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.