My previous post is about IBM Brain Simulator. It turns out that there is still hot discussion about whether it can simulate brain activity or not, as written on an article in Spectrum IEEE.
The IBM Brain Simulator can model the neurons, the synapses and the connectivity of them. It is true that the numbers of neurons and so on are equal to cat's brain or human visual cortex. But one researcher of EPFL Blue Brain, Henry Makram disagreed with the method that IBM Brain Simulator from Almaden's lab used to model the synapses. Henry Makram questioned why ion channeling in the synapses was not modeled in the Almaden's cat brain simulator.
In my opinion, It is already a break-through to model neuronal connectivity. To model the synapses functionality for each connectivity is really hard job. It will take more processors and consume more energy than just 1.4 MW.
My interess is to combine brain simulator and brain-computer interface to create a quasi-telepathic between human and computer. I don't really care which brain model they use: the IBM Almaden's or the EPFL Blue Brain's.
Wednesday, November 25, 2009
Saturday, November 21, 2009
IBM Biggest Brain Simulator in 2009
Three days ago, I read an article from IEEE Spectrum about IBM Brain Simulator. The following day, I read two articles about the brain simulator from the Smart Planet: the first focuses on the technology and the other concerns about what the future will be. Popular Mechanic also has an article about the brain modeling from IBM's Almaden research center compared to others from Stanford University and Neuroscience Institute in San Diego. IEEE Spectrum says that Europe also have similar project called Blue Brain, at EPFL in Lausanne, Switzerland.
The IBM Brain Simulator is featured in Supercomputing 2009 event in Portland, Oregon. This event is about high performance computing. So it is not about brain-computer interface (BCI) or brain robot. There is a possibility to combine BCI and this kind of brain simulator. Maybe I can participate in that kind of research.
There is a concern about the future about the relation between computers and humans. The second article from Smart Planet discussed this. A friend of mine, Mova Al'Afghani, put slides from Karl Fisch in his blog about future prediction, which says that in 2013, super computer will exceed human brain capability and in 2049, a $1000 computer will exceed the capability of entire human species. In 1999, Ray Kurzweil wrote a book: The Age of Spiritual Machines: When Computers Exceed Human Intelligence. In the book, it is predicted that in 2020, a $1000 computer will exceed human intelligence. So you know who makes the prediction. Ray Kurzweil also wrote another book: The Singularity is Near: When Human Trancends Biology. IBM said that in 2019, they can mimic human brain which has 20 billions neurons and 200 trillions synapses.
Singularity (in this context) means that the computer has reached human intelligence and capabilities. TV series Terminator SCC mentioned this singularities. Some people are afraid of this singularity and create Anti Skynet group. (Skynet is fictional "machine" in Terminator). The optimist people build Singularity University to prepare humanity for accelerating technological change.
This is the feature of IBM Biggest Brain Simulator:
The IBM Brain Simulator is featured in Supercomputing 2009 event in Portland, Oregon. This event is about high performance computing. So it is not about brain-computer interface (BCI) or brain robot. There is a possibility to combine BCI and this kind of brain simulator. Maybe I can participate in that kind of research.
There is a concern about the future about the relation between computers and humans. The second article from Smart Planet discussed this. A friend of mine, Mova Al'Afghani, put slides from Karl Fisch in his blog about future prediction, which says that in 2013, super computer will exceed human brain capability and in 2049, a $1000 computer will exceed the capability of entire human species. In 1999, Ray Kurzweil wrote a book: The Age of Spiritual Machines: When Computers Exceed Human Intelligence. In the book, it is predicted that in 2020, a $1000 computer will exceed human intelligence. So you know who makes the prediction. Ray Kurzweil also wrote another book: The Singularity is Near: When Human Trancends Biology. IBM said that in 2019, they can mimic human brain which has 20 billions neurons and 200 trillions synapses.
Singularity (in this context) means that the computer has reached human intelligence and capabilities. TV series Terminator SCC mentioned this singularities. Some people are afraid of this singularity and create Anti Skynet group. (Skynet is fictional "machine" in Terminator). The optimist people build Singularity University to prepare humanity for accelerating technological change.
This is the feature of IBM Biggest Brain Simulator:
- uses Dawn, BlueGene/P supercomputer
- uses C2 cortical simulator
- funded by DARPA (U.S. Defense Advanced Research Projects Agency)
- spended 40 million US dollars
- contains 147,456 processors
- uses 147 TB of RAM
- consumes 1.4 MW
- uses 10 rows of racks (and miles of cables)
- uses 6,675 tons of air-conditioning equipment spouting 2.7 million cubic feet of chilled air
- uses a universal neural circuit called a microcolumn to mimic a single neuron.
- exceed cat's brain capability
- can simulate only human visual cortex capability
- takes 500 seconds to simulate 5 seconds of real mammal's brain activity (in average).
Monday, November 16, 2009
The Gamma-Trait
Today (16th November 2009),
I came to a colloquium in COGNIUM building of University of Bremen. The talk is presented by Prof. Dr. Christoph Herrmann, from the "Institut für Psychologie", University of Magdeburg. Actually, he has moved to the "Institut für Psychologie", University of Oldenburg.
The title of the talk is "Der Gamma-Trait: Inter-individuelle Variation der EEG Gamma-Band-Aktivität spiegelt Unterschiede kognitiver Funktionen wider". The title is in German but the talk is in English. So let me translate the title: "The Gamma-Trait: inter-individual variation of the EEG Gamma band activity reflects the differences in cognitive functions."
Gamma band is the EEG frequency above 30 Hz. Most experiments shown are about event-related potential (ERP) of the EEG. The events are created by stimuli: pictures showing pattern. The response is measured by EEG.
I didn't take note in the talk. I also came late.
But I remember a few things from the talk.
***
There are relationship between genes and the cognition.
The certain genes play a role in dopamine production and other neuronal activity.
The dopamine has relationship with Gamma band activity.
Gamma Band activity is generated by certain stimuli.
So the response of human brain or the cognition depends on genes.
It could means that the way we (human) think differently and act so because of our genes.
We were meant to be different from each other. So religious fundamentalism and racism, who hate different others, are really against our nature.
***
Prior knowledge is important.
There are two experiments showing pictures and recording EEG: first experiment is without prior knowledge and second experiment (in the following 2 weeks) is with prior knowledge from the first one. The second experiment always shows a higher Gamma trait.
***
Giving an electric current to your head increase your Gamma trait.
The experiment is done with both DC and AC voltage.
If you think you can get smarter after you have an electric current through your head, you are wrong. The effect of an increase of Gamma trait last only a few minutes.
It is more stupid if you think electroshock through your brain can make you genious. :-)
***
A man who has a task to differentiate patterns shows an interesting Gamma Trait.
If a similar pattern (to the targeted pattern) is shown, there is also Gamma activity although not as high as from the targeted pattern.
For example there is pattern A, B, C, D. Pattern A has similarities with pattern B and C but it is totally different from pattern D. A subject should pay attention to pattern A. Gamma activity shows the highest response for A and shows a little response for B and C but no response for D.
***
In the talk, there was also different Gamma activity between healthy people and the ones with ADHD. It is too complicated to tell in this blog.
***
Next Monday, I will come to another talk: "A Bayesian model of Attentional Load".
Maybe the following talk will be useful for my Master Thesis.
I came to a colloquium in COGNIUM building of University of Bremen. The talk is presented by Prof. Dr. Christoph Herrmann, from the "Institut für Psychologie", University of Magdeburg. Actually, he has moved to the "Institut für Psychologie", University of Oldenburg.
The title of the talk is "Der Gamma-Trait: Inter-individuelle Variation der EEG Gamma-Band-Aktivität spiegelt Unterschiede kognitiver Funktionen wider". The title is in German but the talk is in English. So let me translate the title: "The Gamma-Trait: inter-individual variation of the EEG Gamma band activity reflects the differences in cognitive functions."
Gamma band is the EEG frequency above 30 Hz. Most experiments shown are about event-related potential (ERP) of the EEG. The events are created by stimuli: pictures showing pattern. The response is measured by EEG.
I didn't take note in the talk. I also came late.
But I remember a few things from the talk.
***
There are relationship between genes and the cognition.
The certain genes play a role in dopamine production and other neuronal activity.
The dopamine has relationship with Gamma band activity.
Gamma Band activity is generated by certain stimuli.
So the response of human brain or the cognition depends on genes.
It could means that the way we (human) think differently and act so because of our genes.
We were meant to be different from each other. So religious fundamentalism and racism, who hate different others, are really against our nature.
***
Prior knowledge is important.
There are two experiments showing pictures and recording EEG: first experiment is without prior knowledge and second experiment (in the following 2 weeks) is with prior knowledge from the first one. The second experiment always shows a higher Gamma trait.
***
Giving an electric current to your head increase your Gamma trait.
The experiment is done with both DC and AC voltage.
If you think you can get smarter after you have an electric current through your head, you are wrong. The effect of an increase of Gamma trait last only a few minutes.
It is more stupid if you think electroshock through your brain can make you genious. :-)
***
A man who has a task to differentiate patterns shows an interesting Gamma Trait.
If a similar pattern (to the targeted pattern) is shown, there is also Gamma activity although not as high as from the targeted pattern.
For example there is pattern A, B, C, D. Pattern A has similarities with pattern B and C but it is totally different from pattern D. A subject should pay attention to pattern A. Gamma activity shows the highest response for A and shows a little response for B and C but no response for D.
***
In the talk, there was also different Gamma activity between healthy people and the ones with ADHD. It is too complicated to tell in this blog.
***
Next Monday, I will come to another talk: "A Bayesian model of Attentional Load".
Maybe the following talk will be useful for my Master Thesis.
Brain-Computer Interface definition, Allison et al, 2008
"Brain-computer interface (BCI) systems are devices that allow people to communicate without moving. Instead, direct measures of brain activity are translated into messages or commands."
From the paper:
B. Allison, I. Volosyak, T. Lüth, D. Valbuena, I. Sugiarto, M.A. Spiegel, A. Teymourian, I.S. Condro, A. Brindusescu, K. Stenzel, H. Cecotti and A. Gräser. 2008. "BCI Demographics I: How many (and what kinds of) people can use an SSVEP BCI?". Proc. 4th International Brain-computer Interface Workshop and Training Course. Graz, Austria, September 18th-21st. pp 333-338.
They are all from Institute of Automation (IAT), University of Bremen, Bremen, Germany.
You can also visit B. Allison's blog or I.S. Condro's blog (yes, that's me).
Some of us have Facebook:
From the paper:
B. Allison, I. Volosyak, T. Lüth, D. Valbuena, I. Sugiarto, M.A. Spiegel, A. Teymourian, I.S. Condro, A. Brindusescu, K. Stenzel, H. Cecotti and A. Gräser. 2008. "BCI Demographics I: How many (and what kinds of) people can use an SSVEP BCI?". Proc. 4th International Brain-computer Interface Workshop and Training Course. Graz, Austria, September 18th-21st. pp 333-338.
They are all from Institute of Automation (IAT), University of Bremen, Bremen, Germany.
You can also visit B. Allison's blog or I.S. Condro's blog (yes, that's me).
Some of us have Facebook:
Saturday, November 14, 2009
Brain-Computer Interface definition, Wolpaw et al, 2002
"A BCI is a communication system in which messages or commands that an individual sends to the external world do not pass through the brain's normal output pathways of peripheral nerves and muscles."
From the paper:
Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, Theresa M. Vaughan. 2002. "Brain-computer interfaces for communication and control". Clinical Neurophysiology. Ireland: Elsevier. Vol. 113, pp 767-791.
This paper has been cited by more than 1000 papers.
Jonathan R. Wolpaw is a Neuroscientist from the Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health, Albany, New York and from the State University of New York, USA.
Niels Birbaumer is a Neurobiologist from the Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen, Tuebingen, Germany and from the Department of Psychophysiology, University of Padova, Padova, Italy.
Dennis J. McFarland and Theresa M. Vaughan are also from the Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health, New York, USA.
Gert Pfurtscheller is from the Department of Medical Informatics, Institute of Biomedical Engineering, Technical University of Graz, Graz, Austria. Now in TU Graz, they have BCI Laboratory.
Vocabularies:
From the paper:
Jonathan R. Wolpaw, Niels Birbaumer, Dennis J. McFarland, Gert Pfurtscheller, Theresa M. Vaughan. 2002. "Brain-computer interfaces for communication and control". Clinical Neurophysiology. Ireland: Elsevier. Vol. 113, pp 767-791.
This paper has been cited by more than 1000 papers.
Jonathan R. Wolpaw is a Neuroscientist from the Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health, Albany, New York and from the State University of New York, USA.
Niels Birbaumer is a Neurobiologist from the Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen, Tuebingen, Germany and from the Department of Psychophysiology, University of Padova, Padova, Italy.
Dennis J. McFarland and Theresa M. Vaughan are also from the Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health, New York, USA.
Gert Pfurtscheller is from the Department of Medical Informatics, Institute of Biomedical Engineering, Technical University of Graz, Graz, Austria. Now in TU Graz, they have BCI Laboratory.
Vocabularies:
- BCI = Brain Computer Interface
- Padova = Padua
Thursday, November 5, 2009
Brain-Machine Interface in the 19th century
Brain-Computer Interface (BCI) is not really a new technology as we can read from the news from IEEE Spectrum. There was a Head Set in the 19th century by pseudo-scientist, called "Phrenologist". The purpose of phrenology is to find correlation between a person's character and the morphology of the skull.
In one article of IEEE Spectrum, the picture number 2 shows the head set. It is mentioned like this:
From the picture, we can see the early research of Brain-Machine Interface. Well, it is not really a machine since the function is unknown. For more information about the history of Phrenology can be seen from their website.
In one article of IEEE Spectrum, the picture number 2 shows the head set. It is mentioned like this:
HEAD CASE: Today’s electromedical researchers are busy mapping the brain, but 19th-century electrical engineers were already on the case. This electrical phrenology apparatus consists of two parts, a headpiece and a wooden box containing a sledge induction coil and three batteries. The headpiece forms a crown 23 centimeters (9 inches) in diameter with 13 brass electrodes evenly spaced across it.
From the picture, we can see the early research of Brain-Machine Interface. Well, it is not really a machine since the function is unknown. For more information about the history of Phrenology can be seen from their website.
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