Brent Meeker writes:

I find it hard to believe that something as stable as memories that last for decades is encoded in a way dependent on ionic gradients across cell membranes and the type, number, distribution and conformation of receptor and ion channel
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.

--Stathis Papaioannou

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