Event Related Potential , Signal processing & Analysis discussion Forum

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Event Related Potential , Signal processing & Analysis discussion Forum

A group of scientists ranging from mathematicians,physicists,computer scientists,neurologist,neurosurgeons,psychologists,electrical and electronic engineers,signal processors and analyses specialists who are interested researchers in this field

Website: http://www.medic.usm.my/~neurosciences/laboratory.php
Location: MEG and ERP Neuroscience Lab,Hospital Universiti Sains Malasyia
Members: 33
Latest Activity: Mar 14

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Nature latest publication and how it may effect our thinking of Visual ERP

http://www.nature.com/nature/journal/v473/n7345/full/nature09880.html is one paper which now has tickled my brain…Continue

Tags: Nature, ERP

Started by Professor Jafri Malin Abdullah May 27, 2011.

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Comment by Professor Jafri Malin Abdullah on December 21, 2010 at 6:48am

Do extraverts process social stimuli differently
from introverts?

http://lcn.salk.edu/publications/2009%202010/Fishman%20-%20Extraver...

Comment by Aamir Saeed Malik on December 11, 2010 at 11:52pm

The message bounced back.

Can you send me some other email address? Thanks.

Aamir

Comment by Aamir Saeed Malik on December 11, 2010 at 11:44pm

Our concerned department has sent me an email asking some questions. I will appreciate if you can provide us the related information. I am sending you an email at your email address brainscience@gmail.com.

Aamir

Comment by Professor Jafri Malin Abdullah on December 11, 2010 at 6:36pm

I would like to confirm the August participation for the summer school and that Pedro Valdes will be there,Also we are waiting for the Research Agreement MOU between USM and UTP sent last week to your PRO,any news?

Comment by Professor Jafri Malin Abdullah on December 3, 2010 at 8:57pm
Liley's model consists of 14 first order nonlinear ODE with 29 physiological and anatomical parameters, some of which may take values from continuous ranges of possible values Is this correct and humanistics?
Ref:Bojak I, Liley DT: Modeling the effects of anesthesia on the electroencephalogram.
Phys Rev E Stat Nonlin Soft Matter Phys 2005 , 71(4 Pt 1):041902.
Comment by Professor Jafri Malin Abdullah on December 3, 2010 at 8:45pm
It is a magnificent feeling to recognize the unity of complex phenomena which appear to be things quite apart from the direct visible truth.

Albert Einstein
Comment by Professor Jafri Malin Abdullah on December 3, 2010 at 8:43pm
Is brain deterministic or stochastic?

A2. Human brain may neither act as a fully deterministic system because it would not be able to invent anything new, nor may it act as a fully stochastic system because it would not be able to learn and exactly repeat any sequence of thoughts. The answer to this dilemma lies in nonlinear dynamics and deterministic chaos – human brain is a complex nonlinear system showing complicated emergent properties, including consciousness. It is much more appropriate to use nonlinear methods for analysis of signals generated by such a complex nonlinear system, despite the fact that for short time intervals linear methods like FFT may work o.k. Nonlinear methods may be applied to linear signals – one might try to approximate straight line using parabolic function only to find that coefficient of the quadratic term was practically equal zero. It is the opposite that obviously fails – if one uses linear approximation then one will never be able to appropriately approximate a nonlinear function on a sufficiently long interval, but on a short interval linear predictability may work o.k. It is unbelievable but in the XXI century some scientists still maintain they have demonstrated by using methods like linear forecasting or surrogate data tests of EEG time series that EEG is linear signal as if the human brain is a linear system. Although linear systems may have a small range of applicability, it is inappropriate to use a linear system to deal with the highly nonlinear complexity of the brain. Perfect linear system is a kind of abstraction like an ideal gas.frm:Everything you wanted to ask about EEG but were afraid to get the right answer

Wlodzimierz Klonowski,
Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
Nonlinear Biomedical Physics 2009, 3:2doi:10.1186/1753-4631-3-2
Comment by Nidal Kamel on November 21, 2010 at 10:37pm
From fundamental point of view, we agreed on the stochastic nature of brain signals. This definitely applies to the related signals to epilepsy or Alzheimer or schizophrenia. These signals are stochastic in terms of their amplitude variation with time (amplitude-time) but in terms of their envelop variation with time (envelop-time) the signal could exhibit less randomness and could be close to Non stochastic. In this case the classical pattern recognition techniques can be used to indicate the occurrence of the seizures.
Comment by Professor Jafri Malin Abdullah on November 19, 2010 at 5:42pm
Do you agree that in diseased states the Non stochastic mechanisms take place like in epilepsy or Alzheimer or schizophrenia.
Comment by Nidal Kamel on November 18, 2010 at 8:15pm
Yes Prof. analyzing ERP is different from analyzing (deterministic) structures like the cerebellar surface. In the case of cerebellar surface the process (surface) is well-defined and can be accurately modeled. Contrary to that, the ERP is generated as a contribution of millions of neurons generating signals random in nature (underlying stochastic mechanism). This contribution will definitely create an overall signal (ERP) with unpredictable features. Thus, we can't find deterministic mathematical model describing it. In fact, the sought model should accommodate the random nature and include some random parameters. This form of signal modeling is called stochastic. If you need reference on this topic I can send some (E-book).
 

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