To try everything Brilliant has to offer-free-for a full 30 days, visit brilliant.org/ArtemKirsanov . You’ll also get 20% off an annual premium subscription
Great video, thanks! What do you think about this theory: Rvachev, M. M. (2024). An operating principle of the cerebral cortex, and a cellular mechanism for attentional trial-and-error pattern learning and useful classification extraction. Frontiers in Neural Circuits, 18, 1280604? This includes reinforcement mechanism, Hodgkin-Huxley, attention, classification, free will, etc.
as someone who has been trying to understand differences in cognition due to chloride ion channel differences (KCC2 related autism and epilepsy), this is THE BEST. I’ve basically been looking for exactly this explanation for over a year. This is really, really important information.
I remember seeing the Hodgkin-Huxley model in first year of medical school and thinking it was a thing of beauty. Most of my compatriots thought I was nuts, but my undergrad degree was from the biophysics department at Berkeley. (This was 50 years ago.)
@@panizzutti try university of Sheffield, uk… they have an amazing program (plus faculty) that offers a double specialty - MSc in cognitive and computational neuroscience … a background in physics and a bit of biology would be helpful
@@panizzutti but if by advice you mean more “learn in your spare time” sort of thing, then I think the recent book titled “models of the mind” by Grace Lindsay is the best intro into the field. She dwells on both the history and technical details in a very lucid and easy to understand way for the uninitiated. You can might after that think of reading up the classic by Churchland “computational brain”
I understand that subjects like this are only attempts at how things work in order to make as accurate as possible prognoses, but not too long ago it's been proven that, at least consciousness, is non-computable.
So I have a physics degree, but no neurophysiology background. This presentation was so clear that I found it almost trivially easy to follow. Well done!
Me too. That was a really intuitive explanation, I liked the whole journey! I'm kind of surprised how someone comes up with the particular fitting functions for alpha and beta. They don't look familiar from a physics point of view
I did a whole giant deep dive video about Rhodopson and the chemical pathway for photo transduction. The whole time, I was slamming my head against the wall trying to figure out a way to communicate the neural side of that equation. Gave up and focused on the biochem. This video absolutely knocked the answer OUT OF THE PARK. So good.
This has some amusing timing for me! I'm taking a class on multiple processor systems, and for an assignment we were given a piece of code that simulates a neuron using the Hodgkin-Huxley model and tasked with parallelizing it with MPI and running some experiments on a cluster. We didn't need to touch the inner workings of the model (we parallelized computing independent dendrites), but it's still a fun coincidence
Thank you for this amazing explanation. Your explanation literally helped me to abstract the mathematical model for my PhD proposal. I will never forget this.😮
I’m not usually commenting RUclips videos, but after watching a few of yours, i feel the urge to say that your ability to bring down to Earth such tricky topics, together with those beautiful visuals, is just inspiring. Amazing work, just keep going. Greetings from Spain 🇪🇸
God bless the calsequestrin that got inhibited to release calcium ions which made conformational changes to troponin that made the lumbricals and interosse work and write the algorithm that recommended this video to me with the help of prefrontal cortex and the motor cortex area in the parietal lobe that recommended this video to me , special thanks to all the ions and energy sources .
Thank you a lot for explaining the HH model in such mesmerizing beauty and using these iconic animations. It really helped me grasp the content of books in one single video. I can´t wait for the second part that will discuss the simplified version of the model which I guess will lead to the LIF model.
I think we need to turn these equations into Linear Algebra and accelerate on GPUs. 😆 On a series note, this system is nonlinear and is very difficult to have a closed form solution. Really love your videos. Please don't stop making these. Thank you!
As someone with an electrical engineering background, some of this stuff was surprisingly intuitive for me to grasp (like the lowkey KCL equation at 4:36, the idea of modelling non-electrical problems as electrical engineering problems by drawing an equivalent circuit, the voltage controlled sodium/potassium channels basically being analogous to transistors, specifically n-channel mosfets where the conductive channel grows in response to an applied gate voltage, the statistical modelling of diffusion and drift currents at 6:36 like its done in basic semiconductor theory, to mention a few). Also worth mentioning is that the probabily of mutliple gates being simultaneously permissive is nothing but the multiplication theorem in probabilty assuming the gates being in permissive states are independent events. I'm blown away. Love your enthusiasm and the high quality of your production. Keep it up! Edit: im just curious if the logical next step is to model our brains network of neurons as electrical circuits, with all of this being established? I could be wrong but im really curious to see how far we can go with this model.
I'm a first-year neuroscience student currently taking my calculus prereqs. Even though I already know about ion channels, action potential propagation and about Hodgkin and Huxley's work with squids, I hadn't heard much about the math they did to solve this. I'm not a huge fan of calculus but I know I need it and this was really helpful and motivating and reminded me why it's important that I learn it and how it works to explain the physiology. This was explained wonderfully. Time to study!
Dear Artem Kirsanov, I hope this message finds you well. I recently watched your RUclips video, "Wavelets: A Mathematical Microscope," and I must say, I was truly amazed by the clarity and elegance of the animations and graphics you used to explain the concepts. The presentation style really helped me understand the subject, and I can tell a lot of care went into creating it. I'm very interested in learning more about the tools you used to make these visuals. Could you please share which software or techniques you used to create such engaging animations and graphs? I'm currently working on similar material, and your approach would be incredibly helpful for my project. Thank you very much for your time, and I look forward to your response. Best regards, Mohamed
Thank you this is so ridiculously helpful. I am going to school for neuroscience and psychology. I am going for my doctorate and my brain has thrived off of learning this important piece of information
This is one of the best videos I have ever found on RUclips. For the longest I have feared math and physics but recently that is starting to change and this video should be added as a variable that contributes to accelerate the rate of change at which my fear is decreasing 😅 thank you very much!
Great video! However, focusing solely on sodium and potassium ions only scratches the surface of neuroscience. To get a fuller picture, it’s crucial to delve into other key elements like glutamate and GABA, which are the primary excitatory and inhibitory neurotransmitters, respectively, and play central roles in learning, memory, and regulating neuronal excitability. Calcium ions (Ca²⁺) are essential for neurotransmitter release and synaptic plasticity, which are fundamental for cognitive processes. Meanwhile, chloride ions (Cl⁻), through GABA receptors, help maintain the balance of excitation and inhibition by hyperpolarizing neurons to prevent overactivity. Covering these additional ions would provide a richer, more complete view of neuronal signaling.
Fascinating how you inspired me with your work of computational neuroscience and research in Obsidian to help me work on my PhD thesis research in Obsidian! Thanks for the vids and keep the coming! Female subscriber in the USA!
Goddamnit if only i wasnt a student i would've subscribed to your patron. This is so so good. I can't express it in words. I don't even have biology but seeing how beautifully the physics plays is so fascinating. Thankyou so much! This is god tier content
It's important to remember that it isn't just sodium or potassium ions that are moving. You also need to allow chloride ions to migrate with the positive ions.
My brother who is graduating high school this year recently said to me that he might do neuro science in uni because he feels like the brain would be easy to study. It was at that moment that I realized my brother does not have a brain
i literally had an exam on this on tuesday, great timing!! would love to see where you take this series, in my course we're starting with mutli neuron simulations & hebbian learning and it would be awesome to have such high quality explainers on these topics :)
I’m in engineering, but I did my physics 2 project on the circuitry of the Hodgkin-Huxley model, though looking back on it, it was more chemistry and math than physics for me, I remember I spent like 90% of the presentation giving the chemistry background and the differential equations describing the voltage gated resistors, then I just like showed a few slides at the end of the actual derivation and working of the circuitry.
This is the best video on the HH model that I have seen in a while. Even the MIT introduction to neural computation wasn't this intuitive. The animations, in particular, made it much easier to understand these concepts. Can you please make a video of the Izhikevich model or the epileptic model by Victor Jirsa?
I love learning about computational neuroscience, but I am not in that field and I have to rely on difficult textbooks and papers. Thank you for making easier for me to grasp the inner workings of my own algorithmic procssor! ❤
Im torn between telling all my friends about how awesome this channel is, but I also wanna gatekeep it because of how good it is! But growth is good for you so ill go with the former
An interesting video Artem. The next useful thing to consider is how the frequency of signals and ordering of signals (ie. multiplexed signal encoding) from each dendrite at each synaptic interface affects the voltage dependent ionic conductance, and thus the consequent probability of the neuron firing a pulse down its axon.
5:20 -- it worth noting that the membrane potential is negative at rest and the voltage rising equates to decrease of the potential difference (hence depolarization). The graph confusingly places the horizontal axis below the chart, making an impression that the zero is below and the voltage rise causes increase of polarization.
Wow . Thanks . bTW can we interpret neighbourhood currents within a neuron as interlayer connectivity in neural network but that would mean that single neuron is a deep neural network and every gate is a layer
i was hoping for the nernst equation (though you did mention the equilibrium potential) and the ghk equation to get mentioned a bit more, since i had an interesting experience with it, but this is really cool and well-done regardless. thank you for the video!
Is the distribution of ions depicted at 2:06 correct? I thought that inside the cell, there are a lot of other anions (amino acids, nucleic acids, phosphate groups on proteins, and so on), whereas outside the cell the inorganic anions are much closer to balancing the inorganic cations. Of course, the diagram isn't big enough to show the distinction between the charge balance of ions in the bulk fluid and the charge imbalance at the membrane. That would have made the representation of individual ions too small. But if I understand right, it only takes a relatively small imbalance to create enough voltage to make the physiology work, compared to the difference in composition. So even right next to the membrane, I thought there was more chloride on the outside of the membrane. It's been a lot of years since I read about this, though.
Question: I am currently majoring in computer science with a concentration in AI and a minor in mathematics, but I'm also interested in neuroscience (as evident by me watching your videos). Unfortunately, my university doesn't offer a neuroscience degree for undergrads. After I graduate with a BS in CS, if I want to pursue computational neuroscience, how would I do that? Should I try to get a BS in neuroscience? Does a masters or PhD in computational neuroscience require a BS in neuroscience, or can I pursue it even without having taken any neuroscience classes in school? Love your videos btw
In my country there is also a deficit in computational neuroscience degrees. I suspect that is the case in most of the world, since computational neuroscience is known for being interdisciplinary. What does that mean? People from all sorts of backgrounds can end up working in computational neuroscience research. You could look for computational neuroscience research groups who offer masters or Phd programs (such is the case in my country). That would be sufficient. I also suspect that it isn't even necessary for your degree to say "neuroscientist" explicitly to be capable of working in neuroscience.
Sodium channels, potassium channels, calcium channels that's very common in cells and science, IN THIS PRESENT ENVIRONMENT, was the ideal mindset you have a complete science in open space ?
Is there a nice textbook, paper, or article to help explain the continuously distributed ion channel equation? As a neuromorphic researcher, I'm very interested in dendrite dynamics and want to model these dynamics to see what benefits they might give
this is how to turn capacistance recharge and discharge into equeations and then someone claim it has to do with intelligence and neurons. you can try with analog electronic components and network a bunch of capacitors with transistors or vaccuum tubes and see if you can make these interaction in some intelligent way that can mimic just the action potential of the cell to emulate analog cell but it would never work cause there is something missing. the cell is not just creating a voltage. there is chemicals molecules created that is send from axons to dentries by the action potential that regulate the metabolism of the cell that then produce chemical molecules that then trigger another transmission. that is what controls the firing in the first place. there is nothing quantum about this.
The opening and closing of gated channels according to you depends on voltage, that's the ideal environment what if there's anomalies or anomaly stimulants to produce an effect.
Why would neurons use so many different ions (potassium, sodium, calcium, magnesium, chloride)? Why not just one for positive, one for negative? Seems overly complex to achieve the same result?
Good question! It's not only about charge - ions play many other crucial roles in various chemical reactions, serving as cofactors in proteins or as intracellular signals for proteins to essentially communicate with each other within a cell :)
To try everything Brilliant has to offer-free-for a full 30 days, visit brilliant.org/ArtemKirsanov . You’ll also get 20% off an annual premium subscription
Great video, thanks! What do you think about this theory: Rvachev, M. M. (2024). An operating principle of the cerebral cortex, and a cellular mechanism for attentional trial-and-error pattern learning and useful classification extraction. Frontiers in Neural Circuits, 18, 1280604? This includes reinforcement mechanism, Hodgkin-Huxley, attention, classification, free will, etc.
as someone who has been trying to understand differences in cognition due to chloride ion channel differences (KCC2 related autism and epilepsy), this is THE BEST. I’ve basically been looking for exactly this explanation for over a year. This is really, really important information.
Dude is doing god's work for med students out here with peak motion graphics and simple descriptions
I remember seeing the Hodgkin-Huxley model in first year of medical school and thinking it was a thing of beauty. Most of my compatriots thought I was nuts, but my undergrad degree was from the biophysics department at Berkeley. (This was 50 years ago.)
Are you high?
You summarized almost an entire term of my computational neuroscience masters program in under a half hour!!! And that too so beautifully!
Man you have any advice on comp neuro sci? It’s my dream to get into that field and i’m willing to do anything
@@panizzutti try university of Sheffield, uk… they have an amazing program (plus faculty) that offers a double specialty - MSc in cognitive and computational neuroscience … a background in physics and a bit of biology would be helpful
@@panizzutti but if by advice you mean more “learn in your spare time” sort of thing, then I think the recent book titled “models of the mind” by Grace Lindsay is the best intro into the field. She dwells on both the history and technical details in a very lucid and easy to understand way for the uninitiated. You can might after that think of reading up the classic by Churchland “computational brain”
@Tom-sp3gy Thanks man! I’ll try that
I understand that subjects like this are only attempts at how things work in order to make as accurate as possible prognoses, but not too long ago it's been proven that, at least consciousness, is non-computable.
as a statistics major, I dont' usually watch these videos but it warms my heart there are so many scientifically minded people in the world
So I have a physics degree, but no neurophysiology background. This presentation was so clear that I found it almost trivially easy to follow. Well done!
Me too. That was a really intuitive explanation, I liked the whole journey! I'm kind of surprised how someone comes up with the particular fitting functions for alpha and beta. They don't look familiar from a physics point of view
I did a whole giant deep dive video about Rhodopson and the chemical pathway for photo transduction. The whole time, I was slamming my head against the wall trying to figure out a way to communicate the neural side of that equation. Gave up and focused on the biochem. This video absolutely knocked the answer OUT OF THE PARK. So good.
This has some amusing timing for me! I'm taking a class on multiple processor systems, and for an assignment we were given a piece of code that simulates a neuron using the Hodgkin-Huxley model and tasked with parallelizing it with MPI and running some experiments on a cluster. We didn't need to touch the inner workings of the model (we parallelized computing independent dendrites), but it's still a fun coincidence
Wow, that’s awesome!!
There is a lot here that can be simplified for performance as well to increase parallel scaling.
What is your subject in university if I may ask? Seems interesting!
@@ohnenamen0992 computer engineering
Best assignment ever
Thank you for this amazing explanation. Your explanation literally helped me to abstract the mathematical model for my PhD proposal. I will never forget this.😮
The value that these videos add to the public is astonishing! Thank you Artem
I am not a medical doctor, but I found this very interesting. Thank you for the clear explanation.
I’m not usually commenting RUclips videos, but after watching a few of yours, i feel the urge to say that your ability to bring down to Earth such tricky topics, together with those beautiful visuals, is just inspiring. Amazing work, just keep going. Greetings from Spain 🇪🇸
Great explanation! Thanks!
btw...I find it always weird that the anglophones call natrium sodium and kalium potassium.
Yeah, same! I just had to get used to it xD
absolute peak🙌 we need part 3 ASAP!!!
God bless the calsequestrin that got inhibited to release calcium ions which made conformational changes to troponin that made the lumbricals and interosse work and write the algorithm that recommended this video to me with the help of prefrontal cortex and the motor cortex area in the parietal lobe that recommended this video to me , special thanks to all the ions and energy sources .
I love this video. Im a neuroscience undergraduate major.
I have never had a video blow my mind as much as this one and I have no background in physics or neuroscience. Congratulations !
One of the most precious channel on RUclips
I love the visuals, clean and aesthetically pleasing to the eye.
Very clear and classy explanation Artem. A great distillation. I look forward to the next video.
Incredibly helpful video for such a vital topic
Such a gem of topic. Unselfish land so enthusiastically produced. Thank you. Foe putting this together for the interested. ❤
I am currently a Maths Major. I found the explanation quite easy to understand, it used only fundamental Physics. ❤❤❤
Please keep going, I am watching all of these videos in the series!!
You publish this video right as I'm learning of state systems, great timing!
Thank you a lot for explaining the HH model in such mesmerizing beauty and using these iconic animations. It really helped me grasp the content of books in one single video. I can´t wait for the second part that will discuss the simplified version of the model which I guess will lead to the LIF model.
Amazingly perfect explanation! Thank you! Such a great video for even Basic Neuroscience (and mandatory for Computational Neuroscience)
I think we need to turn these equations into Linear Algebra and accelerate on GPUs. 😆
On a series note, this system is nonlinear and is very difficult to have a closed form solution.
Really love your videos. Please don't stop making these. Thank you!
As someone with an electrical engineering background, some of this stuff was surprisingly intuitive for me to grasp (like the lowkey KCL equation at 4:36, the idea of modelling non-electrical problems as electrical engineering problems by drawing an equivalent circuit, the voltage controlled sodium/potassium channels basically being analogous to transistors, specifically n-channel mosfets where the conductive channel grows in response to an applied gate voltage, the statistical modelling of diffusion and drift currents at 6:36 like its done in basic semiconductor theory, to mention a few). Also worth mentioning is that the probabily of mutliple gates being simultaneously permissive is nothing but the multiplication theorem in probabilty assuming the gates being in permissive states are independent events. I'm blown away. Love your enthusiasm and the high quality of your production. Keep it up!
Edit: im just curious if the logical next step is to model our brains network of neurons as electrical circuits, with all of this being established? I could be wrong but im really curious to see how far we can go with this model.
I'm a first-year neuroscience student currently taking my calculus prereqs. Even though I already know about ion channels, action potential propagation and about Hodgkin and Huxley's work with squids, I hadn't heard much about the math they did to solve this. I'm not a huge fan of calculus but I know I need it and this was really helpful and motivating and reminded me why it's important that I learn it and how it works to explain the physiology. This was explained wonderfully. Time to study!
Dear Artem Kirsanov,
I hope this message finds you well. I recently watched your RUclips video, "Wavelets: A Mathematical Microscope," and I must say, I was truly amazed by the clarity and elegance of the animations and graphics you used to explain the concepts. The presentation style really helped me understand the subject, and I can tell a lot of care went into creating it.
I'm very interested in learning more about the tools you used to make these visuals. Could you please share which software or techniques you used to create such engaging animations and graphs? I'm currently working on similar material, and your approach would be incredibly helpful for my project.
Thank you very much for your time, and I look forward to your response.
Best regards,
Mohamed
Thank you this is so ridiculously helpful. I am going to school for neuroscience and psychology. I am going for my doctorate and my brain has thrived off of learning this important piece of information
This is one of the best videos I have ever found on RUclips. For the longest I have feared math and physics but recently that is starting to change and this video should be added as a variable that contributes to accelerate the rate of change at which my fear is decreasing 😅 thank you very much!
Great video! However, focusing solely on sodium and potassium ions only scratches the surface of neuroscience. To get a fuller picture, it’s crucial to delve into other key elements like glutamate and GABA, which are the primary excitatory and inhibitory neurotransmitters, respectively, and play central roles in learning, memory, and regulating neuronal excitability. Calcium ions (Ca²⁺) are essential for neurotransmitter release and synaptic plasticity, which are fundamental for cognitive processes. Meanwhile, chloride ions (Cl⁻), through GABA receptors, help maintain the balance of excitation and inhibition by hyperpolarizing neurons to prevent overactivity. Covering these additional ions would provide a richer, more complete view of neuronal signaling.
My ChatGPT senses are tingling.
I remember learning it in medical school 12 years ago. Man, that was hard. Your explanation would be helpful back then.
Thanks so much for uploading this to the public ❤ 🧠
Thanks for helping neurologist, thanks math genius, good work
I hope you would never stop. Your work is amazing, thank you so much!!!
Fascinating how you inspired me with your work of computational neuroscience and research in Obsidian to help me work on my PhD thesis research in Obsidian! Thanks for the vids and keep the coming! Female subscriber in the USA!
Obrigado, prof. Artem, por nos apresentar as "Equações Centrais/Principais da Neurociência."
Funny how I was just studying this. The video is perfect, amazing job! I can't thank you enough!
That's a pretty sick tat. Kudos to the artist.
Goddamnit if only i wasnt a student i would've subscribed to your patron. This is so so good. I can't express it in words. I don't even have biology but seeing how beautifully the physics plays is so fascinating. Thankyou so much! This is god tier content
It's important to remember that it isn't just sodium or potassium ions that are moving. You also need to allow chloride ions to migrate with the positive ions.
This is a good starting point...for Penrose, Hameroff, and Micheal Levin.
My brother who is graduating high school this year recently said to me that he might do neuro science in uni because he feels like the brain would be easy to study. It was at that moment that I realized my brother does not have a brain
Even before I watch the full video: Thank you for making such mesmerizing content!
Facts
i literally had an exam on this on tuesday, great timing!!
would love to see where you take this series, in my course we're starting with mutli neuron simulations & hebbian learning and it would be awesome to have such high quality explainers on these topics :)
I’m in engineering, but I did my physics 2 project on the circuitry of the Hodgkin-Huxley model, though looking back on it, it was more chemistry and math than physics for me, I remember I spent like 90% of the presentation giving the chemistry background and the differential equations describing the voltage gated resistors, then I just like showed a few slides at the end of the actual derivation and working of the circuitry.
Really amazing video! I could follow this as a high school physics student. Thanks for introducing me to this amazing field
coolest tattoo I've seen in a while.
This is the best video on the HH model that I have seen in a while. Even the MIT introduction to neural computation wasn't this intuitive. The animations, in particular, made it much easier to understand these concepts. Can you please make a video of the Izhikevich model or the epileptic model by Victor Jirsa?
again, how does artem not have 1mil subs yet, I will never understand
I love learning about computational neuroscience, but I am not in that field and I have to rely on difficult textbooks and papers. Thank you for making easier for me to grasp the inner workings of my own algorithmic procssor! ❤
hardest tattoo
beautiful, both the information and the guy
12:04 these gates sound like transistors such as MOSFETs
That tattoo is the coolest thing man
Im torn between telling all my friends about how awesome this channel is, but I also wanna gatekeep it because of how good it is! But growth is good for you so ill go with the former
Bro is somehow getting even better 😭🙏
Nice explanation.
An interesting video Artem. The next useful thing to consider is how the frequency of signals and ordering of signals (ie. multiplexed signal encoding) from each dendrite at each synaptic interface affects the voltage dependent ionic conductance, and thus the consequent probability of the neuron firing a pulse down its axon.
your graphics r so good
Thank you for the wonderful video! Though I do wonder how you managed to get through it all without mentioning the magnetic field???
5:20 -- it worth noting that the membrane potential is negative at rest and the voltage rising equates to decrease of the potential difference (hence depolarization). The graph confusingly places the horizontal axis below the chart, making an impression that the zero is below and the voltage rise causes increase of polarization.
Thank you very much for all of your free stuff here Mr. Kirsanov! Great great great!!!👍👌✌️💎👋
Thank you man! You’re work is incredible
all of your videos are just Amazing, high quality and well-made, thanks you so much for your effort
The legend has delivered! Again.
Great explanation!!!
Great video. I like the way you break down the content.
Wow . Thanks . bTW can we interpret neighbourhood currents within a neuron as interlayer connectivity in neural network but that would mean that single neuron is a deep neural network and every gate is a layer
i was hoping for the nernst equation (though you did mention the equilibrium potential) and the ghk equation to get mentioned a bit more, since i had an interesting experience with it, but this is really cool and well-done regardless. thank you for the video!
Is the distribution of ions depicted at 2:06 correct? I thought that inside the cell, there are a lot of other anions (amino acids, nucleic acids, phosphate groups on proteins, and so on), whereas outside the cell the inorganic anions are much closer to balancing the inorganic cations. Of course, the diagram isn't big enough to show the distinction between the charge balance of ions in the bulk fluid and the charge imbalance at the membrane. That would have made the representation of individual ions too small. But if I understand right, it only takes a relatively small imbalance to create enough voltage to make the physiology work, compared to the difference in composition. So even right next to the membrane, I thought there was more chloride on the outside of the membrane. It's been a lot of years since I read about this, though.
Question:
I am currently majoring in computer science with a concentration in AI and a minor in mathematics, but I'm also interested in neuroscience (as evident by me watching your videos). Unfortunately, my university doesn't offer a neuroscience degree for undergrads.
After I graduate with a BS in CS, if I want to pursue computational neuroscience, how would I do that? Should I try to get a BS in neuroscience? Does a masters or PhD in computational neuroscience require a BS in neuroscience, or can I pursue it even without having taken any neuroscience classes in school?
Love your videos btw
In my country there is also a deficit in computational neuroscience degrees. I suspect that is the case in most of the world, since computational neuroscience is known for being interdisciplinary. What does that mean? People from all sorts of backgrounds can end up working in computational neuroscience research. You could look for computational neuroscience research groups who offer masters or Phd programs (such is the case in my country). That would be sufficient. I also suspect that it isn't even necessary for your degree to say "neuroscientist" explicitly to be capable of working in neuroscience.
cant wait for the next video! amazing summary
good quality my friend
Love it, brother--great video!
This is a very very very good channel 👍 dont stop
Спасибо за видео! Вы в кадре двигаетесь слишком неестественно, а материал отличный!
Thank you!
LOVE THESE VIDEOS💯
Sodium channels, potassium channels, calcium channels that's very common in cells and science, IN THIS PRESENT ENVIRONMENT, was the ideal mindset you have a complete science in open space ?
Please do more videos about biophysics 😢❤❤❤
Is there a nice textbook, paper, or article to help explain the continuously distributed ion channel equation? As a neuromorphic researcher, I'm very interested in dendrite dynamics and want to model these dynamics to see what benefits they might give
Yes, as you say: all it is, I.S. an electric charge.
A Neuron in no other than an 0n ~ 0ff quantum switch ~ 010 Infinity Squared.
this is how to turn capacistance recharge and discharge into equeations and then someone claim it has to do with intelligence and neurons. you can try with analog electronic components and network a bunch of capacitors with transistors or vaccuum tubes and see if you can make these interaction in some intelligent way that can mimic just the action potential of the cell to emulate analog cell but it would never work cause there is something missing. the cell is not just creating a voltage. there is chemicals molecules created that is send from axons to dentries by the action potential that regulate the metabolism of the cell that then produce chemical molecules that then trigger another transmission. that is what controls the firing in the first place. there is nothing quantum about this.
When the wind is slow and the fire's hot,
That has to be the coolest tattoo I’ve ever seen.
The opening and closing of gated channels according to you depends on voltage, that's the ideal environment what if there's anomalies or anomaly stimulants to produce an effect.
amazing video!
Sir, your work is really amazing
Thank you
❤❤
Wow! Thank you for sharing this information with us.
Great videos. Thanks.
Why would neurons use so many different ions (potassium, sodium, calcium, magnesium, chloride)? Why not just one for positive, one for negative? Seems overly complex to achieve the same result?
Good question! It's not only about charge - ions play many other crucial roles in various chemical reactions, serving as cofactors in proteins or as intracellular signals for proteins to essentially communicate with each other within a cell :)
Extremely interesting!!!
I feel atracted to your content, I wanna know what you studied , statistical fysics or computacional neurosciencie?
You are brilliant
0:49 savage
Man that's a well-made tattoo