MRI Resolution Progresses From Millimeters To Microns

Neuroscientists have been mapping and recreating the nervous systems and brains of various animals since the microscope was invented, and have even been able to map out entire brain structures thanks to other imaging techniques with perhaps the most famous example being the 302-neuron brain of a roundworm. Studies like these advanced neuroscience considerably but even better imaging technology is needed to study more advanced neural structures like those found in a mouse or human, and this advanced MRI machine may be just the thing to help gain better understandings of these structures.

A research team led by Duke University developed this new MRI technology using an incredibly powerful 9.4 Tesla magnet and specialized gradient coils, leading to an image resolution an impressive six orders of magnitude higher than a typical MRI. The voxels in the image measure at only 5 microns compared to the millimeter-level resolution available on modern MRI machines, which can reveal microscopic details within brain tissues that were previously unattainable. This breakthrough in MRI resolution has the potential to significantly advance understanding of the neural networks found in humans by first studying neural structures in mice at this unprecedented detail.

The researchers are hopeful that this higher-powered MRI microscope will lead to new insights and translate directly into advancements healthcare, and presuming that it can be replicated, used on humans safely, and becomes affordable, we would expect it to find its way into medical centers as soon as possible. Not only that, but research into neuroscience has plenty of applications outside of healthcare too, like the aforementioned 302-neuron brain of the Caenorhabditis elegans roundworm which has been put to work in various robotics platforms to great effect.

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E4 Empatica device for measuring location, temperature, skin conductance, sleep, etc. on arm

Choosing The Optimal Sampling Rate For Your DIY Heart Rate Monitor

With wearables still trying to solidify themselves in the consumer health space, there are a number of factors to consider to improve the reliability of such devices in monitoring biometrics. One of the most critical such parameters is the sampling rate. By careful selection of this figure, developers can minimize errors in the measurement, preserve power, and reduce costs spent on data storage. For this reason, [Brinnae Bent] and [Dr. Jessilyn Dunn] wanted to determine the optimal sampling rate for wrist-worn optical heart rate monitors. We’ve shared their earlier paper on analyzing the accuracy of consumer health devices, so they’ve done a lot of work in this space.

The results of their paper probably don’t surprise anyone. The lower the sampling rate, the lower the accuracy of the measurement, and the higher the sampling rate the more accurate the measurement when compared to the gold standard electrocardiogram. They also found that metrics such as root mean square of successive differences (RMSSD), used for calculating heart rate variability, requires sampling rates greater than 64 Hz, the nominal sampling rate of the wearable they were investigating and of other similar devices. That might suggest why your wearable is a bit iffy when monitoring your sleeping habits. They even released the source code for their heart rate variability analysis, so there’s a nice afternoon read if you were looking for one.

What really stood out to us about their work is how they thoroughly backed up their claims with data. Something crowdfunding campaigns could really learn from.