Using synthetic evolution to study the brain: Researchers model key part of neurons

October 2, 2009

The human brain has evolved over millions of years to become a vast network of billions of neurons and synaptic connections. Understanding it is one of humankind's greatest pursuits.

But to understand how the brain processes information, researchers must first understand the very basics of — even down to how proteins inside the neurons act to change the neuron's voltage.

To do so requires a balance of experimentation and computer modeling — a partnership across disciplines traversed by Bill Kath, professor of engineering sciences and applied mathematics in the McCormick School of Engineering and Applied Science, and Nelson Spruston, professor of neurobiology and physiology in the Weinberg College of Arts and Sciences.

The two have worked together for more than a decade, with Spruston designing experiments and Kath developing computer models that explain the results that Spruston found. (It also works the other way: Kath's models have provided Spruston with ideas to test experimentally.)

Spruston has been studying of neurons that change their shape when activated, allowing sodium to enter from outside the neuron. This changes the voltage of the neuron, causing the neuron to fire and send off a chain of within the brain. The difficulty in modeling such behavior lies in the time scale over which this happens — anywhere from fractions of a millisecond out to several seconds.

So the two, along with graduate student Vilas Menon, took a cue from nature and used the process of to study one of evolution's greatest achievements.

Evolutionary algorithms work like this: rather than making one model, researchers make 100 models with many different parameters. They then run those models (using high-speed computers) and compare the results to the experimental data to see how well they match. Researchers then keep the best traits of different models and mix and match (breeding) to make 100 more models. Thousands of generations later they get a model that matches the characteristics of the real thing. Researchers have used this technique in modeling before, but Kath and colleagues introduced a new twist: they allowed the structure of the model (not just its parameters) to be "mutated" during the "breeding".

"In the end, the computer found a quite simple state-dependent model for the sodium channels that provides a very accurate behavior on short time scales and out to several seconds, as well," Kath says. Their results were recently published in the Proceedings of the National Academy of Sciences.

Modeling of even this small a process is important, Spruston says, because it helps scientists understand the important details about how the brain works.

"We want to make sure we truly understand how these channels work by building a model that can recapitulate all the features we've observed," he says. "Making computer models is a way of identifying both what you understand and also where the gaps in your knowledge need to be filled. The cool thing is you're taking a page from a part of biology — evolution — and applying it to another part of biology — neurobiology — and using the computer in the middle."

The neurons the group studied are in the hippocampal region of the , which researchers have identified as being important for memory.

"If you want to understand how this neural circuit is processing information and memory, you have to understand how these neurons behave in different situations," Kath says. "If you leave out key details, you might miss something important."

Source: Northwestern University (news : web)

Explore further: 'Chatter Box' computer will unravel the science of language

Related Stories

Neural modeling helps expose epilepsy's triggers

February 16, 2009

( -- A brain scan of a person experiencing an epileptic seizure looks like the Great Plains during an early evening in midsummer. Fierce electrical storms pop up seemingly at random, proliferate over large areas ...

Neurons found to be similar to Electoral College

September 14, 2009

A tiny neuron is a very complicated structure. Its complex network of dendrites, axons and synapses is constantly dealing with information, deciding whether or not to send a nerve impulse, to drive a certain action.

New model suggests how the brain might stay in balance

September 24, 2009

( -- Physicists have theorized for decades about how neural networks might be able to accomplish the incredibly complex calculations the human brain performs all the time. But simply stabilizing such a powerful ...

Recommended for you

Study suggests fish can experience 'emotional fever'

November 25, 2015

(—A small team of researchers from the U.K. and Spain has found via lab study that at least one type of fish is capable of experiencing 'emotional fever,' which suggests it may qualify as a sentient being. In their ...

Winter season reverses outcome of fruit fly reproduction

November 24, 2015

Male fruit flies could find their chances of fathering offspring radically reduced if they are last in the queue to mate with promiscuous females before winter arrives, according to new University of Liverpool research.


Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.