Brent Meeker writes:
I find it hard to believe that something as stable as memories that last
decades is encoded in a way dependent on ionic gradients across cell
and the type, number, distribution and conformation of receptor and ion
proteins. What evidence is there for this? It seems much more likely that
long term memory would be stored as configuration of neuronal connections.
You have to keep in mind that every living organism is being continually
remodelled by cellular repair mechanisms. Jesse Mazer recently quoted an
article which cited radiolabelling studies demonstrating that the entire
brain is turned over every couple of months, and the synapses in particular
are turned over in a matter of minutes. The appearance of "permanent"
anatomical structures is an illusion due to the constant expenditure of
energy rebuilding that which is constantly falling apart. If anything,
parameters such as ionic gradients and protein conformation are more closely
regulated over time than gross anatomy. Cancer cells may forget who they
are, what their job is, what they look like and where they live, but if an
important enzyme curled up a little tighter than usual due to corruption of
intracellular homeostasis mechanisms, the cell would instantly die.
Recent theory based on the work of Eric Kandel is that long term memory is
mediated by new protein synthesis in synapses, which modulates the
responsiveness of the synapse to neurotransmitter release; that is, it isn't
just the "wiring diagram" that characterises a memory, but also the unique
properties of each individual "connection". But let's suppose, for the sake
of argument, that each distinct mental state were encoded by the simplest
possible mechanism: the "on" or "off" state of each individual neuron. This
would allow 2^10^11 possible different mental states - more than enough for
trillions of humans to live trillions of lifetimes and never repeat a
thought. In theory, it should be possible to scan a brain in vivo using some
near-future MRI analogue and determine the state of each of the 10^11
neurons, and store the information as a binary srtring on a hard disk. Once
we had this data, what would we do with it? The details of ionic gradients,
type, number and conformation of cellular proteins, anatomy and type of
synaptic connections, etc. etc. etc., would be needed for each neuron, along
with an accurate model of how they all worked and interacted, in order to
calculate the next state, and the state after that, and so on. This would be
difficult enough to do if each neuron were considered in isolation, but in
fact, there may be hundreds of synaptic connections between neurons, and the
activity of each connected neuron needs to be taken into account, along with
the activity of each of the hundreds of neurons connected to each of *those*
neurons, and so on.
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