The whale can navigate at thousands of kilometers of open see and return to
its start point. It is also known that they seem to communicate by sounds
similar to a song.
It is believed about whales that they can use the magnetic field of the bottom
of the ocean to build a map (image model). If so, they could find their
position on this primitive map. However, if this map becomes incorrect, due to
changes of the magnetic field, they could navigate in a wrong direction,
including landing on ocean shores. Moreover, if taken back to the open see,
they will repeat the path that lead them to trouble, because their navigation
system indicates the same direction as before. Simply, the whales get lost,
and have no means to find again their position in the ocean.
We can take a risk and say that, if the information of navigation associated
with the magnetic field were recorded in a story-type model (equivalent to a
map), then the whale would know how to return to the starting point by
"rewinding the tape". Thus, it has to compare the story-type model with IR
generated by the direct interaction with external reality.
If this is the method, a transfer of this itinerary model from a whale could
be possible to another, which did not make this trip yet, through that "song".
Seems fascinating, but also it is possible to check by experiment.
ETA 25: Very complicated operations on image models (walk, jumps, climbing
trees) of humans
We will apply the theory to see the exact way of walking, jumping and tree
climbing at humans. In accordance to MDT, an action on the external reality
(e.g. walking) implies the existence of a long-range action model (ZAM). This
model generates the approximate plan of the action. ZAM will build and
activate a number of local models (ZAM and AZM) to reach its goals.
A local ZAM will simulate the movement of the leg for the first step. If the
simulated step is successful, then ZAM will activate the action on the
external reality. The leg will move in the same way as the leg 'moved' during
the simulation. It is not possible to do any movement, if it had not been
successfully simulated before.
Let's see the case of jumping. In front of an obstacle, which has to be jumped
over, the brain will 'execute' a simulated jump. If the simulated jump
succeeds, it can be done in the external reality as well, activating the
model, which did the simulated successful jump. If the simulation does not
succeed, there will be no model to activate the muscles of the body, and the
being will be blocked to act. Any attempt to go against the internal decisison
will fail.
The conclusion from the previous analysis is that a more or less elaborate
simulation precedes any action on the external reality. The result is that an
extremely complicated activity, like e.g. walking, is executed with remarkable
precision and elegance.
At first sight, walking seems to be a relatively simple activity. At a closer
analysis, one can see extreme complexity. The first problem is keeping the
equilibrium during walking. The stability of humans and animals during walking
is a dynamical stability. This means that, if we "froze" the body in an
intermediate position, the body would not be stable and would fall. During
walking, the models anticipate the movements of the body through simulation
and send suitable commands in advance. If there was no anticipation of the
evolution and we counted only on the stability and position sensors, the
information would get delayed to the device taking the decision and such, the
system would have a reduced stability. This is how all the electronic
stabilizer systems work: they wait for something to happen to make a
correction.
In the case of the brain, the information from the stability and position
sensors is used to anticipate the possible future problems and act before the
problem arised. This is the dynamical stability and, I think, this problem
cannot be solved in real time by any existing computer due to the low power of
the present computers.
From here we can see the huge capacity of information processing of any brain,
starting with mammals. The most primitive mammals, with brains of a few grams
or tens of grams, are able of higher performance than humans, in running and
jumping.
We should think of the fact that, for walking, a correlation of hundreds or
thousands of musculars fibers is needed. Dynamically, i.e. depending on the
specifics of any individual movement, on the previous behaviour, on the
anticipated behaviour, on the goal to be attained and on the various external
perturbations, all these fibres will be activated/deactivated in a precise
order, each with the suitable intensity to solve the given problem. At any
moment the problems which could appear are anticipated and the corrections are
made, before the problems occur. The number of models (which are built or
activated), associated with this type of activity, can be tens or hundreds in
a second.