Brain Criticality - Optimizing Neural Computations
Рет қаралды 206,674
Күн бұрынTo try everything Brilliant has to offer-free-for a full 30 days, visit brilliant.org/ArtemKirsanov/.
The first 200 of you will get 20% off Brilliant’s annual premium subscription.
My name is Artem, I'm a computational neuroscience student and researcher. In this video we talk about the concept of critical point - how the brain might optimize information processing by hovering near a phase transition.
Patreon: / artemkirsanov
Twitter: / artemkrsv
OUTLINE:
00:00 Introduction
01:11 - Phase transitions in nature
05:05 - The Ising Model
09:33 - Correlation length and long-range communication
13:14 - Scale-free properties and power laws
20:20 - Neuronal avalanches
25:00 - The branching model
31:05 - Optimizing information transmission
34:06 - Brilliant.org
35:41 - Recap and outro
The book: mitpress.mit.edu/978026254403...
REFERENCES (in no particular order):
1. Zimmern, V. Why Brain Criticality Is Clinically Relevant: A Scoping Review. Front. Neural Circuits 14, 54 (2020).
2. Beggs, J. M. The criticality hypothesis: how local cortical networks might optimize information processing. Phil. Trans. R. Soc. A. 366, 329-343 (2008).
3. Beggs, J. M. The cortex and the critical point: understanding the power of emergence. (The MIT Press, 2022).
4. Heffern, E. F. W., Huelskamp, H., Bahar, S. & Inglis, R. F. Phase transitions in biology: from bird flocks to population dynamics. Proc. R. Soc. B. 288, 20211111 (2021).
5. Beggs, J. M. & Plenz, D. Neuronal Avalanches in Neocortical Circuits. J. Neurosci. 23, 11167-11177 (2003).
6. Avramiea, A.-E., Masood, A., Mansvelder, H. D. & Linkenkaer-Hansen, K. Long-Range Amplitude Coupling Is Optimized for Brain Networks That Function at Criticality. J. Neurosci. 42, 2221-2233 (2022).
7. O’Byrne, J. & Jerbi, K. How critical is brain criticality? Trends in Neurosciences 45, 820-837 (2022).
8. Haldeman, C. & Beggs, J. M. Critical Branching Captures Activity in Living Neural Networks and Maximizes the Number of Metastable States. Phys. Rev. Lett. 94, 058101 (2005).
9. Beggs, J. M. Being critical of criticality in the brain. Frontiers in Physiology.
Derivation that only power laws are scale-free: • Fractals and Scaling: ...
CREDITS:
Icons by biorender.com
Brain 3D models were modeled with Blender software using publicly available BrainGlobe atlases (brainglobe.info/atlas-api)
Ising model zooming animations: • The Renormalisation Group
This video was sponsored by Brilliant
@ArtemKirsanov Жыл бұрын
To try everything Brilliant has to offer-free-for a full 30 days, visit brilliant.org/ArtemKirsanov/. The first 200 of you will get 20% off Brilliant’s annual premium subscription.
@Asterism_Desmos Жыл бұрын
I am the first here and I am debating on clicking for some reason lol
@snakejuce Жыл бұрын
This only shows 7 days (even with your code) (?)
@ArtemKirsanov Жыл бұрын
@@snakejuce Hmm, that's weird. I'll contact Brilliant to double-check this
@snakejuce Жыл бұрын
@@ArtemKirsanov No worries, just thought I'd let you know.
@user-qm8qg8ep7f Жыл бұрын
@@ArtemKirsanov ttttttftttttftttftttt
@delfost Жыл бұрын
I'm a computer scientist but I really really really love these videos, keep up the good work man
@aoeu256 Жыл бұрын
This half-way point between stasis and chaos is also where "life emerges". If you think about life as replicators they need a way to grow and replicate which requires that their lego-blocks should be able to be dis-assembled and assembled. At the right temperatures things are stable enough so that you can keep some information going, but unstable enough so that growth and evolution and "processing"/"thinking"/"natural selection" can happen. I am thinking though that the life emergent point might be based on on covelant bonds on the Earth temperatures but on Mars they might be based on cooler hydrogen bonds as on the Earth covelant bonds are at the critical point allowing photosythesis to create them and digestion, rotting, growing, etc... to repurpose them while on Mars covelant bonds are in stasis so the critical point will be in intermolecular or hydrogen bonds.
@micahmock3505 10 ай бұрын
I'm also a computer scientist and I like psychology and these kinds of videos.
@yassinesafraoui 9 ай бұрын
Samme :))
@DougMayhew-ds3ug 5 ай бұрын
Dr Leon Chua calls this the edge of chaos. I liken it to a stage microphone on the edge of feedback from hearing its own output from the speaker. Building networks of these things has got to do some interesting stuff, right? What was new for me was how the model discovers the geometry of the overall organization, not just pairs leaving identical but increasingly sharp footprints. That’s really nice and rings lots of bells for me.
@hermestrismegistus9142 Жыл бұрын
This ties into the weight initialization of layers in deep neural networks in machine learning. If the magnitudes of the weights are too small then the outputs diminish with each layer, otherwise if the magnitudes are too great then the outputs blow up. Balancing these weights allows for the stacking of many layers which has enabled the great progress we have seen in deep learning in recent years.
@chocochip8402 Жыл бұрын
I thought exactly about the same thing. This is the vanishing or exploding issue in the forward/backward pass in ANNs. To alleviate this problem, there is also batch normalization which helps keeping the activations std to 1 throughout the training process. The skip connections also help keeping the flow of information. I also thought about the attention mechanism used in transformers. For each output, it takes the weighted average of the input tokens. These positive weights add up to 1 thanks to the use of the softmax function, keeping the flow of information constant through the layers. Transformers combine all these tricks (they use layer normalization instead of batch normalization, but the idea is the same). Moreover, the original problem solved by the attention mechanism used in transformers was that the hidden state in RNN/LSTM acting as a memory state hardly retained all the information of the sequence of tokens that was previously processed. The information about the past tokens sort of vanishes (or at least is incomplete) as the model goes forward through the tokens. The attention mechanism serves as a kind of skip connection that allows the model to look at all the previous information which is then preserved and can flow much more easily. In the end, even in ANNs, good information flow is central to their proper functioning. Now, it would be very interesting to know how nature came up with a good information flow management in the brain. The critical brain hypothesis is interesting, but it seems to me that it only makes some observations related to the critical phenomena but doesn't really explain the mechanism causing this criticality (it might very be the ultimate goal of neuroscience). Researchers in AI could then take inspiration from it.
@-slt Жыл бұрын
Absolutly facinating. I am a Machine learning engineer and I could not stop thinking how this knowledge and intuition based on it might be transferred to ML.
@user-hy6cp6xp9f Жыл бұрын
Do certain ANN models run near critical points?
@macchiato_1881 Ай бұрын
I don't think standard ML can implement criticality. I'm looking towards Spiking Neural Networks / Neuromorphic models as the prime candidate for this type of behavior.
@ianmatejka3533 Жыл бұрын
Every video you have made so far is a masterpiece. You cover a wide variety of computational neuroscience topics from place cells to wavelets; with each topic covered in exceptional detail. You are able to convey abstract topics in an intuitive and visual way that is unparalleled. Keep up the great work man
@gara8142 Жыл бұрын
This is one of the best videos I've ever come across in something like 10 years using this platform. I can't overstate how good this was. Amazing job, I'm looking forward for your future content
@ArtemKirsanov Жыл бұрын
Wow, thank you so much!
@aoeu256 Жыл бұрын
At a long-time and large-size scale water is at a critical point on the earth (in that it is in liquid, gas, and solid state). However, more importantly carbon-nitrogen-oxygen covelant bonds in life are at the critical point in long and short time scales, allowing its bonds to be repurposed and allowing self-replication and evolution. On Venus these bonds are unstable, while on Mars these bonds are at stasis. I think on around Mars/Europa hydrogen bonds may be at the critical point so you might see complex "ice crystal" life while on Venus some sort of weird sulfuric acid compounds are at the critical point.
@loftyTHEOWNER Жыл бұрын
No one explains better than you do. I knew all these stuff in their separate domains, but I've never truly understood the connection as I have now. When at 25:07 you justified the passage between electrodes and neurons it blew my mind of pure happiness!!
@NajibElMokhtari Жыл бұрын
This is the most amazing video I have seen on KZfaq for a while. This is Science Communication at its best. Thank you so much!
@KalebPeters99 Жыл бұрын
Completely agreed 👌
@ArtemKirsanov Жыл бұрын
Wow, thank you so much!
@Ethan-cn5wr Жыл бұрын
Are you kidding man? On a road trip rn and have been talking about this with friends. Can’t believe this just came out, very excited to listen!
@sissiphys7834 Жыл бұрын
Dear Artem, thank you for this glorious video! Well made and inspiring! You triggered another neural avalanche of excitement in me! My brain transitioned from rapid eye movements and sleepiness to the rabbit hole of self-organized criticality!
@parl8150 4 ай бұрын
Studying the Ising model for my thesis right now. I never would have thought that there is a connection between the model and NN's (which also feels extremely natural). Nice content
@angelogunther6445 Жыл бұрын
Your videos are truly a gift! Amazing research and video quality. Keep it up!
@rodrigodamotta2876 Жыл бұрын
Amazing video! I did an undergrad research about brain criticality. The idea was to create an analog of the connectivity matrix for the Ising model in the critical temperature to check if the graph topological properties match with the ones measured in the resting state with fNIRS.
@danyielsanchez5159 Жыл бұрын
Oh that's sound great! There's something you've published?
@RodrigodaMotta Жыл бұрын
@@danyielsanchez5159 Not yet
@DevashishGuptaOfficial Жыл бұрын
This is so so so well made! It makes you feel as if you're gradually discovering these results for yourself and it feels fantastic doing so!
@anywallsocket Жыл бұрын
This is SO well done. Scale-free avalanches in the brain makes perfect sense, since we are trying to self-resonate, such that information is not lost as it echoes up and down the various physical thresholds which constitute our brains from atoms all the way up to the whole structure.
@petevenuti7355 Жыл бұрын
Despite these epiphanies handed to me on a silver platter, I'm still having trouble wrapping my brain around how any of this helps keep neural networks in a state of unstable equilibrium, what are the hidden variables that prevent self feedback oscillations from getting phase locked much like a seizure, or descending into complete chaos? It's much reminds me of a table full of pendulums that stand upright when the table is randomly vibrated but much more complicated.(because they're all connected to the same table they want to sync up, because the vibration is random they seldom do, yet within the narrow range of vibration they all stand up!)
@anywallsocket Жыл бұрын
@@petevenuti7355 You have to remember our brains, like the rest of us, evolved naturally. Therefore the near-critical point is a universal feature of life. Imagine you want to farm entropy, where do you go? You go where it’s being formed, at the edge of a phase transition - kinda like how we build along coastlines, or better yet how primordial life still clings to hydrothermal vents deep underwater. The transition from eddies to flows is where all the magic happens. In the brain then there are feedback systems preventing your bad feedbacks, because it’s actually designed around physical minima, carved a home in energy gradient which is stable despite its complexity - life is a self-stabilizing dissipative structure, using the pull of entropy to orbit equilibrium.
@joecarioti629 Жыл бұрын
@@anywallsocket "life is a self-stabilizing dissipative structure, using the pull of entropy to orbit equilibrium" what an interesting way to think about it.
@thegaspatthegateway Жыл бұрын
@@anywallsocket That's beautiful, thank you
@domorobotics6172 14 күн бұрын
@@anywallsocketbeautiful
@InterfaceGuhy Жыл бұрын
Wow. Self-Organized Criticality. Scale invariance of Relevance Realization. Deep-continuity hypothesis. Our metabolism powers our virtual engines which are optimized and orchestrated on top of the background "hum" of critical neural objective reduction. Thanks for this great work.
@ChristianSt97 Жыл бұрын
finally someone talking about phase transitions
@roholazandie3515 Жыл бұрын
Artem you are a genius! Your videos made me interested in neuroscience and now I am fully devoted to reading about it. I recently read about criticality and now I see your video and it's just so beautiful. I wish you talked about self organized criticality too
@Dillbeet Жыл бұрын
This is beautiful. I am interested in seeing the effect of psychedelics on control parameters.
@ArtemKirsanov Жыл бұрын
Thank you! Interesting thought indeed!
@philipm3173 Жыл бұрын
I had a powerful realization during a deep trip where I realized that life and consciousness are the result of the feedback/recursive character of the critical line. The more you can tune toward greater coherence, the higher the degree of consciousness.
@jon...5324 Жыл бұрын
your intuition is right, read: Carhart-Harris, R.L., 2018. The entropic brain-revisited. Neuropharmacology, 142, pp.167-178.
@lgbtthefeministgamer4039 Жыл бұрын
guy who's fried his brain with psychedelics: WOAHHH BUT WHAT IF HE WAS ON ACID MAN
@trapsarenotgay8228 Жыл бұрын
@@philipm3173 holy fuck I did that on weed but I failed to realize the second part.
@iip 10 ай бұрын
This work of art is as valuable as works of Plato. Thank you for bringing to our consciousness
@asdf56790 Жыл бұрын
OUTSTANDING video! :D You taught the concepts in a very clear way and the animations are simply insane. I love it!
@jozsefgyorgykiss352 Жыл бұрын
Kiváló előadás a lényegről. Nagyon jó oktatási anyag, kutatóknak is javasolható. Köszönet érte!
@gustavocortico1681 Жыл бұрын
Dude, this is otherworldly.
@ioannismalekakis2997 Жыл бұрын
This is one of the greatest channels on KZfaq.
@phil5037 Жыл бұрын
Very impressive visual animations. Helped a lot with understanding the concepts
@eugeniosilvarezendebh Жыл бұрын
This is super-high quality content ! Congratulations !
@defenestrated23 Жыл бұрын
Always a joy when Artem drops a video!
@stevenschilizzi4104 Жыл бұрын
Another fascinating video, Artem. The work you’ve put in to making the material accessible to non-specialists has definitely produced a pedagogical jewel. Amazing.
@SyrosAlex Жыл бұрын
One of the most intellectually rewarding videos I've ever seen!
@gef56 Жыл бұрын
Your videos are always enlightening; thanks for the consistently great content!
@entropica Жыл бұрын
Brilliantly explained. Please carry on making this type of videos.
@pparsons12 Жыл бұрын
This might be my favorite Artem Kirsanov video. A masterpiece of masterpieces. Thank you so much for making these.
@NovaSaintz 3 ай бұрын
Thanks for leaving sponsor at the end. I watched the whole thing.
@ConnoisseurOfExistence Жыл бұрын
Awesome! I'm going to recommend this channel to my Neuroscience class.
@Rulian_Sama Жыл бұрын
OH MY GOD, this blew mind off, this is in my top best informative video ever for sure... dude, flow states and fractals, the border between chaos and order, the state of epilepsy being similar to a huge chaos eruption but with intense meaning... Like this 30min explains life itself, or at least a very significant base, it's astonishing
@-abigail 2 ай бұрын
right? as a mentally ill former computer scientist, it fills my heart with joy to know that science says that my brain is *supposed* to be living on the critical point between two opposite deaths, solid and liquid at the same time, so that my head can fit more fractals in it, so that i can pick up long distance messages from inside my own mind better. i know that's not what the video is really supposed to be about but it intuitively feels to me like the video is describing a lot of my internal experience in ways that i haven't heard before.
@jon...5324 Жыл бұрын
Perfect, I've been reading connectome harmonics papers recently so this is very much topical to me.
@tonythetiger3317 Жыл бұрын
This Video is so so wonderful, thank you!! All very beautiful, interesting and clear. Good luck for next videos and thank you
@chinhoiwong9645 Жыл бұрын
This video is so interesting. Thanks a lot for making this video and please keep delivering content about computational neuroscience in an informative yet easily digestible way!!
@bananprzydawka7129 Жыл бұрын
incredible video, hope you make more like this!
@elefantsnablar Жыл бұрын
Fascinating and incredibly well put together video!
@tanchienhao Жыл бұрын
This neuroscience video is probably the best explanation on the Ising model I’ve seen!
@ArtemKirsanov Жыл бұрын
Thanks! :D
@falklumo Жыл бұрын
This is true. Although I missed a word that the Ising model stands out in that it can be solved analytically.
@labanpede6913 Жыл бұрын
You have a talent of combining beauty and science. These are often thought to be separate; thanks for illuminating the bridge.
@linklm780 9 ай бұрын
Fascinating. Thanks for making this.
@jayp6955 Ай бұрын
I was sick today and binged some of your videos. So far, they're all brilliant and I love the aesthetic and craftsmanship you put into them. I thought of the Ising model as you were talking about phase transitions, and then you bring it up -- truly comprehensive and love that you are bringing physics into your videos! Super interested in similar systems, like Kuramoto oscillators which can possibly describe large scale brain oscillations, and which have mathematical similarities to Bose-Einstein condensates.
@impxlse Жыл бұрын
This is one of the most thought provoking videos I have ever seen. This is now one of my favorite channels.
@ptrckqnln Жыл бұрын
Exceptional video. Thanks for putting in what I'm sure was a monumental amount of work to explain several quite complex concepts clearly and concisely. Subbed!
@luker.6967 Жыл бұрын
This is fascinating work and you explain it perfectly! Thank you!
@quaidcarlobulloch9300 Жыл бұрын
22:48 you absolutely just blew my F-ing mind.
@matteobecchi1210 Жыл бұрын
This video is extremely well done! Thank you!
@tomasreunbrouck6365 Жыл бұрын
Such an intricate and complex topic, so well explained. Truly remarkable!
@SuperHddf Жыл бұрын
Exceptional work explaining and visualizing this fascinating topic! Thank you from the bottom of my heart for gifting us your videos ♥
@willcarson6680 Жыл бұрын
One of the best videos I’ve seen on KZfaq! (The others are also your videos)
@senseofmindshow Жыл бұрын
This is so well explained and an amazing video!
@azurebrown3756 Жыл бұрын
My first time viewing. What an excellent job. Simply correct in matters, meaning and math. I am very impressed.
@wugythebug Жыл бұрын
Bro this video is just outright phenomenal . Thank you for your time
@Grateful.For.Everything Жыл бұрын
Finally!! So awesome that this is finally being discovered by scientists, definitely gets to the core of what is really going on on a lot levels and scales, and non scales lol. Thank You Bro, this was masterfully put together, super appreciative for this work You are doing here presenting these truths to us in the way that only You know how to do, I don’t study any of this on my own lol, I just wait and learn from You, You have the highest grasp on all this so it’s so incredible that You are so damn good at sharing your perspectives through such wonderfully effective graphics, really can’t thank You enough!
@ArtemKirsanov Жыл бұрын
Wow, thank you! I really appreciate it!
@s0ft466 Жыл бұрын
@@ArtemKirsanov Would love to discover the relevance of scale-invariance in fluid systems (thinking Reynolds number).
@aoeu256 Жыл бұрын
Is there scale invariance of life/evolution on life? I think carbon-nitrogen-oxygen covelant bonds are at the critical point allowing life to do "computation" via "evolutionary algorithms". However, in cold areas ice lens/permafrost complexes may be at the critical point, but maybe only at perhaps long or short (non-human) time scales.
@s0ft466 Жыл бұрын
Life pretty much needs criticality, it seems.
@Mohamova Жыл бұрын
Wow! This was the best video I've seen for a while! And it gave me an idea about how this ideas described here that can have a huge impact on Graph Neural Networks! Thanks for such an amazing content!
@AncestorDigital Жыл бұрын
I'm a computer so I really really really love these videos, keep up the good work man
@MachineLearningStreetTalk Жыл бұрын
Well done!
@jonathan.gasser Жыл бұрын
Damn, that was eye opening! Thank you for making this!
@Roxas99Yami Жыл бұрын
Hey Artem Very nice video, i have been doing Percolation models for physical systems for a while. It is rare to get percolation lattice simulations on youtube outside of very esoteric channels that nobody knows of. It is interesting how it can be mapped to Neuroscience. 10/10
@DialecticRed Жыл бұрын
OMG the graphics of this video are just popping off! I absolutely adore the font choice and visualizations. I can't believe you haven't passed 100K subs yet! But I'm sure you'll get their soon, and I'll add a small +1 to that count :)
@sirencomposition4432 Жыл бұрын
you explain concepts so well & eloquently. the theoretical simulations, etc.
@user-fy1lm5dr8i Жыл бұрын
Thanks a lot, Artem....This viedo was awesome
@leyasep5919 Жыл бұрын
Awesome presentation !!!
@pallasashta9129 Жыл бұрын
Thank you. Very informative
@pacificll8762 Жыл бұрын
What a beautiful video !
@DougMayhew-ds3ug 5 ай бұрын
This is a great topic and a beautiful presentation based on a great paper. Excellence all around. The insight, that cyclic relations define the geometry of the map, is a nice key insight breaking out of simple Pavlovian association lists.
@Thomas-gz4ln Ай бұрын
What a great video! Keep it up
@joesmith8288 Жыл бұрын
Please do an analysis of the renormalization group. Your exposition of critical phenomenon and self-similarity is extremely elegant and intuitive, beautiful work!
@mahbodnr Жыл бұрын
Great content. Thanks.
@jimmypk1353 Жыл бұрын
This channel is about to go into a PHASE TRANSITION. That's a MILLION subscribers in 1 year.
@yat-lokwong2163 Жыл бұрын
I think your video inspired me to how to solve a problem in my research project, about the optimization in critical stage, and the communication by long-range coupling. Thank you!
@nenadnen11111 Жыл бұрын
U dont know shiiiiit u are talking about 🤣.....samo rokni malo magnezijuma i malo cinka...odma ti bude bolje 🙃
@zackbarkley7593 Жыл бұрын
THANKYOU so much for scale invariance.
@AB-wf8ek Жыл бұрын
This resonates strongly with my exploration with video feedback in the past, and describes my infatuation with generative art. Self similarity is the keyword and a great way to define the region of the edge of chaos, so enlightening!
@dimitarbogoev4539 Жыл бұрын
Amazing content, thank you so much
@bigjukebox3370 Жыл бұрын
this is literally so good. nice job! i learned so much :)
@Originalimoc Жыл бұрын
😮😮this is how teacher works, very clear in a 30min video, the channel should be on the same size as 3b1b
@rb8049 Жыл бұрын
Geoffrey Hinton has developed a forward forward algorithm for learning. Essentially there is an awake and sleeping phase both required for learning.
@CSMHD 9 ай бұрын
Thank you. Very, very interesting.
@TeslaElonSpaceXFan Жыл бұрын
Thank you.
@rabiaedaylmaz1198 Жыл бұрын
Amazing work, thanks a lot!!
@adamr.5486 Жыл бұрын
Thanks man, you helped me to finally understand this stuff.
@deadmanzclanleader Жыл бұрын
This video helped me get dangerously close to thinking I understand the nature of the universe and myself inside it. Thank you for making such a brilliant video that's available for everyone to learn from.
@jamesmoore4023 Жыл бұрын
Amazing video! I saw this talk related to neurofeedback and your video helps to understand it better. I plan on picking up a copy of the book. Thank you. Tuning Pathological Oscillations with EEG Neurofeedback and Self-Organized Criticality - Tomas Ros
@willcowan7678 Жыл бұрын
Artem, man, really great content. Making me want to go into research/industry neurosci or neuromorphic computing.
@indrawee Жыл бұрын
Such quality content 👍👍👍
@tante4dante Жыл бұрын
Still watching it, but i'm currently at the power law vs exponential curve and i just thought "OMG, you just solved my animation problem i had months ago in blender!"... i wanted to make an infinite zoom animation and i tried different inbuilt curves for the camera zoom and none worked... i'm a little dumb, and not good at math, but thank you for solving a totally non related problem for me :D next step, how to get this into blender XD just was so happy, i needed to communicate my thanks immediatly XD
@ArtemKirsanov Жыл бұрын
Wow, thank you! :) What a coincidence! That particular animation was done using matplotlib (through FuncAnimation) simply by adjusting the axis limits on every frame. Matplotlib is really good at automatically redrawing the labels when you change the limits programatically. Unfortunately, off the top of my head I have no idea how to do something similar in Blender...
@ndiaz9676 Жыл бұрын
awsome video! I am a physicists and I want to share a small comment: I was puzzled at first by the average over time when you described correlations, since we usually calculate an averages over ensambles (thermal states, etc). Then I recalled the basic assumptions behind ensemble theory which identify the two quantities. You decided not to describe the abtraction itself but the underlying physical reality it represents in both a pedagogical and perfectly correct way. I congratulate you for that
@ArtemKirsanov Жыл бұрын
Thank you! I really appreciate it
@zwazwezwa Жыл бұрын
Great vid, impressive work
@tomaszsikora6723 Жыл бұрын
I am experimenting with spiking neural networks evolved through indirect encoding and i experienced spike wanishing in the past. This video blew my mind and i've learned a ton from it. I'm super inspired. Thank you!
@KalebPeters99 Жыл бұрын
Artem, you do sci comm like no other. Thank you 🙏
@simonstrandgaard5503 Жыл бұрын
Beautiful visualizations.
@jinbaofan8957 11 ай бұрын
I'm studying chemical physics. The first half is soooooooo clear! Thank you
@ChaoticNeutralMatt Жыл бұрын
Thank you for this video, I just learned about some of these concepts without knowing any of this background. Thank you again!
@drstrangecoin6050 Жыл бұрын
Thank you for posting this. I've been trying to find new ways of explaining the 'grokking' behavior of ML, and how this is a phase transition behavior similar to Flory-Huggins, liquid crystals, weather patterns, etc. but have not had a good way of describing it beside vaguely grasping at Fourier decomposition of a signal. This is a more detailed overall explanation. Glad it also applies (as expected) to biological neurons. Best wishes.
@anatolykarpov2956 Жыл бұрын
I know you know but your videos make real intellectual satisfaction because they are sooooo great
@johnstifter Жыл бұрын
This is reminding me of the book.. The computaional Beauty of Nature. Great work.
@MrTomyCJ Жыл бұрын
13:00 I don't understand why correlation implies transmission of information. It could just be that both cells (even if far away) are being affected in the same way by an external force. 2 radios picking up the same noise doesn't mean they're talking to each other. 14:34 fractals are typically not self similar. Instead of mentioning self-similarity, I'd be more general and say it displays the same properties (but not necessarily the exact same shape) across multiple scales.
@vladyslavkorenyak872 Жыл бұрын
Could we actually sample the "sigma" for different brain areas and make a topological map of the brain? If we could do this, maybe we could study the brain in terms of the local sigmas for each area, discover correlations between diseases or intelligence and how sigma is distributed. Also, maybe we could use some sort of transistors that spontaneously activate, and arranged in such a way such as critical states are possible. Maybe this would be the future for efficient AI hardware design.
@ArtemKirsanov Жыл бұрын
Yeah, estimating the branching ratio from experimental observations is actually quite straightforward, since it is a ratio of activated descendants vs number of ancestors. More reliable methods have also been developed to estimate the value when the sampling is sparse (see www.nature.com/articles/s41467-018-04725-4 ) Comparing the sigma between different brain areas is a very interesting idea! I'm not aware of the exact studies, but I suspect it might have been done. If you find out, please let me know! It would be really interesting to look at.
Astonishing Hypothesis
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