IUBio

Brain-Computer Interface, long

Andrew Wright 93asw at williams.edu
Sun Dec 6 21:27:26 EST 1992


On Designing a Brain-Computer Interface:
After all, computers were once science fiction, too.

Andrew Wright
NSCI 401
Williams College
11/20/92
93asw at williams.edu
awright at mindvox.com

Note1: This paper is copyright 1992.  I am making this paper available
becuase of a large interest in the topic among people on the net.  Since
this is an academic paper, I am making the assumption that people out there
will be ethical enough not to pass this work off as their own.  To that
end, feel free to disseminate this and use it in your own research, but
please make sure to cite your source.  Thanks - Andrew.

Note2: This is a loosely edited version of this paper, with much of the
technical detail left out.  A full version is available on request.  I
would also be willing to place it on a site allowing anonymous ftp, if
anyone knows of an appropriate site.

	A Brain-Computer interface is a staple of science fiction writing.  In
itUs earliest incarnations no mechanism was thought necessary, as the
technology seemed so far fetched that no explanation was likely.  As more
became known about the brain however, the possibility has become more real
and the science fiction more technically sophisticated.  Recently, the
cyberpunk movement has adopted the idea of Rjacking inS, sliding RbiosoftS
chips into slots implanted in the skull (Gibson, W. 1984).  Although such
biosofts are still science fiction, there have been several recent steps
toward interfacing the brain and computers.  Chief among these are
techniques for stimulating and recording from areas of the brain with
permanently implanted electrodes and using conscious control of EEG to
control computers.  Some preliminary work is being done on synapsing
neurons on silicon transformers and on growing neurons into neural networks
on top of computer chips.
	The most advanced work in designing a brain-computer interface has stemmed
from the evolution of traditional electrodes.  There are essentially two
main problems, stimulating the brain (input) and recording from the brain
(output).  Traditionally, both input and output were handled by electrodes
pulled from metal wires and glass tubing. [] (Pickard 1979). Using
conventional electrodes, multi-unit recordings can be constructed from
mutlibarrelled pipettes.  In addition to being fragile and bulky, the
electrodes in these arrays are often too far apart, as most fine neural
processes are only .1 to 2 5m apart. [] It is difficult to permanently
implant such arrays, and consequently it is difficult to directly study the
brain as a function of animal behavior. []
	Pickard describes a new type of electrode, which circumvents many of the
problems listed above.  These printed circuit micro-electrodes (PCMs) are
manufactured in the same manner of computer chips.  A design of a chip is
photoreduced to produce an image on a photosensitive glass plate.  [] This
is used as a mask, which covers a UV sensitive glass or plastic film. A PCM
has three essential elements: 1) the tissue terminals, 2) a circuit board
controlling or reading from the terminals and 3) a Input/Output
controller-interpreter,  such as a computer.  The circuit board and
computer are often located outside the skull, to minimize tissue invasion,
allow for long-term implantation and permit the electrodes to be detached
between trials (Kuperstein and Eichenbaum 1985). []
	In addition to the ability to make multiple, closely spaced recordings,
P[CMs] often outperform the traditional electrodes in a number of
electronic measures (Kuperstein and Eichenbaum 1985). A further advantage
of PRONG [a type of PCM] was it's continued functioning after as many as
four days implantation. [] PRONG was able to simultaneously make 10-11
recordings from one side of the electrode.
	While it is tempting to see in PRONG the potential for permanently
implanted brain recording and stimulating devices in the manner of
cyberpunk fiction, more mundane if equally exciting applications of similar
technology are being found now.  A six channel PCM is being commercially
produced for use as an implant in patients who have lost hearing but not
functioning of the auditory nerve (Ineraid Multichannel Cochlear Implant). 
[] This device allows for hearing and speech recognition, although there
are limits to the amount of information that can be extracted.  In
two-syllable recognition tests, scores range from 0 to 100%, with the
median being 44% (Dorman et al. 1991).  
	Interestingly, these limits may not be inherent in the cochlear device,
but in the encoding algorithm.  Wilson et al. (1991) have designed a new
technique, CIS, which is presumably based on improved Digital Signal
Processing (DSP) capabilities. []  The increase in comprehension engendered
by this technique overwhelmed the sensitivity of the tests.  In some cases,
the subjects were well within the range of mild to moderate hearing loss. 
[]
	Another possible use for PCMs is controlling robotic prosthetics.  A
special type of tissue terminal, an enclosure terminal, has holes in or
across conductors through which developing or regenerating neurons can
grow(Pickard 1979).  These are especially suitable to chronic preparation,
and could be implanted in the PNS where nerve regeneration is possible. 
The chip could then interpret motor neuron signals for use controlling
prostheses.[] [PCMs] may even be useful in administering micro-doses of
ionotophoretic drugs (Pickard 1979).  
	A fundamentally different approach to interpreting output from the brain
is the use of EEGs.  According to Wolpaw et al. (1991), "in theory [the]
brain's intentions should be discernible in the spontaneous EEG."  However,
the vast number of neurons and the complex structure of the brain make such
interpretation difficult if not impossible.  Therefore, efforts have
focused on training people to produce desired EEGs through biofeedback
mechanisms.  [] An immediate use for such a system can be seen in providing
a mechanism for communication between paralyzed patients and the outside
world through the computer.
	The possibilities of interpreting EEG data and using it to control
computers have been brought to the consumer electronics front by the IBVA,
or Interactive Video Brainwave Analyzer (Nathan 1992).  A headband with
four adhesive electrodes sends data through a radio transmitter to a port
on a Macintosh personal computer.  The EEG is the filtered and run through
a fast fourier transform before being displayed as a three dimensional
graphic.  The data can then be piped into MIDI compatible music programs. 
Furthermore, MIDI can be adjusted to control other external processes, such
as robotics.  The level of control provided by IBVA is limited at best and
the software does not actually interpret the brain's impulses.  Instead,
the user must program the software to interpret consciously determined
gross changes in the EEG.
 	The interface between the brain and computers, either through
interpreting EEGs or through recording directly through PCMs is currently
limited by computing strength.  Conventional computers are well suited to
processing linear data, but only have limited application to more
distributed processes such as pattern recognition.  In order to address
these problems, neural net computers are modeled after the brain's complex
system of weighted synapses.  The strength of these neural nets can be
considered a function of the number of connections made between functional
units.  Computers are hampered by the limited number of connections imposed
by the constraints of processing time and memory space.  
	To circumvent this, Masuo Aizawa is working on growing neurons into neural
net computers (Freedman 1992).  A neuron is capable of p


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