A brain-computer interface with vibrotactile biofeedback for haptic information

<p>Abstract</p> <p>Background</p> <p>It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only <it>vibrotactile feedback</it>, a commonly used method to convey haptic senses of contact and pressure, is demonstrated with a high level of accuracy.</p> <p>Methods</p> <p>A Mu-rhythm based BCI using a motor imagery paradigm was used to control the position of a virtual cursor. The cursor position was shown visually as well as transmitted haptically by modulating the intensity of a vibrotactile stimulus to the upper limb. A total of six subjects operated the BCI in a two-stage targeting task, receiving only vibrotactile biofeedback of performance. The location of the vibration was also systematically varied between the left and right arms to investigate location-dependent effects on performance.</p> <p>Results and Conclusion</p> <p>Subjects are able to control the BCI using only vibrotactile feedback with an average accuracy of 56% and as high as 72%. These accuracies are significantly higher than the 15% predicted by random chance if the subject had no voluntary control of their Mu-rhythm. The results of this study demonstrate that vibrotactile feedback is an effective biofeedback modality to operate a BCI using motor imagery. In addition, the study shows that placement of the vibrotactile stimulation on the biceps ipsilateral or contralateral to the motor imagery introduces a significant bias in the BCI accuracy. This bias is consistent with a drop in performance generated by stimulation of the contralateral limb. Users demonstrated the capability to overcome this bias with training.</p

Accelerated functional brain aging in pre-clinical familial Alzheimer’s disease

Resting state functional connectivity (rs-fMRI) is impaired early in persons who subsequently develop Alzheimer’s disease (AD) dementia. This impairment may be leveraged to aid investigation of the pre-clinical phase of AD. We developed a model that predicts brain age from resting state (rs)-fMRI data, and assessed whether genetic determinants of AD, as well as beta-amyloid (Aβ) pathology, can accelerate brain aging. Using data from 1340 cognitively unimpaired participants between 18–94 years of age from multiple sites, we showed that topological properties of graphs constructed from rs-fMRI can predict chronological age across the lifespan. Application of our predictive model to the context of pre-clinical AD revealed that the pre-symptomatic phase of autosomal dominant AD includes acceleration of functional brain aging. This association was stronger in individuals having significant Aβ pathology

On varying b-values with depth: results from computer-intensive tests for Southern California

International audienceThe Gutenberg-Richter b-value is thought to reflect the stress conditions in the crust; therefore, spatial and/or temporal variations of the b-value can provide important information regarding crustal tectonics. We investigate the variation of b-value with depth in seven selected areas of Southern California. A previous study provided a detailed mapping of the variations of b with depth in California; our study is less systematic than this study. Our approach is more similar to the regional one used by Mori & Abercrombie. In comparison to these previous studies, our investigation indicates that the variability of b is often not statistically significant and that the decrease of b with depth should be interpreted with caution. The seismic catalogues used are subsets of a set of about 100000 seismic events recorded by the Southern California Seismic Network (SCSN) and relocated by Richards-Dinger & Shearer. We study the performance of Utsu's test compared to bootstrap tests for comparison of b-values. The results of our investigation also raise the question of the relevancy of Utsu's test when comparing b-values. Both simulations and real cases show that the Utsu's test is biased towards rejection of the null hypothesis in favour of the hypothesis that b-values are significantly different