They look like Pollocks…

But actually, these are two simulations of a whole cortical column, and 1000 pyramidal cells (a type of neuron) during a network simulation (blue cells are silent, red cells are firing), respectively, left—›right.

via EPFL, at Henry Markram’s Human Brain Project.

Kurtzweil AI:

a number of scientists have expressed serious reservations about Markram’s project.

Some say we don’t know enough about the brain to simulate it on a supercomputer. And even if we did, these critics ask, what would be the value of building such a complicated “virtual brain”? Some researchers say it is premature to invest money in a simulation while important principles of brain function remain to be discovered.

Haim Sompolinsky, a neuroscientist at the Hebrew University of Jerusalem, said: “The rhetoric is that in a decade they will be able to reverse-engineer the human brain in computers. This is fantasy. Nothing will come close to it in a decade.”

But those who say “it’s fantasy” and “never” have consistently been proven wrong. Although I agree with Sompolinsky, I do hope he will be, as well.

Meanwhile, despite all this, Itskov and the 2045 project…

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Photograph of blood & milk by { Frederic Fontenoy }, via { but does it float }

••••••

The liquids form tendrils, veins, cells, branches, { networks },
following { repeating orders } — how did this become?

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{ Simple mathematical pattern describes shape of neuron ‘jungle’ }

A 2/3 power law: L = (3/4π)^1/3 × V^1/3n^2/3
where n is the number of dendritic sections to make up the tree, L is the total length of these sections, and V is the total volume

{ A scaling law derived from optimal dendritic wiring }

Authors:
    Hermann Cuntza,b,c,1,
    Alexandre Mathya, and
    Michael Häussera

Abstract:
The wide diversity of dendritic trees is one of the most striking features of neural circuits. Here we develop a general quantitative theory relating the total length of dendritic wiring to the number of branch points and synapses. We show that optimal wiring predicts a 2/3 power law between these measures. We demonstrate that the theory is consistent with data from a wide variety of neurons across many different species and helps define the computational compartments in dendritic trees. Our results imply fundamentally distinct design principles for dendritic arbors compared with vascular, bronchial, and botanical trees.

The late, great Hungarian-American physicist Leo Szilard invited a colleague and me to attend an international meeting on arms control. My colleague, “Murph” Goldberger (later president of Caltech and then director of the Institute of Advanced Study in Princeton), replied that he could attend only the second half of the meeting. Leo turned to me, and I said that I could attend only the first half. Murph and I then asked if we could share an invitation. Leo thought for a moment and then told us, “No, it is no good; your neurons are not interconnected.

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NEW RESEARCH:

{ The brain’s connections follow a grid } rather than a tangle…

“Far from being just a tangle of wires, the brain’s connections turn out to be more like ribbon cables — folding 2D sheets of parallel neuronal fibers that cross paths at right angles, like the warp and weft of a fabric,”

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{ Surprising responses to faces from single neurons in the amygdala }
Kurzweil AI

This figure shows the kind of stimuli used in the study: whole faces (left) and only partly revealed faces. According to the researchers, the surprising finding was that although neurons respond most strongly to seeing the whole face, they actually respond much less to the middle panel than to the far right panel, even though the middle panel is more similar to the whole face. (Credit: Ralph Adolphs, California Institute of Technology)

“The finding really surprised us,” says Ueli Rutishauser, first author on the paper, a former postdoctoral fellow at Caltech, and now a visitor in the Division of Biology. “Here you have neurons that respond well to seeing pictures of whole faces, but when you show them only parts of faces, they actually respond less and less the more of the face you show. That just seems counterintuitive.”

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Ask any artist — this is neither surprising nor counterintuitive. We’ve known for a long time that a viewer responds to a sketch more readily than he does to a finished painting. For the artist, the reason is understood as being because the sketch (or even, an impressionistic style or something not quite “perfected”) gives him something to finish, gives his mind some work to do, so it’s interesting. In this case, we could compare the finished painting to something like the reality with some of the details gone… but maybe not different enough to be as striking as the sketch — it’s the middle panel.

We have known for a long time that neuronal circuits become established and get reinforced via experience – it’s a phenomenon known as “synaptic plasticity.” For example, this is how memories become anchored in the brain. The team working on the Blue Brain Project at EPFL, led by Professor Henry Markram, however, is offering radically new evidence that this may not be the whole story. The researchers were able to demonstrate that small clusters of pyramidal neurons in the neocortex interconnect according to a set of immutable and relatively simple rules.
…
These clusters contain an estimated fifty neurons, on average. The scientists look at them as essential building blocks, which contain in themselves a kind of fundamental, innate knowledge – for example, representations of certain simple workings of the physical world. Acquired knowledge, such as memory, would involve combining these elementary building blocks at a higher level of the system. “This could explain why we all share similar perceptions of physical reality, while our memories reflect our individual experience”, explains Markram.
…
“Since John Lock, about 400 years ago, research into how the brain learns and remembers has been guided by the belief that we start from a clean slate and then print memories with each new experience. The idea that memory is like building lego with fundamental building blocks of knowledge opens up an entirely new door for research”, explains Markram.
…
Current technology is now allowing us to qualify the “tabula rasa” hypothesis, which argues that our brains are a “blank slate” at birth, and we only gain knowledge through experience. It’s an idea that has permeated science for centuries. There is no question that knowledge, in the sense that we typically understand it (reading and writing, recognizing our friends, learning a language), is the result of our experiences. But the EPFL team’s work demonstrates that some of our fundamental representations or basic knowledge is inscribed in our genes. This discovery redistributes the balance between innate and acquired, and represents a considerable advance in our understanding of how the brain works.