Updated word search and mirror-tracing tasks for Qualtrics

I finally had some spare time to document and post the mirror tracing and word-search tasks I developed for some replication work my students and I completed ​(Cusack, Vezenkova, Gottschalk, & Calin-Jageman, 2015)​.

Each task is (I think) pretty nifty, and I’ve had lots of emails about them over the past couple of years. I’ve finally posted both code bases to github along with working demos in Qualtrics and some rudimentary instructions. The code itself is not pretty–I was learning javascript and wrote most it during a conference I was attending in Amsterdam. Still, it works, and I’m sure it could come in handy.

The mirror-tracing task is just like it sounds–participants trace an image with their mouse or track pad but the mouse movements are mirrored, making it hard to stay in the line. You can vary task difficulty by changing line thickness. There is an expected weak negative correlation with age. The script can even posts the traced images back to your server, which is cool for making figures showing how groups differ with representative data.

The word-search task is also like it sounds. You can use pre-defined grids, or the script can generate a grid for you. I’ve used it to try priming for power (control vs. power-related words hidden in the grid) and to look at frustration (by having a grid that *doesn’t* have all the target letters…mean, I know).

  1. Cusack, M., Vezenkova, N., Gottschalk, C., & Calin-Jageman, R. J. (2015). Direct and Conceptual Replications of Burgmer & Englich (2012): Power May Have Little to No Effect on Motor Performance. PLOS ONE, e0140806. doi: 10.1371/journal.pone.0140806

Kids, Neurons, and Robots

At the end of February I (Dr. Bob) visited a local elementary school as part of the Oak Park Educational Foundation’s Science Alliance Program.

I was matched up with Sue Tressalt’s Third Grade Class at Irving Elementary. For an activity, I brought along the neuroscience program’s collection of Finch Robots, a set of laptops, and the Cartoon Network simulator I have been developing (Calin-Jageman, 2017, 2018). I introduced kids to the basic rules of neural communication, and they explored Cartoon Network, learning how to make brains to get the Finch Robots to do what they wanted (e.g. avoid light, sing when touched, etc.). It was a great class, and a ton of fun.

I’m proud of Cartoon Network, and the fact that it can make exploring brain circuitry fun. It’s simple enough that the kids were able to dive right in (with some help), yet complex enough that really interesting behaviors and dynamics can be modelled.

As a kid, my most formative experience in science was learning logo, the programming language developed by Seymour Papert and colleagues at MIT. Logo was fun to use, and it made me need/want key programming concepts. I clearly remember sitting in the classroom writing a program to draw my name and being frustrated at having to re-write the commands to make a B at the end of my name when I had already typed them out for the B at the beginning of my name. The teacher came by and introduced me to functions, and I remember being so happy about the idea of a “to b” function, and I immediately grasped that I could write functions for every letter once and then be able to have the turtle type anything I wanted in no time at all.

Years later I read Mindstorms and it remains, to my mind, one of the most important books on pedagogy, teaching, and technology. Papert applied Piaget’s model of children as scientists (he had trained with Piaget). He believed that if you can make a microworld that is fun to explore, children will naturally need, discover, and understand deep concepts embedded in that world. That’s what I was experiencing back in 2nd grade–I desperately needed functions, and so the idea of them stuck with me in a way that they never would in an artificial “hello world” type of programming exercise. Having been a “logo kid” it was amazing to read Mindstorms and recognize Papert’s intentionality behind the experiences I had learning Logo.

Anyways, bringing Cartoon Network to an elementary school for a day gave me a great feeling of carrying on a tiny piece of Papert’s legacy. The insights kids develop in just an hour of playing with neural networks are amazing–the idea of a recurrent loop made immediate sense to them, and that also sets up the idea that both excitation and inhibition are important. And, like in Logo, the kids were excited to explore–to know that their experience was not dependent on getting the ‘right’ answer but on trying, observing, and trying again.

The day was fun and even better I received a whole stack of thank-you cards this week. Reading through them has kept a smile on my face all week. Here’s a sample.

This kid has some great ideas for the future of AI

“I never knew neurons were a thing at all”–the joy of discovery
“Your job seems awesome and you are the best at it”—please put this kid on my next grant review panel.
  1. Calin-Jageman, R. (2017). Cartoon Network: A tool for open-ended exploration of neural circuits. Journal of Undergraduate Neuroscience Education : JUNE : A Publication of FUN, Faculty for Undergraduate Neuroscience, 16(1), A41–A45. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/29371840
  2. Calin-Jageman, R. (2018). Cartoon Network Update: New Features for Exploring of Neural Circuits. Journal of Undergraduate Neuroscience Education : JUNE : A Publication of FUN, Faculty for Undergraduate Neuroscience, 16(3), A195–A196. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/30254530

The remarkably long-lasting fragments of memory

It was a whirlwind 2018. Irina and I are just now catching our breath and finding some time to update the lab website.

One awesome piece of news we forgot to publicize is that our latest paper came out in the August issue of Neurobiology of Learning and Memory (Patel et al., 2018).   This paper continues our work of tracking the molecular fragments of a memory as it is forgotten.  Specifically, we tracked 11 genes we suspected of being regulated *after* forgetting (Perez, Patel, Rivota, Calin-Jageman, & Calin-Jageman, 2017).  Things didn’t work out quite as well as we had expected: of our 11 candidate genes 4 didn’t show much regulation, meaning that our previous results with these genes were probably over-estimating their importance (curse you, sampling error!).  On the other hand, we replicated the results with the other genes and found that some of them are actually regulated for up to 2 weeks after the memory is induced, long after it seems forgotten.

Here are two key figures.  The first is the memory curve for sensitization in our Aplysia -it shows that after memory induction there is strong sensitization recall that decays within a week back to baseline.  Even though the memory seems gone, giving a reminder 2 weeks after learning rekindles a weak re-expression of the memory. That’s a classic “savings” effect.  

The next figure traces the time-course of memory-induced gene expression (levels of mRNA) for 6 specific genes, measured in the pleural ganglia that contains neurons known to be important for storing sensitization memory.  You can see that each of these transcripts is up- or down-regulated within 24 hours of learning, and that in each case this regulation lasts at least a week and sometimes out to 2 weeks.  So, just as the behavioral level of the memory fades but isn’t really completely gone, the some of the transcriptional events that accompany learning also seem to persist for quite some time. 

Why would this occur?  Perhaps these transcripts are part of savings…maybe they set the stage for re-expressing the memory?  Or maybe they are actually part of forgetting, working to remove the memory?  Or maybe both?  For example, one of the transcripts is encodes an inhibitory transmitter named FMRFamide.  It is really up-regulated by learning, which would normally work against the expression of sensitization memory.  So perhaps this helps suppress the memory (forgetting), but in a way that can be easily overcome with sufficient excitation (savings)… that’s an exciting maybe, and it’s the thing we’ll be working this summer to test.

As usual, we’re so proud that this paper was made possible through exceptional hard work from some outstanding DU student researchers: Ushma Patel, Leticia Perez, Steven Farrell, Derek Steck, Athira Jacob, Tania Rosiles, and Melissa Nguyen.  Go slug squad!

Patel, U., Perez, L., Farrell, S., Steck, D., Jacob, A., Rosiles, T., … Calin-Jageman, I. E. (2018). Transcriptional changes before and after forgetting of a long-term sensitization memory in Aplysia californica. Neurobiology of Learning and Memory, 155, 474–485. doi:10.1016/j.nlm.2018.09.007
Perez, L., Patel, U., Rivota, M., Calin-Jageman, I. E., & Calin-Jageman, R. J. (2017). Savings memory is accompanied by transcriptional changes that persist beyond the decay of recall. Learning & Memory, 25(1), 45–48. doi:10.1101/lm.046250.117

New preprint on the very long-lasting transcriptional response to learning

The sluglab has a new preprint out, currently under review at the Neurobiology of Learning and Memory.  We shows that both transcription and savings can persist for as long as 2 weeks after the induction of long-term sensitization, way beyond the decay of recall.  Interestingly, all the long-lasting transcriptional changes start within 1 day of training.  Lots of student co-authors on this one; it was a *lot* of work.  Looking forward to the reviews.

Slug Lab Triumph! First place in the cSFN undergraduate poster competition for Leticia Perez and Ushma Patel

So pleased and proud to announce that Leticia Perez and Ushma Patel have won first place in the Chicago Society for Neuroscience undergraduate poster competition.   Congrats Leticia and Ushma on a great presentation on the work you’ve been doing in the slug lab on the transcriptional correlates of forgetting and savings memory.

Leticia and Ushma are following up their spectacular win with exciting post-graduation plans.  Leticia is enrolling at the University of Illinois School of Vetrinary Medicine (and had her choice of programs!).  Ushma is enrolling at UIC’s prestigious medical illustration MA program (and also had her choice of programs!).  Congrats to both on all the hard work they put into collecting data, analyzing results, and presenting their exciting research.

Want to know more about the research Leticia and Ushma presented?  See their paper in Learning and Memory here: (Perez, Patel, Rivota, Calin-Jageman, & Calin-Jageman, 2017)

Not to brag, but this is the 3rd time a DU student has placed in this competition in the past 10 years (Kristine Bonnic had a 3rd place win and Tim Lazicki had a first place win).  That means DU neuroscience students have earned 1/3 of all the awards given out for undergraduate research by the Chicago Society for Neuroscience–an organization that includes Northwestern, Loyola, University of Chicago, DePaul, Midwestern, Roosevelt, North Central, and more…. relative to our student body we’re punching way above our weight!

Perez, L., Patel, U., Rivota, M., Calin-Jageman, I., & Calin-Jageman, R. (2017). Savings memory is accompanied by transcriptional changes that persist beyond the decay of recall. Learning & Memory (Cold Spring Harbor, N.Y.), 25(1), 45–48. [PubMed]

Memories fade..but something remains

Most long-term memories are ‘forgotten’–meaning that it becomes harder and harder to recall the memory.  Psychologists have long known, though, that forgetting is complex, and that fragments of a memory can remain.  For example, even after a memory seems forgotten it can be easier to re-learn the same material, something called ‘savings memory’.  That suggests that there is at least some fragment of a memory that persists in the brain even after it seems forgotten…but what?

Today our lab has published a paper shedding a bit of light on this long-standing mystery (Perez, Patel, Rivota, Calin-Jageman, & Calin-Jageman, 2017).  We tracked a sensitization memory in our beloved sea slugs.  As expected, memories faded–within a week animals had no recall of the prior sensitization.  Even more exciting, we found similar fragments of memory at the molecular level–there was a small set of genes very strongly regulated by the original training even though recall had fully decayed.

Why?  Do these persistent transcriptional changes help keep a remnant of the memory going?  Or are they actually doing the work of fully erasing the memory?  Or do they serve some other function entirely (or no function at all)?  These are some of the exciting questions we now get to investigate.  But for now, we have these fascinating foothold into exploring what, exactly, forgetting is all about in the brain.

As usual, we are enormously proud of the undergraduate students who helped make this research possible: Leticia Perez, Ushma Patel, and Marissa Rivota. Ushma, who wants to do science illustration, is making an incredible piece of artwork representing these findings.  A draft is shown above.  She submitted it for the cover of the journal, but sadly they journal selected a different image (boo!).  Still, a very exciting and proud day for the slug lab!

Perez, L., Patel, U., Rivota, M., Calin-Jageman, I. E., & Calin-Jageman, R. J. (2017). Savings memory is accompanied by transcriptional changes that persist beyond the decay of recall. Learning & Memory, 25(1), 45–48. doi: 10.1101/lm.046250117

Workshop at the Society for Neuroscience Meeting

This year was a big year for our lab at the Society for Neuroscience conference.  Leticia Perez, who has been in the lab for the past two summers, gave an amazing talk on our work on forgetting.  In addition, I (Bob) helped organize a Professional Development Workshop on doing better neuroscience.

It was a huge honor to get to lead this workshop.  I gave a presentation on sample-size planning (which is sooo vital to doing good science).  David Mellor at the Open Science Framework spoke about pre-registration.  And Richard Ball, who co-directs project Tier, spoke about reproducible data analysis.  Like the good Open Scientists we are, we used the Open Science Framework to post all our slides and resources: https://osf.io/5awp4/.  SFN also made a video, which should be posted soon.

SFN staff told us it was the best attended workshop for the meeting.  Hooray!  Hope all our attendees will go forth to spread the good word about these small tweaks that can have such a big impact on scientific quality.

Here’s what it looked like from my perspective:

An unforgettable experience talking about forgetting

Wow! Our lab just returned from the 2017 Society for Neuroscience meeting.  It was the typical maelstrom of neuroscience–with more than 20,000 neuroscientists bustling about trying to share the latest and greatest about their research.

This turned out to be an especially great year for the Slug Lab.  Leticia Perez, who has been working in our lab for the past two summers, submitted an abstract to present the work she and others in the lab have been doing on forgetting.  We’ve been really excited about the results of this project.  It turns out the SFN organizers were excited, too–they selected Leticia’s abstract for a 10 minute talk during a mini-symposium on the mechanisms of learning and memory.

Leticia absolutely crushed it–she gave a concise, clear, and exciting presentation on what happens in the Aplysia nervous system as a long-term memory is forgotten.  She handled the questions wonderfully, and was soundly congratulated by many researchers in the learning and memory community.  Of the 20,000+ in attendance, I’m willing to be she was the only undergraduate to give a talk at this year’s meeting.  It was *such* an accomplishment.

In case that wasn’t enough, Leticia also brought along a poster presenting the research.  She gave the poster at the pre-meeting on molecular and cellular neuroscience and at the undergraduate poster session.  Yes, that means she gave 3 presentations last weekend!  Wow!  And, again, all went wonderfully.

Part of the reason Leticia was able to attend the meeting to earn all this acclaim is that she was awarded an Excel scholarship through Dominican University–this paid her registration, hotel, and airfare to make it affordable to attend the meeting.  She still had to work like crazy to collect the data, refine the presentation, and clear her class schedule to attend.  Lab alumnnus Marissa Rivota also attended–so her and Leticia also got to see the capital and the White house.

We’re so proud of Leticia, and of the many other students who have worked so hard in the lab for the past summers to make this forgetting project such a success.  There will be a paper on it coming out very soon in Learning and Memory.  It’s tremendous work to do good science–we’re so happy to have wonderful students who want to get involved and excel.

Below are photos of Leticia giving her talk, giving her poster, and celebrating with me, Irina, and Marissa.  Congrats, Leticia!

Slug Lab – Distinguished Service Awards from the Faculty for Undergraduate Neuroscience

At this year’s Society for Neuroscience meeting, Irina and I were honored for our contributions to the Faculty for Undergraduate Neuroscience (FUN).  Specifically, we were both given the annual Distinguished Service Award.  The honors were bestowed for our work organizing the FUN conference this past summer and for other work supporting the mission of undergraduate neuroscience education.

We’re so fortunate to be a part of FUN–it’s our favorite people all working towards a mission that is so very important.  Thanks for the great honor, and we’re looking forward to staying very involved with FUN.

Here’s a photo of Irina’s award.



The New Statistics for Neuroscience Education.

This summer I (Bob) was asked to write a series of perspective pieces on statistical issues for the Journal of Undergraduate Neuroscience.

My first effort has just been published–it is a call for neuroscience education to shift away from p values, and an explanation of the basic principles of the New Statistics with an example drawn from neuroscience.

It turns out that the paper was published just before the annual meeting of the Society for Neuroscience, which I am currently attending.  It’s been very gratifying to see the paper is already sparking some discussion.

Here’s the key figure from the paper comparing/contrasting the NHST approach with the New Statistics approach with data from a paper in Nature Neuroscience.