What neuroscience researchers really, really want is to figure out the neural (brain) code. What are all those neurons saying to each other? That’s an analogy, of course. There are many analogies that can be used to describe the brain. For the moment, let’s use a big tangled ball of thread. The neurons, brain cells, connect to each other through myriads of dendrites (long, thread-like filaments extending from each neuron). Along these connections, electrons (a current, though very small) create ‘spikes’ that jump from cell to cell over biological junction boxes called synapses. It has been the custom – one forced by a lack of research tools – to experiment with one neuron communicating with one other neuron. But it’s been known for some time that’s not how it works. Many neurons communicate to one neuron at a time, with spikes jumping over thousands of synapses. It’s that tangled ball of thread.
It’s also like a shouting crowd. Or that must be what it might seem like to the cerebral cortex. Neurons in the cortex (the ‘thinking’ part of the brain), called spiny stellate cells, sometime receive thousands of spikes from other parts of the brain. In particular, they must receive spikes from the thalamus, which intermediates all the sensations from the body, and sends them on to the cortex. These are crucial, because these signals tell the brain what’s happening outside and inside the body. They’re all clamoring for interpretation.
How does the cerebral cortex handle that much traffic? It’s been an important question for neuroscience. A possible answer has been worked out by researchers at the Salk Institute for Biological Studies (La Jolla, California, USA). Using some of the latest computer modeling techniques, they experimented with a representation of stellate cells with up to 6,000 synapse connections. They found that it’s not the number of signals (firing synapses) that matters, but the number of signals arriving simultaneously. In fact, the model predicts that only 30 out of the 6,000 synapses need to fire (at once) to get a message across loud and clear from the thalamus.
Note the word ‘predicts.’ That’s like a call for scientists to set up an experiment – to see if in some way they can detect and measure the activity between thalamus and cerebral cortex. This is not easy. It is very difficult to put probes in a living brain, and scanning techniques are, at least for now, more accurate at detecting regions of activity than in pinpointing activity in single or small groups of cells. Nevertheless, the computer models help lead the way by showing what likely outcomes to look for.
“But it’s not known whether that happens under natural conditions, and it’s technically very difficult to measure, ” says senior researcher and co-author Donald Spencer, Ph.D. “That’s where the power of computational neurobiology really comes to bear on otherwise intractable questions.”
“Applying theories of engineering to the study of the brain has helped us gain new insight into how neurons communicate with each other,” says Wang. “On the other hand, there are certain things that the brain does in unique ways that are completely different from how computers work. A better understanding of the brain allows us the capture these algorithms and could very well affect the things engineers do in everyday life.”
To pick up analogies – finding the neural code is like unraveling a tangled ball of threads and picking out the gist from the noise of a yelling crowd. Not easy, especially when tools to work at the neuron level (in living subjects) aren’t ready yet. (They are being researched, especially in the form of nanosensors.) Advances in this part of neuroscience are hard won, but many think that this coming decade will see progress, if not a cracking of the neural code.