The brain's electrical signals enable people without muscle control to physically interact with the world.

Brain-computer interfaces for communication and control

Imaging human brain function with techniques such as magnetoencephalography typically requires a subject to perform tasks while their head remains still within a restrictive scanner. This artificial environment makes the technique inaccessible to many people, and limits the experimental questions that can be addressed. For example, it has been difficult to apply neuroimaging to investigation of the neural substrates of cognitive development in babies and children, or to study processes in adults that require unconstrained head movement (such as spatial navigation). Here we describe a magnetoencephalography system that can be worn like a helmet, allowing free and natural movement during scanning. This is possible owing to the integration of quantum sensors, which do not rely on superconducting technology, with a system for nulling background magnetic fields. We demonstrate human electrophysiological measurement at millisecond resolution while subjects make natural movements, including head nodding, stretching, drinking and playing a ball game. Our results compare well to those of the current state-of-the-art, even when subjects make large head movements. The system opens up new possibilities for scanning any subject or patient group, with myriad applications such as characterization of the neurodevelopmental connectome, imaging subjects moving naturally in a virtual environment and investigating the pathophysiology of movement disorders.

/pdf/moving-magnetoencephalography-towards-real-world-1rrykm4njp.pdf

Moving magnetoencephalography towards real-world applications with a wearable system.

https://www.fil.ion.ucl.ac.uk/spm/doc/papers/meeg_good_practice.pdf

Good practice for conducting and reporting MEG research

Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give each source. We cannot expect each user to know the trustworthiness of each source, nor would we want to assign top-down or global credibility values due to the subjective nature of trust. We tackle this problem by employing a web of trust, in which each user maintains trusts in a small number of other users. We then compose these trusts into trust values for all other users. The result of our computation is not an agglomerate "trustworthiness" of each user. Instead, each user receives a personalized set of trusts, which may vary widely from person to person. We define properties for combination functions which merge such trusts, and define a class of functions for which merging may be done locally while maintaining these properties. We give examples of specific functions and apply them to data from Epinions and our BibServ bibliography server. Experiments confirm that the methods are robust to noise, and do not put unreasonable expectations on users. We hope that these methods will help move the Semantic Web closer to fulfilling its promise.

Trust management for the Semantic Web

We review the aspects that uniquely characterize magnetoencephalography (MEG) among the techniques available to explore and resolve brain function and dysfunction. While emphasizing its specific strengths in terms of millisecond source imaging, we also identify and discuss current practical challenges, in particular in signal extraction and interpretation. We also take issue with some perceived disadvantages of MEG, including the misconception that the technique is redundant with electroencephalography. Overall, MEG contributes uniquely to our deeper comprehension of both regional and large-scale brain dynamics: from the functions of neural oscillations and the nature of event-related brain activation, to the mechanisms of functional connectivity between regions and the emergence of modes of network communication in brain systems. We expect MEG to play an increasing and pivotal role in the elucidation of these grand mechanistic principles of cognitive, systems and clinical neuroscience.

/pdf/magnetoencephalography-for-brain-electrophysiology-and-4hva2lb0g0.pdf

Magnetoencephalography for brain electrophysiology and imaging

Scalp electrical recording during paralysis: quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG.

Thinking activates EMG in scalp electrical recordings.

Cell swelling, seizures and spreading depression: an impedance study.

Body fluids (biofluids) are used as a means of examining various biomarkers of health and disease both as a means of rapid diagnosis and monitoring of chronic health conditions Biomarker detection in non-invasively collected biofluids is considered an easy and rapid method in medical diagnostics A novel group of bioprobes with aggregation-induced emission (AIE) properties is being developed for monitoring analytes in biofluids which could facilitate widespread use via commonly available technologies This review describes the constituents and clinical biomarkers in urine, saliva, and sweat, and the role of currently developed AIE bioprobes that can quantitatively detect disease-related biomarkers in these biofluids Several applications of AIE bioprobes, such as paper-based strips and POC devices, are currently under development, and offer potential to be realized simply by use with smartphone data capture and analysis and data cloud storage These low-cost and highly reliable AIE bioprobe applications are beneficial for both early detection of disease and chronic disease management, especially in rural areas and developing countries and may facilitate greater involvement of health care consumers in managing their own care

/pdf/detection-of-biomarkers-in-body-fluids-using-bioprobes-based-4bz3pn8xxr.pdf

Detection of biomarkers in body fluids using bioprobes based on aggregation-induced emission fluorogens

HF and VHF radios retain considerable operational benefits for disaster communications. In particular, they can be the only available communications channel into a disaster zone, and are capable of communications over tens to thousands of kilometers. However, their bandwidth is extremely limited, as low as 1 bit/second, which has previously limited their utility as a backbone for public telecommunications. The Serval Mesh already includes the Low-Bandwidth Asynchronous Rhizome Delivery (LBARD) function, which scales down to 10s of bytes per second, and allows for near real-time two-way encrypted and authenticated text messaging using Android mobile telephones. In this paper, we present several improvements to LBARD, including a locality heuristic algorithm that allows for effective prioritization of HF transmission queues. The improvements enable LBARD to scale down to the ultra-low bandwidths (as low as 1bit/second) of even older HF radio equipment. Simulation and live HF-radio test results of a proof of concept are presented confirming the possibility of delivering hundreds to tens of thousands of text messages to be delivered per day using commercially-off-the-shelf HF radio equipment. In doing so, we create a new use-case for existing HF radios, and create the tantalizing possibility of providing basic day-to-day mobile telecommunications in regions too isolated to be viably serviced by other means.

Angus Wallace

Papers

Scalp electrical recording during paralysis: quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG.

Thinking activates EMG in scalp electrical recordings.

Cell swelling, seizures and spreading depression: an impedance study.

Detection of biomarkers in body fluids using bioprobes based on aggregation-induced emission fluorogens

Scalable telecommunications over ultra-low-bandwidth radio backbones