Latest SlugLab paper now out at eNeuro!

The Sluglab’s latest paper is now live at eNeuro! You can find it here: ​(Calin-Jageman et al., 2024)​.

We’ve already blogged about the paper: it tested our hypothesis that we could manipulate forgetting by changing signalling of an inhibitory peptide neurotransmitter called FMRF-amide. Our hypothesis was informed by the fact that we observe a huge and long-lasting increase in FMRF-amide transcription when animals acquire a long-term sensitization memory ​(Conte et al., 2017; Patel et al., 2018)​. Given that FMRF-amide serves to inhibit withdrawal reflexes, we reasoned that it represents an active-forgetting process that could be manipulated.

Our results were equivocal. On the one hand, we found that blocking FMRF-amide did, indeed slow down forgetting. On the other hand, we obtained a very wide confidence interval: we can’t be sure it is a large/replicable effect. Moreover, boosting FMRF-amide did not seem to speed up foregetting, as we predicted. So: a very intriguing finding we’ll need to follow-up on, but not the most clear-cut evidence. It was great that we pre-registered our study and published at a journal that is open to all well-conducted results, so we didn’t have to feel any pressure to “pretty up” these somewhat ambiguous results or to make strong claims from what ended up being somewhat noisy data.

The best thing about this project was the great DU students who made the whole project happen in just one summer. Amazing! Here’s the crew celebrating at SFN this fall. Congrats!

Oh, and one of these great students, Theresa Wilsterman, made this fantastic illustration for the paper (and just got a job at Rush Medical!)

  1. Calin-Jageman, R. J., Gonzalez Delgadillo, B., Gamino, E., Juarez, Z., Kurkowski, A., Musajeva, N., … Calin-Jageman, I. E. (2024). Evidence of Active-Forgetting Mechanisms? Blocking Arachidonic Acid Release May Slow Forgetting of Sensitization inAplysia. Society for Neuroscience. doi: 10.1523/eneuro.0516-23.2024
  2. Conte, C., Herdegen, S., Kamal, S., Patel, J., Patel, U., Perez, L., … Calin-Jageman, I. E. (2017). Transcriptional correlates of memory maintenance following long-term sensitization of Aplysia californica. Cold Spring Harbor Laboratory. doi: 10.1101/lm.045450.117
  3. 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. Elsevier BV. doi: 10.1016/j.nlm.2018.09.007

A new series on “Improving Neuroscience”

I (Dr. Bob) am excited to be organizing a new series of papers in eNeuro on Improving Neuroscience.

eNeuro has been leading the way for rigorous and reproducible research for some time. This new series will provide accessible, authoritative, hands-on tutorials for steps you can take to improve your research. We’ll cover sample-size planning, how to prove a negligible effect, per-registration, Bayesian methods, and much more.

If you have a topic you’d love to see covered or a tutorial you’d like to contribute, let me know!

Here is the editorial I wrote announcing this project ​(Calin-Jageman, 2024)​: https://www.eneuro.org/content/11/3/ENEURO.0048-24.2024. This all grew out of the editorial I wrote in 2019 about improving statistical practices in neuroscience ​(Calin-Jageman & Cumming, 2019)​.

Can’t say much yet, but already have a couple of great authors lined up to contribute tutorials. More soon!

  1. Calin-Jageman, R. J. (2024). NeweNeuroSeries: Improving Your Neuroscience. Society for Neuroscience. doi: 10.1523/eneuro.0048-24.2024
  2. Calin-Jageman, R. J., & Cumming, G. (2019). Estimation for Better Inference in Neuroscience. Society for Neuroscience. doi: 10.1523/eneuro.0205-19.2019

Is forgetting an active process? Some new evidence from Aplysia

The SlugLab has a new preprint from a really cool experiment we conducted this summer (2023). Check it out here ​(Calin-Jageman et al., 2023)​: https://osf.io/preprints/psyarxiv/xgfdk.

The results are a bit equivocal, but that’s the messiness of doing good science (“the data is the data”, as Bob’s PhD advisor was always fond of saying). In addition, we’re proud that this work has so many excellent student co-authors — well done Bryan, Elise, Zayra, Anna, Nelly, Leslie, Zayra, Jash, Elise, Dina and Theresa!

Now to the science. We’ve been studying the transcriptional changes that occur when Aplysia form long-term sensitization memories. One intriguing thing we’ve found, is that some of the transcriptional changes we observe would seem to work against the expression of sensitization ​(Conte et al., 2017)​. Specifically, one of the strongest transcriptional changes that occurs when sea slugs form a new sensitization memory is a strong and long-lasting up-regulation of a transcript encoding FMRFamide (FMRFa), a peptide neurotransmitter ​(Patel et al., 2018; Perez, Patel, Rivota, Calin-Jageman, & Calin-Jageman, 2017)​. This is strange begauce FMRFa is inhibitory and it generally works to depress synapses and specifically undoes the types of synaptic changes that help encode sensitization. Why would this be happening?

We’ve proposed the FMRFa is up-regulated because it is part of an active forgetting process — meaning a specific, biological pathway designed to erode/prune away memories. The idea would be that training produces transcriptional changes that encode sensitization but also produces a slower-developing increase in FMRFa, and that as FMRFa signalling increases it wears away the changes that maintain a sensitization memory, producing memory. Consistent with this hypothesis, we’ve found that FMRFa transcripts are up-regulated for a long time, even after sensitization memory seems completely forgotten.

To test the role of FMRFa signalling in forgetting, we gave animals sensitization training and then manipulated FMRFa signalling: boosting it with direct injections or blocking it with injections of a drug (4-BPB) that prevents arachidonic acide release, a key step in the G-protein-coupled-signaling that FMRFa triggers in Aplysia neurons. After these injections, we tracked forgetting of sensitization, measuring the strength of memory 4, 6, and 13 days after training.

What did we find? Well, inconsistent with our hypothesis we found that direct injection of FMRFa did alter forgetting at all. Bummer — sometimes you’re wrong! Or maybe we just didn’t use a strong enough dose, or the FMRFa didn’t get to the nervous system…. not sure. On the other hand, we found that 4-BPB slowed forgetting — animals in this condition had a stronger senstization memory 6-days after training than controls, and even had detectable levels of sensitization at day 13 (though no longer a clear difference from controls).

So, what does this mean? Well, it seems pretty clear that arachidonic acid plays some type of role in forgetting of sensitization. But FMRFa may not… or maybe it does but our FMRFa condition just wasn’t strong/direct enough. We’re going to repeat the study in reduced preps where we can control the drug application just a bit more strongly (though where we’ll have to rely on a physiological measure of memory strength). Excited to see where this goes.

  1. Calin-Jageman, R., Delgadillo, B. G., Gamino, E., Juarez, Z., Kurkowski, A., Musajeva, N., … Calin-Jageman, I. (2023). Evidence of Active-Forgetting Mechanisms:  Blocking Arachidonic Acid Release May Slow Forgetting of Sensitization in Aplysia. Center for Open Science. doi: 10.31234/osf.io/xgfdk
  2. Conte, C., Herdegen, S., Kamal, S., Patel, J., Patel, U., Perez, L., … Calin-Jageman, I. E. (2017). Transcriptional correlates of memory maintenance following long-term sensitization of Aplysia californica. Cold Spring Harbor Laboratory. doi: 10.1101/lm.045450.117
  3. 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. Elsevier BV. doi: 10.1016/j.nlm.2018.09.007
  4. 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. Cold Spring Harbor Laboratory. doi: 10.1101/lm.046250.117

New Review Article: Transcriptional Mechanisms of Long-Term Sensitization

Psychologists and neuroscientists have long been fascinated by memory: how do we learn and carry with us new skills and memories? One key insight is that lasting memories require both transcriptional change and neural plasticity.

Much of what we know abou tthe links between transcription and memory has been revealed through the study of long-term sensitization in Aplysia.

The sluglab has a a new review paper reviwing what we’ve learned from Aplysia, summarizing the state of the art of how sensitization memories are induced, encoded, and maintained . You can check it out here: https://osf.io/preprints/osf/urxk2

This review was a lot of work — but also a lot of fun to work on. This is a topic we know well — it’s the main thing the sluglab has studied over the past 15 years. But it was still incredible (and overwhelming) to get a chance to sit down and intensely re-read the many amazing papers that have explored this topic. Pulling it all together was tough, but rewarding; we especially appreciated being able to carefully explain the evidence behind the synchronization model of the induction of sensitization memory that has emerged from recent empirical an computational work.

Writing this review re-newed our appreciation for the incredible work of Gary Philips, the lab of Jack Byrne, Eric Kandel, and the many other folks who have studied sensitization in Aplysia. It was a real honor to be asked to write about all this work; we hope we’ve done it justice.

Writing this review was also fun because Theresa Wilsterman (DU class of 2023) worked up some really amazing figures — nice work, Theresa, and congrats on graduating!

Oh – it was also fun to make a preprint of this review using Quarto and RStudio — it was easy to produce a really beautiful document.

SlugLab at the 2023 Chicago Society for Neuroscience Meeting

The SlugLab was in full force at the 2023 meeting of the Chicago Society or Neuroscience.

  • Zayra, Jackie, and Jash presented a poster reporting the very-long-term sensitization project we worked on this past summer.
  • Theresa snuck in some science before escaping for her softball team’s spring break trip.
  • We got to catch up with Cristian, a SlugLab alum now working as a lab technician at Rush.
  • And, nearly all of C-J’s neurobio class attended, soaking up some fantastic neuroscience.

A big highlight was the address by Carl Hart: “Exaggerating Harmful Drug Effects on the Brain Is Killing Americans” — it was a heartfelt, heartbreaking, and fascinating talk. Bravo to cSFN for highlighting Dr. Hart’s work and perspective.

Here are some photos to enjoy!

Research lemonade: RRR on the short-term benefits of emotional reappraisal interventions in an online context

When the pandemic hit, all in-person research was shut down at Dominican (of course). This left a real challenge in terms of trying to figure out how our psychology majors could continue to engage in authentic and interesting research.

One solution I (Bob) worked on during the summer of 2020 was to assemble a collection of studies that would be a) socially relevant, and b) feasible to replicate and extend fully online (https://osf.io/xnuap/). This worked out really well for our research methods sequence.

I also worked with colleague TJ Krafnick on another approach: getting DU involved in some RRR projects (registered replication reports). Specifically, TJ and I applied to take part in a massive RRR organized by the psychological science accelerator (https://psysciacc.org/). What was especially exciting about this RRR was that it featured a trio of experiments, each designed to test online interventions to help modify emotional/behavioral responses to the Covid-19 pandemic (https://psysciacc.org/studies/psacr-1-2-3/). TJ and I obtained local IRB approval, and then we worked with our research methods students to collect data at DU. Students in my fall 2020 research and methods course then analyzed the data from our DU and wrote it up for their semester-long term projects. It was a really good experience for the class; we turned lemons into lemonade.

Now the psych science accelerator has assembled the data from all the team sites and published the manuscript for the first project ​(Wang et al., 2021)​. TJ and I are proud to be co-authors in a very long-list of talented collaborators (reading through the Google docs of draft proposals and manuscripts was incredible–at times, the manuscripts were probably more comment than actual text!).

So what was the actual study and what did it find? Participants (N > 23,000!) were randomly assigned to receive either a brief training in an emotional regulation strategy (reappraisal or reconstrual) or to a control condition. Participants were then asked to rate their positive and negative emotions in response to a series of genuinely heartbreaking images related to the Covid-19 pandemic. There were clear and consistent effects of the interventions on self-reported emotions: participants who received the training reported more positive emotions (d = -0.59!) and fewer negative emotions (d = -0.39) in response to the photos. This was true across essentially all study sites regardless of language or culture. That’s pretty amazing! On the other hand, the intervention was short term, and the dependent variable relied entirely on self-reported emotional responses, which might not be very reliable and which could be susceptible to demand effects from the study. Still, an encouraging win for emotional re-appraisal strategies.

  1. Wang, K., Goldenberg, A., Dorison, C., Miller, J., Uusberg, A., Lerner, J., … Moshontz, H. (2021). A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic. Nature Human Behaviour, 5(8), 1089–1110. doi: 10.1038/s41562-021-01173-x

What is forgetting? Slug lab provides some new insights!

Today, the SlugLab can share an exciting new paper, with contributions from Tania Rosiles, Melissa Nguyen, Monica Duron, Annette Garcia, George Garcia, Hannah Gordon, and Lorena Juarez ​(Rosiles et al., 2020)​.

Where to even start?

  • Contributions from 7 student co-authors! It’s been such a long haul; we’re proud of each of you for sticking with it and for all your contributions to this paper.
  • This paper is a registered report: We first proposed the idea and the methods, even writing a complete analysis script. This was then sent to peer review (you know, when you can still do something if the reviewers turn up an issue or problem to consider!) and after some back and forth received an ‘in principle’ acceptance. Then we completed the work and the analysis and submitted it for one more round of review focused solely on the interpretation of the data. This approach to publication lets peer reviewers have a more meaningful impact on the project and it also helps combat publication bias. People tend to think of this model for replication research, but in our case we used a registered report because we wanted to establish a fair and valid test between two competing theories and to ensure that the approach and analysis were pre-specified.
  • This paper is exciting! We were able to test two very different theories of forgetting:
    • decay theory, which says that memories are forgotten because they physically degrade
    • retrieval failure, which says that memories don’t degrade at all, but simply become more difficult to retrieve due to interference

We found clear support for the retrieval failure theory of forgetting, something I (Bob) was completely not expecting.

So, what was the study actually about?

Even memories stored via wiring changes in the brain can be forgotten. In fact, the majority of long-term memories are probably forgotten. What does this really mean? Is the information gone, or just inaccessible?

One clue is from savings memory, the fact you can very quickly re-learn seemingly-forgotten information. Savings memory is sometimes taken to mean the original memory trace persists, but it could also be that it had decayed, and the remnants prime re-learning.

We noticed a testable prediction:

  • If forgetting is decay, savings re-encodes the memory and must involve the transcriptional and wiring changes used to store new information.
  • If forgetting is inaccessibility, savings shouldn’t involve transcriptional/wiring changes

To test this prediction, we tracked transcriptional changes associated with memory storage as a memory was first formed, then forgotten, then re-activated. We did this in the sea slug, Aplysia calinfornica as a registered report (with pre-registered design and analyses).

The memory was for a painful shock—this is expressed as an increase in reflexes (day 1, red line way above baseline). Sensitization is forgotten in about a week (day 7, reflexes back to normal), but then a weak shock produces savings (day 8, reflexes jump back up)

What’s happening in the nervous system? Our key figure shows expression of ~100 transcripts that are sharply up- or down-regulated when the memory is new. At forgetting, these are deactivated (all lines dive towards 0). At savings? No re-activation! (lines stay near 0)

Our results show that savings re-activates a forgotten memory without invoking *any* of the transcriptional changes associated with memory formation. This strongly suggests the memory is not rebuilt, but just re-activated—the information must have been there all along?!

Lots of caveats (see paper), but the results seem compelling (though surprising) to us. In particular, we used an archival data set to show we would have observed re-activation of transcription had it occurred. Transcriptional changes with savings are clearly negligible.

  1. Rosiles, T., Nguyen, M., Duron, M., Garcia, A., Garcia, G., Gordon, H., … Calin-Jageman, R. J. (2020). Registered Report: Transcriptional Analysis of Savings Memory Suggests Forgetting is Due to Retrieval Failure. Society for Neuroscience. doi: 10.1523/eneuro.0313-19.2020

What psychology instructors should know about Open Science and the New Statistics

Beth Morling and I (Bob) have a new commentary out in Teaching of Psychology that provides an overview of the Open Science and New Statistics movements and gives some advice about how psychology instructors can bring these new developments into the traditional psychology curriculum ​(Morling & Calin-Jageman, 2020)​.

Beth is a superstar, on many fronts, but is perhaps best known for her incredible Research Methods in Psychology textbook (https://wwnorton.com/books/9780393536263). Just being asked to work on this commentary was a thrill. Then, working together, I learned a lot from her, especially with her approach to writing, which kept us on task and productive.

The article is open-access, so check it out. Here’s my favorite paragraph:

Introductory coursework is the ideal time to foster estimation thinking. Teachers can use the prompt, “How much?” to help students consider the magnitudes of effects and to seek context. Using the prompt, “How wrong?” can encourage students to embrace uncertainty and to introduce the key idea of sampling variation. Finally, prompting students with, “What else is known?” helps them see science as a cumulative and integrative process rather than as a series of “one-and-done” demonstrations. These three questions instill a nuanced view of science, where any one study is tenuous, and yet the cumulative evidence from a body of research can be compelling. This is a sophisticated epistemic viewpoint that avoids both excessive confidence and undue cynicism.

Morling & Calin-Jageman, 2020, p. 174
  1. Morling, B., & Calin-Jageman, R. J. (2020). What Psychology Teachers Should Know About Open Science and the New Statistics. SAGE Publications. doi: 10.1177/0098628320901372

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