Contents
The Brain
This system takes as it’s input, electrical stimuli from our sense organs and
generates as output what are known as “brain waves”.
Brain has been one of the most complex systems for engineers to study. It is
so because we can not characterize it under any of the properties that we
have so far seen and many others which make studying a system easier.
Brain is
1) not a linear system
2) not a stable system – stability can here be seen as property of the
system to come back to same output after deviating from it due to
small disturbance. Eg- a vertical pendulum is an unstable system.
Fig.2 Vertical Pendulum- falls to ground as soon as disturbed slightly.
A small disturbance is enough to deviate brain from equilibrium.
On the whole, brain is a very chaotic system to study. For this system, we
have seen how we can apply “signals and systems” to study some properties
of it’s
1) memory
2) response or brain waves
3) not, quite obviously, memory less.
• MEMORY
We will see, under this sub-section, an unconventional but very convincing theory about the form in which brain stores the information. But before that we will look into an important property of FOURIER TRANSFORMATION.Fourier transform of a function represents the magnitude of complex exponentials in it’s Fourier Series.
Now consider a black and white image. We can express it as brightness as a function of (x,y). Let it be B(x,y). If we lose information of B(x,y) over a range of (x,y), we will lose the image from those points also.
Fig 3. A B&W image before and after losing information in spatial domain.
Fig: The graph of the transform is
Now if we inverse transform only a part of this graph and not the complete one, we will still get whole of the image, but only suffering in its resolution. This happens because we lose information in frequency domain and not in spatial domain i.e. we will still have a function (say B’(x,y) ) on inverse transformation such that we have information of image over the entire area of original image but only varying a little from previous information.
Fig: Image after inverse transforming a part of the Fourier transform.
Coming back to brain now; there have been experiments which show that if a part of brain’s memory is lost, it can still remember something completely but suffering only in finer details. The explanation to these observations is given on the basis of above mentioned property of Fourier transforms. It has been proposed that brain actually stores information, not as it is, but in form of Fourier-like-transform distributed over a certain region of brain.
Memory can now be defined as the experience generated when brain inverse transforms the stored information back to special domain. There are many experimental evidences beyond the scope of this presentation which establish this fact more firmly.
• BRAIN WAVES
The response of brain towards the stimuli is in form of electrical signals called brain waves. These waves are actually the voltage generated across the joints between neurons. Brain waves, on the basis of the stimuli that originate them, can be classified in four classes1) Alpha waves- they originate when person is awake but in a very relaxed state. The frequency of these waves lies between 8 to 13 hz.
2) Beta waves- originate when a person is involved in some thinking process. Their frequency lies between 15 to 25 hz. These are of great significance, as these are the ones which, if analyzed finely, could reveal a great deal about the processes going in brain. And that is exactly what we need for our “thought controlled devices”.
3) Theta waves –originate when person is sleeping.
4) Delta waves –originate while deep sleep
Fig: Four types of brain waves
We now proceed to our second system “THOUGHT CONTROLLED DEVICES”.
