Real-World Neuroimaging Technologies

Abstract

Decades of heavy investment in laboratory-based brain imaging and neuroscience have led to foundational insights into how humans sense, perceive, and interact with the external world. However, it is argued that fundamental differences between laboratory-based and naturalistic human behavior may exist. Thus, it remains unclear how well the current knowledge of human brain function translates into the highly dynamic real world. While some demonstrated successes in real-world neurotechnologies are observed, particularly in the area of brain-computer interaction technologies, innovations and developments to date are limited to a small science and technology community. We posit that advancements in realworld neuroimaging tools for use by a broad-based workforce will dramatically enhance neurotechnology applications that have the potential to radically alter human-system interactions across all aspects of everyday life. We discuss the efforts of a joint government-academic-industry team to take an integrative, interdisciplinary, and multi-aspect approach to translate current technologies into devices that are truly fieldable across a range of environments. Results from initial work, described here, show promise for dramatic advances in the field that will rapidly enhance our ability to assess brain activity in real-world scenarios.

How Low Can You Go? Empirically Assessing Minimum Usable DAQ Performance for Highly Fieldable EEG Systems

“…Our vision of "real-world neuroimaging" (RWN) involves conducting neuroimaging within realistic, non-contrived situations, where neural responses reflect what is expected in real-life situations [6,7,11]. While some RWN scientific endeavors can be managed using currently available DAQ approaches without the need for high mobility or long-term recording, in order to fully realize our goals of measuring and monitoring brain activity in truly unconstrained circumstances, we must re-think the way DAQ occurs with EEG.…”

“…While there is increasing interest in performing so-called real-world neuroimaging [7] -that is, monitoring brain activity within its full, natural context of the real world -current designs for EEG systems are not amendable to usage in a truly fieldable format, and a number of technical hurdles must be addressed. For example, because the brain-source voltage fluctuations represented by EEG are extremely small (microvolts) against a potential background that is heavily contaminated by larger fluctuations (milivolts to volts) created by movement artifacts [8,9], environmental electrical noise, and long-term capacitive drift effects [10], the overall signal-to-noise (SNR) is very poor.…”

“…This is generally a trivial concern for typical laboratory or patient-care environments where the benefits of having a high-quality DAQ system outweigh the disadvantages of size, cost, and power consumption of the system. However, it creates substantial limitations on the ability to build and use truly fieldable, long-application-time systems designed for use in every-day settings [7,11] or use in large scale "crowdsourced" implementations where cost would play a major factor [12].…”

A Subthreshold Digital Library Using a Dynamic-Threshold Metal-Oxide Semiconductor (DTMOS) and Transmission Gate Logic

“…A key challenge to this mobility lies in the lack of "real-world neuroimaging" tools that can accurately and appropriately collect low signal-to-noise ratio (SNR) data outside of controlled conditions such as specialized laboratories or clinical environments. 1 The development of such tools will enable optimization of brain-computer interactive technologies (BCIT) in a fieldable form factor. 2 The major barrier for achieving such a device that can handle low SNR data and wirelessly transmit the information is power consumption.…”

State-of-the-art MEMS and microsystem tools for brain research

“…Technology improvements for EEG systems have also witnessed an increase in funding, including those made at the Army Research Laboratory in the United States, with the goal of making EEG a practical tool for widespread human-based neuroscience in real-world applications 70 . EEG systems will benefit from microscale electrode features such as microneedle electrode designs that reduce the variability in skin contact 71 and mixed-signal front-ends with reduced size and power to eliminate long analog wires.…”