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Become a Cricket Pick-Up-Artist with Nick!

So you’re trying to pick up Crickets?

In this day and age there are services for everything; online dating for farmers, pastors, and anyone who’s looking for that special someone. Just nothing out there to help you find that very special cricket love. Well don’t worry, you won’t need a special site or even special skills!  All you need is a couple calling songs and you can find the male or female of your dreams, if in those dreams you happen to be a brown cricket (Acheta domestica).

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When I posted previously I was in stages of nailing (pinning?) down the right prep to get the best results possible. Suction electrodes were a possibility but proved to be too much of a time consuming, finicky prep. So when I went back to the silver wires, I tried new placements within the cricket and ended up finding a couple sweet spots that yielded some interesting results. Pictured above is the prep that has been giving me the best signal to noise ratio possible to see neuron spikes when frequencies are being played to the cricket. After several trials with this prep we found out that 3, 4, and 5 kHz frequencies would be the best ones to test at this point because this is the range male crickets produce their calling chirps in. So if you can chirp like that you can get a date with any cricket in the land. Quick Pro Tip: the females tend to roam during the day and in warmer weather so that’s when the optimal pickup tones should be tried.

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This is a 3 kHz frequency trial. Each trial was performed on female crickets with recordings played on their left side (where the wires were placed). These tones were produced manually at the time, however it has become automated through Matlab since then. The color bar above the green, in this case orange, represents each tone being played for roughly 25 trials. The green spikes represent the neuron spiking in reaction to the tone being played. As you can see the 3 kHz produced a lot of neuron spikes. Looking at this makes it seem like 3 kHz would be a “sweet spot” for optimal spiking in accordance to their naturally attuned frequencies, however this response doesn’t always happen.

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This is the 4 kHz trial, clearly also producing many spikes. Not as many as the 3 kHz trial but according to some literature this range 4-5 kHz is the main calling song brown crickets produce. So going forward, most of my tests will consist of frequencies within this range.

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The 5 kHz trail producing a poor amount of definitive neuron spikes. Some of the spiking in response to tone playing was removed because it was confirmed to be muscle movement of the cricket and not specifically a neuron responding to sound.

3 kHz:

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4 kHz:

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5 kHz:

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These Raster Plots represent the number of spikes produced by the neurons in the cricket’s ear after the onset of the tone (colored line). So each tick mark represents one action potential.  In most cases there is a delay after the tone before the first neuron fires in response to it. It will take more trials to determine the exact time of it, or to test if it coincides with some other studies.  The y-axis represents what number trial it was and the bottom is time in seconds, with 0 representing tone onset. In the histogram the number of spikes correlates with the time. So each bar represents the number of spikes that occurred during the same time period across trials. Each tone, whether it was 3, 4, or 5 kHz produced valuable data, and showed that each frequency could elicit a neuronal response in cricket’s ears. 3 and 4 however seemed produced a much better response it terms of neurons firing.

With all this information gathered I made a poster and presented it at Mid-SURE. While this shows a clear response to frequencies, I think this information more importantly represents an ability to obtain this kind of data with this simple, accessible, and easy to understand setup.  I will be trying to find the best signal to noise ratio such that I can objectively determine what is a neuron spike vs a muscle signal vs noise. As far as the cricket “cat calling” goes, I know which frequencies should produce a response and will be testing those more thoroughly moving forward, as well as a few frequencies that the crickets should be deaf to, and therefore should not elicit a response as a control.  I have automated tones playing and a randomization protocol which ensures a pure response to the frequency. So now my research will involve tweaking the silver wire placement and playing different series of tones to elicit a response, so essentially the same prep I have been doing this whole summer but much more concentrated now that I have a better understanding of the prime frequencies to play and where to put the recording electrodes, the silver wires. My end goal would be to reproduce this same type of data and conclusions as presented on my poster but with much more trials and many more frequencies. We have the ability, now, to test ultrasonic frequencies like 18 kHz and above, important because the crickets detect these frequencies to avoid being eaten by bats. So many more tiny surgeries are needed to ensure you guys the best possible call to get the male or female cricket of your dreams.


Are you conscious? Now with our consciousness detector, you can find out!

Hello again! This is the mind-reader reporting to you with updates on my project. I have had quite the scientific adventure since last sharing my research so sit down, grab your tea (or coffee or pop or kool-aide – I don’t judge) and prepare for a rollercoaster.

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With no success from LED oddball tasks, I moved to replicate an auditory oddball task from a paper that describes P300 responses from minimally conscious and vegetative subjects. If subjects with severe brain damage are able to produce results from that task, shouldn’t a healthy brain produce them as well? With this thinking in mind, I created a task that produces an Arduino-driven tone from a buzzer that lasts 100 ms, with 900 ms between each tone.  The oddball tone is coded to appear 14% of the time. When this tone appears, the subject makes a tally until we reach 50 tallies, as the P300 signal is reliable after 30 to 40 oddball stimuli have been presented. The signal sent to the buzzer is essentially copied and sent to the EEG so that the tone activation can be seen in the Spike Recorder app, as shown below.

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With this information in the app, the data can be averaged around tone onset. I set out to make this work – except it didn’t. Trial after trial returned a flat average. I was finding something that I thought looked like the P300 but the absence of anything substantial from the average suggested that what I was looking at was not consistent enough to be called science.

This lack of success caused me to scale back the project and start from the absolute basics.

One of the current BYB EEG experiments involves finding the alpha wave: a 10 Hz signal that appears from the occipital lobe when the eyes are closed (can be viewed at https://backyardbrains.com/experiments/eeg). This experiment was used as a control to ensure that the EEG was working as it should. We attached three shields to the board to allow for three recording locations: occipital lobe, right temporal lobe, and a forehead control.

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To ensure that activity was not dependent on the shield, we cycled the inputs from each recording location so that every location was recorded through each shield. The results confirmed that the alpha wave is most intense over the occipital lobe, less intense but still visible over another cortical location, and nonexistent over a non-cortical location (changes in intensity can be seen in RMS values). With confirmation that the shields are functioning as they should, I climbed to the next control: the flash visual evoked potential.

Flash visual evoked potentials (fVEP) represent electrical signals generated by the occipital region of the cortex when the subject is stimulated with flashes. The main components of the signal are those displayed to the right and are named for their latency, which is highly variable between subject and taskkylie6, and their polarity. kylie5The flash task created to elicit this waveform was powered by an Arduino and a surge protector that has been engineered to receive power inputs through a wire. The Arduino sends constant power to the bulb until the push of a button begins light flashes at a rate of 1/sec for 60 ms each. Each recording begins with an alpha task to ensure that the signal is legitimate. After the signal is verified, the subject sits motionless in my office for one minute and watches the flashing of the bulb. Because of the small amplitude of the fVEP response, the waveform is easily
lost in a raw EEG signal. It is only through averaging of trials that this evoked potential is visible, since the information common to the entire recording will be averaged out. Errors in the Spike Recorder software averaging caused us to call in Matlab for offline data
analysis. One second of data was collected surrounding flash onset and all of these epochs were averaged after eliminating outlier responses. The fVEP mean is then plotted against a Monte Carlo mean to show where and when the data is statistically significant – any data falling within the 95% confidence interval is deemed insignificant. If the data is significant and the waveform components match the literature in latency and amplitude, I considered the trial a success. Several successful trials indicated to me that the fVEP procedure produced what was necessary for the signal to appear and that the data analysis allowed us to see this particular event-related potential. Hoorah! It is possible. Equipped with new Matlab skills and some inspiration, I refocused my project to finding the P300.

 

My initial set-up for the oddball task was not scientifically sound, so some adjustments to better control and rkylie7ecord the stimuli were necessary. With a better designed experiment and several loyal subjects, data collection was in full swing. After collection, the data was run through an adapted Matlab script specific to the task. This script creates a plot of 1.4 seconds surrounding standard tone onset, 1.4 seconds surrounding oddball tone onset, a Monte Carlo simulation, and a plot of all three plotted together for comparison with outlier data excluded, same as before.

The code outputs the largest positive potential between 300 and 600 ms after tone onset, displaying the latency and change in amplitude from baseline for that point. The results are very exciting! We appear to have a P300 on our hands. Nearly half of the recordings taken thus far have had significant results. As I am only three days of data collection in, I’m happy with that! A lack of significance in the other trials could be from poor recording location, high impedance between the electrode and the skin, or simply poor attention allocation on the part of the subject. My goal now is to keep the positive results coming – more collection, more collection, more collection! Replication = science, right?

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Lord of the Flies-Optogenetic Fruit Fly Conditioning

You know what’s great about fruit flies? Nothing.

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fig. 1 Fruit flies suck

Nothing, that is, other than their benefit as a model organism for simple and fast transgenic experimentation — but who really cares about all that. Drosophila melanogaster are butts, so what if they could die? Well they can (vinegar and plastic-wrap), we don’t need science for that. We can go one further. What if we can make the flies loathe existence as much as the rest of all life hates them? What if we could take away the one thing that makes their nasty, brutish, and short existence bearable?  Make them lose life’s purest love? The love of…sugar?

 

Yeah, we did that.

With

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Look at this little guy, basking in the sweet, sweet 625nm rays of ghost sugar:

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fig. 2 How long can you hold out against science little guy, how long?

If you remember from my first post, red light activates the Gr5a sweet taste neuron, making the fly feel like a kid in a candy store after the adult-apocalypse. Now if we interrupt this tiny love affair with a SYRINGE OF SCIENCE and also quinine we can get the fly to associate the bliss of sugar (which flies love), with the bitter sting of quinine (which flies do not love).

Syringes-delivering Science since 1st century CE

Syringes-delivering Science since 1st century CE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

That’s classical conditioning, Kyle. After a few pairings of the two, the flies become depressed. Or I would, if I were a fly, because at that point they can’t stomach anything sweet, and don’t even respond to a fly sized glob of syrup. I’d do things to a human sized glob of syrup you’d probably try to get me arrested for, and the knowledge that science could some day deprive me of this pleasure is a sobering thought. After this I sat in a dark room for 3 days eating candy.

When I came out, the data was still there and I learned to love the bomb. Here’s a bit more detail on the way we played with fly tastes and the numbers we got:

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fig. 3 What I done do to them flies

The flies were taken off of food for 12hr before experimentation, then adhered to a foil slide with nail polish and mounted on a stand. For the conditioning test (A, purple), proboscis extension reflex (PER) was first tested via optogenetic, and then actual sugar stimulation, to establish a baseline of both the light-induced and real sugar-induced response.  For each trial, PER was optogenetically induced 3 times, and quinine applied to the extended proboscis. After 3 trials, PER was measured as a response to light, and then sugar again. A simple control used non-optogenetic flies-with the gene for the optogenetic channel, but no second gene activating its expression, and then the same opto/quinine pair trial (B, purple).  For further control trials, (C, red) quinine was applied to the proboscis sans opto- stimulation, (D, yellow) opto- stimulation was paired with water, and (E, green) opto- stimulation was used without quinine.  Though this may seem like a lot of controls experiments, we want to establish as firmly as possible that the response we are getting is solely a result of the paired conditioning experiment we are running.

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fig. 4 ALL THE DATA

These data show strong aversion to sugar after the conditioning. Only the trials where sweet taste activation is paired with bitter shows a marked decrease in response to sugar over the average indicating that the result was due to conditioning, not random chance. Future experimentation will also see pairing the light activation with a neutral taste to the flies, like salt, to see if we can condition the flies to respond to salt as they respond to sugar, as well as the possibility of optogenetically activated bitter taste activation combined with the introduction of real sugar. Optogenetics is the cutting edge of neuroscience technology, however, so whatever comes next will be exciting!