So this is your soma, and this is your dendrite, and you have synapses.

Inhibitory, excitatory, inhibitory, excitatory, and so on.

Only the mere fact that you have a structure enables you to write a more

extended logical to perform a more extended, logical operation, rather than

this, something like this. And let me explain you very briefly why.

Because here now, the location of the inhibition becomes important.

Of course, when you have a point, there is no location, everything is on the

point. But here, this inhibition is more close

to the cell body than this inhibition. And intuitively, you may understand

already now that this inhibition is more global, affects all the excitation that

comes from more distant region. So, if this excitation or this excitation

or this excitation is active, this proximal to the soma inhibition can veto

it. This inhibition for example, is most

effective on this excitation but not on this excitation.

Because for this excitatory input, most of the current goes this direction, and

it doesn't care there is inhibition backwards so to speak.

So this in arrangement of inhibition relative to the excitation, the strategic

location of inhibition, makes a difference in terms of what kind of

logical operation you may do. For example, now you can write the

following sentence. Rather than this one, I can say I will

get an output one. I will get an output if e3 is active and

not i1, or i2, or i3. Everything that is on the way, on the

path between the excitation and the soma, all the inhibition here is harmful, may

veto this excitation. Or, or e2 may be active and not e2 or e1.

Then I get an output. Or, e1 may be active, and not i1, then I

will get an output. So, you can see that Koch and Poggio

suggested the dendritic tree endows the neuron with a most sophisticated logical

operations. Compared to a point McCulloch-Pitts

neuron. So, that's the first idea to mention

regarding the affect of distributed cable system in this strategic location of

inhibition versus excitation, that's what I do.

Another idea about Bartlett Mel is the notion of this functional sub-units.

So here, I, he drew a neuron with regional inputs.

So, this is one region recieving synaptic inputs, this is another region receiving

on the dendritic tree, synaptic inputs. He was wondering, can you think about the

neuron is locally performing some kind of a non-linear operation, non-linear

summation of this local synapses. Or this local synapses independently

first? So this n1 synapses locally is performing

some non-linear operation here, then here, then here.

And only then, you sum these local operations globally at the soma, what he

calls the Pi Sigma Neuron. Locally, you perform some non-linear

operations only between your neighboring synapses, and only then, you sum up all

this local operation. This is because the neuron is distributed

system and he was showing that indeed, because of certain properties of

dendrites. The fact that you have clustered

synapses, here a cluster, here a cluster, here a cluster, here, locally.

You may get some non-linearity which eventually will sum up the same body

differently than if you don't have clustered synapses.