Showing posts with label mental-uploading. Show all posts
Showing posts with label mental-uploading. Show all posts

11 Mar 2013

Some Recent Scientific Developments in Brain Machine Interface (for Robotic Prosthesis), Neuroplasticity, Neurocomputation, and Whole Brain Emulation

summary by Corry Shores
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[All boldface is my own]




Some (mostly) Recent Scientific Developments in Brain Machine Interface (for Robotic Prosthesis), Neuroplasticity, Neurocomputation, and Whole Brain Emulation



Brief Summary: New scientific advances support the posthuman vision of robotically enhanced and reconstructed post-humans. Neuroplasticity and brain machine interface (also brain computer interface) empower brains to control robotic parts just like biological ones. Whole brain emulation and cognitive prosthetics could allow brain implanted chips to replace or enhance our brain functioning, perhaps even completely “uploading” our brain onto a computerized simulation. Progressive replacement of bodily and neural parts with robotic and computerized ones could enable one to make a complete and continuous transition from human to robot.

 




"Brain" In A Dish Acts As Autopilot Living Computer

Explore: Research at the University of Florida

Spring 2005 Vol. 10 No.1

http://www.research.ufl.edu/publications/explore/v10n1/extract2.html


Thomas DeMarse has created a miniature living brain on a dish. He placed neurons that grew connections to form a network, and it can perform tasks in a virtual world.

“It’s essentially a dish with 60 electrodes arranged in a grid at the bottom,” DeMarse said. “Over that we put the living cortical neurons from rats, which rapidly begin to reconnect themselves, forming a living neural network — a brain.”

The brain and the simulator establish a two-way connection, similar to how neurons receive and interpret signals from each other to control our bodies. By observing how the nerve cells interact with the simulator, scientists can decode how a neural network establishes connections and begins to compute, DeMarse said.

When DeMarse first puts the neurons in the dish, they look like little more than grains of sand sprinkled in water. However, individual neurons soon begin to extend microscopic lines toward each other, making connections that represent neural processes. “You see one extend a process, pull it back, extend it out — and it may do that a couple of times, just sampling who’s next to it, until over time the connectivity starts to establish itself,” he said. “(The brain is) getting its network to the point where it’s a live computation device.”

To control the simulated aircraft, the neurons first receive information from the computer about flight conditions: whether the plane is flying straight and level or is tilted to the left or to the right. The neurons then analyze the data and respond by sending signals to the plane’s controls. Those signals alter the flight path and new information is sent to the neurons, creating a feedback system.

“Initially when we hook up this brain to a flight simulator, it doesn’t know how to control the aircraft,” DeMarse
said. “So you hook it up and the aircraft simply drifts randomly. And as the data come in, it slowly modifies the (neural) network so over time, the network gradually learns to fly the aircraft.”

Although the brain currently is able to control the pitch and roll of the simulated aircraft in weather conditions ranging from blue skies to stormy, hurricane-force winds, the underlying goal is a more fundamental understanding of how neurons interact as a network, DeMarse said.

“There’s a lot of data out there that will tell you that the computation that’s going on here isn’t based on just one neuron. The computational property is actually an emergent property of hundreds or thousands of neurons cooperating to produce the amazing processing power of the brain.”



Monkeys Think, Moving Artificial Arm as Own

By Benedict Carey

New York Times

Published: May 29, 2008

http://www.nytimes.com/2008/05/29/science/29brain.html?_r=0


Two monkeys with brain-controlled prosthetics successfully use their robotic arms to reach for food and feed it to themselves.

Two monkeys with tiny sensors in their brains have learned to control a mechanical arm with just their thoughts, using it to reach for and grab food and even to adjust for the size and stickiness of morsels when necessary, scientists reported on Wednesday.

The report, released online by the journal Nature, is the most striking demonstration to date of brain-machine interface technology. Scientists expect that technology will eventually allow people with spinal cord injuries and other paralyzing conditions to gain more control over their lives.


ALSO reported at MIT Technology Review

Monkey Thinks Robot into Action

A monkey is able to feed itself with a robotic arm.

    By Emily Singer

MIT Technology Review

May 28, 2008

http://www.technologyreview.com/news/410189/monkey-thinks-robot-into-action/


It’s the first time a monkey–or a human–is directly, with their brain, controlling a real prosthetic arm,” says Krishna Shenoy, a neuroscientist at Stanford University who was not involved in the research. (Singer)




TED

Henry Markram: A brain in a supercomputer
Filmed Jul 2009 • Posted Oct 2009 • TEDGlobal 2009

http://www.ted.com/talks/henry_markram_supercomputing_the_brain_s_secrets.html


Supercomputers are being used to simulate brain activity. They began with animals and are moving up to human brain. They first catalogued neurons and described their interactive behavior. They can simulate human neuronal activity on a small scale. Also see:

http://en.wikipedia.org/wiki/Blue_Brain_Project




Rat memory under computer simulation

Eric Mankin

Public release date: 17-Jun-2011

Restoring memory, repairing damaged brains
Biomedical engineers analyze -- and duplicate -- the neural mechanism of learning in rats

Eureka Alert

http://www.eurekalert.org/pub_releases/2011-06/uosc-rmr061211.php


Scientists have developed a way to turn memories on and off—literally with the flip of a switch.

Using an electronic system that duplicates the neural signals associated with memory, they managed to replicate the brain function in rats associated with long-term learned behavior, even when the rats had been drugged to forget.

"Flip the switch on, and the rats remember. Flip it off, and the rats forget," said Theodore Berger of the USC Viterbi School of Engineering's Department of Biomedical Engineering.” (Mankin)



ALSO reported in The New York Times

Memory Implant Gives Rats Sharper Recollection

By Benedict Carey

The New York Times

Published: June 17, 2011

http://www.nytimes.com/2011/06/17/science/17memory.html?_r=0


The authors said that with wireless technology and computer chips, the system could be easily fitted for human use.
(Carey)




New horizons in auditory prostheses

Zeng, Fan-Gang PhD

Hearing Journal

November 2011 - Volume 64 - Issue 11 - pp 24,26,27

http://journals.lww.com/thehearingjournal/Fulltext/2011/11000/New_horizons_in_auditory_prostheses.5.aspx


There are many recent developments in cochlear implants.

All contemporary cochlear implants use similar signal processing that extracts temporal envelope information from a limited number of spectral bands, and delivers these envelopes successively to 12-22 electrodes implanted in the cochlea. As a result, these implants produce similarly good speech performance: 70-80 percent sentence recognition in quiet, which allows an average cochlear implant user to carry on a conversation over the telephone. Interestingly, though, sentence recognition in quiet has essentially remained at this same level since 1994. (Figure 1.)




Active tactile exploration using a brain–machine–brain interface

Joseph E. O’Doherty, Mikhail A. Lebedev, Peter J. Ifft, Katie Z. Zhuang, Solaiman Shokur, Hannes Bleuler & Miguel A. L. Nicolelis

Nature 479, 228–231 (10 November 2011)

http://www.nature.com/nature/journal/v479/n7372/full/nature10489.html


Monkeys operating virtual robotic arms had their brains given touch stimulations.



ALSO reported by The Huffington Post

Is It Possible To Feel Textures Using Just Brain Waves? New Study Shows How

The Huffington Post

Amanda Chan Posted: 10/07/11 11:49 AM ET

http://www.huffingtonpost.com/2011/10/07/brain-touch-texture-feelings-senses_n_996844.html

 

This is basically one of the holy grails of this field," study researcher Miguel Nicolelis, a neurobiology professor and co-director of the Duke Center for Neuroengineering, told Bloomberg. "No other study has provided an artificial sensory channel directly to the brain of animals. This is really needed to restore in patients that have a spinal cord injury not only their mobility, but their sense of touch." (Chan)




Going mental: Study highlights brain’s flexibility, gives hope for natural-feeling neuroprosthetics

By Sarah Yang, Media Relations

UC Berkeley News Center

March 4, 2012

http://newscenter.berkeley.edu/2012/03/04/brain-flexibility-gives-hope-for-neuroprosthetics/


Researchers at the University of California, Berkeley have shown that neurons used for physical tasks can be retrained for brain machine interface usage. This shows that neuro-prosthetics can feel natural.

“Their new study, to be published Sunday, March 4, in the advanced online publication of the journal Nature, shows that through a process called plasticity, parts of the brain can be trained to do something they normally do not do. The same brain circuits employed in the learning of motor skills, such as riding a bike or driving a car, can be used to master purely mental tasks, even arbitrary ones.

[…]

To clarify these issues, the scientists set up a clever experiment in which rats could only complete an abstract task if overt physical movement was not involved. The researchers decoupled the role of the targeted motor neurons needed for whisker twitching with the action necessary to get a food reward.

The rats were fitted with a brain-machine interface that converted brain waves into auditory tones. To get the food reward – either sugar-water or pellets – the rats had to modulate their thought patterns within a specific brain circuit in order to raise or lower the pitch of the signal.

Auditory feedback was given to the rats so that they learned to associate specific thought patterns with a specific pitch. Over a period of just two weeks, the rats quickly learned that to get food pellets, they would have to create a high-pitched tone, and to get sugar water, they needed to create a low-pitched tone.

If the group of neurons in the task were used for their typical function – whisker twitching – there would be no pitch change to the auditory tone, and no food reward.

“This is something that is not natural for the rats,” said Costa. “This tells us that it’s possible to craft a prosthesis in ways that do not have to mimic the anatomy of the natural motor system in order to work.”





Simulated brain scores top test marks

First computer model to produce complex behaviour performs almost as well as humans at simple number tasks.

    Ed Yong

Nature | News

29 November 2012

http://www.nature.com/news/simulated-brain-scores-top-test-marks-1.11914


A computer simulated brain with 2.5 million virtual neurons can perform simple mathematical calculations.




Mind-controlled robot arms show promise

People with tetraplegia use their thoughts to control robotic aids.

    Alison Abbott

Nature | News

16 May 2012

http://www.nature.com/news/mind-controlled-robot-arms-show-promise-1.10652

[AP Report here]

Two tetraplegics use brain machine interface to gain some lost abilities.

Neurosurgeons implanted tiny recording devices containing almost 100 hair-thin electrodes in the motor cortex of their brains, to record the neuronal signals associated with intention to move.” (Abbott)

Cathy can use her thoughts to direct the motion of a robotic arm. She is able to direct it to grab a bottle of coffee and lift it to her lips. Bob as well operates the arm successfully. There is also a subject who operates a computer cursor using this interface, as if operating a computer mouse. The subjects used the BrainGate2 brain implant system [image below from the BrainGate wiki page.]

Braingate model wiki
(Thanks wiki)




Paralyzed Man Uses Thoughts Alone to Control Robot Arm, Touch Friend's Hand, After Seven Years

Science Daily

Feb. 8, 2013 —

http://www.sciencedaily.com/releases/2013/02/130208124818.htm

Based on this journal article

Wei Wang et al.

An Electrocorticographic Brain Interface in an Individual with Tetraplegia. PLoS ONE, 2013; 8 (2): e55344

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0055344


Researchers at the University of Pittsburgh School of Medicine and UPMC describe in PLoS ONE how an electrode array sitting on top of the brain enabled a 30-year-old paralyzed man to control the movement of a character on a computer screen in three dimensions with just his thoughts. It also enabled him to move a robot arm to touch a friend's hand for the first time in the seven years since he was injured in a motorcycle accident. (Science Daily)


ALSO reported by AP

Paralyzed Man Uses Mind-Powered Robot Arm To Touch
Tim Hemmes

By Lauran Neergaard  

10/10/11 10:04 AM ET  

AP

http://www.huffingtonpost.com/2011/10/10/mind-powered-robot-arm_n_1003204.html


"It wasn't my arm but it was my brain, my thoughts. I was moving something," Hemmes says. (Neergaard)




Bionic Eye Implant Approved by U.S. for Rare Disease
By Anna Edney

Bloomberg

Feb 15, 2013 7:01 AM GMT+0200

http://www.bloomberg.com/news/2013-02-14/bionic-eye-implant-approved-by-u-s-for-rare-disease.html


New neuroprosthetic eye implant restores some visual capabilities.

While the $100,000-plus system won’t restore sight, it gives patients the ability to perceive the difference between light and dark. The device consists of a video camera, a transmitter mounted on a pair of eyeglasses and a processing unit that transforms images into electronic data sent to an implanted retinal prosthesis, the FDA said.

[…]

Konstantopoulos, of Glen Burnie, Maryland, said he was diagnosed with retinitis pigmentosa when he was in his early 40s and became completely blind about six months ago. He can see shadows now with the device and tell if the sun is behind a tree. Argus II is comfortable and the surgery was painless, he said.

[…]

A clinical study of 30 people showed the eye device helped patients recognize large letters or words, detect street curbs, walk on a sidewalk without falling and match black, gray and white socks.




Rats With Linked Brains Work Together
Megan Gannon, News Editor

Live Science

Date: 28 February 2013 Time: 12:23 PM ET

http://www.livescience.com/27544-rats-with-linked-brains-work-together.html


Brain plasticity so great that brains can use information from other brains.

Scientists have engineered something close to a mind meld in a pair of lab rats, linking the animals' brains electronically so that they could work together to solve a puzzle. And this brain-to-brain connection stayed strong even when the rats were 2,000 miles apart.

The experiments were undertaken by Duke neurobiologist Miguel Nicolelis, who is best known for his work in making mind-controlled prosthetics.

"Our previous studies with brain-machine interfaces had convinced us that the brain was much more plastic than we had thought," Nicolelis explained. "In those experiments, the brain was able to adapt easily to accept input from devices outside the body and even learn how to process invisible infrared light generated by an artificial sensor. So, the question we asked was, if the brain could assimilate signals from artificial sensors, could it also assimilate information input from sensors from a different body?"

For the new experiments, Nicolelis and his colleagues trained pairs of rats to press a certain lever when a light went on in their cage. If they hit the right lever, they got a sip of water as a reward.

When one rat in the pair called the "encoder" performed this task, the pattern of its brain activity — something like a snapshot of its thought process — was translated into an electronic signal sent to the brain of its partner rat, the "decoder," in a separate enclosure. The light did not go off in the decoder's cage, so this animal had to crack the message from the encoder to know which lever to press to get the reward.

The decoder pressed the right lever 70 percent of the time, the researchers said.

[…]

"We saw that when the decoder rat committed an error, the encoder basically changed both its brain function and behavior to make it easier for its partner to get it right," Nicolelis explained in a statement. "

[…]

The connection was not lost even when the signals were sent over the Internet and the rats placed on two different continents, 2,000 miles (3,219 kilometers) apart.”





.

14 Jun 2009

Conclusion; Bostrom and Sandberg's Brain Emulation, Examined and Critiqued. Section 6


by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]

[Central Entry Directory]
[Posthumanism, Entry Directory]
[Other entries in this paper series.]

[The following is tentative material for my presentation at the Society for Philosophy & Technology Conference this summer.]





Corry Shores


Do Posthumanists Dream of Pixilated Sheep?

Bostrom and Sandberg's Brain Emulation,

Examined and Critiqued


Section 6:


Conclusion



I do not discourage this technology’s development. I hope in fact that my critical objections are wrong. For that way we will have reason to believe that Bostrom & Sandberg’s philosophical assumptions are in fact correct. This would lend support to the theories that our minds are emergent phenomena, that analog technologies are unnecessary for artificial intelligence, that we may artificially simulate our brain’s randomness that is essential for creativity, adaptation, and perhaps free choice, and that this randomness does not make it impossible to replicate someone’s personal identity. In this sense, the technology can never really be a failure. For even if results indicate it will never succeed, that lends support to the contrary philosophical assumptions.



Even While Men’s Minds are Wild?; Bostrom and Sandberg's Brain Emulation, Examined and Critiqued. Section 5


by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]

[Central Entry Directory]
[Posthumanism, Entry Directory]
[Other entries in this paper series.]

[The following is tentative material for my presentation at the Society for Philosophy & Technology Conference this summer.]




Corry Shores


Do Posthumanists Dream of Pixilated Sheep?

Bostrom and Sandberg's Brain Emulation,

Examined and Critiqued


Section 5:


Even While Men’s Minds are Wild?



Neural noise can result from external interferences like magnetic fields. Or internal random fluctuations might make the signals unpredictable. (Ward 116-117) In both cases, chance & chaos reign our brains. According to Steven Rose, our brain is an “uncertain” system on account of “random, indeterminate, and probabilistic” events that are essential to its functioning (Rose 93). Alex Pouget and his research team recently found that the mind's ability to compute complex calculations has much to do with its noise. The word noise is misleading, he says, because it implies something goes wrong. But these unpredictable irregularities are the mind’s way of running at optimum performance. Our mind produces noisy signals to represent the uncertainty of the world around us. Pouget explains,

if we want to do something, such as jump over a stream, we need to extract data that is not inherently part of that information. We need to process all the variables we see, including how wide the stream appears, what the consequences of falling in might be, and how far we know we can jump.

In this way, the brain is flooded with countless variables. And the neurons transmit various signal patterns for the same stimulus. This allows us to estimate margins of error. We then use a probabilistic inference to make what is most likely to be the best decision. (Pouget, interview with Science Daily) So we might jump the stream, if probably we can cross it, even though we can never be certain about such matters.

Some also theorize that noise is essential to the human brain’s creativity. Johnson-Laird claims that creative mental processes are never predictable. (Johnson-Laird, The Computer and the Mind 256) He hypothesizes that we could make a machine creative by programming it to alter its own functioning according to generated random variations. (Human and Machine Thinking, 119-120) This would produce what Ben Goertzel refers to as “a complex combination of random chance with strict, deterministic rules.” (Goertzel 119) And according to Daniel Dennett, this indeterminism is precisely what endows us with what we call free will. (Dennett 295, cited in Dartnall 37) Likewise, Bostrom & Sandberg suggest we introduce random noise into our simulation by using pseudo-random number generators. They are not truly random, because eventually the pattern will repeat. But if it takes a very long time before the repetitions appear, then probably it would be sufficiently close to real randomness (Bostrom & Sandberg 38-39). Also, there might be random variations that are hidden to our observations, and thus would not be properly represented in the simulation. They recognize the profound difficulty in incorporating true randomness or hidden variables into the simulation. Yet they believe these sorts of randoms most likely will be unnecessary for whole brain emulation.

But perhaps there is more to consider. Lawrence Ward reviews findings that demonstrate neural noise is pink noise, or what is called 1/f noise. (Ward 145-153, citing research by Lundström and McQueen, and Novikov, Shannonhoff-Khalsa, Schwartz, and Wright) On account of its fractal nature, 1/f noises are always parts of similar larger-orders of variation happening on much longer time-scales. We might have to wait weeks or months to see larger-scale variations that were varying the randomness of the more local noisy events. (Anderson & Mandell 78-79) These are what Gregory Bateson calls metarandom variables. They are hidden to us, because we never see the whole picture (Bateson Steps to an Ecology 418). It’s why live lobsters never notice their cooking water gradually increase to boil (Mind and Nature 109). They only notices alterations on a local level, so nothing really seems to be changing. In a similar way, if all we are observing is randomness on a smaller scale, we might be missing the larger scale variations. It would be like randomly adjusting a radio to pick up different bands of radio static. If all we knew was the randomness of radio static at each moment, we might not also notice the higher order randomness that varies the lower one that we are listening-to. Because these uncontrollable unpredictabilities are essential to all the random changes happening around us, Bateson calls them wild variables. (Mind and Nature 49-50)

Perhaps it is for similar reasons that Benoit Mandelbrot classifies 1/f noise under what he terms “wild randomness” and “wild variation.” (Mandelbrot The (mis)Behavior of Markets 39-41) This sort of random might not be so easily simulated. Mandelbrot gives two reasons for this.

1) In wild randomness, there are events that defy the normal random distribution of the bell curve. He cites a number of stock market events that are astronomically improbable. But such events in fact happen quite frequently in natural systems despite their seeming impossibility. There is no way to predict when they will happen or how drastic they will be. (The (mis)Behavior of Markets 4)

2) Each event is random and yet it is not independent from the rest, like each toss of a coin is. One seemingly small anomalous event will echo like reverberations at unpredictable intervals into the future. (The (mis)Behavior of Markets 181-185)

For these reasons, he considers wild variation to be a qualitatively different state of indeterminism than the usual mild variations we encounter at the casino. For, there is infinite variance in the distributions of wild randomness. Anything can happen at any time (Mandelbrot, Fractals and Scaling 128). He says, “the fluctuation from one value to the next is limitless and frightening.” (Mandelbrot (mis)Behavior of Markets 39-41) This is the wildness of our brains.

Paul Shepard considers our minds to be wild in an even more literal sense: we are wild animals. He distinguishes tameness from domestication. Cows are domesticated. They have been bred to suit our needs. And now their genes would probably not prepare them to live in the wild without human protections. But the human species has merely been tamed by culture and not domesticated like cows. Genetically, we are still the same wild creatures who hunted the Pleistocene savannas. So to emulate the human brain is to simulate the workings not of a rational machine, but of a wild animal. (Shepard 132-133) He writes, “The savage mind is ours! ... as a species we have in us the call of the wild.” (143)

Shepard’s characterizes the wild, like Bateson and Mandelbrot do, as being too complex for any simulation. But he offers his own theory to explain why. He notes the fractal nature of reality. Within every scale is another smaller scale, and so on to infinity. He says that every layer of complexity operates according to deterministic principles. But, there is no lowest level of complexity. Hence there is no way to get to the bottom of what is happening now. It’s turtles all the way down. Thus there is no way to fully understand why things are the way they are now. And thus we can never know how things will be in the future. (146-147)


But let’s suppose that the brain’s wild randomness can be adequately simulated. Will brain emulation still attain its fullest success of perfectly replicating a specific person’s own identity? Bostrom & Sandberg recognize that neural noise will prevent precise one-to-one emulation. However, they think that the noise will not prevent the simulation from producing meaningful brain states (
Bostrom & Sandberg 7). But to pursue further the personal identity question, let’s imagine that we want to emulate a certain slot machine. A relevant property is its unpredictability. Consider these two possibilities. 1) We set the original and the simulation to the same starting position. We give both handles a number of pulls. Each time, they both show the same outcomes, because we replicated the mechanics perfectly. But then, we cannot say that we have preserved its relevant essential property of being unpredictable. For, we can just run the simulator by itself and that will predict the original’s future outcomes. Or, 2) instead the emulation produced its own different random series of outcomes. Then in fact we would be replicating the original’s property of unpredictability.

The problem is that the brain’s 1/f noise is wildly random. So suppose we emulate some person’s brain perfectly. And suppose further that the original person and her emulation have an identity merger where each one thinks they are talking to their very own selves when really they are talking to the other. They confuse themselves with one another. They are completely aware of what is in the other’s mind at that first moment, because they can tell it is the same as what is in their own mind. And suppose further that the original person loses her fear of death, knowing that something she cannot distinguish from himself will carry on after her body dies. But if both minds are subject to wild variations, then their consciousness and identity might come to differ more than just slightly. They could veer-off wildly. The original person and her emulation might become so mistrustful of each other, that they want to end the other’s existence.

So we might need to emulate this wild neural randomness. But that seems to remove the possibility that the emulation will continue on as the original person. Perhaps our very effort to emulate a specific human brain results in our producing an entirely different brain altogether.


[Next entry in this series.]


Anderson, Carl M. & Arnold J. Mandell. Fractal Time and the Foundations of Consciousness: Vertical Convergence of 1/fPhenomena from Ion Channels to Behavior States. in Fractals of Brain, Fractals of Mind. Ed. Earl Mac Cormac & Maxim I. Stamenov. Amsterdam: John Benjamins Publishing Company, 1996. More information and limited preview available at: http://books.google.be/books?id=WdERazd7Ik4C&hl=en


Bateson, Gregory. "Effects of Conscious Purpose on Human Adaptation." in Steps to an Ecology of Mind. London: Granada Publishing, 1972. . More information and limited preview available at: http://books.google.be/books?id=FQvfqk31zFQC&hl=en


Bateson, Gregory. Mind and Nature: A Necessary Unity. London: Fontana, 1979. More information available at: http://books.google.be/books?id=aQtHAAAAMAAJ&hl=en&pgis=1


Sandberg, A. & Bostrom, N. (2008): Whole Brain Emulation: A Roadmap, Technical Report #20083, Future of Humanity Institute, Oxford University. Available online at:http://www.fhi.ox.ac.uk/Reports/2008-3.pdf


Dartnall, Terry. "Introduction: On Having a Mind of Your Own." in Artificial Intelligence and Creativity: An Interdisciplinary Approach. Ed. Terry Dartnall. Dordrecht: Kluwer Academic Publishers, 1994. More information and limited preview available at: http://books.google.be/books?id=4phC9RwvC8YC&hl=en


Dennett, Daniel. Brainstorms. Hassocks: Harvester Press, 1978. More information available at: http://books.google.be/books?id=s3V-AAAAMAAJ&hl=en&pgis=1


Goertzel, Ben. Chaotic Logic: Language, Thought, and Reality from the Perspective of Complex Systems Science. London: Plenum Press, 1994. More information and limited preview available at: http://books.google.be/books?id=zVOWoXDunp8C&hl=en

Johnson-Laird, R. N. The Computer and the Mind: An Introduction to Cognitive Science. Cambridge: Harvard University Press, 1988. More information and limited preview available at: http://books.google.be/books?id=Tf5gRFgVuegC&hl=en


Johnson-Laird, Philip. Human and Machine Thinking. London: Lawrence Erlbaum Associates, Publishers, 1993. More information and limited preview available at: http://books.google.be/books?id=sPbdQjtkIhkC&hl=en


Mandelbrot, Benoit B., & Richard L. Hudson. The (mis)Behavior of Markets: A Fractal View of Risk, Ruin, and Reward. New York: Basic Books, 2004. More information available at: http://books.google.be/books?id=DPwBTj99a7UC&hl=en


Science Daily. "Mysterious 'Neural Noise' Actually Primes Brain For Peak Performance." Nov. 13, 2006. Available online at: http://www.sciencedaily.com/releases/2006/11/061112094812.htm


Shepard, Paul. Coming Home to the Pleistocene. Washington, D.C.: Island Press, 1998. More information and limited preview available at: http://books.google.be/books?id=5b18NqLB8LMC&hl=en


Ward, Lawrence M. Dynamical Cognitive Science. London: MIT Press, 2002. More information and limited preview available at: http://books.google.be/books?id=g1ZMAoWGYesC&hl=en


Also mentioned:

(Lundström and McQueen, 1974, "A proposed 1/f noise mechanism in nerve cell membranes," Journal of Theoretical Biology, 45, 405-409).


(Novikov E., A. Novikov, Shannonhoff-Khalsa, Schwartz, and Wright, 1997, "Scale-similar activity in the brain," Physical Review E, 56, R2387-R2389,)



11 Jun 2009

Awake! Arise! or be Forever Disorganized; Bostrom and Sandberg's Brain Emulation, Examined and Critiqued. Section 3


by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]

[Central Entry Directory]
[Emergentism, Entry Directory]
[Posthumanism, Entry Directory]
[Other entries in this paper series.]

[The following is tentative material for my presentation at the Society for Philosophy & Technology Conference this summer.]


[Other entries in this series.]



Corry Shores


Do Posthumanists Dream of Pixilated Sheep?

Bostrom and Sandberg's Brain Emulation,

Examined and Critiqued


Section 3:


Awake! Arise! or be Forever Disorganized



Bostrom’s & Sandberg’s Roadmap presupposes a physicalist standpoint. So everything has a physical basis. Minds emerge from the brain’s pattern of physical dynamics. If you replicate this pattern-dynamic in some other physical medium, the same phenomena should likewise emerge. They write that “sufficient apparent success with [Whole Brain Emulation] would provide persuasive evidence for [this theory that consciousness may be realized in multiple distinct physical forms, or what’s called] multiple realizability.” (Bostrom & Sandberg 14)

Our mind’s emergence requires a dynamic process. Paul Humphreys calls it diachronic pattern emergence. (Humphreys 438)

According to emergentist theories, all reality is made-up of a single kind of stuff. But its parts aggregate and assemble into dynamic organizational patterns. The higher levels exhibit properties not found in the lower ones. Yet, the higher level would not exist were it not for its constituent lower level. (Clayton, 2-3)

Todd Feinberg suggests water, for example. The H2O molecule does not itself bear the properties of liquidity, wetness, and transparency. However, an aggregate does. (Feinberg, 125) Emergent features go beyond what we may expect from the lower level. Hence the higher levels are greater than the sum of their parts.

In our brains, no one single neuron is conscious. Yet our minds emerge from the complex dynamic pattern of all our neurons communicating and computing in parallel. Roger Sperry offers compelling evidence. There are "split brain" patients whose right and left brain hemispheres are disconnected from one another. Nonetheless, they maintained unified consciousness. But there is no good account for this on the basis of neurological activity. (Clayton 20)

William Hasker follows Sperry. He says that mental properties “manifest themselves when the appropriate material constituents are placed in special, highly complex relationships.” (Hasker, 189-190) He offers the analogy of magnetic fields, which he says are distinct from the magnets producing them. For, they occupy a much broader space. The magnetic field is generated because its “material constituents are arranged in a certain way – namely, when a sufficient number of the iron molecules are aligned so that their ‘micro-fields’ reinforce each other and produce a detectable overall field.” Once generated, the field exerts its own causality, which affects not only the objects around it, but even the very magnet itself. Hence Hasker’s analogy: just as the alignment of iron molecules produces a field, so too the particular organization of the brain’s neurons generates its field of ‘consciousness.’ (190) This emergent consciousness-field permeates and haloes our brain-matter, occupying its space and traveling along with it. (192)

Suppose whole brain emulation continually falls short. This could support Todd Feinberg’s argument that the mind does not emerge from the brain. He agrees with Searle that

the naïve idea here is that consciousness gets squirted out by the behavior of the neurons in the brain, but once it has been squirted out, then it has a life of its own (Searle, 1992) (qt. in Feinberg 126)

Feinberg does in fact think consciousness results from the interaction of many complex layers of neural organization. However, no level emerges, because none are more independent than any other. Our vision illustrates. We see a wide variety of stuff. But we can recognize singularities like our grandmother. Much visual information must be processed through many layers of neuron-circuits until finally arriving at the “grandmother cell.” Yet all layers must work together at once to achieve this recognition. The brain is a vast network of circuits far too interconnected to discern higher and lower levels of organization. (Feinberg 130-131)

But perhaps Feinberg, so to speak, looks too much among the iron atoms and so he never notices the surrounding magnetic field. Nonetheless, his objection may still be problematic for whole brain emulation. Bostrom & Sandberg write:

An important hypothesis for WBE is that in order to emulate the brain we do not need to understand the whole system, but rather we just need a database containing all necessary low-level information about the brain and knowledge of the local update rules that change brain states from moment to moment. (Bostrom & Sandberg 8)

But if Feinberg’s holistic theory is correct, we cannot only emulate the lower levels and expect the rest to spontaneously emerge. For, we need already to understand the higher-levels in order to program the lower ones. Thompson et al. write:

The brain is thus a highly cooperative system: the dense interconnections among its components entail that eventually everything going on will be a function of what all the components are doing. (Thompson, Varela, & Rosch 94a-b)

Thus the behavior of the whole system resembles a cocktail party conversation much more than a chain of command. (96a)

Consciousness results from neural activity. But it might do so in a way that is not perfectly suited to emergentist theories. Hence whole brain emulation might provide evidence indicating whether and how our minds relate to our brains.



[Next entry in this series.]



Clayton, Philip. "Conceptual Foundations of Emergence Theory." in The Re-Emergence of Emergence: The Emergentist Hypothesis from Science to Religion. Ed. Philip Clayton and Paul Davies. Oxford: Oxford University Press, 2006. More information and partial preview available at: http://books.google.be/books?id=KJF1ydg3HJQC&hl=en


Feinberg, Todd E. "Why the Mind is Not a Radically Emergent Feature of the Brain." in The Emergence of Consciousness. Ed. Anthony Freeman, Thorverton, UK: Imprint Academic, 2001. More information and partial preview available at: http://books.google.com/books?id=YBnLgsAOe6AC&printsec=toc&dq=Why+the+mind+is+not+a+radically+emergent+feature+of+the+brain&lr=&source=gbs_summary_s&cad=0#PPA136,M1


Hasker, William. The Emergent Self. London: Cornell University Press, 1999. More information and limited preview available at: http://books.google.be/books?id=dCW023Hc1q4C&hl=en


Humphreys, Paul. "Synchronic and Diachronic Emergence." Minds and Machines. Vol.18, Number 4, December, 2008, pp.431-442. More information and online text available at: http://www.springerlink.com/content/d442431150343t17/?p=f1cef51a00d346b582d2c3ad1386c814π=1


Sandberg, A. & Bostrom, N. (2008): Whole Brain Emulation: A Roadmap, Technical Report #20083, Future of Humanity Institute, Oxford University. Available online at:http://www.fhi.ox.ac.uk/Reports/2008-3.pdf


Searle, J. R. The Rediscovery of the Mind. Cambridge: MIT Press, Bradford Books, 1992. (Cited in Feinberg)


Varela, Francisco J, Evan Thompson, & Eleanor Rosch. The Embodied Mind: Cognitive Science and Human Experience. Cambridge, Massachusetts: The MIT Press, 1991. More information and limited preview available at: http://books.google.be/books?id=QY4RoH2z5DoC&hl=en