Wordle is a rather popular online code-breaking game that works as a words-based version of the old Mastermind game. If you do not know what wordle is, you may want to read this nice overview of the game and its success published in the Guardian. If you do know what Wordle is then you have probably wondered whether there is a perfect strategy to play it. I wondered the same and dedicated a Sunday evening of my time to run some experimental analysis which I like to share with the wordle world.
I then coded a wordle solver: a piece of software that will get the computer to play wordle against itself so that we can run hundreds of thousands of iterations and do some stats (here is a sample notebook on how to use it). The first thing to check is to calculate the null hypothesis: how successful would we be if we were to try and solve the puzzle using completely random words at every attempt? The answer, based on a Montecarlo repeat of 100k games, is 0.25%. That means we would fail 99.75% of the time. We can certainly do better than that!
We can now go and evaluate different strategies. I am not going to take a brute-force approach for this problem but rather a hypothesis drive one, listing strategies that I believe real users are considering. I evaluate two variables in the strategy: the first variable is whether it makes sense to start with a “smart word”, that is a word that contains a pondered amount of carefully selected letters. For instance, we may want to start with words that contain the most frequently used letters in the list. Analyzing the letter frequency in all the 2315 wordle words, we come down with the following values:
We can now come up with a list of word that uses the most frequent letters, excluding of course words that have double letters inside. The first 20 words in the list for the wordle dataset would be the following ones:
['LATER', 'ALTER', 'ALERT', 'AROSE', 'IRATE', 'STARE', 'ARISE', 'RAISE', 'LEARN', 'RENAL', 'SNARE', 'SANER', 'STALE', 'SLATE', 'STEAL', 'LEAST', 'REACT', 'CRATE', 'TRACE', 'CATER', 'CLEAR', 'STORE', 'LOSER', 'AISLE', 'ATONE', 'TEARY', 'ALONE', 'ADORE', 'SCARE', 'LAYER', 'RELAY', 'EARLY', 'LEANT', 'TREAD', 'TRADE', 'OPERA', 'HEART', 'HATER', 'EARTH', 'TAPER', 'PALER', 'PEARL', 'TENOR', 'ALIEN', 'AIDER', 'SHARE', 'SHEAR', 'CRANE', 'TAMER', 'GREAT']
Some of these words actually have the same valence given that they are anagrams of each other but the list provides some sensible starting point for what I will be calling the “smart start strategy”. The alternative to a smart strategy is to be using a random word every time.
The second variable in our strategic considerations is whether it makes sense to use exclusion words. Exclusion words are words that do not contain letters that we have already tested. They allow us to learn more about which letters are or are not present in the final word. For instance, in the two examples below we use a smart word start and then an exclusion word next which not only ignores but actually avoids all the letters used in the first attempt, even when successful. This allows us to learn more about which letters we should be using.
An exclusion strategy could be used for attempts number 2 and attempt number 3 in principle, like in the two examples below:
Obviously, the drawback of using an exclusion strategy is that we are not going to be able to guess the word because we are purposely excluding the letters we know are in the final word!
There are other aspects of the strategy that we should be using that we could in principle test: for instance, when should we start using words with double letters? If we take the smart word start, I believe we should exclude words with double letters and the same of course apply with the exclusion strategy too. So, all in all we can now compare four different strategies:
|Strategy||Use Smart Start?||Exclusion words|
We run a Montecarlo simulation of all four strategies, setting 1000 games each and we find the following performance per strategy
All strategies perform very well overall, with a success rate above 95%. The distribution of successful attempts is gaussian as expected, with a peak at attempt 4. Obviously, any exclusion strategy will preclude the possibility to guess the word at attempts number 2. So the take-home message is the following: if we want to maximize the probability of finding the word we should use strategy number #4 which gives us the highest success rate of 97%. However, that high success rate comes at the expense of renouncing the possibility of finding a guess at attempts 1-3. If we want to maximize early successful attempts (at the expense of success rate) we should go for strategies 2 or 3.
Interestingly enough, the system can also be used to evaluate how difficult a word is. For instance, in the example below we try to solve the word QUERY (left) or DRINK (right)
The social restrictions caused by the pandemic have annihilated the galaxy of scientific conferences as we knew it. Many conferences have tried to move online, in the same way we moved 1-to-1 meetings or teaching online: we applied a linear transposition trying to virtually recreate the very experience we were having when traveling physically (for good and for bad). I would argue that the linear translation of a physical conference to the virtual space, has managed to successfully reproduce almost all of the weaknesses, without, however, presenting almost any of the advantages. This is not surprising because we basically tried to enforce old content to a new medium, ignoring the limits and opportunities that the new medium could offer.
Something similar happened in science before, when journals transitioned from paper to the web: for years, the transition was nothing more than the digital representation of a printed page (and for many journals, this still holds true). In principle, an online journal is not bound to the physical limitation on the number of pages; it can offer new media experiences besides the classical still figure, such as videos or interactive graphs; it could offer customisable user interfaces allowing the reader to pick their favourite format (figures at the end? two columns? huge fonts?); it does not longer differentiate between main and supplementary figures; it costs less to produce and zero to distribute; etc, etc. Yet – how many journals are currently taking full advantage of these opportunities? The only one that springs to mind is eLife and, interestingly enough, it is not a journal that transitioned online but one that was born online to begin with. Transitions always carry a certain amount of inherent inertia with them and the same inertia was probably at play when we started translating physical conferences to the online world. Rather than focusing on the opportunities that the new medium could offer, we spent countless efforts on try to parrot the physical components that were limiting us. In principle, online conferences:
Instead of focusing on these advantages, we tried to recreate a virtual space featuring “rooms”, lagged video interaction, weird poster presentations, and even sponsored boots.
Rather than limit myself to discussing what we could do, I shall try to be more constructive and offer some practical suggestions on how all these changes could be implemented. These are the tools I have just used to organise a dummy, free-of-charge, online conference.
For live streaming: Streamyard
The easiest tool to stream live content to multiple platforms (youtube but also facebook or twitch) is streamyard. The price is very accessible (ranging from free to $40 a month) and the service is fully online meaning that neither the organiser not the speakers need to install any software. The video is streamed online on one or multiple platforms simultaneously meaning that anyone can watch for free simply by going to youtube (or facebook). The tutorial below offers a good overview of the potentiality of this tool. Skip to minute 17 to have an idea of what can be done (and how easily it can be achieved). Once videos are streamed on youtube, they will be automatically saved on their platform and can be accessed just like any other youtube video (note: there are probably other platforms like streamyard I am not aware of. I am not affiliated to them in any way).
For asynchronous discussion and interaction between participants: reddit
Reddit is the most popular platform for asynchronous discussions. It is free to use and properly vetted. It is already widely used to discuss science also in an almost-live fashion called AMA (ask-me-anything). An excellent example of a scientific AMA is this one discussing the discoveries of the Horizon Telescope by the scientist team behind them. Another interesting example is this AMA by Nobel Laureate Randy Sheckman. As you browse through it, focus on the medium, not the content. Reddit AMAs are normally meant for dissemination to the lay public but here we are discussing the opportunity of using them for communication with peers.
For sake of example, I have just created a dummy conference on reddit while I was writing this post. You can browse it here. My dummy conference at the moment features one video poster and two talks as well as a live lounge for general discussions. All this was put together in less than 10 minutes and it’s absolutely free. Customisation of the interface is possible, with graphics, CSS, flairs, user attributes etc.
Notice how there are no costs of registrations, no mailing lists for reaching participants, no zoom links to join. No expenses whatsoever. The talks would be recorded and streamed live via streamyard while the discussion would happen, live or asynchronously, on reddit. Posters could be uploaded directly by the poster’s authors who would then do an AMA on their data.
Both talks in my dummy conference were taken by the World Wide Neuro seminar series, the neuro branch of the world wide science series. Even though this is seminar series, it is as close as it gets to what an online conference could be and the project really has to be commended for its vision and courage. This is not the online transposition of a physical conference but rather a seminar series born from scratch to be online. Videos are still joined via zoom and the series does lack features of interaction which, in my opinion, could be easily added by merging the videos with reddit as I did in my dummy conference example.
It is technically possible to create an online conference at absolutely no expense. The tools one can use are well-vetted and easy to use on all sides. This does require a bit of a paradigm shift but it is less laborious and difficult than one may think.
One of the most puzzling aspects of sleep is that it cannot happen without depriving us of our full conscious experience. Whatever the function of sleep is, it cannot be achieved without disconnecting our brains from the external world. A full conscious state and sleep are not compatible, it seems, to the point that one of the definitions of consciousness is that “it is all that fades away when we are in dreamless sleep”.
The fact that the brain has to surrender to the tyranny of sleep is also the main reason why scientists believe (in a rather dogmatic fashion) that sleep is “of the brain, by the brain for the brain“. Yet, even during sleep parts of our brains retain some ability to process external information. In the 1960s, Oswald et al formally showed that sleeping humans could wake up in response to some salient stimuli, such as their names being called, but not in response to stimuli of identical strength but no salience, such as other people’s names or their names played in reverse.
This finding has been confirmed and extended over the decades in the scientific literature, providing evidence that it applies to even more complex nuances of saliency, such as an angry tone of voice. The videos below suggest that scientific literature is certainly less comprehensive and (less amusing) than the phenomenon in its entirety.
Even though we have numerous scientific and anecdotal evidence that animals and humans can wake up to salient sensory stimuli during sleep, hardly anything is known about the biological underpinning of this phenomenon. And here: enter Drosophila melanogaster! What better animal model than flies to dissect this amazing brain property?
In a paper titled “Sensory processing during sleep in Drosophila melanogaster” published in Nature, we introduce flies as the ideal animal model to dive into the biology of how a brain can simultaneously be asleep and respond to external stimuli.
Postdoc Alice French took the lead on this amazing project to show that even flies can recognise salient stimuli in their sleep and react accordingly, modulating their response based on their internal state. We initially expanded the robotic platform we had previously built in the lab, called ethoscopes, which allows us to monitor and interfere with flies using inexpensive @Raspberry_Pi computers. Alice wanted to build a robotic component able to challenge single flies with specific odour but only while they were asleep, to record whether they would wake up or not. She obviously started with…. LEGO!
In our first prototype, we built a robot able to operate a LEGO valve so to send a puff of air to the sleeping fly. LEGO valves were a good start because we needed 500 of them.
The system worked and we went from those early all-LEGO prototypes (left) to the final 3D printed product (right).
Using this ethoscope module we could challenge sleeping flies with different odours and check whether they would respond differently to some of them. We found they did! Flies would respond to 5% acetic acid for instance, but not to 10% acetic acid. Not only that, the valence of the odour could be modulated by internal states. Flies that had received a little starvation were increasing their response specifically to food-related odours. When we gave alcohol to flies, on the other hand, we found drunk Drosophilae were less responsive to odours in general showing somehow a deeper sleep state.
Now, flies are arguably the best animal model to study circuit neuroscience these days. We have a full connectome of the fly brain and countless genetic tools that allow us to turn neurons on and off. So that is what we did. We started turning neurons on and off in the fly brain, looking for some that would modulate their ability to sense stimuli during sleep. We found them!
We actually found the whole circuit, connecting the “fly nose” all the way to the sleep centers in the brain. And when we used thermogenetics to switch those neurons on or off with infrared radiation, we could interfere with that process and make the flies more or less responsive.
In short, we have shown that flies can recognise and respond to odours during sleep, waking up only to those that they consider salient. We also show that this phenomenon is plastic and modulated by internal states, with animals being more likely to wake to food odours after a little starvation. We also described a blueprint for a neuronal circuit that connects the peripheral olfactory receptor neurons all the way to known sleep-regulating centres in the fly brain. We explore three prototypical gate-points that modulate subconscious processing of olfactory information during sleep: two at the periphery and one in the central brain.
The story is important and of general interest for at least three reasons:
Drosophila has been employed to study arousal threshold many times before. There are many studies in which flies can be used to gauge sleep “depth” by using quantitative mechanical stimuli, such as simple vibration or touch. Our study is the first one to study a more puzzling property: how do we recognise qualitative stimuli during sleep? How do we recognise our own name while unconscious?
The video abstract below provides more information on the contents and the implications of the work.
The full reference to the paper is:
The work was supported by BBSRC and H2020-Marie Curie funding. The lead author of the study is Dr. Alice French.
Nature has featured the paper with a dedicated News & Views by Wahne Li and Alex Keene.
Imperial wrote a little PR piece.
Drosophila melanogaster, commonly known as fruit fly or more appropriately vinegar fly, is the second most common animal model used in research. Initially established by Thomas Hunt Morgan at the beginning of 1900s to provide an empirical base to the groundbreaking hypotheses of Darwin, flies have contributed to science in every realm, from development to genetics and neuroscience. 6 Nobel prizes have been awarded to flies in the past century, with the last one being awarded in 2018 to three Drosophila researchers for their work in the characterisation of circadian behaviour.
My laboratory uses flies to try and answer one simple, yet fascinating question: why do we sleep? What is sleep for and why humans and all animals seem to require sleep? Our approach is somehow different mainstream one, because flies force us to think to the problem in an unusual and more creative way. So far this has paid off egregiously, and we have managed to make very important discoveries that apply well beyond the fly realm.
One aspect of our research that may be particularly interesting for someone puzzled about the science of physical well being, is that we do not consider sleep to be a prerogative of the brain but actually a phenomenon that affects every part of our body. Whenever we lack sleep – whether for fun or for work – we can feel an effect of sleep deprivation not just on our cognitive performance but on our very body too. This is more than a subjective feeling: it is a well-established phenomenon in humans and animals. Why is it so? Studying sleep deprivation in flies we hope to give an answer to this question.
In particular, we use state of the art technology to a) deprive flies of sleep employing custom-made robots and b) exploring what changes at the cellular level when we lack sleep. How genes, proteins, and other molecules change their composition when we lack sleep?
We can use the same robotic technology to also study physical behaviour in these animals: are they in good shape? Can they climb a wall as they normally do? Can they fly with the same stamina and precision? A great amount of literature in the field of muscular degeneration has been obtained in fruit flies and we have learned a great deal about genes controlling these aspects and how they fail in disease.
A very important corollary of our research is that understanding the functions of sleep opens the door to what we somehow half-jokingly call “the sleep pill”. If could understand what aspects of sleep make us refreshed and performing – both behaviourally and physically – we could then replace sleep pharmacologically. Or we could consolidate the beneficial aspects of sleep to increase its restorative power. To do that, we first need to understand what sleep is and what it does.
What would we do with a philanthropic donation?
We would employ the money to retain a brilliant young research assistant for a year or longer so that she could continue working on her project. The student recently graduated from an MSci in Neuroscience and she joined our laboratory for a summer placement in order to gain first-hand insights into our research. If she could stay longer, she could join and potentiate the research line of the laboratory that looks at the direct consequences of sleep deprivation. I have been working with Imperial Alumni who were kind enough to donate to my laboratory in the past. It has been a great honour and a pleasure and I am looking forward to doing this again.
Nat Protoc. 2012 Apr 26;7(5):995-1007.
Video tracking and analysis of sleep in Drosophila melanogaster.
Giorgio F. Gilestro
In the past decade, Drosophila has emerged as an ideal model organism for studying the genetic components of sleep as well as its regulation and functions. In fruit flies, sleep can be conveniently estimated by measuring the locomotor activity of the flies using techniques and instruments adapted from the field of circadian behavior. However, proper analysis of sleep requires degrees of spatial and temporal resolution higher than is needed by circadian scientists, as well as different algorithms and software for data analysis. Here I describe how to perform sleep experiments in flies using techniques and software (pySolo and pySolo-Video) previously developed in my laboratory. I focus on computer-assisted video tracking to monitor fly activity. I explain how to plan a sleep analysis experiment that covers the basic aspects of sleep, how to prepare the necessary equipment and how to analyze the data. By using this protocol, a typical sleep analysis experiment can be completed in 5-7 d.
pyREM: a crowd trained machine learning approach to automatic analysis of EEG data
Quentin Geissmann, and Giorgio F Gilestro
EEG data are at the basis of a plethora of neuroscientific questions: from sleep to consciousness and attention, many aspects of neuroscience heavily rely on electrophysiological correlates of brain activity. Yet, EEG analysis heavily relies on subjective scoring and interpretation to the point that many neuroscientists consider it an art, more than a systematic tool.
Can we teach this art to a computer?
Attempts at creating an objective way of scoring EEG data have been less than perfect so far, mainly because humans are reluctant about trusting the judgement of a machine, programmed according to hard-coded values and thresholds.
pyREM aims at solving this issue, using a machine learning approach to automatically analyse EEG data. pyREM learns how to classify EEG directly from humans, mimicking all the human’s principles and criteria without any apriori knowledge of what an EEG means. The overall goal of the project is to teach pyREM how 1, 10, 100 or 1000 laboratories score EEG so that the software will be able to automatically grasp and isolate the key fundamental criteria and become, in this way, the universal scorer.
If you are a laboratory interested in being part of this, please get in touch.
If you want to know more, you can
PLOS Biology, 19 Oct 2017; 15(10): e2003026
Ethoscopes: An Open Platform For High-Throughput Ethomics
Quentin Geissmann, Luis Garcia Rodriguez, Esteban J. Beckwith, Alice S. French, Arian R Jamasb, and Giorgio F Gilestro
We present ethoscopes, machines for high-throughput analysis of behaviour in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behaviour using a supervised machine learning algorithm; can deliver behaviourally-triggered stimuli to flies in a feedback-loop mode; are highly customisable and open source. Ethoscopes can be built easily using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.
Supplementary material 1 – webGL model of the ethoscope.
Supplementary material 2 – instruction booklet for the LEGOscope.
Supplementary material 3 – instruction booklet for the PAPERscope.
Supplementary Video 1 – Introduction to the ethoscope platform.
Supplementary Video 2 – The optogenetics component of the optomotor in action.
What is teaching? In general terms, I believe there are two possible answers to this question. In its simplest – yet admittedly not trivial – form, teaching is the organised transfer of information from a teacher to a student. Finding the best strategy to act on this process may seem like a novel problem to a newly starting university lecturer but, conceptually, it is a problem that mankind has in fact solved about 5000 years ago, during the bronze age, with the advent of writing. Information, especially when factual, does not require the physical co-presence of teacher and student, for it can almost always be conveyed using written words and diagrams. Especially in the Biological Sciences, a textbook is a sufficient instrument of information transfer more often than not. What we teach is factual, usually not conceptually challenging and only partly mnemonic. In general, all the factual contents we offer to first and second-year undergraduate students can be easily found on a plethora of textbooks; third years’ and postgraduate contents should be found in textbooks and in academic literature. If all the information we aim to transfer can be conveniently and efficiently read on paper, why do we even bother? Why are the students investing time and resources to pursue an activity that could be easily be replaced by accessing a library? The answer to this latter question is what I refer to as “the added value” of university teaching and it describes the second, less obvious, and most challenging definition of what teaching really means.
My teaching philosophy has evolved around this concept of added value. What is my role as teacher and how can my work and presence enrich the learning experience of the student? What can I offer than a very well written book cannot? I came to the conclusion that my added value breaks down into 4 parts:
Being able to recognise quality in information is a fundamental translational skill. University libraries are normally maintained by scholars to feature only reliable sources and therefore students learn to see the University library as a knowledge sanctuary where any source can safely be considered as “trusted”. This indubitably helps them in selecting material, but will not develop their critical sense. Being able to find and recognise trusted sources and reliable material should be a key translational skill of their degree, which they will value in their careers and also as responsible citizens. To help with this goal, I encourage them – read: I force them – to go out of their literature comfort zone. In the classroom, I focus lectures on topics that are new and developing so that they will be driven to explore primary literature and not rely on textbooks when studying and revising. Another advantage of selecting developing topics is that these are often genuinely controversial. Research that is still developing is usually prone to multiple, often contrasting, interpretations by scholars. I present students with the current views on the topic and ask them to dissect arguments in one or another direction. This develops their critical sharpness. Literature dissertations and “problem-based learning” (PBL) are also an excellent exercise for them to browse and pick literature. I dedicate half spring-term to literature dissertation in the MSc course I am currently co-directing, and I supervise PBL tutorials for the 2Yr Genes and Genomic course. Both activities are very successful.
Obviously, not all our students will become scientists but I believe they should all be trained to be. Thinking and acting according to the Galilean method is an undervalued translational skill of modern society. Also, not many other Universities in the world have a research environment as vibrant and successful as Imperial College London, and being exposed to real cutting-edge Science is certainly an important potential added value for our students. I try to bring scientific ethos in the classroom by presenting the actual experimental work behind a given discovery. In a second year module on RNA interference, I present one by one the milestone papers that created and shaped the field and I elucidate the key experiments that have led, eventually, to a Nobel prize. In the same course, I also teach about CRISPR-Cas9, presenting the controversy between the two research groups that are still fighting for the associated patent (and, most likely, for another upcoming Nobel prize). I present experiments in the way they are naturally laid out, from hypothesis to theory. I also try my best to instil a sense of criticality and a sense of “disrespect towards Aristotelian authority”. Ultimately, my goal is for students not to be afraid to contradict their teacher – as long as they can back up their claims with factual information, that is. Admittedly, this exercise does not achieve the same result with all students as it requires a particular mindset of self-confidence that not all students possess. It does, however, greatly benefit the most independent and intellectually acute ones, who show great appreciation informally and formally on SOLE.
Being able to intellectually capture the students’ curiosity is possibly the most powerful skill of a teacher. My ultimate goal is to “seed” information into my lecture and let the students develop it on their own. If they develop wonder and curiosity towards an argument, they will be more likely to master it and enjoy it. There is no secret recipe for doing this – as passion must be genuine and cannot be mimicked – but I found there are four steps that definitely help.
a) and b) are factors that largely depend on the course convenors. For instance, convenors can organise lecturers so that they are asked to lecture on topics that are close to their own research area. This is a very easy way to generate transmissible enthusiasm. For developing b), it is normally preferable to have longer contact with the same cohort of students: I would very much rather do 8 hours in the same course than 8 hours spread to a different cohort of students. c) can be achieved by intercalating the lecture with historical anecdotes, for instance about the biography of scientists behind a certain discovery or even about personal events that I lived or witnessed in my research activity, throughout my career. This teaching style will make the lecture conversational, it will generate curiosity and set a more natural discursive pace of interpersonal communication. d) is an underestimated, very powerful exercise. In fact, I think the EDU office should actually consider a new course devoted to teaching without the use of powerpoint slides. Not relying on anything but our own theatricality is the best way to gather the undivided students’ attention.
I am quite satisfied with the progress I made so far on points 1-3, and this last fourth step represents my next challenge as a teacher. When facing a cohort of 150 students, as we do with our 1st and 2nd year UG courses, we clearly deal with students of different academic abilities. For whom should we teach? What pace should we follow? Where shall we set the intellectual bar? I found that creating a right mix of “facts and passion” is a good strategy: the average student will receive all the facts; the more intellectually gifted one will then expand on those inspired by the newly found passion. However, I also believe that delivering different contents to different parallel streams is the one aspect where modern technology can really come to help. My plan for the future is to develop a series of “reverse classroom” lectures, presenting all students with prerecorded material and – possibly – with lecture notes too. The goal is to keep classroom time for passion and discussion and stream the basic factual information through video and notes.
I found my experience as a teacher so far together with the introductory courses of the EDU team gave me enough background material on the educational science. However, my goal for the future is to tackle the theoretical aspects of teaching in the same way and to the same extent as I do my research. In particular, I want to deepen my knowledge of andragogy and venture in the current literature of instructional theory.
This is something I actually had to produce for my educational training at the College. I thought it may be useful to share with the world. Apologies for the akward writing style.
Why we sleep remains an unresolved mystery of biology. Why do humans have to spend one-third of their lifetime in a status of profound unconsciousness which leaves them vulnerable and endangered? What do we gain from it? We still do not possess an answer to this question but we assume that it must be something tremendously important, also considered that sleep appears to be a necessity not just in humans but in all animals – including fruit flies. A particularly intriguing evolutionary conserved feature of sleep is what we call “sleep homeostasis”, that is: the innate modulation of sleep pressure based on previous sleep amount. If we have a good long nap, we may have a harder time falling asleep at night; conversely, if we pull an all-nighter partying on Sunday night, we are going to have a hard time at the office on the following morning. That is sleep homeostasis.
Is sleep homeostasis an unmodifiable, sovereign need in the animal or can it somehow be suppressed? Previous studies showed that migratory birds may be able to resist the temptation to sleep while flying above the ocean. Similarly, male pectoral sandpipers, a type of Arctic bird, can forego sleep in favour of courtship during the three weeks time window of female fertility. Could we find a similar behaviour in a genetically amenable animal model, like fruit flies?
In a “blind date” experiment, we forced interaction in a restricted space between socially naive, young, male fruit flies and receptive females. The interaction between the two led to an uninterrupted passionate courtship lasting the entire 24 hour period (and to one – and, in some cases, more – events of copulations). Surprisingly, not only did male flies forego sleep when prompted with a receptive female counterpart, but they also suppressed their natural sleep homeostasis and never recovered from the sleep lost courting. In the second set of experiments, we forcefully kept flies awake by employing robots that would automatically disturb the flies whenever they would fall asleep. At the end of the sleep deprivation treatment, flies would normally recover the lost sleep by having an extra nap. However, raising the sexual arousal of male flies by simply exposing them to the female pheromone, abolished their homeostatic need.
Ours is a study on the fundamental biological underpinnings of sleep. Our goal is to show that sleep is not a disconnected, uncontrollable phenomenon but a biological drive that can, in some conditions, be overcome. The study is particularly directed at other researchers and provides an important caveat not to be forgotten when conducting sleep experiments: it is possible to create an internal state in the animal that will heavily affect sleep regulation, without interfering with sleep regulatory circuits. A researcher may be artificially activating neurons that make an animal stressed, anxious, angered, or in love and all of these neurons will ultimately have an effect on sleep. Yet, they shall not be classified directly as “sleep neurons” or we will end up with a false map of where sleep neurons really are.
eLife 2017 Sep 12;6;e27445
Regulation of sleep homeostasis by sexual arousal
Esteban J. Beckwith, Quentin Geissmann, Alice S. French, and Giorgio F. Gilestro
eLife insight: Sleep: To rebound or not to rebound — Stahl BA, Keene AC