Temporal Windowing in Neurons
According to Wikipedia, https://en.wikipedia.org/wiki/Neuron
Neurons are electrically excitable, due to maintenance of voltage gradients across their membranes. If the voltage changes by a large enough amount over a short interval, the neuron generates an all-or-nothing electrochemical pulse called an action potential.
But what, I wonder, is the mechanism by which a neuron imposes a time window on recognizing the threshold change in voltage? I haven’t found anything about this online, and it seems that the particular mechanism employed could have an important effect on how the neuron functions.
Neurons receive both excitory and inhibitory input voltages, and it seems that the neuron sums these positive and negative voltages to test whether the threshold voltage has been reached. It’s puzzling to me, though, what mechanism the neuron might use to limit the timeframe in which it will recognize a change in the sum of its input voltages that would trigger its action potential.
One possibility is that there could be a “timer” mechanism that simply “flushes” the accumulated potential when the time period expires. But in that case, the response of the neuron to its input stream could vary in an arbitrary manner depending on where the timer boundary happened to fall in relation to the input stream.
Another possibility is that there could be a “moving window”. The cell would keep track of the value of each input and the time it arrived. As inputs become “stale”, they would be dropped from the “queue” and the accumulated potential recalculated using only more recent inputs. This is how a computer programmer might code such a process. But how would it keep track of when the inputs arrived? Perhaps the voltage from a particular input simple “bleeds off” over time, so that the contribution of that input to the accumulated voltage diminishes at a constant, or perhaps inconstant, rate. Earlier inputs would gradually bleed off and contribute less and less to the accumulated voltage. It’s also possible that each input has a timer mechanism which flushes that input precipitously at the expiration of the time period.
Besides the question of what mechanism is involved, there is the question of what is the length of the time period. It could be the same for all cells, or vary for different cells, or for different inputs, or for different voltages, or depending on other circumstances?
It wouldn’t surprise me to find that little or nothing is known about this timing mechanism. It must be very difficult to know anything about how neurons work and it’s remarkable to me that we know much of anything about them at all.
There is a project, Open Worm, to build a computer model of an entire organism, C. Elegans, also called nematodes or roundworms. This worm has only 320 neurons and the entire neuronal network has been mapped. The platform serves as a test bed for simulation experiments. By comparing the behavior of the simulation with the behavior of actual worms, it’s possible to test ideas about how the worm’s nervous system works. One possible use of the simulation could be to try different approaches to the problem of how the neuronic temporal window works and what the temporal values might be.
Of course, it could also turn out that the detailed functioning of the temporal window in neurons is not important to understanding how neurons function, but I suspect that it is. Nature seems to take advantage of every possible trick that will provide even the slightest benefit to the organism. It would be nice if things were simpler but usually they’re not.
Neurons are electrically excitable, due to maintenance of voltage gradients across their membranes. If the voltage changes by a large enough amount over a short interval, the neuron generates an all-or-nothing electrochemical pulse called an action potential.
But what, I wonder, is the mechanism by which a neuron imposes a time window on recognizing the threshold change in voltage? I haven’t found anything about this online, and it seems that the particular mechanism employed could have an important effect on how the neuron functions.
Neurons receive both excitory and inhibitory input voltages, and it seems that the neuron sums these positive and negative voltages to test whether the threshold voltage has been reached. It’s puzzling to me, though, what mechanism the neuron might use to limit the timeframe in which it will recognize a change in the sum of its input voltages that would trigger its action potential.
One possibility is that there could be a “timer” mechanism that simply “flushes” the accumulated potential when the time period expires. But in that case, the response of the neuron to its input stream could vary in an arbitrary manner depending on where the timer boundary happened to fall in relation to the input stream.
Another possibility is that there could be a “moving window”. The cell would keep track of the value of each input and the time it arrived. As inputs become “stale”, they would be dropped from the “queue” and the accumulated potential recalculated using only more recent inputs. This is how a computer programmer might code such a process. But how would it keep track of when the inputs arrived? Perhaps the voltage from a particular input simple “bleeds off” over time, so that the contribution of that input to the accumulated voltage diminishes at a constant, or perhaps inconstant, rate. Earlier inputs would gradually bleed off and contribute less and less to the accumulated voltage. It’s also possible that each input has a timer mechanism which flushes that input precipitously at the expiration of the time period.
Besides the question of what mechanism is involved, there is the question of what is the length of the time period. It could be the same for all cells, or vary for different cells, or for different inputs, or for different voltages, or depending on other circumstances?
It wouldn’t surprise me to find that little or nothing is known about this timing mechanism. It must be very difficult to know anything about how neurons work and it’s remarkable to me that we know much of anything about them at all.
There is a project, Open Worm, to build a computer model of an entire organism, C. Elegans, also called nematodes or roundworms. This worm has only 320 neurons and the entire neuronal network has been mapped. The platform serves as a test bed for simulation experiments. By comparing the behavior of the simulation with the behavior of actual worms, it’s possible to test ideas about how the worm’s nervous system works. One possible use of the simulation could be to try different approaches to the problem of how the neuronic temporal window works and what the temporal values might be.
Of course, it could also turn out that the detailed functioning of the temporal window in neurons is not important to understanding how neurons function, but I suspect that it is. Nature seems to take advantage of every possible trick that will provide even the slightest benefit to the organism. It would be nice if things were simpler but usually they’re not.
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