When the idea of studying learning began to grow in my head I was sure it
would be an easy task, the library had at least 100 aisles dedicated to
different strategies, models, explanations, theories about how it should be
taught. Education, teaching, or learning problems were kind of synonyms of
learning.
After reading all the books, magazines were a good source of inspiration,
but only created more notes into pages of my notebooks which ended quickly and
I finally decided to look in the brain, it was the logical step, because it’s where
learning is scanned, processed and stored.
I believed it was going to be
easy to find answers in this lump that all of us carry all on our shoulders, and it seemed an
easy journey, after all, how much can
fit in an average area of 1130 cm3?.
My trip was from structures with their latin names to the connectome, which is a map of the neural
connections, and seeks to describe the brain structure, as well as the genome
is more than just a juxtaposition of genes, the set of neural connections is
much more than the sum of its individual components (Biswal, Mennes, Zuo,
Gohel, Kelly Smith; Beckmann, Adelstein, Buckner, Colcombe et al., 2010).
Connections
A great expert in this topic, Sebastian Seung (2012) explains that the connectome contains millions of times
more connections than the letters of the genome, and each one will be building
specific connections, all those networks is the personal connectome, which is created on 4 principles: reweighting
this means changes in the strength of the synapses; reconnection is
the creation and elimination of synapses; rewiring that is the
creation and elimination of neuronal branches and regeneration which
is creation and elimination of neurons.
If neurons were all, it seemed logic that understanding learning should not
take me more than 10 years, but as Dehaene (2011) figured out, brain represents the reply of the slow
evolution of species governed by the principle of the same natural selection
that has been perfected over the years allowing the brain to optimize the way
in which processes the huge flow of sensory information received to adapt the
reactions of the body to a competitive and hostile environment.
If the key of learning is exclusively in the brain, then the idea of
learning adapting to the environment was valid and I mistakenly arrived to
propose that learning allowed this adaptation, I cannot deny the error because
I published in different articles. I changed my mind when a biologist made me
remember that other species adapt, including proteins as I explained in another
entry on this blog (Dzib Goodin, 2012). Prions took away my sleep for a while.
So it was time to seek the evolutionary mechanisms. Finally we are the sum
of the processes of changes and adaptations.
Years of change
Someone kindly suggested me to explore the
Baldwin effect, also known as
ontogenetic evolution which is a theory of the likely evolution process of
learning, which was published for the first time in 1896. The theory proposes a
mechanism for learning ability in general, based on the idea of selected
descendants of a group can have greater capacity to learn new skills rather
than simply the abilities granted by the genetic code which is relatively
rigid.
The idea sounds very logical but theory has been controversial from the modern
evolutionary synthesis, and it has not been easy to prove the occurrence of the
phenomenon. Personally I'm going to start documenting my summer battles between
weeds, slugs, and snails to keep my gardens healthy.
The main limitation of the Baldwin effect from Hinton and Nowlan point of
view (1984) is the fact this idea is only effective
in spaces that would be difficult to find, very specific species to which it is
possible to continue without an adaptive process of restructuring from the
space. But for those biologists, who say that wilderness areas are well
structured, the Baldwin effect is an important mechanism to allow adaptive
processes within the body to greatly improve the space in which a species
evolves.
This theory led me to find something else, and I returned to an old topic, Can
you believe the evolution of brain processes has been best explained by
theorists of artificial intelligence?.
Some researchers has the assumption that brain can adapt and learn from
past experience, because the specific evolution is not only inherited behavior
but adds inherited goals that are used to guide the learning
under the orders of a genetic code that has two components in the species. The
first component is a set of initial values to create a network of action which
maps the sensory input to behavior, this is presented as a set of innate behaviors
that are inherited from the parents (Stefano, Elman, and Parisi, 1994).
The example that comes to my mind is a newborn baby, who is beginning to
recognize the environment, his initial reactions are sensory, as Piaget recognized
from the last century. Some of these reactions begin to distinguish between the
species, for example, reflexes are becoming more sophisticated, and some babies
show signs of maturity, while others follow a different pattern of development.
The second component is a network
of evaluation, this focused
action on the sensory input to a value scale that help to move from a bad to a
good situation by changing its weight in the action of the network during the
process and that the individuals maintain as learning goals (Stefano and Parisi
1994).
There is no a bigger pleasure than observing a baby who is in a dilemma. If
he manages to control the motor actions and builds the network between look at
an object and take it, how does he react when despite the same movements, but
the object doesn’t move?. His first reaction is: hey, come to me, I am taking
you!. Other babies will try it more than 5 times, while some observe the
problem, and maybe one or two will try to solve the problem crying, explaining
to the toy that mom will know soon about his rebelliousness and nobody plays
with mom.
In this sense, it can be said that the evolution of neural networks
contains information not only in genetic terms, but also a collection of
behaviors developed by the ancestors and this can be understood as a culture
(Dehaene, 2012, Conrad, 2004).
It is then that culture has a major role since the adaptations in the
environment are not always determined by closed codes and therefore not can
become stronger than those established by the selection (including the changes
in the social environment). The best example of this is the language, since
previously the specie was not dependent on the speech, until it begin to evolve
the language skills, is so development processes that had not participated
previously in the language can be selected object because of its effects on the
acquisition of the language, resulting in the modification of older adaptations
(Barret, 2012).
However, culture is not absorbed in the whole brain how explains Stanislas
Dehaene (2004) in his theory of neuronal recycling, he says that cultural
purchases can take place in a limited surface area bounded by the cerebral
cortex. As an example, the author analyzes reading and arithmetic that have
greater reproducibility in the neo cortex.
This idea has been explored in more than one research, for example in an
article published by Conrad (2004) it presents a theory about the formation of
the central nervous system based on the processing of information from the
description of the molecular biological systems. He explains that the central
nervous system consists of several types of unitary regions, of which there are
many interchangeable replications.
Each region contains neurons whose power is determined by the enzymes that
recognize the specific input patterns to that region specify by genes inherited
or cultivated. Finally, the central nervous system has selection circuitry that
put test and evaluation of different regions, determining control of the
production of genes on the basis of such an assessment.
At the same time, there are genes whose production is stimulated in a
diffuse way in regions in which occur to transform other relevant regions of
the same type. In this sense, the function of the molecules is the same in
these new regions because the structure of the tissue and cell properties is
the same.
This makes possible a process of trial and error to learn mediated by the
same mechanisms as the natural evolution, except that it is more efficient
because the circuits of selection. Systems that operate on the previous basis
are capable of performing any executable as a conventional computer, but with
significant restrictions on the programming. Thus, these systems are also
(structurally) simpler than more susceptible to learning and evolution and
conventional information processing devices (Conrad, 2004; Changeux and Dehaene, 2000).
It seems during the evolution of the brain the properties
of its tissues development are subject to evolutionary change from the effects
on the phenotypes of the brain. This can be initiated by the changes in systems
development (for example, through mutation), changes in the environment in
which they develop (culture, environment), or both (Barret, 2012).
An idea of how happens this is
provided by Fernando, Szathmary, and Husbands (2012) who claims that
Darwinian evolution can happen in the brain during, for example complex
thought, or the development of language in children, though nothing further
than the level of the synapse is subject to Darwinian evolution in the brain.
Which confirms the affirmation of Seung: we are our connectome.
Evolutionarily, the advantage of
having algorithms of replication occurring by natural selectionis not
observable to the naked eye, compared to the instrumental learning models
(Fernando and Szathmary 2010). In
fact, the notion of the dynamics of replication in the brain remains
controversial and the creation of neural networks is a cost process that depends
on technological development, example of this is the Blue Brain Project.
Artificial neural networks
Thus, the technological advances to make possible the creation of
neural networks that tries to simulate the biological capacity to adapt and
learn from past experience that has the brain.
However, even for experts in
neural networks, the task of explaining the learning mechanisms have not been
easy, because as explain Iriki and Taoka, (2012) brain evolution has three
essential components, one developed by multisensory integration (sight, hearing, smelling, feeling) and
transformation of coordinates for the control of movements in the living space
is an essential function of the nervous system (what is known as ecological
niche). But this neural enhancement is not an isolated event, since it allowed
the brain to move processing to the summary of information, through the
implementation and reuse of the existing principles of information processing
space that adapted to the subjection of mental functions and which ultimately
led to the development of the language with which it was possible to
communicate locations or spaces (which resulted in a cognitive niche). This was
also useful handling of the image of the body in space, which became essential
for the handling of tools, giving as a result the acceleration of interactive
links between cognitive, neural bases cognitive and gave way to the third niche
which is building.
Just in case here sounded a simple explanation, complex that a baby may
formulate coordinated words, you must know how to use the tongue, move it in a
coordinated manner, and learn to control the air, when it manages to dominate
the difference between a sound and reaching a word to take the
race to perfect this ability. I personally really enjoy these attempts, babies
range from simple ma, pa, aba sounds to words: mom, wad, water. Once they have
established that, begin to use the tools and parents are scared when they see
the child with the Ipad or the cell phone in their possession, nothing more fun
to do than using a pencil, or a touch screen. When parents learn to relax, and
children send their first text message, or read their first book, tools have sense.
Hence to describe the world.
This explains that a modified human environment exerts pressure on future
generations to adapt to it, perhaps through the acquisition of new resources
that have to adapt to the different organs, with which is possible to explain
plasticity induced epigenetically (this term refers to the study of non-genetic
factors involved in the development of an organism), including the development
of mechanisms of learning involved in such processes. In this way, the
additional genomic information can be transmitted between generations through
mutual interactions between neuronal, ecological niches and cognitive domains.
This scenario locates the brain as part of a comprehensive ecosystem in
evolution (Iriki and Taoka, 2012).
It is so arises the neuroevolucion as a field of study, which seeks the
creation of artificial neural networks (ANN) through evolutionary algorithms,
and sometimes has focused its efforts on static neural networks that cannot
change its function during lifetime, since these are the easiest to replicate
(Miikkulainen, Feasly, Hohnson, Karpov, Rajagopalan, Rawal and Tansey, 2012;
Gauci and Stanley, 2010).
However, a serious problem with the evolution of adaptive systems is that
learning to learn is very misleading, as describe Risi, Hughes and Stanley
(2010), because a principle is easier to improve physical condition without the
ability to learn, evolve by that is not based on the heuristic adaptation. This
is learning a stiff task with no greater decision making, which is a model away
from reality.
In their study, the authors find as a conclusion that novelty search has
the potential to foster the emergence of adaptive behavior in reward based
learning tasks, which opens up a new direction for research in the evolution of
neural networks of plastic, which makes it more interesting and easy to learn adaptive
behaviors that had been difficult to observe in human models.
But is Henry Markram, who has a good idea about this, he says brain has led
billions of years evolve and has many rules, so the challenge of the
neuroevolucion is to describe them carefully using mathematical laws and if it
is possible to achieve that, the challenge will then be to build a realistic
model of the brain (Kushner, 2012).
Brain and school
Although it sounds like a foolish, learning process has a long way,
developing its own rules and the school as an institution should not ignore,
but does it. The result is not only unhappily educated children, but jobless
adults. But, there is no perfect educational system, even the brain has
established laws, it modifies them generation after generation, trying to find
a biological balance.
Of course, it’s possible to expect a programming expert to design an
application that connects through an interface with a single click, so we could
learn anything, even those for which we are not physically fit, as in the The
Matrix movie, but while that happens, it is worth putting the brain in the
classroom and understands its mechanisms.
It is not my idea that teachers know neuroscience, that is not the goal,
but at least I would like to explain to teachers when they see a child with learning problems they
can see him as a problem of education, since the brain has adapted and survived on the face
of the Earth much more better than any curriculum has done so.
Part of that evolution implies as studies indicate, the brain changes all
the time, and in this sense, if a child is not capable of running a task today,
far from tag it, should think that under the correct strategies, he or she will
do it, with their own pace, accuracy and specificity, different than others,
after all, there is nothing more impressive being unique different and special.
The success of the brain is such
that it has been able to look to infinity and beyond, the Moon was not its
limit, right now is exploring Mars, has done its utmost, has grown, invented,
fantasized and made possible what was thought impossible, in a 1130 cm3
average space., imagine now that they will be able to make many with
a common goal: an effective teaching
If you would like to know more about my writing, you can visit my web
site,
http://www.almadzib.com/
http://www.almadzib.com/
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