The brain is not a computer! Or is it?

In a recent article, reputed psychologist Robert Epstein, the former editor-in-chief of Psychology Today, argues that the brain is not a computer and it is not an information processing device. His main point is that there is no place in the brain where “copies of words, pictures, grammatical rules or any other kinds of environmental stimuli” are stored. He argues that we are not born with “information, data, rules, software, knowledge, lexicons, representations, algorithms, programs, models, memories, images, processors, subroutines, encoders, decoders, symbols, or buffers” in our brains.

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His point is well taken. We now know that the brain does not store its memories in any form comparable to that of a digital computer. Early symbolic approaches to Artificial Intelligence (GOFAI: good old-fashioned artificial intelligence) failed soundly at obtaining anything similar to intelligent behavior.

In a digital computer, memories are stored linearly, in sequential places in the digital memory of the computer. In brains, memories are stored in ways that are still mostly unknown, mostly encoded in the vast network of interconnections between the billions of neurons that constitute a human brain. Memories are not stored in individual neurons, nor in individual synapses. That, he says, and I agree, is a preposterous idea.

Robert Epstein, however, goes further, as he argues that the human brain is not an information processing device. Here, I must disagree. Although they do it in a very different ways from computers, brains are nothing more than information processing devices. He argues against the conclusion that “all entities that are capable of behaving intelligently are information processors”, which he says permeates all of current research in brain and behavior. Needless to say, I disagree. Any entity capable of behaving intelligently needs to be able to process information.

Epstein concludes by arguing that we will never, ever, be able to reproduce the behavior of a human mind in a computer. Not only the challenge of reverse engineering is just too big, he argues, but the behavior of a brain, even if simulated in a computer, would not create a mind.

The jury is still out on the first argument. I agree that reverse engineering a brain may remain, forever, impossible, due to physical and technological limitations. However, if that were to be possible, one day, I do not see any reason why the behavior of a human mind could not emanate from an emulation running in a computer.

 

Image from the cover of the book “Eye, Brain, and Vision”, by David Hubel, available online at http://hubel.med.harvard.edu/.

 

Whole brain emulation in a super-computer?

The largest spiking neural network simulation performed to date modeled the behavior of a network of 1.8 billion neurons, for one second or real time, using the 83,000 processing nodes of the K computer. The simulation took 40 minutes of wall-clock time, using an average number of sinapses, per neuron, of 6000.

This result, obtained by a team of researchers from the Jülich Research Centre and the Riken Advanced Institute for Computational Science, among other institutions, shows that it is possible to simulate networks with more than one billion neurons in fast supercomputers. Furthermore, the authors have shown that the technology scales up and can be used to simulate even larger networks of neurons, perhaps as large as a whole brain.
K-Comp-640x353The simulations were performed using the NEST software package, designed to efficiently model and simulate networks of spiking neurons. If one extrapolates the use of this technology to perform whole brain (with its 88 billion neurons) emulation, the simulation performed using the K super-computer would be about 100,000 times slower than real time.

The K-computer has an estimated performance of 8 petaflops, or 8 quadrillion (10 to the 15th power) floating point operations per second and is currently the world’s fourth fastest computer.

Is consciousness simply the consequence of complex system organization?

The theory that consciousness is simply an emergent property of complex systems has been gaining adepts lately.

The idea may be originally due to Giulio Tononi, from the University of Wisconsin in Madison. Tononi argued that a system that exhibits  consciousness must be able to store and process large amounts of information and must have some internal structure that cannot be divided into independent parts. In other words, consciousness is a result of the intrinsic complexity of the internal organization of an information processing system, complexity that cannot be broken into parts. A good overview of the theory has been recently published in the Philosophical Transactions of the Royal Society.

The theory has been gaining adepts, such as Max Tegmark, from MIT, who argues that consciousness is simply a state of matter. Tegmark suggests that consciousness arises out of particular arrangements of matter, and there may exist varying degrees of consciousness. Tegmark believes current day computers may be approaching the threshold of higher consciousness.

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Historically, consciousness has been extremely difficult to explain because it is essential a totally subjective phenomenon. It is impossible to assess objectively whether an animal or artificial agent (or even a human, for that matter) is conscious or not, since, ultimately, one has to rely on the word of the agent whose consciousness we are trying to assert. Tononi and Tegmark theories may, eventually, shed some light on this obscure phenomenon.

Research platforms of Human Brain Project released

The Human Brain Project (HBP), a flagship project of the European Union, has just released the initial versions of its six Information and Communications Technology (ICT) platforms to users worldwide.

The six HBP Platforms are:

  • Neuroinformatics
  • Brain Simulation
  • High Performance Computing
  • Medical Informatics
  • Neuromorphic Computing
  • Neurorobotics

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These platforms enable researchers to use the tools developed by the Human Brain Project to search and analyse neuroscience data, simulate brain sections, run complex simulations, searching of real data to understand similarities and differences among brain diseases, access computer systems that emulate brain microcircuits,  and test virtual models of the brain by connecting them to simulated robot bodies and environments.
All the Platforms can be accessed via the HBP Collaboratory, a web portal where users can also find additional information.

Becoming immortal: pipe dream or reachable goal?

Woody Allen’s famous quote on immortality “I don’t want to achieve immortality through my work; I want to achieve immortality through not dying. I don’t want to live on in the hearts of my countrymen; I want to live on in my apartment.” has a different meaning for Dmitry Itskov. He aims to achieve immortality both through his work and through not dying.

Dmitry Itskov is a Russian entrepreneur and billionaire, best known for creating the 2045 initiative, which aims to achieve cybernetic immortality by the year 2045.

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Cited in a recent BBC article, Dmitry Itskov promises that “Within the next 30 years, I am going to make sure that we can all live forever.”

The idea sounds preposterous, but there is no doubt he is not deranged and is serious about it. It is indeed a breathtaking ambition, to achieve mind uploading by the year 2045, but could it actually be done?

The scientific director of the 2045 initiative, Randal Koene, a neuroscientist, who has done work on diverse aspects of brain modeling, believes the task is extremely difficult but not impossible, at least in theory. In a number of videos and presentations available in YouTube, he explains how existing technologies could be used, in principle, to reach this goal.

The question remains: will it ever become possible and, if so, when?

Image by Nevit Dilmen, via Wikimedia Commons

The first complete computer simulation of an entire animal, in your browser

Recent news about OpenWorm, a project that aims at recreating in a computer the behaviour of a complete animal, the roundworm Caenorhabditis elegans. The OpenWorm project aims at constructing a complete model of this worm, not only of the 302 neurons and the 95 muscle cells, but also of the remaining thousand cells in each worm (more exactly, 959 somatic cell plus about 2000 germ cells in the hermaphrodite sex and 1031 cells in the males).

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The one millimeter long worm C. elegans has a long history in science, as one of the animals more extensively used as a model for the study of simple multicellular organisms. It was the first animal to have its genome sequenced, in 1998.

But well before that, in 1963, Sydney Brenner proposed it as a model organism for the investigation of neural development in animals. In an effort that lasted for more than twelve years, the complete structure of the brain of C. elegans was reverse engineered, leading to a diagram of the wiring of each neuron in this simple brain. The effort of reverse engineering the worm brain included slicing, very thinly, several worm brains, obtaining roughly 8000 photos of the slices using an electron microscope and connecting, mostly by hand, each neuron section of each slice to the corresponding neuron section in the neighbor slices. The complete wiring diagram of the 302 neurons and the roughly 7000 synapses, which constitute the brain of this simple creature, was described in minute detail in a 340 pages article, published in 1986, entitled The Structure of the Nervous System of the Nematode Caenorhabditis elegans, with a running head The Mind of a Worm.

Brain uploading in the NY Times

An article in the NY Times, by Kenneth Miller, addresses the question of whether or not we will one day be able to upload a brain, that is, to simulate in a computer the complete behaviour of a human brain.

The author, a neuroscientist from Columbia University, addresses carefully the challenges involved in mind uploading and whole brain emulation.

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The author’s (wild) guess is that it will take centuries to determine a connectome that is detailed enough to enable us to try brain uploading.

However, he also recognises that we may not need to reconstruct all the fine details of a brain, with its billions of neurons and trillions of synapses, whose structure varies in time and space. Still, a level of detail incommensurable with existing technology would be required to even have a shot of creating a model that would reproduce actual brain behaviour.

It seems the singularity may not be over the corner, after all…

(Image by Thomas Schultz, avaliable at Wikimedia commons).

Reverse engineering the brain, one slice at a time

Narayanan Kasthuri and a team of researchers  from Harvard, MIT, Duke, and John Hopkins universities, fully reconstructed all the neuron sections and many sub-cellular objects, including synapses and synapse vesicles, in a volume of 1500 µm3 (which is just a little more than one millionth of a cubic millimeter) using 3×3×30 nm voxels.

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The results, published in an article in the journal Cell, in July 2015, describe the experimental procedure and the conclusions. The data was obtained by collecting 2,250 brain slices, each roughly 30 nm thick, obtained with a tape-collecting ultramicrotome that slices brain sections using a diamond knife.The slices were imaged using serial electron microscopy and the images processed in order to reconstruct a number of volumes. In this volume, the authors have reconstructed the 3D structure of the 1500 µm3 of neural tissue, which included hundreds of dendrites, more than 1400 neuron axons and 1700 synapses, which corresponds to about one synapse per cubic micron.

(Rendering by the authors, used with permission)