Logarithmic nature of the brain

articule locked without a subscription🙄

Rich club I always think of Olaf Sporns. Going to review this again after Jeff Hawkins new book

Synapse has a soft 'in' sound. Not like 'sign'...

great effort

This channel is the most beautiful thing that has happened in my life this week, maybe even this month. Thank you for your effort, greetings from Mexico!

Brain does Multiplications natively???? 🤯🤯🤯🤯🤯

The log bell curve looks like 20 80 rule

This is a really interesting video but I have some doubts regarding the multiplication mechanism that you explained as it doesn't validate an important criterion. Instead, it seems to behave like a regulation system around a resting value (that can slide through learning/sufficient and maintained excitation) which looks more like regulation systems: we approximate linearly the interval around the regulated measure and the system should produce an appropriate response to regulate the value so it stays within that interval (otherwise it's not anymore approximately linear which makes calcul hell more complicated)

But a true multiplication, if you think about it, requires different unities. It doesn't make sense to have 8 candies multiplied by 4 candies; you multiply candies per baskets but you sum candies and baskets together. Even when you multiply meters together; there are width meters and there are height meters; because it doesn't make sense to multiply 2 width meters to make a surface.
In a more general way: how do you get back the typing of sum/product or vectorial product/dot product (according to the algebraic body you use)?

If you can prove to me that neurons are typed and this product behavior only occurs when types are crossed/different; I'll believe your statement :)

Very nice!
An explanation of why the distribution of firing rates in the cortex is log-normal can be found in Roxin, Alex, et al. "On the distribution of firing rates in networks of cortical neurons." Journal of Neuroscience 31.45 (2011): 16217-16226.

Why Guys like this are so under subscribed . Wish you success

If you know the seed you can know the tree by genetics a seed has a blue print of tree
llly in every cell

Awesome episode

what is the distribution of weights for neural network?

Thanks for the informative video

🧡

i have a heavy background in audio production, and i figured this made a lot of sense given the logarithm nature of how we perceive sound, it’s cool to see that this is just inherent to our brains in general

subtitle please!

Very good. Thank you.

Which software do you use to make such great videos ??

That was amazing! Great work, Artem - love your videos :-)

Wow! That was informative! Thank's Artem. It keeps me wondering: Would we find evidence that the log-normal structure and distributions in our brains support how efficiently they operate (compared to a digital computer) ? Or is it just that the log-normal distributions MUST naturally arise from underlying mechanisms anyway?

Turtles and power laws all the way down...

Log-normal distributions are also pretty common, especially with frequency. For instance, I think that's what the black-body curve is, though I may be wrong.

I didnt really understand the transition from the normal distribution to the logarithmic distribution can someone explain it in an easier way?

Wonderful content on a most interesting topic.

The shape certainly makes some intuitive sense. Extremely short firing rates are more likely to be mistaken as random noise so a neuron wants to be above that limit. However, it doesn't want to be too far above it, because firing is energy-intensive and the brain is already a calorie-hungry organ. At the same time if information is encoded partially in the firing rate, then utilizing only a small subsection of possible firing rates is not information efficient, so neurons that need to be heard more often would be incentivized to use lower utilized firing rates as there is less noise in those channels. I don't know whether that explanation would necessarily result in a log-normal distribution as opposed to a low-median normal distribution, but it is interesting to see roughly the shape I was thinking emerge at the end.

Fascinating! But what brain region are you sampling from to see the 1 Hz to 10 Hz spread? Like your other video where sparcity amount varied by brain region, it would seem that occipital cortex might show more up to 40 Hz range.

How does the fact that brain is firing at all frequencies at once reconcile with observation (using nmda antagonists) that consciousness is sometimes an all-or-none thing (either a frame is printed or it isn't at any given millisecond), and the change in frequency of these all-or-none frames is smooth, as though having inertia like the boutons' change being proportional to their currently accumulated size? Might it be the thalamo-cortical resonant circuit bringing transient coupling to a particular frequency and this chosen coupled frequency changes smoothly over time?

Or, might each 'frame' of consciousness be a set of ensembles of neurons put together to make that full meaning, and each time you change the set of ensembles, you make a new frame of consciousness, and this frequency of change can vary, but has a mechanism to remain smooth (as though rate of change of frequency is itself important to stay smooth, etc., upwards in nested derivatives)?

Hey, are you still able to pivot into neuroscience with a cs undergrad? Does cs or physics make more sense for computational neuroscience

Shure sm7b🎉

Question: Have anybody ever predicted anything important and completely unexpected based on only dreams, sorry thought experiences that turned out to be true after the appropriate experience became technically doable?

I can’t believe this valuable information is available on YT for free!! I just finished my a level studies and am keen on biology and neuroscience so I loved the fact I got to see a computational perspective on the brain. Makes me wonder where else can the log-normal distributions be seen in the body or what other mathematical models can be deduced in Biological systems.

Keep up!

This is definitely one of my favourite channels now. Up there with 3B1B. You explain things really well, and the topics you cover are just my cup of tea.

can you be my guru

Wow man amazing videos, I wanna do research as a computational neuroscientist and your content is really what I was looking for!

Why this bro looks like young stephen hawking?

Can you talk about power laws in neuroscience?

Terrific video, Artem. Mind-blowing: not only the production values, but in particularly highly engaging content. Thank you for sharing with us. Fantasti❤

So even if you flip a unfair coin, if you flip it often enough, you get a Gaussian distribution? That part confused me 😅

This is super interesting! I wonder if there is a parallel between this and High Spontaneous vs Low Spontaneous fibers at the ribbon synapses in the Cochlea.

Your videos are awesome!

내 생각엔 프랙탈의 복잡도를 넘어선 것도 매우 흔하다.다만 우리가 아직 발견하지 못했을뿐

Fantastic video! Two of my interests, probability, and brain operation, in one video. Very well-done explanation. Thank you Artem!

What a great video! Thanks for your effort in making this <3

Great job Artem, you made these advanced stuff readily understandable to people from all backgrounds!