Brain Buys (4 page)

Figure 1.2 Neurons: Neurons receive input through their dendrites and send output through their axons. The point of contact between two neurons (
inset
) corresponds to a synapse. When the presynaptic neuron (
left
; the “sender”) fires an action potential it releases vesicles of neurotransmitters onto the postsynaptic neuron (
right
; the “receiver”). The dendrites often have protrusions (spines), where the synapses are formed, while the axons are smooth. In humans the cell body of a pyramidal neuron is roughly 0.02 millimeters, but the distance from the cell body to the tip of the dendrites can be over 1 millimeter.

What is the “zebra” node in terms of neurons? Does one neuron in your brain represent the concept of
zebra
and another your
grandmother
? No. Although we do not understand exactly how the brain encodes the virtually infinite number of possible objects and concepts we can conceive of, it is clear that every concept, such as
zebra
, is encoded by the activity of a population of neurons. So the “zebra” node is probably best thought of as a fuzzy group of neurons: a cluster of interconnected neurons (not necessarily close to each other). And just as an individual can simultaneously be a member of various distinct social groups (cyclists, Texans, and cancer survivors), a given neuron may be a member of many different nodes. The UCLA neurosurgeon Itzhak Fried has provided a glimpse into the relationship between neurons and nodes. He and his colleagues recorded from single neurons in the cortex of humans while they viewed pictures of famous individuals. Some neurons were active whenever a picture of a specific celebrity was shown. For instance, one neuron fired in response to any picture of the actress Jennifer Aniston, whereas another neuron in the same area responded to any picture of Bill Clinton.
⁷
In other words, without knowing which picture the patient was looking at, the experimenters could have a good idea of who the celebrity was by which neurons were active. We might venture to say that the first neuron was a member of the “Jennifer Aniston” node, and the other was a member of the “Bill Clinton” node. Importantly, however, even those neurons found to be part of the Jennifer Aniston or Bill Clinton node might also fire in response to a totally unrelated picture.

If a node corresponds to a group of neurons, you have probably deduced that synapses correspond to the links. If our “brain” and “mind” nodes are strongly associated with each other, we would expect strong synaptic connections between the neurons representing these nodes. Although the correspondence between nodes and neurons and between links and synapses provides a framework to understand the mapping between semantic networks at the psychological level and the biological building blocks of the brain, it is important to emphasize this is a stupendously simplified scenario.
⁸

MAKING CONNECTIONS

Information is contained in the structure of the World Wide Web and in social networks because at some point people linked their pages to relevant pages, or “friended” like-minded people. But who connected the “zebra” and “Africa” nodes? The answer to this question leads us to the heart of how memory is physically stored in the brain.

Although it would be a mistake to imply that the riddle of memory storage has been solved, it is now safe to say that long-term memory relies on
synaptic plasticity
: the formation of new synapses or the strengthening (or weakening) of previously existing ones.
⁹
Today it is widely accepted that synaptic plasticity is among the most important ways in which the brain stores information. This consensus was not always the case. The quest to answer the question of how the brain stores information has been full of twists and turns. As late as the 1970s, some scientists believed that long-term memories were stored as sequences of the nucleotides that make up DNA and RNA. In other words, they believed that our memories were stored in the same media as the instructions to life itself. Once an animal learned something, this information would somehow be translated into strands of RNA (the class of molecules that among other functions translate what is written in the DNA into proteins). How memories would be retrieved once stored in RNA was not exactly addressed. Still, it was reasoned that if long-term memories were stored as RNA, then this RNA could be isolated from one animal and injected into another, and, voilà, the recipient would know what the donor animal had learned. Perplexingly, several papers published in the most respected scientific journals reported that memories had been successfully transferred from one rat to another by grinding up the brain of the “memory donor” and injecting it into the recipient.
¹⁰
Suffice it to say, this hypothesis was an unfortunate detour in the quest to understand how the brain stores information.

The current notion that it is through synaptic plasticity that the brain writes down information, not coincidently, fits nicely into the associative architecture of semantic memory. Learning new associations (new links between nodes) could correspond to the strengthening of very weak synapses or the formation of new ones. To understand this process we have to delve further into the details of what synapses do and how they do it. Synapses are the interface between two neurons. Like a telephone handset that is composed of a speaker that sends out a signal and a microphone that records a signal, synapses are also composed of two parts: one from the neuron that is sending out a signal and one from the neuron that is receiving the signal. The flow of information at a given synapse is unidirectional; the “messenger” half of a synapse comes from the
presynaptic neuron
, while the “receiver” half belongs to the
postsynaptic neuron
. When the presynaptic neuron is “on” it releases a chemical called a neurotransmitter, which is detected by the postsynaptic half of a synapse by a class of proteins referred to as
receptors
that play the role of microphones (refer back to Figure 1.2). With this setup a presynaptic neuron can whisper to the postsynaptic something like “I’m on, why don’t you go on too” or “I’m on, I suggest you keep your mouth shut.” The first message would be mediated by an
excitatory synapse
; the second by an
inhibitory synapse
.

To understand this process from the perspective of a single postsynaptic neuron, let’s imagine a contestant on a TV game show trying to decide whether to pick answer A or B. The audience is allowed to participate, and some members are yelling out “A,” others “B,” and some aren’t saying anything. The contestant, like a postsynaptic neuron, is essentially polling the audience (a bunch of presynaptic neurons) to decide what she should do. But the process is not entirely democratic. Some members of the audience may have a louder voice than others, or the contestant may know that a few members of the audience are highly reliable—these individuals would correspond to strong or influential synapses. The behavior of a given neuron is determined by the net sum of what thousands of presynaptic neurons are encouraging it to do through synapses—some excitatory, some inhibitory, some strong and others that generate a barely audible mumble but together can add up to a roar. Although the distinction between pre- and postsynaptic neurons is critical at a synapse, like humans in a conversation, any given neuron plays the role of both speaker (presynaptic) and listener (postsynaptic). The game-contestant analogy provides a picture of neuronal intercommunication, but it does not begin to capture the actual complexity of real neurons embedded in an intricate network. One of many additional complexities—perhaps the most crucial—is that the strength of each synapse is not fixed, synapses can become stronger or weaker with experience. In our analogy this would be represented by the contestant’s learning, over the course of many questions, to pay more attention to certain members of the audience and ignore others.

Although the term
synapse
had not yet been coined, Santiago Ramón y Cajal suggested in the late nineteenth century that memories may correspond to the strengthening of the connections between neurons.
¹¹
But it took close to a hundred years to convincingly demonstrate that synapses are indeed plastic. In the early 1970s, the neuroscientists Tim Bliss and Terje Lømo observed long-lasting increases in strength at synapses in the hippocampus (a region known to contribute to the formation of new memories) after their pre- and postsynaptic neurons were strongly activated.
¹²
This phenomenon, called
long-term potentiation
, was an example of a “synaptic memory”—those synapses “remembered” they had been strongly activated. This finding, plus decades of continuing research, established that changes in synaptic strength are at some level the brain’s version of burning a hole in the reflective surface of a DVD.

As is often the case in science, this important discovery led to an even more baffling question: if synapses are plastic, then how do two neurons “decide” if the synapse between them should become stronger or weaker? One of the most fundamental scientific findings of the twentieth century provided a partial answer to this question—one that offers powerful insights into the workings of the organ we use to ask and answer all questions. We now know that the synaptic strength between neurons
X
and
Y
increases when they are active at roughly the same time. This simple notion is termed Hebb’s rule, after the Canadian psychologist credited with first proposing it in 1949.
¹³
The rule has come to be paraphrased as “neurons that fire together, wire together.” Imagine two neurons Pre
₁
and Pre
₂
that synapse onto a common postsynaptic neuron, Post. Hebb’s rule dictates that if neurons Pre
₁
and Post are active at the same time, whereas Pre
₂
and Post are not, then the Pre
₁
Post synapse will be strong, while the Pre
₂
Post synapse will be weak.

Great discoveries in science are often made in multiples: scientists working on the same problem arrive at similar answers at approximately the same time. The discovery of calculus is credited to independent work by Isaac Newton and Gottfried Leibniz, and Darwin was spurred to publish his masterpiece
On the Origin of Species
by converging ideas coming from Alfred Wallace. The finding that synapses obey Hebb’s rule was no different. In 1986 no fewer than four independent laboratories published papers showing that a synapse becomes stronger when its presynaptic and postsynaptic partners are activated at the same time.
¹⁴
These studies established the existence of what is called
associative synaptic plasticity
, and fueled thousands of other studies and many breakthroughs over the following decades.

How does a synapse “know” that both its presynaptic and postsynaptic neurons are active at the same time, and then proceed to become stronger? Establishing these neuronal associations is such a pivotal component of brain function that evolution has concocted an “associative protein”—a molecule found in synapses that can detect whether the presynaptic and postsynaptic neurons are coactive. The protein, a receptor of the excitatory neurotransmitter glutamate, called the
NMDA receptor
, works as a gate that opens only if the presynaptic
and
postsynaptic neurons are active at about the same time, which allows it to implement Hebb’s rule. We could say that the NMDA receptor functions much like the Boolean “and” used in search engines, that is, it only returns a result (it opens) if two conditions are satisfied (activity in the presynaptic
and
postsynaptic neurons). Once the NMDA receptors open, a complex series of biochemical events that lead to long-term potentiation of a synapse are triggered.
¹⁵
Thanks to its unique properties the NMDA receptor detects the “associations” between neurons, and is pivotal to the implementation of Hebb’s rule and associative synaptic plasticity.
¹⁶
To return to the social network analogy, if Hebb’s rule were applied to Facebook, people that logged into their account at the same time would automatically become friends, ultimately creating a network of people with synchronized schedules.