This older paper breaks down the basic ideas used here in a straightforward way.
This is really interesting, thanks so much!
It says here that the “maximum amount of information that could be communicated by the sequence of sounds made is less than 1 bit per second.” This is exactly what I’ve been looking for. I’ve been trying to find if this was a metric that various species communication systems were being measured by. Which animals have the most potential information being sent, and how does it compare to human communication? Are there other animals potentially transmitting more information per second than us?
Also, it seems like there is another way that a communication system could be measured for information density. There is the amount of data per time, but also the amount of unique items or sequences that ever even get made. It would be fascinating to see a chart of a bunch of species being compared by these measures.
In this paper they talk about these units as being the smallest symbols, but i wonder if it is known for sure that there are no temporal fine structures or minor fluctuations or anything else that might also be holding information.
It’s been a minute since I read it but I recall an argument about the attenuation of sounds in water as the basis of their confidence they had found the fundamental unit of sound. I’m feeling that the rabbit hole goes a lot deeper on that question though.
Im thrilled you liked it. I read this back when it was new because I had just wrapped my head around information theory for my own dissertation work. Information theory is a super handy conceptual tool that I think needs to be introduced at a lower level in education.
Shannons entropy equation is quite simple symbolically. It is a good entry point to symbolic reasoning because the concept of information optimality is easy to convey by common analogy and simple plots. I remember reading the whale song paper as a twisted form of graduate student relaxation, (I’m better now thank you) and seeing the different application of the same math really made many things fall into place.
Haha, I’m glad you’re better!
I have just a very casual understanding of information theory with a slight grasp on Shannon entropy. I was wondering if we mathematically had any sort of provable limits on the amount of data that a particular species’ communication system could be transmitting. It would be interesting to compare whatever human’s theoretical max data rate is(based on acoustic space) to what the actual amount of data that is being transmitted.
We had an article on here a little while ago about diabetes being detectable by listening to a voice recording. That would be information that is encoded in our voices without us even trying to do so, and even without others being able to naturally detect it. That seems to mean that the amount of data being sent intentionally is different than the amount of being actually sent. I wonder how common this is in nature for an animal to send information in their voice without knowing they are sending it, and if it does happen, are other animals able to pick up on this unknowingly transmitted information.
Just a recent primer on how ecology and evolutionary biology look at the question…
Ecology and Evolution of Bird Sounds
Interesting questions!
I think the hardest methodological constraint to answering those questions is the difficulty of determining the intent of a bird. How in the world would we determine what the bird wanted versus what it was actually conveying?
Thanks for the link, but unfortunately, I can’t get it to load anything other than science directs website. Do you have a link to the page before the pdf or something?
It would indeed be difficult to get intent from a bird, or really from any animal. There is a bird, the blue throated hummingbird, that makes sounds at a higher frequency than its able to hear. Not exactly the same thing though.
https://www.sciencedirect.com/science/article/pii/S0960982222012258
Sorry for the bogus link. Try the above link and if that fails the title yields one exact result on google scholar. Ecology and Evolution of Bird Sounds.
The example of a hummingbird emitting sounds higher than it can hear is so fascinating. Mere artifact or evolution?
Thanks, yeah, this link works, I’ll check it out.
I heard about the hummingbird in Ed Yong’s book, An Immense World. He said in there that the theory is that it is making such high songs(~30KHz), despite having a range of hearing that only goes up to about 8KHz, most likely due to the fact that the insects it eats is using high frequencies. I don’t know if they are actually attracting insects with it or just messing with their own communication or what. In general, that book by Yong was really good, it’s a decently in-depth look at all the different senses.
That article was really good. It has a great list of related articles at the end as well. Thanks for sharing it! I’ve made it is own post.
Summary made by ChatGPT
The paper “Information Theory Opens New Dimensions in Experimental Studies of Animal Behaviour and Communication” by Zhanna Reznikova provides a comprehensive review on the application of information theory to the study of animal behavior and communication. It highlights the use of Shannon entropy and Kolmogorov complexity for analyzing and comparing animal behaviors, notably in leader-scouting ant species, and introduces data compression methods for classifying behavioral sequences. This innovative approach allows for the quantification of innate and learned behaviors, offering insights into the complexity and variability of animal communications without the need for signal decoding. It also opens new avenues for understanding animal intelligence and language, demonstrating the potential for abstract information transfer among ants. The paper’s methodological advancements enable the detection of nuanced behavioral patterns and contribute significantly to ethology and computational biology.
Discovery Details: The paper details the discovery of sophisticated “languages” in ants, capable of conveying abstract information about remote events. It also demonstrates the application of information theory in classifying and analyzing animal behavior, providing a quantitative measure to differentiate between innate and learned behaviors.
Methodological Breakdown: The research utilizes Shannon entropy and Kolmogorov complexity to analyze animal behavior sequences as “texts.” It introduces a novel data compression method for classifying these sequences, highlighting the potential for information theory in ethological studies.
Challenges and Opportunities: Challenges include the complexity of applying information-theoretical concepts to biological data. However, the approach offers opportunities for unraveling the complexities of animal communication and cognition, suggesting paths for future interdisciplinary research.
TLDR: The paper showcases the application of information theory to animal behavior analysis, introducing new methods for studying animal communication and cognition, particularly in ants. It highlights the potential of these methods for revealing complex patterns in animal behaviors and communications.
AI Thoughts: This research underscores the profound implications of information theory in understanding animal communication and cognition. It suggests that animals, like ants, possess complex communication systems, potentially comparable to human language in their ability to convey abstract concepts. This opens up exciting prospects for future research across disciplines, including artificial intelligence, where algorithms could mimic or learn from such natural communication systems, enhancing our understanding of both animal intelligence and potential AI development.
