Positive Technology Journal

Virtual reality study of paranoid thinking in the general population.

Br J Psychiatry. 2008 Apr;192:258-63

Authors: Freeman D, Pugh K, Antley A, Slater M, Bebbington P, Gittins M, Dunn G, Kuipers E, Fowler D, Garety P

BACKGROUND: Judging whether we can trust other people is central to social interaction, despite being error-prone. A fear of others can be instilled by the contemporary political and social climate. Unfounded mistrust is called paranoia, and in severe forms is a central symptom of schizophrenia. AIMS: To demonstrate that individuals without severe mental illness in the general population experience unfounded paranoid thoughts, and to determine factors predictive of paranoia using the first laboratory method of capturing the experience. METHOD: Two hundred members of the general public were comprehensively assessed, and then entered a virtual reality train ride populated by neutral characters. Ordinal logistic regressions (controlling for age, gender, ethnicity, education, intellectual functioning, socio-economic status, train use, playing of computer games) were used to determine predictors of paranoia. RESULTS: The majority agreed that the characters were neutral, or even thought they were friendly. However, a substantial minority reported paranoid concerns. Paranoia was strongly predicted by anxiety, worry, perceptual anomalies and cognitive inflexibility. CONCLUSIONS: This is the most unambiguous demonstration of paranoid ideation in the general public so far. Paranoia can be understood in terms of cognitive factors. The use of virtual reality should lead to rapid advances in the understanding of paranoia.

The development of brain-machine interface neuroprosthetic devices.

Neurotherapeutics. 2008 Jan;5(1):137-46

Authors: Patil PG, Turner DA

The development of brain-machine interface technology is a logical next step in the overall direction of neuroprosthetics. Many of the required technological advances that will be required for clinical translation of brain-machine interfaces are already under development, including a new generation of recording electrodes, the decoding and interpretation of signals underlying intention and planning, actuators for implementation of mental plans in virtual or real contexts, direct somatosensory feedback to the nervous system to refine actions, and training to encourage plasticity in neural circuits. Although pre-clinical studies in nonhuman primates demonstrate high efficacy in a realistic motor task with motor cortical recordings, there are many challenges in the clinical translation of even simple tasks and devices. Foremost among these challenges is the development of biocompatible electrodes capable of long-term, stable recording of brain activity and implantable amplifiers and signal processors that are sufficiently resistant to noise and artifact to faithfully transmit recorded signals to the external environment. Whether there is a suitable market for such new technology depends on its efficacy in restoring and enhancing neural function, its risks of implantation, and its long-term efficacy and usefulness. Now is a critical time in brain-machine interface development because most ongoing studies are science-based and noncommercial, allowing new approaches to be included in commercial schemes under development.