Oscillations Part VII: Inhibition, Excitation and Balance

(This is a continuation of notes taken from Ginger Campbell's podcast #31 with György Buzsáki, and a continuation from Part VI):


In the brain, inhibition and excitation operate as opposing forces

* inhibitory neurons on a single pyramidal cell from the neocortex are in the minority ... about 15 - 20%.
* however, they are located strategically - most of these inhibitory terminals are near the soma and the axon initial segment, parts of the neurons that are critical for generating action potential output
* inhibitory terminals make sure that the timing of the neuron is optimal - that's what happens in many cases of oscillations


Balance between excitation and inhibition

* even though the number of inhibitory terminals are smaller, the inhibitory terminals are very active, about 5 times more active than the principal cells: i.e., way fewer inhibitory terminals and inhibitory neurons, but activity is higher; the result is that the total number of EPSPs and IPSPs, i.e., the excitatory inputs and inhibitory inputs per unit time, are exactly the same or almost exactly the same, resulting in a balanced system


How fluctuation creates balance

"However, this balance is brought about by fluctuation... if you zoom in in small time windows then we always see that either inhibition or excitation dominates. And the easiest thing to balance the two opposing forces is through oscillations. So that is the reason why inhibition is so important. Without inhibition there would be no computation in the brain. Why? Well, the second law of thermodynamics clearly states that in physical system if you have only collisions then collisions will produce more collisions and the entropy of the system will increase and there will be no order. This applies also to the brain, of course, and any other physical systems, and the brain is a physical system, is that if we had only excitation, and then excitation would produce only further excitation. In fact, in principle, the action potential of one neuron would lead to the discharge of every single neuron in the brain."

Variability

* Shannon's information theory approach works perfectly - at the periphery - at the first senses
* it works good at the retina, at the cochlea, perhaps even at the first relay station in the thalamus

* as one goes deeper and deeper into the brain the variability increases; not because the reliability of the brain isn't good, but because other sources of "noise" come into the picture; this "noise" is generated by the brain itself

* the deeper we go into the brain, the more we find independence from the environment

"The deepest structure in the brain, if there is such a thing as deep, is the hippocampus, or the prefrontal cortex, because they are multiple synaptic connections, far from either the motor output or the sensory inputs, and, they maintain their activity. But this maintained activity is observed almost everywhere. Visual cortical neurons are active, a little bit less perhaps, but they are still active when we close our eyes or when we fall asleep. Many parts of the brain, for example, again, the hippocampus, they are as active during sleep as in the waking state. The number of action potentials of all neurons, that is, the energy they use, is pretty much constant, independent of what happens out in the environment."