and can be applied to many different applications. Typical applications for image analog...

We present sketch-rnn, a recurrent neural network (RNN) able to construct stroke-based drawings of common objects. The model is trained on a dataset of human-drawn images representing many different classes. We outline a framework for conditional and unconditional sketch generation, and describe new robust training methods for generating coherent sketch drawings in a vector format. We demonstra...

The article deals with the problem of artistic image creating in students’ creative works as a productive source an artistic-pedagogical development future teacher artist. An is basis any art form and occupies leading part artwork it has vast significant esthetic value, demonstrating result artist life experience display. analysis theoretical sources, university training internship process fulf...

Artistic image understanding is an interdisciplinary research field of increasing importance for the computer vision and art history communities. One of the goals of this field is the implementation of a system that can automatically retrieve and annotate artistic images. The best approach in the field explores the artistic influence among different artistic images using graph-based learning me...

A support environment for audio-related artistic design is described. The rst part of the paper identiies requirements for artistic design support through an analysis of music composition activities, and presents an artistic design system object model adapted from the more conventional engineering design system technology. The second part examines the problems of representation, visualisation a...

Richard Cytowic has argued that synesthetic experimentation by modern artists was based on deliberate contrivances of sensory fusion and not on involuntary experiences of cross-modal association. He has placed artistic experiments with sensory fusion outside the domain of synesthesia research. Artistic experiments, though historically interesting, are considered irrelevant for the study of syne...