Graphics Reference
In-Depth Information
A need to study the cognitive potential of the
brain results from the understanding of the great
capacity of human memory as compared to the
amount of information stored by a computer
(Bancroft, & Wang, 2011). A storage space on a
computer and the memory is usually measured in
bytes (binary digits as the smallest increments of
data on a computer). Some hold that with about 10
11
neurons, and several thousands synaptic connec-
tions on each neuron, the human brain's capacity
can be estimated in petabytes (10
14
bytes). Some
hold that a number of potential (not necessary
real) neural connections may be bigger than the
number of stars in the universe. With about 1.5
GB of data stored in a human genome, and ten to
one hundred cells existing in human body, about
a zettabyte (10
21
bytes) of genetic data is stored in
the cells of an average human body (Grigoryev,
2012). As a consequence, information-processing
mechanisms in computing are investigated, along
with the cognitive ability of the human brain and
intelligence. Generally, the number of neurons
does not change over the life span of an adult;
information in the brain may grow through the
creation of synaptic connections. Wang and his
colleagues developed a mathematical model to find
that the maximum capacity of human memory,
i.e., the possible number of synaptic connec-
tions among neurons in the brain is up to 10
8,432
bits (Bancroft, & Wang, 2011). According to the
authors, the amount of information the human
brain can hold, the accessibility of that informa-
tion, and speed it can be sorted to recall specific
knowledge reveal how humans are still much
better at understanding patterns than a computer.
The authors conclude that the brain be studied so
that current computers may be improved and the
future generation of cognitive computers may be
developed. Indeed, scientists work on develop-
ing cognitive computers that perceive, deduce,
and learn, as well as on establishing cognitive
computing theories and methodologies. A wide
range of applications of CI are identified such as
in the development of cognitive computers, cog-
nitive robots, cognitive agent systems, cognitive
search engines, cognitive learning systems, and
artificial brains. It is recognized in CI that infor-
mation is the third essence of the natural world
supplementing to matter and energy. Informatics
is the science of information that studies the na-
ture of information, its processing, and ways of
transformation between information, matter and
energy (Wang, 2011). Scientists create cognitive
models of different kinds (ranging from diagrams
software programs) to study specific cognitive
phenomena, processes, and approximate their
possible interactions and behavioral predictions
for selected tasks. By developing models of cog-
nitive architecture scientists examine functional
properties of the structures under study.
EARLIER INVESTIGATION ABOUT
COGNITIVE DEVELOPMENT
Models of cognitive processes developed in the
seventies and eighties derived out of the ratio-
nalistic philosophical tradition; the development
is seen as a process toward greater complexity
and differentiation. Thinking skills development
is usually analyzed in terms of the development
of higher cognitive levels described by Piaget;
intellectual processes, such as problem solving,
decision making, synthesizing, as described by
Bloom; and intellectual activities such as cognition
and memory (Guilford, 1967). In constructivist
terms, knowledge is a process of becoming “re-
sulting from a construction of reality through the
activities of the subject” (Inhelder, 1977, p. 339),
so it is construction of the cognitive schemes, cat-
egories, concepts, and structures that is important
in learning (Bettencourt, 1989).
Swiss developmental psychologists Jean Piaget
and Bärbel Inhelder (Piaget and Inhelder, 1971;
Inhelder & Piaget, 1958) wrote about structural
schema developed in the mind, to recognize and
to process visual patterns. The structural schema
are developed in the mind, to recognize and to
