Stress monitoring has always been a tricky business. As it turns out, there is a somewhat reliable way of monitoring stress by measuring how much cortisol, the so-called “stress hormone,” the human body produces. With that in mind, bioengineering researchers at the University of Texas at Dallas decided to make CortiWatch, a wearable device for continuously monitoring cortisol excreted in sweat, as a sort of DIY stress meter.
They made their own potentiostat, a device for measure small amounts of current produced by electrochemical reactions, similar to the glucometer. We’ve talked about these types of measurements before. Simply put, the potentiostat contains a voltage reference generator which biases the sensing electrodes at a preset potential. The voltage bias causes local electrochemical reactions at the sensing electrodes (WE in the image above), stimulating electron flow which is then measured by a transimpedance amplifier or “current-to-voltage” converter. The signal is then analyzed by an onboard analog-to-digital converter. Simply put, the more cortisol in the system, the higher the transimpedance amplifier voltage.
To validate their system a bit more thoroughly than simple benchtop studies, the researchers did some “real-life” testing. A volunteer wore the CortiWatch for 9 hours. The researchers found a consistent decrease in cortisol levels throughout the day and were able to verify these measurements with another independent test. Seems reasonable, however, it’s not quite clear to us what cortisol levels they were expecting to measure during the testing period. We do admit that it takes quite a bit of calibration to get these systems working in real-life settings, so maybe this is a start. We’ll see where they go from here.
Maybe the CortiWatch can finally give us a proper lie detector. We’ll let you be the judge.
Philosophers have long mused about the concept of a “brain in a jar”, but thus far, it’s remained the preserve of science fiction rather than reality. However, after reading some scientific papers, [Justin] wanted to attempt the feat himself, so set out to grow some human neurons on an electrode array.
The project builds on [Justin]’s earlier work, using his DC sputtering rig to coat a glass microscope slide with electrodes. The first layer is silver for high conductivity, with an added gold layer for biocompatibility. The screw cap from a Falcon tube is then epoxied on to act as a reservoir for culture media for the neurons. Finally, an air filter is added to allow the biological mixture to breathe.
This was [Justin]’s first attempt at culturing neurons, and there were plenty of hurdles along the way. The custom culture assemblies had issues with the epoxy bonds leaking or failing entirely, leading to only one slide making it through the sterilization process. Additionally, the neurons were accidentally added in too high a quantity. While some growth was observed under the microscope, [Justin] was unable to detect any real signal from the system.
Despite a poor final result, plenty was learned along the way. [Justin] has already put plans into place to fix some of the pitfalls of the original experiment, and we look forward to seeing future updates from the project. Video after the break.
Continue reading “Growing Human Neurons Hooked Up To Electrodes”
Eyes are windows into the soul, the old saying goes. They are also pathways into the mind, as much of our brain is involved in processing visual input. This dedication to vision is partly why much of AI research is likewise focused on machine vision. But do artificial neural networks (ANN) actually work like the gray matter that inspired them? A recently published research paper (DOI: 10.1126/science.aav9436) builds a convincing argument for “yes”.
Neural nets were named because their organization was inspired by biological neurons in the brain. But as we learned more and more about how biological neurons worked, we also discovered artificial neurons aren’t very faithful digital copies of the original. This cast doubt whether machine vision neural nets actually function like their natural inspiration, or if they worked in an entirely different way.
This experiment took a trained machine vision network and analyzed its internals. Armed with this knowledge, images were created and tailored for the purpose of triggering high activity in specific neurons. These responses were far stronger than what occurs when processing normal visual input. These tailored images were then shown to three macaque monkeys fitted with electrodes monitoring their neuron activity, which picked up similarly strong neural responses atypical of normal vision.
Manipulating neural activity beyond their normal operating range via tailored imagery is the Hollywood portrayal of mind control, but we’re not at risk of input injection attacks on our brains. This data point gives machine learning researchers confidence their work still has relevance to biological source material, and neuroscientists are excited about the possibility of exploring brain functions without invasive surgical implants. Artificial neural networks could end up help us better understand what happens inside our brain, bringing the process full circle.
[via Science News]
Most posts here are electrical or mechanical, with a few scattered hacks from other fields. Those who also keep up with advances in biomedical research may have noticed certain areas are starting to parallel the electronics we know. [Dr. Rajib Shubert] is in one such field, and picked up on the commonality as well. He thought it’d be interesting to bridge the two worlds by explaining his research using analogies familiar to the Hackaday audience. (Video also embedded below.)
He laid the foundation with a little background, establishing that we’ve been able to see individual static neurons for a while via microscope slides and such, and we’ve been able to see activity of the whole living brain via functional MRI. These methods gradually improved our understanding of neurons, and advances within the past few years have reached an intersection of those two points: [Dr. Shubert] and colleagues now have tools to peer inside a functional brain, teasing out how it works one neuron at a time.
[Dr. Shubert]’s talk makes analogies to electronics hardware, but we can also make a software analogy treating the brain as a highly optimized (and/or obfuscated) piece of code. Virus stamping a single cell under this analogy is like isolating a single function, seeing who calls it, and who it calls. This pairs well with optogenetics techniques, which can be seen as like modifying a function to see how it affects results in real time. It certainly puts a different meaning on the phrase “working with live code”!
Continue reading “Reverse-Engineering Brains, One Neuron At A Time”
When it comes to building a neural network to simulate complex behavior, Arduino isn’t exactly the first platform that springs to mind. But when your goal is to model the behavior of an organism with only a handful of neurons, the constraints presented by an Arduino start to make sense.
It may be the most important non-segmented worm you’ve never heard of, but Caenorhabditis elegans, mercifully abbreviated C. elegans, is an important model organism for neurobiology, having had its entire nervous system mapped in 2012. [Nathan Griffith] used this “connectome” to simulate a subset of the diminutive nematode’s behaviors, specifically movements toward attractants and away from obstacles. Riding atop a small robot chassis, the Arduino sends signals to the motors when the model determines it’s time to fire the virtual worm’s muscles. An ultrasonic sensor stands in for the “nose touch” neurons of the real worm, and when the model is not busy avoiding a touch, it’s actively seeking something to eat using the “chemotaxis” behavior. The model is up on GitHub and [Nathan] hopes it provides an approachable platform for would-be neuroroboticists.
This isn’t the first time someone has modeled the nematode’s connectome in silico, but kudos to [Nathan] for accomplishing it within the constraints an Arduino presents.
Continue reading “Nematoduino: A Roundworm Neural Model On An Arduino”
[Alexandra Olivier] put up an art installation at Wellesley College that looks like a bunch of neurons built out of LEDs. The neurons are connected to a couple PIR sensors and ‘fire’ whenever movement is detected. The result is a lot like being inside a brain. Fitting, then, that the installation is called Social Synapses.
Last year’s big toy was always evil, though
Last year, [Andrew] had to fight the throngs of shoppers to get the must have toy of the season, a Zhu Zhu pet. Since these robotic hamster things have spent the last 11 months in the back of a closet, it seems reasonable to make them evil. They’re still not as evil as a demonic Furby….
So we call it a bifocal, right?
There’s an old photography trick for a really hacky macro setup – just turn the lens around. Well, what if you wanted automatic metering and flash control? Simple, just electrically reverse the lens. Bonus points for being able to use the lens regularly as well.
Control all the bands
Well here’s something cool: an all-in-one USB 315mhz, 433mhz, and 868mhz transceiver. What can you do with it? Well, [codeninja] can control the outdoor lights for two of his neighbors, open gates and doors, crash his weather station, and just about anything else in those bands. It’s pretty much like war driving for important stuff nobody cares about.
So this is our favorite holiday now
There’s a Dutch tradition to play Sinterklaas and make someone a present. [Jenor] decided to build an antique-looking DC voltmeter with a pair of vacuum tubes. The tubes don’t work anymore, but the heaters still provide a nice warm glow. It’s a bit large to be regularly used as a piece of test equipment, but it really does look awesome. Very steampunkey, and it’s the though that counts anyway.
We’re not quite sure what’s going on with our fellow hackers lately, but they all seem quite interested in finding inventive ways to scramble their brains. [Ben Krasnow] has put together a pair of videos detailing his experiments in transcranial magnetic stimulation, a process that looks like it would go quite nicely with the Brainwave Disruptor we showed you just yesterday.
Instead of building a coil gun with a set of supercapacitors he had on hand, [Ben] decided to build a magnetic coil that can be used to stimulate his brain through his skull. Once his capacitor bank is charged, a high current pulse is sent through the coil held against his head. This pulse generates a strong magnetic field in the coil, which in turn produces neuron stimulation in his primary motor cortex.
Be sure to watch both videos embedded below, as the first one mostly covers the theory behind his experiments, while the second video gives us the goods.
[Ben’s] day job involves working with professional grade TMS devices, so he has some experience with this technology. Before you try this on your own, be sure that you are doing this safely, because a misdirected pulse of 1700 volts to the head does not sound like a fun time at all.
Continue reading “Controlling Muscles With High Intensity Magnetic Pulses”