Saturday, April 18, 2015

EEG electrode placement summary, April 2015

After experimenting with different EEG amplifiers, I got more information about different EEG electrode position. And then my summary ought to be revised. Below are the revisions in my PhD note.


In my notes, I add information about CSP spatial filter because this filter is suitable with EEG amplifiers with more than 8 electrodes. CSP is Common Spatial Filter. This filter is used for motor imagery BCI involving lateralization of hand movement: left versus right, contralateral versus ipsilateral.

***

Previous EEG electrode placement summary:



The EEG amplifiers, I have used so far in my PhD study at the University of Oldenburg, as well as in my master study at the University of Bremen, are below.

  • mBrainTrain Smarting, a mobile EEG amplifier with 24 electrodes, since the second year of my PhD study.
  • gtec MOBIlab+, a mobile EEG amplifier with maximum 8 bipolar electrodes, for the third semester of my PhD Study.
  • Easymotiv, which is modified Emotiv EPOC with Easy Cap, a mobile EEG amplifier with 14 electrodes, for the first semester of my PhD study.
  • TMSi Porti 7, an EEG amplifier with 32 electrodes, for my master thesis.
  • gtec USBamp, an EEG amplifier with 16 electrodes, for my master project.


***

Tulisan ini adalah revisi dari rangkuman posisi elektroda EEG untuk Brain-Computer Interface sebelumnya. Revisi dilakukan setelah mencoba beberapa EEG amplifier. Dalam revisi terdapat penambahan informasi tentang Common Spatial Pattern (CSP) sesuai catatan doktoral 24 November 2014.


Bremen, 18 April 2015

iscab.saptocondro
Darah Juang!

Tuesday, August 26, 2014

Bandung Brain-Computer Interface on Indonesia Morning Show, Net TV, June 2014

Bandung Brain-Computer Interface (BCI) Bionic Arm (wp,blog) is on Indonesia Morning Show, Net TV. There we can see the demo:
  • Putting the Emotiv EPOC headset.
  • Calibration with ball and box from the laptop.
  • Single-trial Motor imagery BCI  to control the robotic/bionic arm



From the video, I can see that BCI2000 is used to connect the Emotiv EPOC system and the bionic arm system. One student said that the price is less than 10 millions rupiahs. This means that Emotiv EPOC Research SDK (with a price of 750$) is used. Since August 2014, research SDK is not sold anymore and there is new Emotiv EPOC Education with a price of 1799$, now. It is unknown if the dll files still compatible with BCI2000 or not. Well, I had problem connecting Emotiv EPOC Education with OpenVibe.

The classifier are not explained nor seen from the video. It would be too complicated for "non-scientific" news channels. The calibration takes about 1 minute, on the video. The calibration method is using a ball and a box. On the monitor, there is a ball and a box. The ball should be moved closer to the box, using imagination of motoric movement. In calibration, both the machine (as classifier) and the human (as user) will learn to perform the motor imagery task. Well, 1 minute is fast. It is unknown whether the user had trained backstage before performing on camera. Haha!

For real-time usage of BCI, single-trial motor imagery has to be used. In calibration, more-trial motor imagery has to used for calculating the parameters of the classifier. From the video, we can see that the bionic arm moves only when the user do mental task of motor imagery. So I think the classifier is good and the user is "BCI-literate". When the user clapped her hand, the bionic arms didn't move. So I think the classifier detects hand grasping or finger movement and neglects other hand movement. In my opinion, the user has trained backstage before she is on camera. She has known that she has to imagine grasping movement. The classifier parameters may have been saved before the show. That's why she is doing calibration fast and she can easily move the bionic arm (without instruction from the experimenters).

From the video, there are 3 students (Electrical Engineering from ITB, Bandung, Indonesia). I think they have to separate tasks to do the projects. One should manage software and hardware to drive bionic arm. One should manage Emotiv EPOC connection with BCI2000. One should connect all the system to make sure that everything works. Also, one should design what kinds of classifier that works: linear discriminant analysis (LDA), common spatial pattern (CSP), or simple thresholding of ERP (event-related potential) or others. I think they use C++. From my experience with BCI2000, Microsoft Visual C++ has to be used. I haven't tried the new BCI2000. Maybe it works with C++ in many other environments: Eclipse and Linux.



Well, I should go back to my real research, instead of blogging.


Bremen, 26 Agustus 2014

iscab.saptocondro
Darah Juang!

Saturday, August 23, 2014

EEG electrode placement summary, August 2014


After reading the theses from my research mates from Uni Oldenburg, as well as Uni Bremen, I summarized some EEG electrode placements in my PhD note. So these are the links to my note.


SSVEP stands for steady-state visually evoked potential.

The idea is to minimize the number of EEG electrodes, which I am planning to use with my mobile EEG device. Putting electrodes to the scalp takes a lot of time. If 192 electrodes were put on whole scalp, it could took 1 hour or more and it would not be practical for the users. Also, analyzing the data from a large number of electrodes has a curse of dimensionality. I am planning to record using 8 or 16 or 24 EEG electrodes. Less is more! The EEG electrode placement which I need have been noted, so I just look into those specific electrode positions for my analysis, as well as, online signal processing.  

***

Tulisan ini adalah rangkuman dari posisi elektroda EEG untuk Brain-Computer Interface (BCI) berbasis SSVEP, P300,  dan "motor imagery" atau gelombang mu, untuk bulan ini.

Bremen, 23 Agustus 2014

iscab.saptocondro
Darah Juang!

Wednesday, May 28, 2014

Bandung Brain Computer Interface: Bionic Arm 2014

Previously, I have written about Bandung Brain Computer Interface (1,2,3) and the lack of research publication from Indonesia about BCI (wp, blog). Now, there are new youtube video from Ary Setijadi Prihatmanto, my former lecturer at the Electrical Engineering of Institut Teknologi Bandung (ITB). The video is about the research on bionic arm, controlled by Brain Computer Interface (BCI). The BCI Bionic Arm will be shown in the Electrical Engineering Day on June 2nd until 7th, 2014 at the Institut Teknologi Bandung (ITB).



From the video, I have found out that BCI2000 and Emotiv EPOC are used. Of course, MATLAB is also used. However, EEGLAB as a MATLAB toolbox for EEG analysis is not used. OpenVibe works only with Emotiv EPOC Research SDK. If other SDKs are used, for example Education SDK, then instead of OpenVibe, BCI2000 is the right framework to get EEG data from Emotiv.

Beside Electroencephalography (EEG), the video shows also Electromyography (EMG). Based on these signals, a bionic arm is controlled. The movement is hand opening and closing. From the video, there is an example of active motoric execution of a human participant. The subject wears Emotiv EPOC headset and move his hand actively. Emotiv EPOC sends the EEG signals via bluetooth to the computer and then a software decode these signals and transform them into commands for controlling the bionic arm.



I hope there will be other good news from Bandung BCI in the near future. Now, I am back to my real research, instead of blogging.


Bremen, 28 Mei 2014

iscab.saptocondro
Darah Juang!

Tuesday, February 11, 2014

CMS and DRL

CMS and DRL for EEG electrodes

Last week, I am trying to find out what CMS and DRL in my Emotiv EPOC are. For my experiment(s), those electrodes are used reference (REF) and ground (GND) on EEG cap. From the documents, which are found or given, CMS is used as REF and DRL is used as GND. It is unknown whether that configuration is compulsory or optional.

From Biosemi website, I got good explanation about CMS and DRL.
  • CMS is Common Mode Sense, active electrode
  • DRL is Driven Right Leg, passive electrode

They form a feedback loop for references for Analog-to-Digital Converter (ADC) of other electrodes. The schematic of CMS and DRL from Biosemi is shown below.

Explanation of CMS and DRL from Biosemi website


In my electrical engineering view, as passive electrode, DRL is suitable for ground. CMS, as active electrode, can be treated as reference on the head. Both will perform looping to get references in ADC for other electrodes. The idea is understandable for me.



My curiosity about CMS and DRL can be read on  my other blogs:


Well, I am still hoping that my research is going in the right direction.


Bremen, 11 Februari 2014

iscab.saptocondro
Darah Juang!

Friday, December 6, 2013

How seriously is Indonesia doing research on Brain-Computer Interface?

My previous blog post is about Brain-Computer Interface (BCI) research in Bandung, Indonesia (1,2,3). The research is conducted in School of Electrical Engineering and Informatics (STEI) at Institut Teknologi Bandung (ITB). I know some people who has taken part in this Bandung BCI research. However, I wonder what and how are the research outcomes.

Below is the figure of literature study of EEG-based BCI between 2007 and 2011 from Hwang, et al in 2013. The paper is "EEG-Based Brain-Computer Interfaces: A Thorough Literature Survey" in International Journal of Human-Computer Interaction, 29: 814-826 (doi), from Taylor & Francis. The authors are Han-Jeong Hwang, Soobeom Choi and Chang-Hwam Im from Hanyang University in Seoul, Korea, and Soyoung Kim from University of Rochester, New York, USA.



The figure above shows the nationalities of the authors of EEG-based BCI articles between 2007 and 2011. The articles have to be indexed by Web of Science, a database provided by Institute for Scientific Information (ISI, Thompson Scientific, Philadelphia, USA). Conference abstracts and editorials are not included. So the articles are research paper, review paper, feature, brief communication, case report, technical note and chronology.

As we can see from the figure, there are no Indonesian. So Bandung BCI group have never published their research in journals, indexed by ISI. As far as I know, the Bandung BCI group also had a collaboration with the Faculty of Medicine of Universitas Indonesia in Salemba, Jakarta, Indonesia. From some conference papers I have read, Institut Teknologi Telkom (IT Telkom) in Bandung are also doing research on EEG signals processing. But universities and also research institutes in Indonesia have not published scientific articles about EEG-based BCI in reputable journals between 2007 and 2011.



Well, I am Indonesian, currently doing research on EEG-based BCI. I just began my PhD program this September 2013 at Carl von Ossietzky Universität Oldenburg in Germany. So I have not yet published any journal papers. I hope, as an Indonesian, I play important role in international research on Brain-Computer Interface (BCI). In the next literature review, I hope there will be at least one Indonesian and that shall be me.

OK, now I should stop blogging and doing real research. :-)


Bremen, 6 Desember 2013

iscab.saptocondro
Darah Juang!

SSVEP electrode position, on my head

Since Posterous is killed by Twitter, pictures from my blog posts about standard 10-20 system are gone. The figures are not kept  by Posterous nor sent to Blogger. So I post the pictures again, which were saved by Wordpress:



I am wearing EEG cap


The pictures are about EEG electrode placement for SSVEP-BCI, according to 10-20 system (wiki: en,de). EEG is electroencephalography, which is recording of electrical signals from scalp (wiki: en,de,id). SSVEP is steady-state visually evoked potential, which is EEG signal as a response of flickering stimuli with certain frequency (wiki: en). BCI is Brain-Computer Interface (wiki: en,de).

10-20 system for EEG electrode position


The electrode position for SSVEP BCI  is Pz, PO3, PO4, O1, Oz, O2, O9 and O10. The ground is AFz and the reference is one ear lobe, either left or right. This position is used on my master thesis (book,slide).

Bremen, 6 Desember 2013

iscab.saptocondro

P.S. Now, I am thinking about EEG electrode position, for BCI, based on motor imagery.

Sunday, February 26, 2012

Ethical Questions on Brain Computer Interface, by Paul Root Wolpe

Paul Root Wolpe had a talk "It's time to questions bio-engineering" on TED.

In the talk, there are applications of Brain Computer Interface (BCI):

  • Monkey controls robotic arm with brain computer interface. The monkey sits in a room watching monitor and are put on EEG electrodes. In other room, there are robotic arm and camera. The monkey can see from the monitor what happens to robotic arm in the other room through camera. First, the monkey moves his own arm and robotic arm will make the same movement. After some repetitions, the monkey stops moving his arm and the robotic arm moves with the monkey's will.
  • Flies and other insects are put on a chip to their "brain". Then engineers can control the insects to fly with a remote control. Infact, engineers and scientist have made breakthrough with mammals: rats. Here animals are losing the autonomy of their bodies. There are ethical questions on consciousness and autonomy.
  • Eels' brain is put in gel which is put on electrodes. This bio-electronic system is put in a mobile robot as the main controller. The robot has a sensor and wheels. The robot can move toward the light although there are no programming codes to do so. A robot which is directly controlled by brain. (My notes: other researchers in different countries have successfully use rat brain tissues, see here)

Enjoy the video:

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

 

Nürnberg, 26 Februari 2012

iscab.saptocondro

 

 

Saturday, February 18, 2012

Bandung Brain Computer Interface

This is a short video of Brain Computer Interface research in Bandung, Indonesia.

The research is conducted in the School of Electrical Engineering and Informatics (STEI) in Institut Teknologi Bandung (ITB).

 

iscab.saptocondro

Saturday, December 11, 2010

Some scientific papers mentioning me and Brain-Computer Interface

I had involved in Brain-Computer Interface (BCI) research for 2 years. The research was done while studying in the University of Bremen. Now I have got M.Sc. degree in Information and Automation Engineering. After the end of my master study, there have been one master thesis, one master project report and 2 scientific papers related to BCI and me.

***

The master project report
Title: Final Preparation of the CeBit Data
author: Ignatius Sapto Condro Atmawan (That's me!)
supervisors: Prof. Dr.-Ing Axel Gräser & Dr.-Ing Ivan Volosyak
year: 2009
place: Institute für Automatissierungstechnik (IAT), Universität Bremen, Bremen, Germany
about:
The master project is mainly about EEG data format in the IAT. The BrainRobot group from the IAT conducted experiments about steady-state visual evoked potentials (SSVEP) in CeBit 2008, Hannover and RehaCare 2008, Düsseldorf, Germany. Both experiments used different data formats. The project report mentions other alternatives of data format which have already been international standards or at least european ones: GDF, EDF, BDF and BKR.

Other data format which are not mentioned in the report can be found here:

The Master Thesis
Title: Improvement of Response Time in SSVEP-based Brain-Computer Interface
author: Ignatius Sapto Condro Atmawan Bisawarna (That's me!)
supervisors: Prof. Dr.-Ing Axel Gräser, Dr.-Ing Ivan Volosyak & Thorsten Lüth, Dipl.-Ing.
year: 2010
place: Institute für Automatissierungstechnik (IAT), Universität Bremen, Bremen, Germany
This master thesis is about how to make SSVEP-based BCI in the IAT faster (but with less error). A few time series prediction algorithms are then used. There were simulation with MATLAB, programming with C++, using BCI2000 platform and doing EEG experiments with human subjects. In the end, the proposed algorithms to help IAT system detect SSVEP faster are Regression method and Kalman Filter.

***

You can send email to saptocondro@ieee.org for more information and also the pdf files of my master project report and my master thesis.


***

The scientific paper mentioning me as an author
Title: BCI Demographics: How many (and what kinds of) people can use an SSVEP BCI?
author: B. Allison, I. Volosyak, T. Lüth, D. Valbuena, I. Sugiarto, M.A. Spiegel, A. Teymourian, I.S. Condro (That's me!), A. Brindusescu, K. Stenzel, H. Cecotti & A. Gräser.
Proc. 4th International Brain-Computer Interface Workshop and Training Course.
date: September 18-21, 2008
where: Graz, Austria
pages: 333-338

The scientific paper mentioning me in the acknowledgement
Title: BCI Demographics: How many (and what kinds of) people can use an SSVEP BCI?
author: B. Allison, T. Lüth, D. Valbuena, A. Teymourian, I. Volosyak & A. Gräser
date: April 2010
volume: 18
number: 2
pages: 107-116
ISSN:1534-4320
The link to this paper can be found here.

***

I hope someday I can be an author in IEEE Transactions, especially the first author.

Wednesday, January 20, 2010

The perception of scenes with natural light

This Monday, on January 18th, 2010, I came to another neuroscience colloquium in Cognium. The talk is presented by Prof. Dr. Tom Troscianko from the Department of Experimental Psychology, University of Bristol, UK.

The title of the talk is "The perception of scenes with natural light".

The talk is about the visual perception of animals (Homo Sapiens included) as they see some scenes with natural light, in this case is sun light.

The first part of the talk is about the visual perception of primates and some birds: How primate see fruit, how about birds. Some models are shown in the slides. What happened with the monochromatic animals (you can say color blind)? Most primates are not color blind so they can see the contrast better than the birds. The first part is mainly about the perception of colors and contrast. Pictures and their histogram were shown in the talk.

The second part is about the effect of shadow. Can human perceive shadow from natural light and from manipulated image? And how fast?
The first experiment is shadow direction. There are pictures of standing cylinders and their shadow with the "light source" from above. Which shadow has wrong direction?
Then the picture is rotated upside down. Which shadow has wrong direction?
Eye movement and time are measured.
It happened that humans are faster with the light source from below. Human is not aware with the light source from above, for example sun light.

The third part is about the estethic perception. In this part, the talk is about the visual perception of sunset. Is sunset beautiful? Why do people like sunset? Can we measure the beauty of the sunset?
Google give more than 40 millions results for sunset and more than 30 millions results for sunset pictures.
There are also experiments on a ship. People gathers more on the side of a ship where they can see a sunset.
There are two conditions in sunset. When the sun is high, there is Rayleigh scattering of sunlight. The sky looks red at that time. When the sun is low, very near horizon, there is Mie Scattering of sunlight. The sky looks blue with the horizon looks red and yellow.
The experiment is conducted the eye movement.
The result shows that when the sun is high, human prefer to see the sun in the sunset, not the halo or the red sky. On the contrary, after the sun reaches the horizon, human prefer to see the halo and the sky. From this experiment, the "beauty" of the sunset can be measured.

So the whole talk is about the perception of color and contrast, shadow and the esthetic. We can know the research interest of Prof. Troscianko from here.

***

Next talk will be interesting. It will be on February 1st, 2010. It is about neuroethic. The title will be "Von der Neuroethik zur Bewusstseinsethik". Well, reading "mind" can lead to some ethical problems. I will make another blog post of the next talk.

Improvement of Response Times in SSVEP-based Brain-Computer Interface

Starting on December 10th, 2009, I have a master thesis. The thesis should be submitted on May 27th, 2010. The presentation will be conducted in June (I hope).

The title of thesis is "Improvement of Response Times in SSVEP-based Brain-Computer Interface".

The supervisors are
  • Prof. Dr.-Ing Axel Gräser
  • Dr.-Ing. Ivan Volosyak
  • Thorsten Lüth, Dipl.-Ing
The thesis is conducted in the Institute of Automation (IAT) at the University of Bremen.
The research group is no longer called BrainRobot. The name is now BRAIN, which stands for Brain-computer interfaces with Rapid Automated Interfaces for Nonexperts.
Yes, it is funded by European Union. We want to keep up with all research groups in the USA (and Canada) and in the Asia Pasific (China, Japan, Korea, etc).

Back to my thesis!
The proposed question behind the thesis is whether we can improve response times of our system in detecting SSVEP patterns from a subject. We can say that I want to make Bremen BCI system (a little bit) faster than before. I am using time-series manipulation algorithm to do so.

More details will be told in other blog posts.

Monday, December 14, 2009

A Bayesian model of Attentional Load

Last monday, 7th December 2009, I came to another talk in the Cognium building of the University of Bremen. The talk is presented by Prof. Dr. Peter Dayan, from Gatsby Computational Neuroscience Unit, Alexandra House, London. The talk title is "A Bayesian Model of Attentional Load".

I did not understand the talk much. It was about statistic, mostly Bayesian (of course). Basically, we have attention. EEG signals are then classified, based on Bayesian method. I am sorry I really couldn't get the idea of the talk.

I keep the presenter's name and the talk title in order to have a contact if I want to continue Ph.D. next year (2010).

Saturday, December 5, 2009

A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

"A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation" is the title of a paper from MIT and Harvard researcher. The paper can be downloaded from The PLoS Computational Biology. It is about brain modelling. They want to model the how our brain process visual information. The hardware used is GPU (graphical processing unit).

They publish the video which can be seen here. In the video you can see their comments about IBM cat brain. They say implicitly that IBM one do have the power of cat brain but it is not successful (yet) to model how the cat brain works. The same news from Smart Planet can be read here.

***

Finding a better way for computers to "see" from Cox Lab @ Rowland Institute on Vimeo.



***

Other interesting news recently is about Intel processor with 48 cores. Actually it is 24 dual core connected in mesh network. Beside GPU, this 48-core processor can be used also for brain modeling.

Are we closed to Singularity?

Brain, Movement, and Space-Time Perception

Last Monday, 30th November 2009, I went to a talk in Cognium again. Unlike the previous talk, I was early then. I could pick a good seat.

There were 2 presenters: Prof. Dr. David Burr and Dr. Maria C. Morrone.
Both are from Instituto di Neuroscienze del CNR, Pisa, Italien.

Maria C. Morrone presented "Time & Space in the brain for different frames of reference".
David Burr presented "Cross model sensory fusion & calibration: evidence from development, On Bishops & Babies".

***

The first presentation was from Dr. Morrone about time perception, the space perception of our surrounding and the posture of movement of our body and body part, e.g. hand or head. I am not a neurobiologist, so I could not comprehend a lot of vocabularies: retinal snap shot, retinotopic map, allocentric map, ipsilateral vs controlateral, spatiotopic vs retinotopic, craniotopic vs dermotopic and so on. There were many graphics showing correlations and areas of brain. Also the presentation was too fast and in english with italian accent. It was awful for me.

In the end, I can understand only the conclusion about the link between action and time (perception).
Time perception of human brain depends on the posture. If we change our coordinate (e.g. posture), our "internal clock" change. Time perception is highly plastic.

I remember a quote about time perception:
"Put your hand on a hot stove for a minute, and it seems like an hour. Sit with a pretty girl for an hour, and it seems like a minute. THAT's relativity." (Albert Einstein)

***

The second presentation was more interesting. Prof. Burr talked about the way we use our sense to have a space perception. Is our perception robust? How do we develop robust perception through the year?

We use haptic and visual information to explore our world. We see something to guess the size and we touch itu to have the idea of the size. Based on two sensors, our brain process information about the size of a thing. We have more senses to explore space by adding auditory information: sounds. Not only size, we also get idea of space based on our sense of orientation.

Prof. Burr showed an interesting research about the robustness of our perception.
What happens if we see something blurry but we can still touch it?
What happens if we have conflict of direction between eyes and ears?

Fusion of our sense can make better precision. Precision means that the resulting position from our visual sense and our haptic sense (and also other sense) is closed each other. We use all of our senses to get a precise space (and time) perception.

Calibration can make better accuracy. Accuracy means that our sense points close to the targeted position. Which sense calibrate other sense?

A subject should differentiate size of many boxes. Two boxes are put separately by a piece of wood. The subject only see one side of wood with one box. The other box is behind. The subject should see one box and touch the front box and the back box. Combinations of boxes are changing. The subject is supposed to tell which one is big and not.

And then, we make a blurry obstacles so our visual perception is disturbed. Is the subject still good with the task?

After the size, the subject should differentiate orientation. The boxes can be twisted. If we twist the front box, the back box also twist because both are connected. The conflict arise when those two boxes have different angle so it is not parallel. So front and back boxes have orientation conflict. What is the effect with and without blurry obstacles then?

Another experiment is to see a circular dot on screen of television. There are also two speakers: left and right. The dot can be move on screen. Sometimes it is blurry. The speaker can blip. Sometimes it blip consistently, which means if the dot on the left, the left speaker make a sound. But there is also visual and auditory conflict.

The subjects are from different ages.

What is the result?

The 5-year-old subject have problems with conflict of sense and with obstacles. And then as human grows our perception get more robust. A ten-year-old and grown-up subject has a robust perception. They can have a consistent (robust) sense of size and orientation although blurry obstacles are put or audiovisual conflict is put.

If we calibrate position to have a time-space perception, we use the most robust sense. The most robust sense calibrate the other sense.


Other question is how about blind people.

It turns out that blind subject can do well to sense size but they are bad with orientation. Prof Burr concluded that the lack of calibrating sense (vision) at early age impacts on touch.

It is hard to understand this presentation. Both presenters were really fast. One used italian accent and the other used australian accent. Pictures shows better than words and unfortunately I can only write in this blog.

***

Next monday, there is another presentation: "A Bayesian Model of Attentional Load"
Can't wait to see what it will be.

Wednesday, November 25, 2009

About IBM Cat Brain

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.

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:
  • 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).
One more interesting thing. With the same technology, to exceed human brain, the supercomputer will need between 100 MW and 1 GW. It takes a nuclear power plant for simulating only a single human brain. The real human brain takes only 20 watts.

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.

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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.

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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.

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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. :-)

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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.

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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.

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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).
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