Your Mechanical Brain
How Neurons Keep Track of Your Memories
Background
The way neurons send signals to each other using electrical impulses is fairly well understood (summarized in this figure). But there is still much speculation and debate on how the signaling between neurons leads to the formation of memories. The electrical signals that travel through the brain can transmit information between neurons, but they cannot store information. In a recently published paper, Dr. Benjamin T. Goult proposes a new hypothesis for how information is stored in the brain. It’s called MeshCODE theory.
Binary in Biology
The entire theory centers on a protein called talin, which has 13 different domains that can each switch between a folded or unfolded state depending on how much force is being applied to the molecule. Talin is known for its ability to connect with integrins, which are membrane bound proteins that help anchor the cell to both its extracellular matrix and the cytoskeleton on the inside of the cell. The connections between the cytoskeleton, talin, and integrin creates a structural network that crosses the cell membrane and links the inside of the neuron with its outside environment. That idea will become important later.
Goult proposes that the pattern of folding in talin is more than just a structural phenomenon, but a way for the cell to store information as binary code. Now you may be wondering why this suddenly sounds like a computer science course. Bear with me.
Computers use a language with two signals: on or off. Another way of representing this “on/off language” is binary code, where every “on” signal is a 1 and every “off” signal is a 0. Computers use complex (and very rapid) patterns of these binary signals to encode all the information and instruction that it takes to, well, be a computer. Goult is proposing that the protein talin stores the same kind of binary information in its folding pattern. Below, you’ll find a low level sketch based on Figure 2 from the paper.
The next part of Dr. Goult’s theory proposes a mechanism for how this binary code could be changed by neuronal signaling. When an electrical signal courses through a neuron, its cytoskeleton reorganizes in response to the signal. Goult argues that the the cytoskeletal filaments act like the gears and levers of a mechanical computer similar to those imagined by the mathematician Charles Babbage. This cytoskeletal reorganization applies precise forces to the network of talin molecules, changes their folding patterns, and “rewrites” the data stored in them. Figure 3 provides several excellent illustrations of this idea.
If this hypothesis is correct, then every neuron in the brain is connected via a complex network made up of cytoskeletal filaments, talin proteins, integrins and their associated extracellular matrix. This network is what Goult terms the meshCODE. The patterns of electrical impulses traveling through the neuronal network write information into the meshCODE, giving a physical location to memory formation in the brain.
So how does this special binary information in talin actually lead to changes in neurons? After all, this information system is only useful if it can be “read” by the cell somehow. Goult proposes that the folding patterns of talin changes the availability of various protein binding sights on talin. This means that a molecule of talin with the code “000100” can bind different proteins than one with the code “010100.” This concept is easier to see in an illustration. If this seems more polished than the last one…that’s because it is.
Changes in the binary code correspond to changes in protein binding. If you imagine a large meshwork of talin proteins constantly updating their folding patterns, you can see how this opening and closing of binding domains could alter protein levels throughout the neuron.
Dr. Goult’s hypothesis provides a framework for understanding memory creation in neurons. It links every neuron together in a meshwork of dynamic signaling that is constantly updating stored data and recording new information. As you use your mechanical brain to read the last few words of this summary, I invite you to check out the mind-blowing calculations found in Box 1 from the paper (you might have to scroll down to get to it). MeshCODE or not, it is truly incredible what the human brain can do.
