Sensory
neurons belonging to early sensory cortex in the back of the brain are responsible
for creating mental imagery but only hold information for very brief periods.
They stop firing rather quickly after being stimulated and thus quickly lose
the many detailed relationships that they have the capacity to hold. Only some
of these relationships between lower-order features of the environment are
preserved and only because they are shuttled up to association neurons (like
those in the PFC) in the front of the brain where neurons can fire for
sustained periods. These association neurons can then send this information
back to earlier sensory cortex allowing them to rerepresent what they have
forgotten. This is done constantly during the thinking process. However, what
the sensory areas are directed to rerepresent is rarely identical to what they
represented earlier. This is because association areas don’t just hand back the
same information organized in the same way. Association areas actually hold
information from multiple, successive instances of sensory imagery, recombine
the elements that they think are important and then ask sensory areas to build
an unique image using the new set of elements. This process allows conscious
thought, but only really evolved in mammals because it is capable of making
mistakes, unless it has the luxury of a good amount of early trial and error.
Mammals, and especially humans, with their protracted childhoods and doting
mothers, have this opportunity. Thus mammals are capable of carefully
programming their association cortices to understand relationship that are
spread apart in time, whereas other animals (from reptiles to invertebrates)
really only have a chance to program their sensory cortices to understand
relationships between stimuli that present at the same time. This allows lower-order sensory areas to build imagery
that combines features that have never been actually witnessed before, and to
simultaneously represent subjects that are always removed in time, within the
same image.
Sensory
neurons generally hold veridical information, true relationships between
lower-order features in the environment. In other words, they are less susceptible
to certain kinds of mistakes. They might combine simultaneously presented
features in the wrong way, and thus misrepresent what they are perceiving, and
they do this from time to time resulting in illusions or hallucinations. They
are much less likely than higher-order areas though, to make faulty
generalizations across time. In other words, their activity alone could not be
responsible for a delusion. Lower order sensory areas hold snapshots of
environmental imagery and because these neurons do not fire for very long they
can usually safely infer that they are representing existing relationships
between coocurring features. When you look down and see a glass of milk spilled
across the floor your early sensory areas safely know exactly what they are
looking at. There is no ambiguity. When you notice that your glass of milk has
been moved to the sink and you see wet towels in the trash, you can only infer
that your milk was spilled and cleaned up. This kind of inference requires the
persistent firing seen in association area neurons that are capable of bridging
across multiple early sensory images. How is this inference generated? The PFC unconsciously
picks representations that have proven to be reinforced in similar scenarios in
the past. Neurons in association and sensory areas do something very similar.
They are experts at determining which of their neurons should be converged on
by their inputs. In other words, when we find ourselves thrust into a new and
unexpected situation, association areas, taking in to consideration all of
their inputs (as well as their current activity) choose for us what aspect
should be taken through time. This is based on prior probability and is
intended to arm us with the microrepresentations necessary for us to act
adeptly in our current scenario.
Association
neurons are apprised of sensory information but because they fire for longer
periods, they generate inferences based on multiple appraisals that have
arrived at different times. In some ways these time-delayed inferences are more
tenuous, but on the other hand they allow complex and abstract thought. Association
neurons create subjective inferences about relationships between objective
topics. Because they fire for extended periods, they have the capacity to
misrepresent the environment in misleading ways. For instance, we could infer
that the milk cleaned up itself or that the milk and the paper towels fell
directly into the trash. We don’t make these kinds of absurd inferences though,
because we have sufficient early experiences to have a sense for how improbable
such occurrences would be. Our previous experiences, and common sense gained in
our childhood keeps us from activating the neurons that would be responsible
for these kinds of inferences. Sensory areas make records saying, I know that
the sequence of scenes that I just saw are possible in my world but I don’t
know how or why they might be related to each other. The association areas, on
the other hand, are actively trying to make sense of these scenes by perpetuating
the salient features, across many scenes, in the mind’s eye. They do this
hoping that the features that they selected as salient will converge on the
sensory circuits that will result in imagery that represent the proper
inference. It is surprising how well this works for us in today’s world
especially considering that this process was engineered to help humans make
inferences about hunting and gathering.
Read an article that I published on this issue here:
http://www.sciencedirect.com/science/article/pii/S0031938416308289
Read an article that I published on this issue here:
http://www.sciencedirect.com/science/article/pii/S0031938416308289
If you found this
interesting, please visit aithought.com. The site delves into my model of
working memory and its application to AI, illustrating how human thought
patterns can be emulated to achieve machine consciousness and
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neuroscience can unlock the future of intelligent machines.
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