Positive Technology Journal

DXARTS | PROFESSORSHIP in HYBRID ARTS PRACTICE
www.dxarts.washington.edu

Pending budgetary approval, The Center for Digital Arts and Experimental Media (DXARTS) at the University of Washington is seeking to fill a tenured or tenure track faculty position in HYBRID ARTS PRACTICE. Rank is open, and we will consider hires from Assistant to Full Professor with tenure.

Established in 2001, DXARTS is a pioneering experimental arts unit with exciting undergraduate and doctoral degree programs. DXARTS brings together faculty from Art, Music, Dance, Computer Science, Electrical Engineering, Physics, Biology, History of Ideas, and Design in a hybrid research environment dedicated to the invention and exploration of new forms of digital and experimental art.

The successful candidate for this position should be an artist hybrid engaged in advanced generative digital and experimental arts practice, as well as integrating research on the epistemological and ontological questions raised by the broader art, science and technology discipline.

Applicants for this position should at minimum hold a Masters Degree or equivalent experience and present a well documented career of significant creative accomplishments. The ideal candidate will have a strong and deeply integrated background blended across numerous creative, interpretive and technical fields such as art, music, film, design, dance, theater, computer science, cognitive science, engineering, history, psychology, and philosophy.

Applicants should be prepared to pursue innovative art and technology research, as well as teach introductory and advanced courses in comprehensive studio practice, and the history and analysis of digital and experimental arts.

Applications must include: CV, artist statement, statement on pedagogy, and a cohesive portfolio of professional creative work. Support materials must include three references with phone numbers, mail and e-mail addresses, samples of previous course design and recent student work. Portfolio work should be formatted for viewing on any platform. Please include a SASE for return of materials. Also inform us if you will be attending the CAA conference in Los Angeles, CA.

Application materials should be addressed to: Chair, HYBRID ARTS PRACTICE Search Committee, DXARTS, 207 Raitt Hall, Box 353414, University of Washington, Seattle, Washington 98195-3414. Priority will be given to applications received before January 15, 2009. The University of Washington is building a culturally diverse faculty, and strongly encourages applications from female and minority candidates. The University is an Equal Opportunity, Affirmative Action employer.

A competitive recruitment and selection process is being conducted and if a U.S. worker is not selected pursuant to this process, an application for Alien Employment Certification may be filed on behalf of an alien to fill this job opportunity. Any person may provide documentary evidence bearing on the application (such as information on available workers, wages, working terms and conditions, or other pertinent information) to either:

Employment Security Department
AEC Unit
P.O. Box 9046
Olympia, WA 98507-9046

OR

Employment & Training Administration
Region VI, U.S. Department of Labor
Certifying Officer
P.O.Box 193767
San Francisco, CA 94119-3767

The 14th Annual International CyberTherapy and CyberPsychology Conference (CT14) brings together researchers, clinicians, policy makers and funding agencies to share and discuss advancements in the growing discipline of CyberPsychology, CyberTherapy & Rehabilitation.

The focus of this conference is on the increasing use of interactive media in training, education, prevention, rehabilitation, and therapeutic interventions.Technologies featured at the conference include virtual reality simulations, videogames, wearables,  telehealth, the Internet, videoconferencing,  robotics, brain-computer interfaces, and non-invasive physiological monitoring devices.

Visit the conference website

From Pink Tentacle

Artist Pyocotan has developed “Noriko-san,” a sleep mask with an electronic scrolling display that communicates the wearer’s destination to fellow passengers.

A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback.

PLoS Comput Biol. 2008 Oct;4(10):e1000180

Authors: Legenstein R, Pecevski D, Maass W

Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how behaviorally relevant adaptive changes in complex networks of spiking neurons could be achieved in a self-organizing manner through local synaptic plasticity. However, the capabilities and limitations of this learning rule could so far only be tested through computer simulations. This article provides tools for an analytic treatment of reward-modulated STDP, which allows us to predict under which conditions reward-modulated STDP will achieve a desired learning effect. These analytical results imply that neurons can learn through reward-modulated STDP to classify not only spatial but also temporal firing patterns of presynaptic neurons. They also can learn to respond to specific presynaptic firing patterns with particular spike patterns. Finally, the resulting learning theory predicts that even difficult credit-assignment problems, where it is very hard to tell which synaptic weights should be modified in order to increase the global reward for the system, can be solved in a self-organizing manner through reward-modulated STDP. This yields an explanation for a fundamental experimental result on biofeedback in monkeys by Fetz and Baker. In this experiment monkeys were rewarded for increasing the firing rate of a particular neuron in the cortex and were able to solve this extremely difficult credit assignment problem. Our model for this experiment relies on a combination of reward-modulated STDP with variable spontaneous firing activity. Hence it also provides a possible functional explanation for trial-to-trial variability, which is characteristic for cortical networks of neurons but has no analogue in currently existing artificial computing systems. In addition our model demonstrates that reward-modulated STDP can be applied to all synapses in a large recurrent neural network without endangering the stability of the network dynamics.

Sleep-related improvements in motor learning following mental practice.

Brain Cogn. 2008 Oct 4;

Authors: Debarnot U, Creveaux T, Collet C, Gemignani A, Massarelli R, Doyon J, Guillot A

A wide range of experimental studies have provided evidence that a night of sleep may enhance motor performance following physical practice (PP), but little is known, however, about its effect after motor imagery (MI). Using an explicitly learned pointing task paradigm, thirty participants were assigned to one of three groups that differed in the training method (PP, MI, and control groups). The physical performance was measured before training (pre-test), as well as before (post-test 1) and after a night of sleep (post-test 2). The time taken to complete the pointing tasks, the number of errors and the kinematic trajectories were the dependent variables. As expected, both the PP and the MI groups improved their performance during the post-test 1. The MI group was further found to enhance motor performance after sleep, hence suggesting that sleep-related effects are effective following mental practice. Such findings highlight the reliability of MI in learning process, which is thought consolidated when associated with sleep.