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Edwin Dalmaijer

@dalmaijer.bsky.social
826 followers 673 following 477 posts

Cognitive neuroscientist with many interests, including why our stomachs churn when we feel disgust. I also write books on programming; teach Python, statistics, and machine learning; and develop open-source software. www.dalmaijer.org

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Edwin Dalmaijer @dalmaijer.bsky.social · 06/10/2026
Bit of a random blog post, but sometimes my weird little hobbies and work coincide: How to build a watch to celebrate an academic milestone! www.dalmaijer.org/2026/10/maki...
This is a photo of a watch in a presentation box. The box is of a brown wood, with a glass top, and a velvety brown interior. The watch inside is on a black strap; the case is polished stainless steel, 33 mm in diameter, and fitted with a  curved crystal and a modest crown. The dial shows the red logo of the University of Bristol above the hands, the text “PhD” in black, and red lines to mark the hours. The hour and minute hands are steel-coloured with rounded tips and bars of lume, and the second hand is black with a curved end.
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Edwin Dalmaijer @dalmaijer.bsky.social · 17/09/2026
If you're unsure about modern medicine and whether to vaccinate your kids, I recommend visiting a local church's old graveyard. Look at the ages of the deceased. It's utterly devastating just how many children are buried there. We don't have to repeat this.
Grave/memorial stone for three children from one family, who died aged 6, 7, and 1.
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Edwin Dalmaijer @dalmaijer.bsky.social · 05/06/2026
In this time of redundancies all across UK higher education, it feels a bit worrying when administrators take an interest in your work...
Variation on the classic meme of Ralph Wiggum sitting in a bus, chuckling, and then saying "I'm in danger!" Wiggum is wearing a mortar board. Next to him we can see a LinkedIn screenshot that says "Education Administrator at University of Bristol viewed your profile."
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Edwin Dalmaijer @dalmaijer.bsky.social · 23/04/2026
Finally had enough of my smart watch. Constant notifications, patronising reminders, and low sleep scores for waking to attend children. I used to sell expensive watches. Disliked over-affluent customers, but loved the mechanisms. This one isn't particularly high-end, but so much less disruptive!
Watch wrapped around a person’s wrist.
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Edwin Dalmaijer @dalmaijer.bsky.social · 14/04/2026
Absolute goldmine for stats classes. Same website also has other generators?! Students awkwardly wait for lecture to start. They unexpectedly hear the upbeat tones of the Bluey theme song. What is this?! "This episode of Bluey is called… NULL HYPOTHESIS SIGNIFICANCE TESTING!"
Peppa pig font: “Mediation: Three regressions in a trench coat.”Peppa pig font: “Reviewer 2: I see PROCESS macro, I reject”Lego font: “LASSO”Bluey font: “Null hypothesis significance testing”
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Edwin Dalmaijer @dalmaijer.bsky.social · 14/04/2026
Thanks for sharing. My students are about to be flooded.
Peppa Pig and her family (Daddy Pig, Peppa, George, Mummy Pig) at a picnic. The picnic cloth in the centre has a bowl of sweets and a tea pot. The caption reads “I use AI for essays” and the sub-caption “Eat my slop, piggies!”
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Edwin Dalmaijer @dalmaijer.bsky.social · 21/03/2026
The one thing I really appreciate about modern academic publishers is how much value they add. Their copy-editing is of such a high standard that they wouldn’t, for example, publisher a paper with two errors in the title.
Screenshot of a paper in The Journal of Educational Research, published by Taylor & Francis, with the title “Dose local students’ presence affects remote students’ performance in blended synchronous learning?”

“Dose” should have been “Does”; “affects” should have been “affect”.
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Edwin Dalmaijer @dalmaijer.bsky.social · 18/12/2025
Are you curious about electrogastrography, but keep getting chicken-related results when googling "EGG"? We have the preprint for you! In this tutorial, we describe how to acquire and analyse gastric data from human participants. Plus FREE software! Read it here: arxiv.org/abs/2509.17260
Image illustrating sensor placement. The reference sensor is placed on the xiphoid process (just under the sternum), the ground is placed on the left costal margin (just under the bottom rib), and sensors one through four are place over where the stomach would be. Sensor 3 is midway through the umbilicus (navel) and the reference sensor. Sensor 4 is roughly three centimetres from sensor 3 to participant-right. Sensors 2 is also roughly three centimetres away from sensor 3, but along a 45 degree angle upwards and to participant-left. Sensor 1 lies 3 centimetres further from sensor 2, along the same 45 degree line.Two-panel image showing a processed electrogastrogram. The left panel shows five minutes of raw data from four different leads (measured from the four sensors in the previous image and their common reference). The right panel shows the same signal in frequency space, illustrating the typical normogastric peak at 3 cycles per minute.
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Edwin Dalmaijer @dalmaijer.bsky.social · 16/12/2025
This sent me down a spiral, leading to the discovery that the lolcats I wasted my poor parents’ precious dial-up minutes for are from 19 years ago. How is such recent internet history already two decades old?
Meme of a cat with what looks like a smile on its slightly tilted head, captioned “I CAN HAS CHEEZBURGER?”
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Edwin Dalmaijer @dalmaijer.bsky.social · 12/12/2025
Quick post on @jonaspotthoff.bsky.social new paper! We found people looked more at novel foods at an experimental buffet, including insects that they find gross! People suppress disgust avoidance when making foraging decisions. Blog: www.dalmaijer.org/2025/12/fora... Paper: doi.org/10.1016/j.fo...
A three by four grid of example stimuli found in the experimental buffet. The first column shows edible insects: meal worms, crickets, and buffalo worms. The second column shows novel savoury snacks for participants in the UK and Austria: Haldiram's Mullu Murukku, roasted broad beans, and Wah-Yuen fried dough. The third column shows common savoury snacks for the same participants: tortilla chips, crisps, and peanuts. The last column shows visually matched non-foods: Lego, wooden buttons, and wooden clothes pegs.Figure with four panels. In each panel, the x-axis depicts the four types of stimuli: insect snacks, novel snacks, familiar snacks, and non-food. The top two panels show total dwell time across the experiment and average fixation duration. Overall, participants looked at the insects and novel snacks more than at the familiar snacks and non-food. The bottom panels show disgust and desire-to-eat ratings. Insects are scored as much higher on disgust and much lower on desire to eat compared to novel and familiar foods (both of which are rated low on disgust and relatively high on desire to eat).
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Edwin Dalmaijer @dalmaijer.bsky.social · 11/12/2025
Would you eat insects, or is that disgusting? @jonaspotthoff.bsky.social used mobile eye-tracking as people browsed a buffet. They looked longer at insect and unfamiliar snacks, but only rated insects as disgusting. This suggests disgust isn't always avoided when foraging decisions have to be made!
A three by four grid of example stimuli found in the experimental buffet. The first column shows edible insects: meal worms, crickets, and buffalo worms. The second column shows novel savoury snacks for participants in the UK and Austria: Haldiram's Mullu Murukku, roasted broad beans, and Wah-Yuen fried dough. The third column shows common savoury snacks for the same participants: tortilla chips, crisps, and peanuts. The last column shows visually matched non-foods: Lego, wooden buttons, and wooden clothes pegs.Figure with four panels. In each panel, the x-axis depicts the four types of stimuli: insect snacks, novel snacks, familiar snacks, and non-food. The top two panels show total dwell time across the experiment and average fixation duration. Overall, participants looked at the insects and novel snacks more than at the familiar snacks and non-food. The bottom panels show disgust and desire-to-eat ratings. Insects are scored as much higher on disgust and much lower on desire to eat compared to novel and familiar foods (both of which are rated low on disgust and relatively high on desire to eat).
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Edwin Dalmaijer @dalmaijer.bsky.social · 03/12/2025
The perceived embodiment of proper disgust is entirely different than that of “political disgust”, which actually closely overlaps with anger. Excellently timed preprint, with @disgust-nerds.bsky.social starting tomorrow. Hope someone brings this up in the “Is moral disgust really disgust?” debate!
Figure from the preprint with two rows of visualised perceived embodiment, one for the non-political and one for the political emotion. Disgust is perceived by participants to be embodied in the stomach, whereas political disgust was in the chest. This overlaps very closely with political anger, suggesting the two overlap. (And maybe that “political disgust” is not necessarily actual disgust!)
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Edwin Dalmaijer @dalmaijer.bsky.social · 28/11/2025
Reviewer asked something similar for a recent paper on disgust (doi.org/10.1371/jour... ), and we wrote what’s in the image. TL;DR: behaviour can be as good as self-report, and is substantially more robust against demand effects. (CC @tahnee-engelen.bsky.social and @nicolecrust.bsky.social)
Paragraph from Edgar et al. (2024, PLOS ONE): “The summarised studies mostly rely on self-report measures of disgust elicited by written or picture stimuli. Such self-report measures can have excellent psychometric properties, for example the internal consistency [6] and external agreement with others’ ratings [20] of the Three-Domain Disgust Scale, or the high test-retest reliability of self-reported disgust for images [12]. While experimental tasks are often less reliable than self-report measures [21], behavioural disgust avoidance measured in preferential looking tasks has excellent internal consistency, Spearman-Brown ρ = 0.81 to 0.94 and Cronbach’s α = 0.78 to 0.91 [22], and test-retest reliability equal to self-reported disgust ratings [12]. Behavioural disgust avoidance correlates with self-reported disgust sensitivity, R = 0.28 to R = 0.34 [12], and with self-reported disgust ratings for stimuli, R = 0.19 to 0.50 [22]. However, a major difference between self-report and behavioural measures of disgust avoidance is that self-reported disgust shows a very large (Cohen’s d = 1.25) placebo effect, whereas oculomotor avoidance (gaze dwell time) in preferential looking tasks only shows a small to medium (Cohen’s d = 0.44) effect [23].”
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Edwin Dalmaijer @dalmaijer.bsky.social · 10/11/2025
Obligatory reference to “Falsehoods Programmers Believe About Names”: www.kalzumeus.com/2010/06/17/f...
People have exactly one canonical full name.
People have exactly one full name which they go by.
People have, at this point in time, exactly one canonical full name.
People have, at this point in time, one full name which they go by.
People have exactly N names, for any value of N.
People’s names fit within a certain defined amount of space.
People’s names do not change.
People’s names change, but only at a certain enumerated set of events.
People’s names are written in ASCII.
People’s names are written in any single character set.
People’s names are all mapped in Unicode code points.
People’s names are case sensitive.
People’s names are case insensitive.
People’s names sometimes have prefixes or suffixes, but you can safely ignore those.
People’s names do not contain numbers.
People’s names are not written in ALL CAPS.
People’s names are not written in all lower case letters.People’s names have an order to them.  Picking any ordering scheme will automatically result in consistent ordering among all systems, as long as both use the same ordering scheme for the same name.
People’s first names and last names are, by necessity, different.
People have last names, family names, or anything else which is shared by folks recognized as their relatives.
People’s names are globally unique.
People’s names are almost globally unique.
Alright alright but surely people’s names are diverse enough such that no million people share the same name.
My system will never have to deal with names from China.
Or Japan.
Or Korea.
Or Ireland, the United Kingdom, the United States, Spain, Mexico, Brazil, Peru, Russia, Sweden, Botswana, South Africa, Trinidad, Haiti, France, or the Klingon Empire, all of which have “weird” naming schemes in common use.
That Klingon Empire thing was a joke, right?
Confound your cultural relativism!  People in my society, at least, agree on one commonly accepted standard for names.There exists an algorithm which transforms names and can be reversed losslessly.  (Yes, yes, you can do it if your algorithm returns the input.  You get a gold star.)
I can safely assume that this dictionary of bad words contains no people’s names in it.
People’s names are assigned at birth.
OK, maybe not at birth, but at least pretty close to birth.
Alright, alright, within a year or so of birth.
Five years?
You’re kidding me, right?
Two different systems containing data about the same person will use the same name for that person.
Two different data entry operators, given a person’s name, will by necessity enter bitwise equivalent strings on any single system, if the system is well-designed.
People whose names break my system are weird outliers.  They should have had solid, acceptable names, like 田中太郎.
People have names.
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Edwin Dalmaijer @dalmaijer.bsky.social · 17/10/2025
Delighted to see another validation of MouseView.js, this time to test its usability for biases to alcohol-related stimuli. It was reliable, and captured overt attentional bias in those with high problematic drinking scores. For more info, read the paper by Thulin et al.: doi.org/10.1016/j.ps...
The image is a screenshot of the title, authors, and abstract of the paper. Title: "Testing the utility of Mouseview.js for measuring associations between alcohol related attentional bias and problematic alcohol use". Abstract: "Objectives: This study examined the utility of Mouseview.js, an alternative to webcam-based eye-tracking, to assess associations between alcohol-related attentional bias and problematic alcohol use. Methods: Canadians recruited through Academic Prolific (N = 526) completed an online free-viewing task using Mouseview.js to measure biased attention to alcohol-related images. Eighteen alcohol-related images were paired with neutral images matched on visual characteristics. Attentional bias was estimated as the differences in trial-level dwell times for the image pairs. The sample consisted of 132 non-drinkers, 241 recreational drinkers, and 153 problematic drinkers. Participants’ mean age was 33.5 years, 50.8% were men, and 40.4 % identified as a racialized minority. Multi-level modelling was used for statistical analyses. Results: The difference in dwell times between alcohol-related and neutral images was larger for problematic drinkers compared to non-drinkers, B = 3.75, z = 2.61, p = .009. There were no significant differences between recreational drinkers and non-drinkers, or between recreational and problematic drinkers. Reliability for dwell times and dwell time differences ranged from acceptable (≥0.70) to good (≥0.80). Conclusions: There was an attentional bias for alcohol-related images among problematic drinkers relative to non-drinkers and the Mouseview.js indices of bias demonstrated adequate reliability. These findings provide preliminary support for the utility of Mouseview.js as a measure of attentional bias in problematic drinkers. With further validation studies, Mouseview.js may prove to be a powerful tool for conducting high-powered online studies of attentional biases associated with addictive behaviors."
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Edwin Dalmaijer @dalmaijer.bsky.social · 24/09/2025
Such a lovely talk, and I’m glad our admin upgraded the venue as there was standing room only! I particularly enjoyed Aidan’s perspective on hippocampal and non-hippocampal encoding as independent processes, and flexibility of memories within that space. (I also enjoyed the brief Mario Kart break.)
Photo of a projector screen showing the results of a Mario Kart race. Two players are shown, one as Wario in first place and another as Peach in third place.
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Edwin Dalmaijer @dalmaijer.bsky.social · 04/08/2025
I've seen people use "clanker" in the wild, and others commenting how wild it is to live through the invention of the first anti-AI slur. Few seem to realise "clanker" is from a fairly niche Star Wars game and show, where battle droids ("roger, roger!") are called this by clone troopers.
This is a version of the "The More You Know" meme: a screenshot from NBC public service announcement showing a shooting star with a rainbow trail that underscores blue text that says "The More You Know". In this version, the shooting star has the Death Star from Star Wars superimposed, and a Battle Droid seems to be heroically jumping into the frame (from the left) while holding their blaster ready for shooting.
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Edwin Dalmaijer @dalmaijer.bsky.social · 29/07/2025
New gender just dropped!
Text from a paper by Flohr-Devaud and Neumann (2025, Translational Issues in Psychological Science, doi: https://doi.org/10.1037/tps0000469 ). The screenshot offers a larger extract from the Methods section to show the "Sample" heading for context, but the crucial bit is "Paramedics (40 male, 24 female, one diver) from a German emergency service organization (M age = 33.25, SD = 12.87) participated." The section "one diver" is highlighted for the purpose of this post (but not in the original paper).
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Edwin Dalmaijer @dalmaijer.bsky.social · 04/07/2025
To check if our data was just weird, we ran a control analysis to test the effect of participants' ratings of food healthiness on their stomach response. Those awarding higher healthiness ratings increased showed higher normogastric power for healthy and lower for unhealthy foods. Sensible! (5/7)
Figure comprised of three subplots. Each subplot represents a third of the sample, here ordered by the healthiness ratings that participants gave to foods in each category. Each panel shows three lines, each depicting gastric power along its typical frequencies (x-axis, ranging from 1 to 10 cycles per minute). Each line represents a food type: "healthy" (in green), "unhealthy" (in yellow), and "disgusting" (in brown). The important point is that normogastric power is higher for those who gave low healthiness ratings, gastric power is high for unhealthy foods and low for healthy foods. However, those who gave high healthiness ratings show higher gastric power for healthy foods. (Note that the presentation in three groups is just for visualisation; the actual statistical analysis treats orthorexia as continuous variable and shows an interaction between it and food conditions.)
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Edwin Dalmaijer @dalmaijer.bsky.social · 04/07/2025
We expected reduced normogastric power (proto-nausea) for unhealthy foods, but found the opposite! Those higher on orthorexia had similar stomach responses to healthy and unhealthy foods. Do self-denied foods become more appetitive? Or is orthorexia cognitive control to overrule the stomach? (4/7)
Figure comprised of three subplots. Each subplot represents a third of the sample, here ordered by orthorexia scores. Each panel shows three lines, each depicting gastric power along its typical frequencies (x-axis, ranging from 1 to 10 cycles per minute). Each line represents a food type: "healthy" (in green), "unhealthy" (in yellow), and "disgusting" (in brown). The important point is that normogastric power is higher for healthy compared to unhealthy foods for those who score lower on orthorexic traits. However, for those high on orthorexic traits, this difference disappears. (Note that the presentation in three groups is just for visualisation; the actual statistical analysis treats orthorexia as continuous variable and shows an interaction between it and food conditions.)
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Edwin Dalmaijer @dalmaijer.bsky.social · 04/07/2025
We also found that people higher on orthorexia literally turned up their noses at unhealthy and disgusting foods! The coefficient vector maps align with facial expressions of disgust. At this point, orthorexia is associated with a preference for healthy foods and disgust for anything else. (3/7)
Perfect figure for an album cover, depicting nine faces in a 3x3 grid. The middle face looks directly at the viewer, and each other face is looking away in the direction they are in from the central face (e.g. top-left is looking towards top-left). The faces are made up of facial landmarks (grey disks), from each of which originates a coefficient vector. This line is longer and brighter for stronger effects. In this case, that effect is an interaction between orthorexic traits and facial responses to disgusting foods (compared to healthy ones). The largest effects are around the nose, indicating pulling up of the levator labii. There is also a bit of squinting and brow furrowing.
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Edwin Dalmaijer @dalmaijer.bsky.social · 04/07/2025
We used three categories of foods: "healthy" (minimally processed), "unhealthy" (highly processed), and "disgusting" (uncommon in local culture). Participants' ratings confirmed we chose our stimuli well, and people higher on orthorexia reported higher desire to eat healthy foods. (2/7)
This is a figure depicting a series of 15 box plots with density estimates. There are three ratings along the x-axis (healthiness, disgust, familiarity, pleasantness, and desire to eat). Each rating is given for 45 stimuli, 15 each in three food categories: "healthy" (in green), "unhealthy" (in yellow), and "disgusting" (in brown). Healthy foods received higher healthiness ratings; disgusting foods received higher disgust ratings; and familiarity, pleasantness, and desire to eat show very similar distributions between healthy and unhealthy foods (but all are lower for disgusting foods!).
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Edwin Dalmaijer @dalmaijer.bsky.social · 26/06/2025
Ha! I either missed this at the time, or so thoroughly blocked it from memory that it no longer rings familiar! What I do recall is the meeting where you, Kia (@brognition.bsky.social), and several uni officials called us all in to tell us the building would be closing. I still have the photos!
Photo taken from a seat in the Tinbergen’s main lecture theatre, looking out onto the speaker area. Five people, including the Heads of Departments in the Tinbergen and several university officials, are at the front. The speakers are informing staff of the Tinbergen closure, and answering questions.
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Edwin Dalmaijer @dalmaijer.bsky.social · 12/05/2025
If you're thinking "hey, that looks a bit like a sausage fest, and what's with all the references to masculinity in the photo captions?" I have good news! The hospital hired its first women in the two decades after this photo was taken, e.g. Dr Pearl Jane Sproule, chief of ENT 1924-1940.
Yet another image from "Doing Good: The Life of Toronto's General Hospital" by J.T.H. Connor. It shows an official photograph of two rows of physicians: nine standing in the back row, and five seated in the front row. The caption reads: "Although medicine remained an exquisitely male domain, in the twentieth century women started to breach its ranks. Dr Pearl Jane Sproule (seated left) was among the first to be appointed to the hospital's house staff; from 1924 to 1940, she was chief of the ear, nose, and throat department of Toronto's Women's College Hospital. Dr J.N.E. Brown, then medical superintendent, is seated centre."
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Edwin Dalmaijer @dalmaijer.bsky.social · 12/05/2025
I ended up looking up the book, and found the photo with the cited caption but without further context. I assume the newborn babies are indeed borrowed from the maternity ward. The book has pages and pages of photos with brief captions, some of which raise further questions (e.g. attached).
The image is again from the book "Doing good : the life of Toronto's General Hospital" by J.T.H. Connor. It shows ten physicians sat at a table. They are wearing black suits, most with their white cotes still on. Some appear to be smoking or eating, and one is draped over another. The caption reads "Members of the house staff had their own quarters in the hospital. As this 1898 glimpse of 'off-duty' behaviour illustrates, the manly pursuit of boxing, the consumption of beer, and the enjoyment of a good cigar contributed to 'male bonding'."
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Edwin Dalmaijer @dalmaijer.bsky.social · 12/05/2025
Older journal articles are typically uploaded as pages from the print copy, which means you often get the start and/or end of unrelated papers as a little bonus. This is the little bonus I got from @jama.com this morning. There is zero further context.
The image is a screenshot from a 2001 edition of the Journal of the American Medical Association (JAMA), volume 285, number 17. It shows fourteen physicians, posing for a group photo in their white coats. What makes this photo unique, is that all fourteen men are holding newborn babies. The photo caption reads: "“Even while ‘on duty,’ residents might indulge themselves to show the tender side of their masculine nature. Here members of house staff in 1904-5 pose with babies born in the Burnside Lying-In wing.” From: Doing Good: The Life of Toronto’s General Hospital, by J. T. H. Connor, 342 pp, with illus, $60, ISBN 0-8020-4774-2, Toronto, Ontario, Canada, University of Toronto Press, 2001. Reprinted by permission of University Health Network, Toronto, Ontario, Canada."
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Edwin Dalmaijer @dalmaijer.bsky.social · 06/05/2025
A real strength of this study is that we asked participants for their individual ratings for each stimulus and emotion. It allowed us to account for 1) individual differences in stimulus perception, and 2) stimuli often evoking a combination of core emotions.
The image is a graph with six sub-plots, each in a new row, top-to-bottom: Pupil size (arbitrary units), anger, disgust, fear, happy, and sad (all emotions rated 1-9). The x-axis shows the stimulus numbers, each coding for a different 30-second sound-stimulus from Experiment 2 in the paper. A box-plot with distribution estimate is visible for each stimulus-rating combination. Low ratings almost always showing strong agreement within each stimulus, but higher ratings show variability. For example, stimulus 19 was almost exclusively rated low on anger, disgust, fear, and sadness; but while its happiness rating was reasonably high on average (about 6), there was still substantial variability (especially in the 5-9 range). Key take-aways from the plot are  that ratings are variable but have some agreement, that stimuli can be rated high for more than one emotion, and that high disgust ratings mostly occured for stimuli that are also higher in pupil size.
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Edwin Dalmaijer @dalmaijer.bsky.social · 06/05/2025
NEW! Using #pupillometry during emotional stimuli, we found if/when individual stimulus ratings are associated with pupil size. In short, disgust was the strongest pupil dilator, whereas anger constricts it (a bit). Paper by fantastic first-author @kmccul.bsky.social et al.: doi.org/10.1016/j.bi...
The image is a graph that shows five lines (one for each emotion), punctuated with small dots for uncorrected statistical significance and bigger dots for statistical significance after multiple-comparisons correction. The x-axis is labelled "Time (seconds)" and runs from just before 0 to 30 seconds. The y-axis reads "Standardised beta coefficient" and runs from just under -0.15 to 0.3. A dotted line spans across y=0, and labels indicate that positive values mean that "Emotion predicts larger pupil" and negative values that "Emotion predicts smaller pupil". Anger (in red) shows a negative trajectory from ~5 seconds after stimulus onset, with some bits statistically different from 0. Fear (purple) is indistinguishable from 0, until it is associated with larger pupils in the last 2-3 seconds. Sadness is somewhat positively associated with pupil size, but not after multiple-comparisons correction. Happiness is associated with relative pupil dilation from ~3 seconds until the end of the stimulus. Disgust is by far the most prominent predictor of larger pupil size, with standardised coefficients about twice as high as for happiness.
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Edwin Dalmaijer @dalmaijer.bsky.social · 26/04/2025
One of my favourite parts of supervising undergraduate student projects is seeing some of them present at the Southwest undergrad conference. It feels like a proper conference, but is organised by and for final-year students. Lovely to see so many keen beans talking about their work! #SWUC2025
Image is a photo with a view from the back of a conference room, looking at students speaking in front of a projector slide that says “BPS Southwest Undergraduate Conference 2025”.
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Edwin Dalmaijer @dalmaijer.bsky.social · 11/04/2025
Was joined by a cheeky little robin for lunch today. Does this count as #UKbirding, or was I the subject of its human-ing?
This photo shows a pair of shoes, seemingly at the end of crossed legs (not visible). On the tip of the toes is a robin, stood straight up, with its head turned so that one eye looks into the camera.
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Edwin Dalmaijer @dalmaijer.bsky.social · 04/03/2025
OK, but:
Histogram showing a roughly normal distribution that is centred on 0.5. The x-label is "N(top&bottom) / N(top)", the y-label is "N observations". The face colour of the bars is hot pink.
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Edwin Dalmaijer @dalmaijer.bsky.social · 08/02/2025
If, for whatever reason, you're looking for a novel with a fresh take on AI tech dystopia: Adrian Tchaikovsky's Service Model is excellent. It's a clever take on robot cognition (but is it really cognition?), human nature, and societal collapse through perfectly normal function.
The cover of Service Model by Adrian Tchaikovsky. The background shows a modern skyline against a sunset-coloured sky. The foreground shows a robot hand that is shaped like a human's. The hand is delicately holding a cup that is slightly cracked and a has some thick red liquid along the rim.
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Edwin Dalmaijer @dalmaijer.bsky.social · 28/12/2024
DragonForce! First day of their new tour. 🤘
Photo shows a very busy podium during a DragonForce performance. A woman plays guitar on the viewer’s left, and a man sings (or shouts?) on the right. On the front of the podium, fireworks are going off (bright and towards white, possibly magnesium-based). From the back of the podium, but looming over it, are two giant dragons with open mouths full of teeth. In the foreground, the audience is visible.
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Edwin Dalmaijer @dalmaijer.bsky.social · 19/12/2024
Parents' reduced disgust avoidance generalised to non-child disgust elicitors. BUT: self-reported disgust sensitivity was lower only for parent-specific items, and otherwise the same as non-parent controls. This highlights a difference in behavioural and self-report measures of disgust. (3/3)
Graph showing three groups: non-parent controls, parents to exclusively milk-fed babies, and parents to weaning or weaned children. The three groups show no difference on general disgust sensitivity (measured with the revised Disgust Scale questionnaire), but parents do self-report lower disgust sensitivity for parent-specific items and diaper changes.
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Edwin Dalmaijer @dalmaijer.bsky.social · 19/12/2024
Kids are gross, and parents constantly have to deal with their shit (literally). Do they habituate to disgust? 💩 🧠 🧪 In this new preprint, we show that #parents are indeed less #disgust avoidant than non-parents, but only after their (youngest) has started weaning. doi.org/10.31234/osf... (1/3)
A 12-panel figure, with each panel showing the outcomes of a preferential looking task. In this task, participants were shown two stimuli (one neutral, one disgusting), and could freely look at each. Each graph shows the differences in dwell time between the two stimuli, as a function of time in each trial (10 seconds). Most panels show a brief initial bias towards the disgusting stimulus, followed by sustained bias away from it ("disgust avoidance"). The top row shows this for non-parent controls, across all four columns: regular bodily-effluvia, meconium diapers, milk-fed baby diapers, and weaning baby diapers. The bottom row shows the same categories, but for parents. This group shows no bias away from any of the disgusting stimuli! The middle row shows parents to exclusively milk-fed (i.e. very young) babies, and (surprisingly!) shows as much disgust avoidance as the non-parent control group.
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Edwin Dalmaijer @dalmaijer.bsky.social · 10/12/2024
‘t is the season to be cramming a day’s work into ~60-90 minutes of toddler nap time while they’re ill and off nursery, falalalala lala la la…
Photo of, literally, the snottiest baby you will ever see. They are looking directly at the camera, and the entirety of the space between their nose and mouth is snot. Literally all of it. It’s bulging out, it’s green, it’s flowing into their mouth. Frankly, it makes you wonder why the parent who took the photo decided to do that rather than actually wiping this poor child’s nose.
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Edwin Dalmaijer @dalmaijer.bsky.social · 06/12/2024
OMG, Duncan, they even copied the logo! What had Nemo done wrong?!
Google Maps screenshot that shows the storefront to "Frying Nemo" with a logo that closely matches that of the children's film "Finding Nemo".
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Edwin Dalmaijer @dalmaijer.bsky.social · 06/12/2024
Now we know: even in the absence of complex thought or communication, cumulative route improvements between can spontaneously emerge. Unexpectedly, it's because naive individuals helped their more experienced colleagues! Here's a video of the thing in progress. Paper: doi.org/10.1371/jour... (4/4)
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Edwin Dalmaijer @dalmaijer.bsky.social · 06/12/2024
Artificial navigators know roughly where the goal is, seek social proximity, and memorise landmarks along the route. That's it! And yet, naive agents learn routes from experienced ones. Crucially, naive agents err towards the goal, and thus bias each generation towards better efficiency. (3/4)
Figure 3 from Dalmaijer (2024, PLOS Biology). Each panel shows the difference in route efficiency between naive agents in the experimental condition (generational turnover) and the first 12 journeys from agents in the pair control condition (without generational turnover). Positive differences indicate that naive agents had better route efficiency compared to control. Each panel represents a combination of w_goal and w_social parameters, while darker lines indicate higher levels of w_memory. Lines represent averages across 50 independent runs and their shaded areas the 95% confidence interval. The graph shows quite a complex pattern, but in general higher memory weights are typically associated with better-than-control performance for naive individuals. This suggests they are helped by their experienced counterparts when learning a new route.Figure 4 from Dalmaijer (2024, PLOS Biology). Each panel shows the distribution of relative bearings towards the naive agent from the perspective of the experienced agent in generations 2–5 of the experimental condition. Positive values on the x-axis indicate bearings towards the goal, and negative values bearings away from the goal. Distributions are generally right-heavy, indicating a bias of naive individuals to be positioned in the general direction of the goal. This tendency increases as a function of w_social and to a lesser extent as a function of w_goal.
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Edwin Dalmaijer @dalmaijer.bsky.social · 06/12/2024
Pigeons navigate along idiosyncratic routes that improve between generations. Cumulative cultural evolution? This study shows that the same cumulative route improvements spontaneously emerge in simple artificial agents. Paper in @plosbiology.bsky.social: doi.org/10.1371/jour... (1/4; video at end!)
The "is this a butterfly?" meme in which a man looks at object and asks "Is this a ...?" In this case, the man is looking at a graph of inter-generational route improvements in pigeons and asking "Is this cumulative culture?"Figure with four panels. The top panels both show five generations of navigator pairs. They follow idiosyncratic curves, but each generation gets a closer to a straight line from start to finish. The left panels says "Artificial navigators" and the right "Pigeons", and look qualitatively similar. The bottom panels show a mixture model: four Von Mises distributions plotted in a radial plot (bottom-left) or a regular plot (bottom-right). Each is associated with a different navigational component: towards the goal, towards the other bird (labelled "social"), towards the next landmark in memory, and straight ahead (labelled "continuity"). Each component has their own weight and precision (i.e. narrow or wider spread). The sum of the four components is shown in the bottom-right panel, as a probability density function.
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Edwin Dalmaijer @dalmaijer.bsky.social · 06/12/2024
All koroks?! I’m super impressed! I mostly ended up doing silly stuff, like (mostly failing to) build a trebuchet.
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Edwin Dalmaijer @dalmaijer.bsky.social · 05/12/2024
Children are disgusting, it's a known fact. But why?! Adults show proto-nausea: a gastric response to grossness. We found this to be absent in 5-13 year-olds! However, children DID show the exact same behavioural avoidance as adults. Alladin & Berry et al. (2024), doi: doi.org/10.1177/2398... (1/3)
Graph with data from a preferential looking task in children aged 5-13 years. Time is on the x-axis and a measure of behavioural disgust approach/avoidance is on the y-axis. Three lines are shown: the first presentation of a stimulus (light green), and its two repetitions (increasingly darker green). The data shows that children initially looked more at disgusting stimuli, but from about 1 second into a trial they showed a bias towards neutral stimuli. This suggests they preferred to avoid looking at disgusting stimuli in exactly the same pattern that adults show.Graph showing electrogastrography results, with frequency on the x-acis (1-10 cycles per minute) and relative power (max-scaled within individuals) on the y-axis. A pink line indicates results when children (aged 5-13 years) looked at neutral stimuli, and it shows the expected peak in normogastric power at 3 cycles per minute. A green line shows the same but while children were looking at disgusting stimuli (bodily effluvia), and it almost exactly matches the pink line. These results suggest there was no proto-nausea (i.e. no gastric disgust signature) in the tested children (N=44).
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Edwin Dalmaijer @dalmaijer.bsky.social · 04/12/2024
Remember, it's only #Matlab if it's from the Matlab region in Bangladesh. Otherwise it's just sparkling Octave!
Top-down map view of Bangladesh. Dhaka is in the centre of the map, showing Matlab is in its south-south-western direction.Top-down map view of Matlab, showing a few local landmarks including the Matlab ferry terminal, hospital, and Government Degree College.
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