Professor Dave here, let’s check out some neurons.
We now have a pretty solid understanding of how an action potential is generated, and
how this propagates from one neuron across a synapse to the next.
So let’s zoom out a little bit and start to get a sense of the manner in which neurons
are organized.
This is important to understand, because neurons are found in groups, and these groups contribute
to larger structure still, so we must understand the hierarchy of this organization, which
we can also call neural integration.
When we pull back from a single neuron to see a small collection of neurons, we can
call this a neuronal pool.
This will serve to integrate information coming in so that it can be determined how to forward
that information to where it needs to go.
Here we can see a presynaptic fiber with many branching terminal ends leading to a number
of different neurons.
Some of them are more closely associated with the presynaptic fiber, as there are many more
points of contact.
These neurons are in the discharge zone.
Moving outwards, we see other neurons with fewer points of contact, and these sit within
a facilitated zone.
The neurons in the discharge zone are on the receiving end of more synaptic contacts, and
thus many more neurotransmitter molecules.
Therefore, these neurons are more likely to depolarize beyond the threshold required for
an action potential to be generated.
The neurons in the facilitated zone will depolarize to an extent but are less likely to reach
that threshold, unless such stimuli are also received from somewhere else.
While this is oversimplified, we may begin to see how something as simple as the transmission
of an electrochemical signal can encode very complex information when we take into account
the incredible number and organization of neurons, just the way that a bunch of zeros
and ones being transmitted through the circuitry of your computer allows it to perform sophisticated
tasks as well.
In fact, neurons are indeed arranged in circuits that are loosely analogous to computer circuitry.
Each neuron can both send and receive information, and chemical transmission across a synapse
can yield either an excitatory or inhibitory response.
Although it’s not a perfect comparison, these similarities make a neuron not entirely
unlike a transistor.
Let’s look at the types of circuits first.
Here we see a diverging circuit.
We see one input, and many outputs, as the signal is amplified with each transmission.
A single neuron in the brain can activate a huge number of motor neurons in this manner.
We can also see a converging circuit.
Just the opposite of a diverging circuit, here we see multiple inputs, and just one
output, so the signal becomes concentrated.
Sensory information often travels to the brain in this fashion.
Next we see a reverberating circuit.
This is where neurons in a chain can feed back to previous neurons, to form an oscillating
circuit.
These types of circuits control rhythmic activity like breathing, as well as repetitive actions
like walking.
Lastly we can see a parallel after-discharge circuit.
This involves an input that diverges into parallel arrays that then converge on a single
output.
There is some variance in the time required for each individual signal to reach the output,
so a burst of multiple impulses will be produced.
These are involved in more complex brain activity like coincidence detection.
With the types of circuits covered, let’s quickly examine two types of neural processing.
Serial processing is an all-or-nothing type of processing.
A signal travels from one neuron to the next, eventually making it to its destination, and
triggering the desired response.
Reflexes are examples of this type of processing.
Parallel processing, on the other hand, occurs when an input diverges into many pathways,
and the destination of each pathway will receive and interpret the information in its own way.
This is how smelling something or hearing a particular song can trigger a variety of
thoughts, memories, and emotions.
In this way, parallel processing is behind most higher-level brain activity in humans,
as we are capable of synthesizing all kinds of information to recognize obscure objects,
think abstractly, make plans, and do all the other incredible things that humans can do.
Let’s now move forward and take a look at how the brain handles all of this information.