Call for Undergraduates in Biology or Engineering Fields:
Are you a neuroscience nerd? Do you want to learn how the brains of animals like squids or dragonflies work? Is your background in Electrical, Mechanical or Computer Engineering? Want to develop your own innovative experiments and publish your results? Learn to communicate those stunning results with the public? Maybe even all of the above? Then you’re in luck!
2017 Fellows from left to right: Top: Greg Gage (Not a fellow), Zach, Jaimie, Spencer, Nathan, Ilya. Bottom: Joud, Christy, Haley.
The Backyard Brains Summer Research Fellowship is an intensive 10 week program for undergraduates to participate in hands-on neuroscience research and experiment design with award winning neuroscientists. This is the 5th year of running our prestigious (and paid) summer program and this year it will run from May 21, 2018 to Aug 3, 2018 in Downtown Ann Arbor, MI. All applications must be received by noon eastern time (12:00 PM, EST) on March 22, 2018 to be eligible. We will be notifying applicants of their status by March 29, 2018.
This is our 5th iteration of the program, and it just gets better every year. Like a fine wine! Our summer fellowship program is run much like a graduate school laboratory. All participants will be working on their own independent research projects for the whole summer. We will have daily journal clubs to go over key papers and expand knowledge in the area, and each participant will be trained how to develop their own experiments and to build their own devices to perform those experiments. You, future BYB scientist, will be collecting data, analyzing it, and presenting your results.
The end result of your summer fellowship will be a publishable experiment and video for our website, as well as a poster to be delivered at Undergraduate Research Poster Session of the Society for Neuroscience. In 2017, all of our participants presented their research at a Undergraduate Research conference and some were selected to be posters at the Society for Neuroscience Conference. We also brought home the hardware to show for the hard work: all of our research fellows will be featured in a new TED show called “DIY Neuroscience,” which will begin airing on March 14. We will work with each student to prepare a 10 minute TED-style talk for a public event in Ann Arbor, with the possibility of presenting at our annual TEDx event. We have also worked with students to continue refining their experiment writeups into manuscripts in order to publish first-authored papers in peer-reviewed journals.
As interns, you can receive media coverage by the popular press. See below for previous examples:
Two Interns Win Hackaday’s Citizen Scientist Challenge
Arduino, EEG and Free Will by Patrick Glover “If the brain had already been preparing to perform the action for nearly half a second before the individual consciously “decides” to perform the action, did the individual actually… decide?” Read the full article here.
Neuroscience of Grasshopper Jumps by Dieu My Nyugen “Why are they hard to catch? Because they can quickly jump away when a person or another insect or object approaches it. How are they able to quickly hop away to escape a potential predator or avoid collision with an object? To address this specific question, I will look into the movement detector neurons in the grasshopper’s brain—the organ that fascinates me.” Read the full article here.
Optogenetics Featured In Hackaday
“Cort Thompson is working with fruit flies genetically modified so a neuron will activate when they’re exposed to a specific pulse of light. It’s called optogenetics, and [Cort] has a few of these guys who have an ‘I’m tasting something sweet’ neuron activated when exposed to a pulse of red light.” Read the full article here
RoboScorpion Featured in Popular Mechanics
“Backyard Brains, a small Michigan-based company dedicated to spreading the word about neuroscience, has been running surgical experiments on these deadly arachnids for the past two months, using electrical current to induce them to strike. Dylan Miller, a summer intern working the project, insists it’s the first time that an electrical current has ever been used to remotely induce a scorpion to strike with its pedipalps (claws) and tail.” Read the full article here.
This summer you will be trained by Ph.D. Neuroscientists, inventors, makers, seasoned engineers, and public speakers. With the help of our team, each intern will complete a compelling demonstration that the public will be interested and delighted to see. For example, see our recent TED talk on some of our recent work. Yours could be next!
Here’s some testimony from a former Fellow:
“The Backyard Brains summer internship is truly a once in a life time experience. Throughout the summer, we got to work as independent researchers on projects that one wouldn’t typically get to experience in a university setting, which allowed us to explore different realms of our scientific interests and grow immensely as scientists and individuals. I feel so fortunate to have been given the experience to pursue such a unique project, under the guidance of arguably the best boss in the entire world, Greg Gage. He provided guidance whenever we needed it while also allowing us the flexibility to execute a project from start to finish on our own terms. By the end of the summer, we were all able to showcase our work on an amazing platform, and conclude our projects feeling so confident in our abilities and excited to pursue whatever lie ahead for all of us as we returned to school/Work/etc.
I left the internship feeling more part of a family than a company and that is something I will have for the rest of my life. If I could do it over again, I would in a heartbeat!” -H. Smith, 2017 Fellow
This year’s projects will be our most interesting and exciting ones yet!
The Secret life of Jellyfish – Jellyfish have neurons, but no brains. They can show coordinated behaviors like turning and spinning… but how is this possible with no one in control? You will help find out. Using machine learning and a mobile phone camera, we will see if we can crack the code using ocean clytia! This project is in partnership with Dr. Brady Weissbourd of UCLA. Skills required: CS, Neuroscience, Engineering.
Wasp Face Painting – Wasps are known to form a hierarchy. A dominant rank earned through fighting… they only need to fight once to determine the pecking order. But how do the wasps remember their lot in life? This project will look to see if they can recognize each other by looking at their faces. Skills required: Neuroscience.
The Free Will Detector – The task is simple: move your arm. We won’t tell you when to do that… it is up to you. It’s your own free will to do so. Right? Maybe not! If we record your brain signal (EEG), it has been shown that your brain gives some indication its about to move your arm… even before you are aware! Your brain made you do it! In this project, you will use machine learning to predict a movement before the subject is even aware! Skills required: Engineering, CS.
The Electric Fish Piano – Weakly electric fish sing electrical notes to navigate the rivers of South America. It works incredibly well. But if someone else is singing at the same frequency, the interference causes a blindspot. So the fish have evolved to move the note up our down the harmonic scale. What if we had multiple fish? Could we develop a system that “parks” the fish at a given note? Could we actually play a song with many fish? Skills required: CS, EE, Neuroscience.
A Movement Mind-Reader? At BYB we have developed a neuro-prosthetic… a robot claw controlled via the electrical recording of your muscles. People often ask… do I actually have to move my muscle to make the robot move? The answer was yes… but is that true? In this project, you will be searching for “mu rhythms,” or small signatures in the EEG that can encode imagined movements. Can we detect an imagined movement to make a robot claw move? Skills required: CS, Neuroscience, Engineering.
As the Bee Flies – Honeybees tell their colleagues where to find that great patch of pollen they just visited via a wiggle dance. This communication has been shown to encode direction and distance. But how do they actually know how far they went without GPS? The answer is in the eyes… but in an unexpected way. In this project you will set up an experimental hive and experiment by changing the flight path just outside the hive. Skills required: Neuroscience.
What a Plant Knows – The notion that plants can learn in ways that are very animal-like seems too strange to believe… yet scientists have shown that plants can learn many things. Habituation, learning that something you previously thought was scary wasn’t so bad, have been shown in Mimosas… and associative learning have been shown in Pea Pods. We are skeptical, as good scientists are. In this project, you will plant the seeds and grow our understanding… literally. Skills required: Neuroscience, Biology.
Biofeedback for Meditation – Stress is a bummer. It’s a risk factor for neurodegenerative diseases, schizophrenia, and depression. One popular way to reduce stress is to meditate. Studies have shown that meditation has emotional as well as physiological health benefits. Many people, however, struggle in its practice because they don’t have a readout whether they are meditating ‘correctly.’ Studies suggest that our brain activity alters during meditation, increasing frequency and amplitude of the alpha-band. With the Heart and Brain SpikerBox, you can try to reproduce these findings and investigate whether a biofeedback stimulus (Spike Recorder built-in amplitude-to-tone converter) accelerates the meditation learning process. Skills required: CS, Neuroscience, Engineering.
Fastest Claw in the West – The mantis shrimp has the world’s fastest punch… Some species are “smashers” and are capable of smashing open heavy armored clams and crabs, yet other species are “spearers” and have evolved to spear down passing fish with lightning speed. How can the Mantis Shrimp move so quickly? And which type is truly the fastest? You will study the electromyograms of these tiny but mighty animals to gain insights to these questions and more. Skills required: CS, Neuroscience, Engineering.
The Octopus Puzzler – The Octopus is King of the Invertebrate brains. They possess amazingly clever behaviours that allow them to hunt down and kill vertebrates. But just how clever are they? In this experiment, you will be developing “Thorndike Puzzles” for octopodes. You will measure how long it takes the octopus to solve each one, and how much quicker they get in subsequent trials. How does the Octopus stack up to cats and dogs? You will find out! Skills required: Neuroscience.
Become a BYB Research Fellow in 2018, and help start the neuro-revolution!
You will be located at the Backyard Brains headquarters in downtown Ann Arbor (map). You will also be working out of our MakerSpace lab called “All Hands Active.”
Can international students participate?
Yes, we consider all students from all continents.
How much are the interns paid?
The weekly payment is $404/wk.
How much is housing and can you help us find it?
While we do not pay for your housing, we are happy to inform you that summer housing is notoriously easy to find in Ann Arbor, as students leave for the summer and make available sublets. The price varies, but you can find sublet housing on craigslist for under $400. We recommend that you stay close to downtown/central campus.
I am not out of class until June. Can I start a bit later?
We feel that our interns need a full 10w to make significant progress on their projects. If you have a compelling reason on how this will not affect your project, we are willing to evaluate it on a case by case basis.
I am not an undergrad, can I still apply?
While our program is designed for undergraduates… If you are a college graduate, or a super smart High Schooler, we will take your application under consideration.
Is there time off for vacations?
While you will have ample free time in Ann Arbor, we ask that you make the commitment to stay on project for the entire length of the internship.
Are projects assigned to interns or do the interns get some autonomy in deciding the course of their research?
The summer projects are described above and in the fellowship application. Each student will submit the project that they are interested during this process, or can suggest their own ideas. We keep the applicant’s preferences in mind, and we pair a student with a project early on so that the intern will have some time to do some background reading and familiarize themselves with the organism/methods. While we have some idea of the direction or end result of a project, we encourage independent thought throughout the process–some of our most successful projects have come from slight deviations from the original goals. We will send out some suggested papers a few weeks before the program starts.
Over 11 sunny Ann Arbor weeks, our research fellows worked hard to answer their research questions. They developed novel methodologies, programmed complex computer vision and data processing systems, and compiled their experimental data for poster, and perhaps even journal, publication. But, alas and alack… all good things must come to an end. Fortunately, in research, the end of one project is often the beginning of the next!
Some of the fellows intend to continue working with on the research they began here while they’re away and many of these projects will be continued next summer! Definitely expect to hear updates from Nathan’s EEG Visual Decoding project and Joud’s Sleep Memory project. Additionally, two of the projects will continue throughout the next few months: Zach’s Songbird Identification and Shreya’s Electric Fish Detector projects will continue through to December!
Meet the Fellows, See the Projects
The fellows are off to a great start! Check out their blog posts introducing their projects:
A few of our fellows are staying on throughout this next semester for longer term development projects! Zach is going to be back to working with his team on the Songbird Identification Device project, and Shreya will be working through to December on the Electric Fish Detector project. Expect updates on their progress from them soon!
So memory hacking during sleep is a thing? With endless runs back and forth to Om of Medicine chasing down my subjects, to countless hours staring at the Mona Lisa of sleep: Delta waves, and many other ups and downs during this summer…
I can finally tell you it is quite possible!!
As August is here, it is sadly my last few days at Backyard Brains! So let me come back again one last time and give you a final peek at what I have been up to for the past month and a wrap-up spiel on all my findings and exciting results of my research!
The GUI settings for the app look very nice now with new colors and a more user friendly environment!
The reference grid was changed to colored boxes as shown, and the image does not appear in the confines of the boxes anymore. We added this change after noticing that our participants’ performance was being slightly biased by the old grid. Another exciting addition: we can now save experiment sessions within the app itself and be able to come back to it and continue from where we left. Our Exporting function was fully revolutionized.. Take a look
This is the pseudo code I did with Greg to organize our data in a better-structured form. We now export JSON files that have entries easily identifiable and accessible in Matlab to perform data analysis.
TMR technique is a powerful tool to play with, it allows us to test the selectivity of our memory consolidation in various ways, and be able to experiment with many parameters and answer different research questions. For that, I wanted to have built in controls, and give the user the choice to change the parameters of sound cueing. The implementations are:
Setting the percentage for sounds to be cued during treatment. The default that I have been testing with (according to all published papers) is 50% of all sounds presented at the learning phase (so 24 out of the 48). It could be interesting to test if cueing 0%, 25%, 75%, or 100% would hinder or enhance the effectiveness of TMR on memory consolidation.
Manually select cues (and corresponding images accordingly) if a user would like to test with a different number of targets other than the default 48. Check this out:
The most exciting part: the control experiment is now ready! To validate our results, we need to run control experiments where we have subjects do a continuous reaction task instead of sleeping. We imbed the cues within this task as well, and test to see if TMR still has an effect on memory consolidation during wakefulness. The game consists of 4 rounds. A 2.5 minute training phase, then 3 7.5 minutes testing phases. Sound cues play in the second round of the testing phase 1.5 minute after the start of the round. The user will see numbers on the screen, and they should click if both numbers are either odd or even. Here is a video from the app showing how the game works:
With all these amazing implementations I was able to test it on more subjects. This table includes the full database of all subject participants I had over this summer. It was very hard finding people who are willing to spare their time to do the study (which takes up to 2.5-3 hours) in the middle of the day. So most of my subjects were fellow interns and employees at BYB, and Ann Arbor locals who volunteered during Tech Trek, or signed up for my doodle poll.
Mean start time for Slow Wave Sleep = 37.5 minutes +/-5.1 SE amongst all the subjects we tested (who could fall asleep fully for 90 minutes or more, first 8 subjects). Experimental results and post analysis was based on data from the first 4 subjects, as they were the ones able to complete the study fully. Control experiment was conducted on the last two subjects.
Here comes the best part, what we have been waiting for:
Result: Cued sounds during SWS showed better recall after sleep than uncued sounds
This graph is pretty interesting and tells us a lot, but might not be very intuitive at first. So let’s walk through it! The change in spatial recall is measured in terms of the difference in distance in points. This is calculated within the app itself. Points are units of measurement for position in iOS and apple devices similar to pixels. The conversion ratio to cm is 1 point = 0.0352778 cm. The app calculates the distance between where the user taps on the screen according to where they remember the image to appear (as x,y coordinates to a single position point of the tap), and where the original correct location of the image is (taking x,y coordinates of a single point of the bottom left corner of the image). The larger the distance between the two, the more off was the subject from the correct location, so it reflects less accurate recall, indicating more forgetting. This distance in points is measured for each image in both pre and post sleep tests. To find the difference in performance, I subtract the after sleep distance – before sleep distance. Having a negative number, means that the distance after sleep is smaller than the one before, indicating an improvement in performance and recall, as the subject clicked closer to where the correct image location is, and so remembers better. Therefore, grouping data from all 4 subjects and separating the images into cued and uncued, we have 24 cued images per one subject and 96 cued for all 4 subjects. The same applies for uncued. This gives us a total number of 192 images on the x-axis both cued and uncued. Now, with this knowledge in mind, this graph shows us the distribution amongst each and all subjects. We can see there is a higher distribution of the blue columns with larger positive differences in distance above the x-axis for the uncued images. This shows that subjects are forgetting more/scoring a less accurate recall for the uncued images. On the other and, we can see a higher distribution of the green columns with larger negative differences in distance below the x-axis for cued images showing less forgetting-better remembering/scoring a more accurate recall.
This graph is now much easier, it takes the mean distance of all of the differences of the 96 cued and 96 uncued and plots them. This only shows the final overall change in recall for all subjects grouped. We can see a pretty interesting significant difference in performance between the two.
Summary: Better recall for cued images (-12.95 points +/- 15.80 SE) compared to uncued images (33.09 points +/- 16.26 SE), using two-sample independent t-test (p = 0.04).
This graph shows us another analysis of the results. It shows the percentage correct for cued and uncued images before and after sleep for all subjects. This is the number of images subjects got correct out of the 24 cued or uncued before and after sleep. Correctness or incorrectness is decided based on a comparison between the distance in points discussed above, and a set threshold of 15% of the screen width. The % of screen width is just “distance in points/(width of the screen in points)”. The width is adjusted automatically as you change the apple device being used. If the distance is less than 15% of the screen width, it is correct. We can see that subjects had a higher %correct for cued images after sleep, lower %correct for uncued, and overall higher %correct for cued vs. uncued after sleep.
Assembling all these puzzle pieces together, we can conclude that we are seeing a general trend so far that indicates the following: The DIY version of Targeted Memory Reactivation (TMR) technique could potentially enhance memory consolidation during SWS and have suitable applications in learning and teaching in the future. It can be seen that TMR can effectively bias spatial associative memory consolidation, by altering the level of forgetness, more than providing pure gain of remembering cued images better. We definitely still need to test this on more subjects for accurate significance conclusions.
The control experiments involving cueing sounds with no sleep were conducted on two subjects only so far. Results show the same trend of the experiment with slight differences.
Summary: Better recall for cued images (-23.60points +/- 13.29 SE) compared to uncued images (46.77 points +/- 21.53 SE), using two-sample independent t-test (p = 0.007).
It looks like performance was slightly better for the cued images, and worse for the uncued ones compared to the results above. We have to keep in mind that although the results from the control experiment are significant, they are only taken from two subjects. More data needs to be collected, however, for now, this shows us something surprising yet reasonable! TMR appears to work well both during SWS and wakefulness. But which is better? Where does the maximum memory consolidation happen? Does SWS sleep promote consolidation of different types of memory compared to wakefulness? All such questions are yet to be answered!
So, my research does not stop here and it will continue beyond my fellowship this summer with BYB. My goal is to continue collecting more data, and explore the answers to the questions above and others that might come along the way. To do that, and continue with the idea of making this research fully DIY and accessible for the public, my next step would be working on taking the cueing of the sounds during sleep to the next step: automatic cueing using machine learning! This would allow users to run this fully functional study on themselves by buying the Heart and Brain Spiker Shield and downloading our TMR app, without needing a researcher observing their EEG during sleep and manually cueing the sounds when detecting Delta waves as what I have been doing. By having this property, the hope would be to provide a future cloud service for customer data and to use TMR to tackle larger issues:
Can it be used in PTSD research to help patients overcome traumatic memories? Can it be applied in educational settings to improve learning and teaching in institutions? Would it give us more insight into how our brains work when it comes to memory and potentially find a link to Alzheimer’s research?
Stay tuned! You will be hearing from me again in the near future.
Before I leave you for the summer, I would love to share with you some pictures from my best moments during this fellowship with my fellow interns and BYB staff. Last week, we had TED visiting Ann Arbor to film our projects into episodes for an internet show that will be go on live on the internet sometime this fall. This by far has been the best part of this experience and the most exciting one. We all worked so hard preparing for it, and spent long days presenting and explaining our work in front of cameras and lights! You will hopefully like it and share our enjoyment with us soon! Yesterday, we also presented our posters in the UROP Summer Symposium at the University of Michigan and people loved my project and gave some very good feedback on future directions.
It has been a pleasure interning with BYB this summer. It was a very exciting and moving journey, where it helped adding more valuable lessons to my academic and personal growth. I truly appreciate Greg Gage and all his love and support into pushing me to become a better researcher and a believer in his famous quoted piece of advice: “skepticism is a virtue”. This summer was indeed not only about learning how to cook, code/ MATLAB, deal with my best friend – EEGs – or even network and get one step closer towards my professional career aspirations. It was a reassuring discovery of my love for research and passion in literally revolutionizing Neuroscience and making it available for everyone!
See if you can spot how many times I wore my favourite-lucky blue blouse! It should go down in history
With all the awesome interns! Thank you for the greatest summer 🙂 We had very good memories and funny moments, and got to explore Michigan together!! This is not a goodbye!!